# Ryan Doser, all posts > AI marketing strategy, Claude Code workflows, and AI tool reviews. This file holds every published post and original research page on ryandoser.com. Each post begins with a level-2 heading, its canonical URL, dates, and categories. Cite the HTML URL, not this file. Posts: 178. Original research pages: 2 (at the end). Site summary: https://ryandoser.com/llms.txt. Catalog: https://ryandoser.com/.well-known/ai-catalog.json --- ## AI Video Editing: I Tried Replacing My Editor. Here's What Broke URL: https://ryandoser.com/ai-video-editing/ Markdown: https://ryandoser.com/ai-video-editing.md Published: 2026-10-09 Categories: AI Rabbit Holes > I tested AI video editing on a full podcast episode with Claude Code. What it handled, the four places it broke, and the job my editor kept. **AI video editing** got this podcast episode out without my human editor, with me directing and reviewing every step. Claude Code's rough cut was easy (21 seconds of flubs and dead air), but the intro took eight versions over two days before I'd publish it, and my editor still handles my shorts. ### **Watch Me Test AI Video Editing on a Real Episode** Aaron Makelky came back on AI Rabbit Holes on October 8, 2026, and we spent the whole episode on one question: how much of a video edit can you hand to AI right now? I showed the Claude Code workflow that edits my podcast. Aaron showed how he edits his own videos with no editing app at all, just Claude running in a terminal. Those editing skills follow the same rules as my **[Claude Code Skills Stack](https://skills.ryandoser.com)**, the marketing skills I run every day: one narrow job per skill, tuned on my feedback after every run. What changed this year is that editing apps started opening their doors to AI. Riverside and Descript both offer MCP servers now, and [DaVinci Resolve 21.1](https://www.blackmagicdesign.com/support/content/readme/baf7c071c0524fbf8ccc961925c9f443) added a native one in September 2026. ### **What AI Video Editing Did on This Episode** AI video editing now handles my full episode, from rough cut to intro to packaging, and my editor keeps one job: short-form clips. *Who edits what on my podcast now. The full episode runs through Claude Code skills, and short clips still go to my editor.* Everything still starts with a recording in Riverside. Aaron makes the same point: terminal editing tools can't record anything, so he still records in Riverside or Descript every day. #### **The rough cut: 21 seconds gone** Claude Code connects to Riverside through its [MCP server](https://riverside.com/mcp), and my podcast editor skill reads the transcript and makes the cuts inside Riverside. On this episode it made four cuts and trimmed the dead air after the outro, taking the raw 36:09 down to 35:48. Two of the cuts landed where I'd flagged a mistake out loud while recording, like "I'll need to cut that part out." The other two removed a restart after I lost my place in the slides and a quick "are you seeing this?" check during Aaron's screen share. I review every cut before export, and this time I approved all four without changes. That's a light touch on purpose. The skill trims flubs and long dead air, and it leaves the conversation alone. #### **The intro: eight versions in two days** The intro was the hard part. My podcast intro skill learned from every intro my editor has made for me, then picks the best lines from the episode and adds AI B-roll, text and sound effects. The first version came back on October 8, and I rejected it as not ready for production. My notes on the next six rounds were mostly the same note: too much B-roll, show more of the two of us talking. Version eight is the intro that opens the video above. It runs about 50 seconds, and its motion B-roll came from Google's Veo 3.1 Fast through OpenRouter (I covered that setup in my guide to [generating AI video inside Claude Code](/claude-code-ai-video/)). On camera I called an earlier test "like 95% there." Two days of notes is what closed the last few percent. #### **Packaging: titles, description, thumbnails** Once the episode is uploaded, a packaging skill reads the transcript and drafts 10 YouTube titles, the description with every link we mentioned, and the tags. It also designs thumbnail options with official logos, and I pick the winners. ### **Where AI Video Editing Still Breaks** Most AI video editing demos skip the failures. I put mine on a slide. *The four places AI editing broke for me, from the slide I presented on October 8, 2026.* #### **1. Clipped words** The pause trimmer cut the "x" off "Claude Max," so it played as "Claude Mac." In another test, "chat G-P-T" was heard as "tragedy." A bleep in an earlier cut of this episode's intro also ate the "Q" in "IQ," because the transcript's word timing started a fraction of a second early. That got caught and fixed before the intro shipped. What helped was having Gemini watch the final video to catch misses like these, not just read the transcript. #### **2. Stitched bites feel disjointed** My editor builds an intro that tells one story. AI tends to stack the hottest takes back to back, and the result plays like a highlight reel with no thread. #### **3. Stock objects instead of ideas** Same line from Aaron's [ChatGPT Pro episode](/is-chatgpt-pro-worth-it/) ("more air and fewer chips"), two edits. *My human editor drew a labeled illustration that explains the idea. My AI intro skill showed a bag of chips and one word.* The AI grabbed the literal object. My editor designed a graphic that carries the meaning, and that's the taste gap viewers notice. #### **4. Clip tools stop at talking heads** This is why my editor still has the shorts. The Opus Clip MCP can cut and caption clips on command, but it has no tools for music, sound effects or B-roll. I'd still have to open the app and finish every clip by hand. I covered the setup side in my [OpusClip MCP tutorial](/opusclip-mcp/). If Opus Clip adds those to the MCP, I might subscribe again. #### **Beyond the four: rendering needs serious hardware** This one applies when the render happens on your own computer. From personal experience, if you try AI video editing on an underpowered laptop, it's going to sound like it's about to explode. Aaron added that some of these tools need a Mac and won't run on a Linux cloud server. He also warned that you need room for the raw video and plenty of RAM, so in his view a MacBook Air or a Chromebook won't cut it. In my workflow, the rough cut happens inside Riverside's editor, so that step never touches my laptop. The intro is different: it renders on my own machine, and that's where the hardware matters. ### **How Aaron Does Claude Code Video Editing With No App** Aaron's version of AI video editing skips the editing app. He edits most of his videos in a terminal now. His most-used tool is [HyperFrames by HeyGen](https://hyperframes.heygen.com/), a free, open-source framework that turns HTML into video, so Claude can write the captions, graphics and animations as code. His point is that you don't need a $50-a-month video tool for Claude Code video editing. A prompt as simple as "use HyperFrames to edit this down into the best 10 social clips" gets him started. For his clips, Aaron connects Claude Code to the same Riverside MCP and asks for 10 clips based on the transcript. He also uses [Tesseract by Mirage](https://mirage.app/tesseract), which had been out about two weeks when we recorded. That's also his route around the gap that keeps my shorts with an editor: he skips clipping apps and has Claude finish the clips in the terminal. Two of his habits are worth stealing: - He tries one new thing every episode. This week it was looped clips, where the last frame matches the first, on 3 of his 10. - He gave Claude a brand guide for captions: below his chin, never over his face, a tool's logo when he names it, and the main speaker on top in two-person clips. He even had Claude turn one of his edits into a walkthrough, using his own prompts. It's worth reading: [how he one-shot a CarPlay video edit](https://aaronmakelky.com/blog/one-shot-video-edit-claude-tesseract). ### **Turn Each Editing Job Into a Skill** Aaron said the line I'd put on a poster: "edit my video, make it good" is the new version of AI slop. With no direction, AI video editing gives you something that looks like everyone else's. What works is one skill per job, like a cut skill and an intro skill, each fed examples of work you love. My intro skill only got good because it had my editor's past intros to study. Then you improve it every run. Aaron's rule is to make each skill 1% to 5% better every time you use it, and he'd take that over waiting on next week's new model. If you're starting from zero, start with the cuts. Let the skill take the long pauses and obvious mistakes, check its work, and keep a human on the creative until your notes catch up. The same skill approach also turns one episode into a blog post and an email, which I covered in my [Claude Code repurposing workflow](/claude-code-repurpose-youtube-videos/). ### **Your Long-Form Recording Is Still the Main Course** Aaron's best analogy: generated media should be the salt and pepper on the meal. The meat and potatoes are still you, on camera, saying something worth hearing. AI video editing got this full episode out the door without my editor. It still can't match the taste my editor brings to a 30-second clip, and it never recorded a single word for me. So I'd tell any good editor the same thing I said on camera: if you use these tools, your value just went way up. Record the conversation yourself and let skills handle the grunt work. Then spend the time you save on what you actually say. ### **AI Video Editing FAQs** #### **Can AI replace a human video editor?** For a podcast rough cut and intro, it can, if you train the skill on your editor's past work and review every output. Across my runs it still clipped words and picked literal stock objects, and the Opus Clip MCP has no tools for music, sound effects or B-roll, so short-form clips stay with my human editor for now. My view on the episode: a skilled editor who uses these tools just became far more valuable. #### **How do you edit videos with Claude Code?** Connect Claude Code to your recording tool through an MCP server, like Riverside's, or point it at a local file and a code-based tool like HyperFrames. Then build a separate skill for each editing job, with examples of edits you like. Start with cutting silences and flubs, and approve each cut before you export. #### **Do you need a powerful computer for AI video editing?** Yes, if the rendering happens on your machine. Aaron's warning on the episode is that local rendering needs plenty of RAM and disk space, and some terminal-based tools require a Mac, so a Linux cloud server may not run them at all, and in his view a MacBook Air or Chromebook won't cut it. Cuts made inside a cloud editor like Riverside happen in the browser app, so only the local renders need the horsepower. #### **Why do AI-edited videos look like slop?** Often because the prompt gives no direction. Aaron's example, "edit my video, make it good," leaves the model to guess, so it reaches for literal stock visuals and generic hot-take stacking. A skill with a brand guide, examples from a good editor and notes from every past run moves the output toward your style, though my intro still took eight rounds. --- ## How to Get ChatGPT to Recommend Your Local Business URL: https://ryandoser.com/how-to-get-chatgpt-to-recommend-your-business/ Markdown: https://ryandoser.com/how-to-get-chatgpt-to-recommend-your-business.md Published: 2026-10-08 | Updated: 2026-10-08 Categories: AI Rabbit Holes > Linkifi tracked ChatGPT's sources for three weeks. What it found, plus Chris Panteli on how to get ChatGPT to recommend your business. If you're figuring out **how to get ChatGPT to recommend your business**, start here: in a three-week Linkifi study, re-asking the same buying question minutes later changed 60% of the sources ChatGPT cited. Day-to-day churn was no bigger than that same-day randomness (1.01x the noise floor), so most of the movement you see is noise. ### **Chris Panteli on How to Get ChatGPT to Recommend Your Business** Chris Panteli co-founded [Linkifi](https://www.linkifi.io/), a digital PR agency, and he's back for his second AI Rabbit Holes episode after [his first in 2025](https://www.youtube.com/watch?v=ohU7ub1tA1k). This one covers his team's study of what ChatGPT reads before answering a buying question. Press coverage is what Linkifi sells, so read Chris's PR advice knowing that's his business. The free tactics below carry no such conflict. Taken in the order I'd follow it, Chris's advice runs like this. Get listed on the sites ChatGPT keeps returning to for your buyers' questions, ask it why it picked a competitor, then make the people behind your business easy to name. If you want to go deeper on the research side, I put together my **[Claude Code Skills Stack](https://skills.ryandoser.com)** with the SEO and research skills I run for client work. ### **Linkifi's AI Visibility Volatility Index, by the Numbers** Linkifi asked ChatGPT the same 30 buying questions every day for three weeks, in an incognito browser instead of through the API, and measured how much the recommended sources changed. Sources are the pages ChatGPT links in its Sources panel, the documents it read during its search. So the study tracked what ChatGPT read, and it did not track which businesses ChatGPT named. Two corrections to the recording. Chris says "30 days" once, but the study ran 21 days, and he called it local when the PDF also includes national categories like project-management software. The report isn't public yet. Every figure below comes from the PDF Chris showed on screen, labeled Linkifi Research, September 2026. *The cover of Linkifi's report as Chris shared it on screen.* Four numbers sit on the report's summary page: - 40% vs 39%: ask twice in one day and the two answers share 40% of their sources. Ask a day apart and they share 39%, so day-to-day churn is 1.01x the noise floor. - 7 in 10: after Linkifi removed that randomness, 71% of the sources cited on day 1 were still being cited in the final week. - 74%: three-quarters of the websites ChatGPT cited appeared on 4 days or fewer. A core of 3% showed up almost every day, and 12 of those 18 fixtures are directories or "best of" lists. - 36%: the first website ChatGPT cited matched day 1's on only 36% of days, the least stable thing Linkifi measured. *The summary cards from page 2 of the PDF.* Of the four cards, the last two say the most about how to get ChatGPT to recommend your business. The top source matched day 1's only about one day in three, while a small core of sources kept returning almost every day. #### **Why One ChatGPT Check Tells You Almost Nothing** Checked once this morning whether ChatGPT listed your website among its sources? Linkifi's report calls that kind of single check "close to worthless," because re-asking minutes later changed 60% of the sources. Besmir Bregasi showed the same kind of churn in one dashboard on [my earlier episode about tracking AI visibility](/how-to-track-ai-visibility/), where one prompt ranked a brand anywhere from #1 to #8 within a single week. Linkifi measured it at scale. Directories and "best of" lists made up 61% of all citations and were among the stickiest sources. As the PDF puts it, "Being on the right lists matters more than any single mention." Category makes a big difference. Small-business accounting answers kept only 14% of their sources day to day, while project-management software kept 59%. Local, city-specific questions were steadier than national ones, according to the PDF. That matched my guess on the recording, while Chris had guessed local answers would swing more. *Page 2's "What this means in practice" list, footer dated Linkifi Research, September 2026.* Real change is slow, too. Roughly a third of day-1 sources faded over three weeks, and Linkifi's fitted half-life is about 35 days. So review it monthly, across many runs. A daily check mostly measures luck. Whether the businesses ChatGPT names are any good is a separate question Linkifi didn't test. I looked at that in [my two-city test of local AI recommendations](/research/does-chatgpt-recommend-local-businesses/). ### **Reverse-Engineer the Sources ChatGPT Keeps Coming Back To** The fastest win Chris described for how to get ChatGPT to recommend your business costs little. The sources list is your look "behind the magician's curtain," as he put it, so run the questions buyers ask in [ChatGPT](https://chatgpt.com/), write down the sources, and get listed in the ones you're missing. Ask the way a buyer talks, because Chris sees these as conversations more than searches. His example for a personal injury firm was something like "I got run over the other day, my leg's broke, what can I do?" Run each question several times, and the core sources are whichever ones keep showing up. At the local level, Chris said, those are often directories and industry lists that businesses could claim but never have. He called the return on that effort "instant and significant." I like this advice because most people skip it to chase the latest trick. *The decision this loop supports: spend your effort where ChatGPT returns again and again, instead of chasing one day's answer.* I won't repeat the directory list here. My [test of what ChatGPT cited for a local plumber](/how-to-rank-in-chatgpt/) names the directories, subreddits and local press that showed up, and how to qualify for each. Buying an ad won't put you in the answer, according to OpenAI. It opened a [self-serve Ads Manager beta to US advertisers](https://ppc.land/openai-opens-chatgpt-ads-manager-to-all-us-businesses-with-cpc-bidding/) on May 5, 2026, and says its ads are clearly identified and don't influence the answers ChatGPT provides. ### **Ask ChatGPT Why It Picked Your Competitor** Chris's final piece of advice for how to get ChatGPT to recommend your business builds on the sources list. Run a buyer question, note which competitor ChatGPT names, then ask it directly, with wording close to his "why did you not recommend my law firm?" and your firm's name in it. Chris said ChatGPT will answer with reasons. In his example, the other firm is in three trusted directories, has claimed its profiles, and has a lead lawyer who is certified and quoted in reviewed articles. He called that "a pretty decent roadmap and blueprint." Be careful with it, though, because a model explaining itself after the fact can sound sure about reasons that had little to do with the pick. So check its reasons against the cited sources before acting on them. Then re-test, because Chris's closing line was "test, test, test periodically." ### **Why Chris Sees ChatGPT Recommend the Person Behind the Business** Here's something Chris has noticed in his agency's work: on many local questions, ChatGPT names a person rather than a company. "More often than not," he said, it recommends individual brokers over their firms. His example was a Miami home buyer looking for an agent. He sees the same with financial and medical questions, where ChatGPT names a specialist and mentions where they work. That's a field observation, and the study didn't measure it. His advice is to make both the business and its representatives "defined entities," with trust and authority built around the person too. His proof is an Austin, Texas real estate broker Linkifi has worked with for five years, whose name Chris said comes up again and again in ChatGPT. Chris credits that to Linkifi's PR work, which put the broker on CNBC and Bloomberg as a talking head and into the New York Times with bylines. Those were earned media spots the client paid Linkifi to pursue, which is the service Chris sells. The free version for a local firm is naming the owner or lead pro the same way on your site and on every directory profile you claim. Local media coverage helps here too, and I said on the episode it "is huge for this." If you're working out how to get ChatGPT to recommend your business and you run a practice built on one or two people, start with their names. ### **Test the Way Your Customers Actually Find You** Chris warns that results pulled through the API come out "wildly different" from what a person sees in the browser. His fix is the one Linkifi used: an incognito browser with memory off, so the answer looks like what a stranger would get. Before you spend weeks on how to get ChatGPT to recommend your business, check which platform actually sends you traffic. Chris said some of his finance clients get far more visits from X than from ChatGPT, though he expects ChatGPT to lead for the majority of businesses. On Google's AI Mode and Claude, his honest answer was "I don't know." ### **Work the Steady Sources Now, Build the Brand for Later** I told Chris that SEO has always been black hat at its core, a game of manipulating Google, and AI search is no different. Short to midterm, work the lists ChatGPT already trusts. Long term, the most durable answer to how to get ChatGPT to recommend your business is Chris's Nike example: decades of trust are why the brand gets recommended for trainers. ### **How to Get ChatGPT to Recommend Your Business FAQs** #### **How do I get ChatGPT to mention my business?** Get listed on the pages ChatGPT already reads for your buyers' questions. Run them in a private browser several times, note the sites in each answer's sources, and claim the directories and industry lists you're missing. In Linkifi's study, directories plus "best of" roundups made up 61% of all citations, so they're the first place most local businesses should look. #### **Can you pay ChatGPT to recommend your business?** You can pay for ads in ChatGPT. OpenAI's self-serve Ads Manager opened as a beta for US advertisers on May 5, 2026, and OpenAI says its ads are clearly identified and don't influence the answers, so paying doesn't buy a recommendation. Earning one still runs through the sites ChatGPT reads, such as directories, "best of" lists and local press. #### **How do I get my business ranked on ChatGPT?** There's no fixed rank to win, and the Linkifi research never tracked which businesses ChatGPT named. Its figures describe how stable ChatGPT's cited sources are: the first website cited matched day one's on only 36% of days, and 7 in 10 day-one sources were still cited three weeks later once randomness was removed. Judge your own visibility across many runs over weeks. #### **Why did ChatGPT recommend my competitor instead of me?** Ask it. Chris suggests naming your firm and asking something close to "why did you not recommend my law firm?" ChatGPT will list reasons, such as the competitor sitting in trusted directories or having a quoted lead professional. Treat them as a rough roadmap, check them against the cited sources, and re-test, since a model's explanation may not match how it chose. --- ## Is ChatGPT Pro Worth It for Marketers After DevDay? URL: https://ryandoser.com/is-chatgpt-pro-worth-it/ Markdown: https://ryandoser.com/is-chatgpt-pro-worth-it.md Published: 2026-10-02 | Updated: 2026-10-05 Categories: AI Rabbit Holes > Is ChatGPT Pro worth it after DevDay? Claude Max is the better primary plan for most marketers, and ChatGPT Pro still earns a spot as a second plan. **Is ChatGPT Pro worth it** after OpenAI DevDay? As your only plan, not anymore: the $200 tier now buys less, Claude Max is the better $200 for knowledge work, and the entry Pro tier still earns a spot as a second plan. ### **Is ChatGPT Pro Worth It? Our DevDay Recap** Aaron and I recorded this episode of AI Rabbit Holes on October 1, two days after OpenAI's DevDay keynote. Aaron spent at least nine months telling people the $200 ChatGPT Pro plan was the best value in AI. While he watched the DevDay announcements, he signed up for Claude Max. If you want the files that make switching between vendors a one-afternoon job, my **[Claude Code Skills Stack](https://skills.ryandoser.com)** is the same set of skills I run every day. ### **What DevDay Changed on the ChatGPT Pro Plans** On September 29, 2026, OpenAI changed what the money buys, and the price tags barely moved. - ChatGPT Pro is now three plans: Pro 100 at $100, Pro 200 at $200 and a new Pro 500 at $500 a month. Plus stays at $20. - New Pro 200 subscriptions get "a lower usage allowance than previously offered," per [OpenAI's Pro help page](https://help.openai.com/en/articles/9793128-about-chatgpt-pro-tiers). The price stays at $200. - Existing Pro 200 subscribers keep the old allowance through October 29, 2026, then move to the lower one. - Pro 500 gets the highest allowance, 25 times what Plus includes, plus Ultrafast mode, according to [OpenAI's DevDay recap](https://openai.com/index/devday-2026-recap/). I pulled up the upgrade card in my own account while we recorded. Look at what changes between the three tiers. *The three Pro tier cards in my ChatGPT account on October 1, 2026. Every feature line but one matches, and none shows a usage number. Check the live page before you buy.* The headings change from "Standard usage" to "More usage" to "Maximum power," and one feature line moves from "More" to "Faster" to "Fastest Work and Codex." Every other feature line matches, down to the dots agent and the 100 GB of storage. Is ChatGPT Pro worth it at $200, then? The card can't tell you, because none of the three prints a usage number. Aaron put it best when I compared the change to a bag of chips: "There's just more air and fewer chips." Same bag, same price, less inside. That line later became a test case, when my editor and my AI intro skill each turned it into a visual. Here is [a side-by-side of the two edits](/ai-video-editing/). #### **One correction to what we said on the recording** On camera, Aaron said the $200 plan now gets "a quarter of the use" it used to. OpenAI has not published a number for the new Pro 200, so nobody can check that fraction yet. What we do know: before DevDay, OpenAI's own help page listed the $200 plan at 20 times the Plus allowance. Today it says only that Pro 200 includes more usage than Pro 100. Aaron's bigger point was that "the only reason to upgrade to five hundred is to get back to the rate limits that your two hundred plan used to be." The published numbers back him up, since the only tier OpenAI now lists above the old $200 plan is Pro 500, at 25 times Plus. My read is that OpenAI is pulling subscription value closer to what the same usage costs on the API. Aaron's version: OpenAI was the best value in AI "until this week." #### **Who Pro 500 is actually for** Almost nobody, as a daily plan. Its headline feature is Ultrafast, which OpenAI says runs up to 8x faster in Codex. The fine print matters more. OpenAI's help page says Ultrafast uses your included allowance at 8 times the normal rate. Real work also waits on tool calls, file reads and web fetches, and none of that gets faster. I'd save Ultrafast for a real deadline and leave it off the rest of the time. Aaron also warned about drain. He says he saw people burn "the entire $500 a month plan limit" in about 30 minutes on Astra, a model he calls very token hungry. His explanation is that Pro plans have no five-hour limit, which OpenAI's own pricing docs confirm, so nothing pauses a heavy session partway through. Claude Max resets a session limit every five hours. ### **ChatGPT Dots Is Not a Reason to Upgrade** Is ChatGPT Pro worth it just to get a dot? Aaron tested one so you don't have to. "You need a hundred dollar or higher plan to get access to one dot, do not subscribe to that just for a dot if you were having FOMO from that. I'm telling you right now, it's not worth it." A dot is an always-on agent inside ChatGPT, powered by GPT-6 Astra, with its own computer in the cloud. [OpenAI's launch post](https://openai.com/index/introducing-dots/) says your first dot is included in Pro or Business Premium, with more dots coming "in the future." *Aaron's dot showing its own cloud computer during the October 1 recording, with apps like Blender and GIMP already on the desktop.* He set his up, tried one of everything, called it from the ChatGPT app and then stopped using it. His summary: "rough around the edges and kind of janky." Aaron called the cloud computer its biggest unique feature. He explained that you can take over its screen and type a password yourself for a job like booking a flight. Even so, his bigger complaint is that it does nothing you couldn't already do in Codex. It's a new form factor around the same tools. I haven't tested a dot myself yet. From the outside, it looks like a glorified Codex session that runs 24/7. #### **The dots details buyers miss** - Plus does not include dots, and Pro users in the EEA, Switzerland and the UK can't get one at launch. - OpenAI's release notes say dots usage won't count toward eligible Pro plan allowances for the first month, with usage terms to follow after that. - Tasks your dot starts in Codex or ChatGPT Work already draw down your limits today. - The "call your dot" feature is a phone button inside the ChatGPT app. Your dot cannot call you at launch. Aaron's read on that free first month is what you'd expect: "Here's the free sample, get you hooked, and now you're gonna pay next month." Dots is also plural, but you can only make one, while [Grok Bot](/is-grok-bot-worth-it/) already lets Aaron run separate bots for separate jobs. I still expect a polished version to win over people who want official integrations, given time. Aaron dug into where a dot's proactive nudges come from. Per Aaron, it runs on a prompt called Heartbeat Dreamer, where a parent agent works with a child "dreamer" agent that scans your calendar, email and projects. He published that prompt with a [step-by-step guide to building your own dot in Claude](https://aaronmakelky.com/blog/chatgpt-dots-in-claude). You can try the same setup on a Claude plan before paying $100 a month for ChatGPT Pro. #### **What about ChatGPT Space?** DevDay also launched ChatGPT Space, a shared workspace where teams collaborate with AI, on Pro, Business and Enterprise plans. To me, Space is an ecosystem play aimed at Google Drive and Notion, while Anthropic is betting on the better model. Before you move your team's files in, Aaron asks whether you trust OpenAI to support it long term. OpenAI is already retiring [custom GPTs on December 11, 2026](/chatgpt-projects-vs-custom-gpts/) and pointing builders to plugins. My advice from the episode applies here too: "just create skills, use an IDE and call it a day." Space alone doesn't justify a bigger plan, and skill files you own still work after a vendor retires a product. ### **Why Claude Max Is the Better $200 Right Now** Two weeks ago I published a [ChatGPT Pro vs Claude Max comparison](/chatgpt-pro-vs-claude-max/) that leaned toward OpenAI on plan math. At the time, Aaron had no Claude subscription at all. Here is what I said this week, word for word: "A $200 a month Claude Max plan is far better than a $200 a month ChatGPT Pro plan now, which is a complete 180 of what I was telling people a week or two ago." Is ChatGPT Pro worth it as your only plan? Not anymore, for two reasons. OpenAI cut what the $200 buys, and Anthropic shipped two models that are worth the usage. My take on the episode was that Opus 5.5 is the best AI model right now "for most people," with the hedge that I meant knowledge work, not coding. Claude Sonnet 5.5 shipped on September 28 and is now my workhorse. Since signing up, Aaron has used Opus for planning and design and Sonnet for day-to-day tasks. His first reaction to Sonnet was "it's really fast." He also said Opus "blows the OpenAI models out of the water" on anything visual, from landing pages to website animations. Three friends texted him that week asking for the one-sentence answer on all the new releases. His answer was "Don't get an OpenAI sub." Then, to me: "I haven't said that since at least February of 2026 to anybody." [Claude Max](https://support.claude.com/en/articles/11049741-what-is-the-max-plan) costs $100 for 5x or $200 for 20x the Claude Pro plan's per-session allowance. Anthropic has not announced a change to Max like the one OpenAI made to Pro 200. I don't expect that to last. If a $500 Claude plan and a smaller $200 one show up in a few months, I won't be surprised, which is why my advice on the episode was to get Claude Max now and use as much of it as you can. One way I stretch my plan is a markdown file built from Opus 5.5's best outputs plus Anthropic's own documentation. A rule in my workspace tells Sonnet to read it first, so more daily work runs on Sonnet and my Opus usage lasts longer. ### **Why I'm Keeping ChatGPT Pro at the Entry Tier** None of this means I'm canceling ChatGPT. I'm on Pro 100, and that is where I'm staying. Is ChatGPT Pro worth it as a second plan? For me, yes, because every model in my setup has a job written down in the AGENTS.md file that runs my workspace. *The models section of my AGENTS.md on October 1, 2026, the day I moved the gatekeeper role to GPT-6.1 Sol.* - Daily driver: Claude Opus 5.5, for planning, drafting and anything a client sees. - Workhorse: Claude Sonnet 5.5, for SERP pulls, competitor reads, web fetches and data summaries. - Gatekeeper: GPT-6.1 Sol at high reasoning, run through the Codex CLI, which red-teams whatever a Claude model produces. Image generation is the other job that keeps me on OpenAI. Neither job needs more than the entry Pro tier. Red-teaming goes to OpenAI because a critic from another model family catches what a Claude reviewer misses. OpenAI's models are still strong enough for the job, and Sol's landing page in my model test surprised me. Aaron's take is that Sol is the model the new limits push you toward. OpenAI prices it at one-fifth of Astra's token rates. In his first two days with it, Sol made the new limits go much further, at the cost of speed. Aaron clocked it at 20 to 30 tokens per second, which he puts at half his usual pace or slower. His rule of thumb from his own workload: past four or five Codex projects at a time, Pro 100 runs out on anything but Sol. *The buying decision after DevDay. Start with the plan you will actually use up, then add a second only for a specific job.* I walk through the full routing logic in [which Claude model to use for which job](/which-claude-model-to-use/). ChatGPT Pro still has things Claude doesn't. Aaron likes OpenAI's plugins, voice mode and image model, and he finds Anthropic's desktop and phone apps half-baked next to them. His tiebreaker is the one I agree with: "If I don't get a good model at usable rate limits, what good are all those extra add-ons?" ### **Buy the Plan You Will Actually Use Up** So, is ChatGPT Pro worth it now? For most marketers buying one AI subscription, no. For writing, research and client work, my bet is that Claude Max gets you more of a better model for the same $200, at least until Anthropic reprices it. Next to Claude Max, the entry Pro tier still earns its spot in my setup for red-teaming and images. Upgrading for dots or Ultrafast is the move I'd skip. ### **Is ChatGPT Pro Worth It FAQs** #### **Is ChatGPT Pro 500 worth it?** For most people, no. Pro 500 costs $500 a month and gives you 25 times the Plus allowance plus Ultrafast mode. Ultrafast uses your included allowance at 8 times the normal rate, and real tasks still wait on tool calls, so the speed you feel is smaller than the headline. It makes sense only if Pro 200 limits block paid work every week. #### **Do you need ChatGPT Pro to use dots?** Yes, or Business Premium, and Enterprise workspaces can switch on a beta. Plus does not include dots. Your first dot comes with Pro, which starts at $100 a month. Dots usage doesn't count toward your plan allowance for the first month, but tasks a dot starts in Codex or ChatGPT Work still draw down your limits. Pro users in the EEA, Switzerland and the UK can't get dots at launch. #### **Did OpenAI cut ChatGPT Pro 200 usage?** Yes, for new subscribers right away and for existing ones after October 29, 2026. The price stays $200, but new Pro 200 subscriptions get a lower allowance than before. The old plan was listed at 20 times Plus, and OpenAI has not published a number for the new one, so treat Aaron's on-air figure of "a quarter of the use" as unverified. #### **Is Claude Max better value than ChatGPT Pro right now?** For knowledge work, that is where Ryan Doser and Aaron Makelky both landed after DevDay. Claude Max costs $100 for 5x or $200 for 20x the Claude Pro per-session allowance, with Opus 5.5 and Sonnet 5.5 included. If your work depends on OpenAI's image model or plugins, keep the entry ChatGPT Pro tier alongside it, which is what Ryan does. --- ## How to Track AI Visibility in ChatGPT (Stop Guessing) URL: https://ryandoser.com/how-to-track-ai-visibility/ Markdown: https://ryandoser.com/how-to-track-ai-visibility.md Published: 2026-10-01 | Updated: 2026-10-01 Categories: AI Rabbit Holes > One AI answer is a snapshot. Here is how to track AI visibility across ChatGPT, Perplexity and Google, then confirm it with new customers. One prompt ranked a SaaS brand #1 in an AI answer one day and #8 the next, and that swing is where **how to track AI visibility** really starts. A single answer is a snapshot, so the job is tracking the trend across engines and checking it against what new customers say. ### **Watch Besmir Bregasi Break Down How to Track AI Visibility** This episode of AI Rabbit Holes is a conversation with [Besmir Bregasi](https://www.linkedin.com/in/besmirbregasi/), Chief Growth Officer at [ZeroRank](https://zerorank.ai/), an AI search visibility platform. ZeroRank is where he works, so weigh his tool claims with that in mind. He flagged it himself on the recording with "obviously I'm biased." One correction worth making: I introduced him as ZeroRank's founder, which was my mistake. He runs growth there, says he invested in the company, and still runs a few other SaaS products of his own. If you want to turn what you learn from tracking into content, my **[Claude Code Skills Stack](https://skills.ryandoser.com)** includes the research and content skills I run for clients. ### **Same Prompt, Ranked Anywhere From #1 to #8** A single AI answer depends on "many, many things," Besmir said, which is why he samples across browsers, IPs and profiles. His screen share showed the variance, with his dashboard set to the last seven days, two AI models, and only the runs that mentioned AdPlexity Social, a Meta ads tool he owns. *Besmir's ZeroRank dashboard tracking AdPlexity Social, newest run first: the same prompt ranked #8, #1, #6, #8 and #5 in the runs that mentioned the brand.* That view listed five runs of one prompt, "Top alternatives to popular Meta ad spy tools." Oldest to newest, the brand ranked #5, #8, #6, #1 and #8. Even the number of sources behind each answer moved, from 4 to 9. Nothing about the prompt changed between runs. The filter hides runs that left the brand out, so the total run count isn't on screen. Treat it as the noise inside one prompt over one week. What Besmir calls statistical significance is his fix. Run the same prompts many times, across browsers, IPs and profiles, and track the share of answers that mention you. If you are working out how to track AI visibility for your own brand, start there and never report a single run. My roundup of [AI visibility tools and what they actually measure](/best-ai-visibility-tools/) makes the same sampling point with a Perplexity test. Chris Panteli later put a number on that noise. In [Linkifi's three-week study of ChatGPT's sources](/how-to-get-chatgpt-to-recommend-your-business/), re-asking the same question minutes later changed 60% of the sources. ### **How to Track AI Visibility as a Trend, Engine by Engine** So how do you read a number that changes every day? Besmir compares it to a body fat scale, which jumps with how much water you drank but shows the real direction over three months. Besmir's other rule is that you cannot treat AI search as one thing. "A lot of brands will show in one and won't show the other," he said, because each engine leans on different sources. From what he has seen across ZeroRank's clients, Perplexity pulls a lot from Reddit and news sites, Google's AI Overviews from Google's own results, and Grok from X. He also said ChatGPT gets a lot from Bing. I'd hold that one loosely. OpenAI's [ChatGPT search help page](https://help.openai.com/en/articles/9237897-chatgpt-search) says it sometimes partners with other search providers without naming them, and I dug into why the ChatGPT answer is contested in [which search engine each AI actually uses](/what-search-engine-does-claude-use/). Either way, test each engine separately and expect them to disagree. In [my field test of four AI assistants on 12 local questions](/research/does-chatgpt-recommend-local-businesses/), they never once all listed the same business first. Here is what AI search visibility looks like as a trend. Besmir showed the monthly report for AdPlexity Social, his own product measured in his own tool, so read it as an example of the format only. *ZeroRank's AdPlexity Social report: a 38% visibility card, a #3.4 average rank, and monthly visibility climbing from 3% in April 2026 to 26% in September.* Visibility rose every month, from 3% in April to 26% in September. The 38% card on top is the percentage of tracked AI responses that mentioned the brand over a shorter, more recent window. Average rank swung over the same months, from #3.8 in April to #4.1, #3.9, #3.6 and #2.5, then back to #3.3 in September. Visibility share is the number that moved in one direction, and it is the metric Besmir called the most important one on the screen. ### **Ask New Customers How They Found You** I think most advice on how to track AI visibility stops too early, at the dashboard. Besmir ranks one method above every dashboard, and it costs nothing. He asks every new user at onboarding, and every demo call, the same question: how did you hear about us? "The single most accurate thing you can do is just ask them," he said. Tracking scripts, in his view, are "never gonna work." A buyer might see you in one place, read a review somewhere else, and finally come straight to your site. I still call attribution the devil of marketing, especially in a zero-click era. A direct answer from the buyer gets closer than any dashboard. Two guests from different companies have now landed on the same fix. Sam Dunning asks on forms, signup, demo flows and again on sales calls, as he explained in our episode on [measuring SaaS SEO when attribution is a mess](/saas-seo/). Asking also tells you which engines your buyers name. In Besmir's post-signup surveys across his own SaaS products, buyers named ChatGPT and Perplexity, and he said "usually these people convert best." "I don't know why," he added, and he rarely heard Claude named, which he thought might come down to his sample. My guess on ChatGPT is context: people write long, detailed prompts there, so they tend to arrive mid-to-bottom funnel, while a quick Google search is usually top-of-funnel research. The dashboard shows direction, and your customers confirm it. *The tracking loop: run the same prompts on every engine, watch the trend, confirm it with new customers, then keep what moved it.* Besmir's loop from there is short. Make a change, track it properly, double down on what worked and drop what didn't. For a rough second signal, Besmir pointed to Google Search Console, which has offered a [Generative AI performance report](https://support.google.com/webmasters/answer/16984139) for AI Overviews and AI Mode to all websites since August 31, 2026. His example was bottom-of-funnel pages, like competitor alternatives. If those pages show up in AI Overviews, he reads it as buyers in the final stage, and he called the rest of the measurement options "not accurate or noise." If you want a manual version first, the monthly ask-the-models check in my [AI SEO strategy](/ai-seo-strategy/) runs in a spreadsheet. Run each prompt more than once, for the reason the screenshot above shows. ### **What to Do When Competitors Outrank You in AI Answers** Once you know how to track AI visibility, the next question is why five competitors sit above you. The manual step Besmir gave is to open the answer, read the sources it cites, and reverse engineer them. That shows you which pages the engine trusted over yours. He said ZeroRank's suggestions make the job "way easier," a claim about his own product. *The seven sources behind one ChatGPT answer in Besmir's dashboard, tagged utm_source=chatgpt.com. Most are "best tools" and "alternatives" listicles, including adplexity.io's own.* Most of those seven sources were "best tools" and "alternatives" posts. One was AdPlexity's own alternatives post, so own-site listicles clearly can get cited. Besmir said listicles on your own site tend to work, mainly in low-competition niches. His analogy for why offsite usually wins is a company of 30 people. Ask one employee how their performance is and they'll say it's good. Ask their colleagues and you get a much better picture. "Offsite is always going to win compared to whatever you post on your own site," he said, then added, "It doesn't mean you shouldn't." In his view, your pages still count, they just carry less weight than what other people say about you. These are the offsite signals he sees carrying the most weight: - YouTube, weighted more on a trusted channel or a video with a lot of views and shares - Reddit, which he still sees as a very strong source - Trustworthy news sites and editorial coverage - Trending fast on one channel, such as X Besmir also says speed counts, because more mentions in a short window carry more value than the same mentions spread out. In competitive niches, he added, the story has to match everywhere, from your website to Reddit, G2 and Trustpilot. I'd add that YouTube is the ultimate parasite in the age of AI search. Technically you could be cited without having a website at all, from a YouTube channel, a conference talk or a book. The opposite move is spinning up a thousand programmatic pages, advice I see everywhere and that honestly infuriates me. Besmir's take was that it can work in very low competition niches but isn't a long-term strategy. ### **Stop Grading Your Brand on One AI Answer** Pick a fixed set of buyer prompts, run them in each engine, and judge the results over months instead of days. Then add "how did you hear about us?" to your signup flow, because that answer is what ties tracking to revenue. That is how to track AI visibility without guessing, and the first step is as small as running each buyer prompt more than once. ### **How to Track AI Visibility FAQs** #### **How do you measure AI visibility?** Measure the share of AI answers that mention your brand across a fixed set of buyer prompts, run repeatedly on each engine. That share, often called AI share of voice, is steadier than any single rank. Pair it with a "how did you hear about us?" question at signup, so you learn which engines actually sent buyers, the way Besmir's own surveys pointed to ChatGPT and Perplexity. #### **Why does my brand's ChatGPT ranking change every day?** Each answer is generated fresh from whatever sources the engine pulls that time. In Besmir Bregasi's dashboard, one prompt ranked anywhere from #1 to #8 within a single week, and the number of sources behind it ranged from 4 to 9. Report weekly or monthly averages instead of daily ranks, or you will end up reacting to noise. #### **Is an AI visibility tracker worth paying for?** Only if you will act on the trend. A tracker earns its cost when you make a change, watch whether visibility moves over the following weeks, and keep what worked. Besmir, who works at ZeroRank, calls it money well spent. Until you are ready to act, a manual monthly check in a spreadsheet is enough. #### **Can Google Search Console show AI Overview traffic?** Partly. Google says it rolled out a Generative AI performance report in Search Console to all websites as of August 31, 2026, counting AI Overview and AI Mode impressions by page, country and device. It does not show clicks, positions or the queries behind them, so use it to spot which pages AI features surface, and judge revenue on signups and what new customers say. --- ## How to Generate AI Videos in Claude Code (Seedance, Veo, Kling) URL: https://ryandoser.com/claude-code-ai-video/ Markdown: https://ryandoser.com/claude-code-ai-video.md Published: 2026-09-30 | Updated: 2026-09-30 Categories: Claude Code > How to generate AI videos with Claude Code using OpenRouter and models like Seedance 2.0, Veo, and Kling. Full workflow explained. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* This guide shows you exactly how to generate a **Claude Code AI Video** using OpenRouter and models like Seedance 2.0, Veo, and Kling, all without leaving the terminal. ### **How to Generate AI Videos in Claude Code with OpenRouter** You've probably bounced between four different AI video apps just to get one usable clip. That stops once you wire [OpenRouter](https://openrouter.ai) into Claude Code. I tested this with a 10-second NYC drone flyover using ByteDance's Seedance 2.0. The output came back inside the same Claude Code session I use for everything else, no separate tab, no second login. If you want the same Short Video Creator skill I used in the demo, my **[Claude Code Skills Stack](https://skills.ryandoser.com/)** ships with it plus 20+ more marketing skills. *OpenRouter's Models page lists every Claude Code AI video option in one place, including Kling, Seedance 2.0, and ByteDance.* OpenRouter acts as one API key for most of the major video models. ByteDance Seedance 2.0 and 2.5, Google Veo 3.1, Kling 3.0, MiniMax Hailuo, Sora 2 Pro, and Alibaba Wan all live behind a single endpoint. You can browse the full list on the [OpenRouter video models page](https://openrouter.ai/collections/video-models), and pricing scales with the length and resolution of the clip. When a new model shows up in that catalog, calling it is a slug change in your prompt, not a new setup. ### **Setting Up OpenRouter for Claude Code AI Video Generation** Five minutes of setup buys you every video model from one key. Here's the exact flow I use to generate AI videos in Claude Code: - Sign up free at OpenRouter - Add 10 to 15 dollars in credits since video generation costs more than text - Create an API key under the API Keys tab and name it something like claude-code-test - In your project root, create an APIs.env file and paste the key inside - Reference that file in any Claude Code prompt that needs video That's the whole connection. Claude Code reads the key, calls the model you specify, and writes the file back to your project. Rotate the key every few months as a security habit. If you've never paired Claude Code with marketing workflows before, my breakdown on [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) walks through the bigger picture. ### **Running Seedance 2.0, Veo, and Kling Through Claude Code** One Claude Code session can call Seedance, Veo, and Kling without any extra plumbing. *The prompt that kicks off a Claude Code AI video using the Short Video Creator skill and the OpenRouter API key.* For my test I used my Short Video Creator skill with this prompt: find something trending on TikTok, make a 10-second AI video, no text, realistic, use Seedance 2.0. I pasted the [Seedance 2.0 model page](https://seed.bytedance.com/en/seedance2_0) so the skill could confirm the exact slug. Want a different model? Swap Seedance 2.0 for [Veo 3.1](https://aistudio.google.com/models/veo-3) or [Kling](https://kling.ai/) in the same prompt. Same workflow, different output style. That is the entire point of routing through OpenRouter. *A 10-second NYC drone flyover generated through Claude Code using the Seedance 2.0 model via OpenRouter.* The 10-second NYC drone clip cost $1.51 to generate. Quality was solid for B-roll. Realism held up at full screen on a 27-inch monitor, which is a higher bar than most demo clips clear. I have since used Veo 3.1 Fast for the B-roll in a real podcast intro, and getting it right took eight versions. My [full AI podcast editing breakdown](/ai-video-editing/) covers what broke along the way. ### **What Claude Code AI Video Can and Can't Do Yet** Is the output good enough to post on social media today? Honest answer: not on its own. The first test I ran was a Fruit Love Island trend clip with no music and no captions. Visually fine. But a silent 10-second video with no overlay does not perform on Reels or TikTok. What works right now: - Drone B-roll, scenery, product shots, abstract motion - Short clips, since Veo 3.1 stops at 8 seconds and Seedance 2.0 and Kling 3.0 at 15, which covers most B-roll - Native sound, which Seedance 2.0, Veo 3.1, Kling 3.0, and Sora 2 Pro all generate now - Footage you'll edit afterward in CapCut, Descript, or Premiere What doesn't: - Your own music track or voiceover, which still goes on in an editor or a follow-up skill step - On-screen text or captions baked into the clip - Long takes, although newer models like Seedance 2.5 and Wan 3.0 now stretch to 30 seconds Pair this Claude Code AI video workflow with a captioning step and a music overlay and the output starts to compete. As the models improve, the system you built today still works. That same logic applies to [Claude Code AI marketing agents](/claude-code-ai-marketing-agents/) running other parts of your stack. ### **Connecting Blotato to Auto-Post Your Claude Code AI Video** Generate, caption, and post in one Claude Code session. Once a video is sitting on your local drive, [Blotato](https://www.blotato.com/?ref=rdoser) plugs into Claude Code via MCP and pushes the file to every social platform you've connected. Generate with Seedance, post with Blotato, all from the same chat. If you're piecing together a full [AI marketing stack](/ai-marketing-stack/), this is one of the cleanest endpoints to add. That's the long-term play. The video model will keep changing. The pipeline doesn't. ### **Ryan's Final Thoughts** The point of this isn't the Fruit Love Island clip. It's the system. As Veo, Seedance, Kling, and Sora all keep improving, anyone with a Claude Code AI video setup wired up today ships first when the next model drops. Try it on one drone clip this week and see how it feels inside your existing Claude Code workflow. ### **Claude Code AI Video FAQs** #### **How do I generate AI videos in Claude Code?** Connect OpenRouter to Claude Code with an API key stored in an APIs.env file, then prompt Claude Code to call a video model like Seedance 2.0, Veo 3.1, or Kling. The model returns a video file Claude Code saves to your project. The full setup runs in under five minutes. #### **Which AI video model is best inside Claude Code?** When I tested in April 2026, Seedance 2.0 from ByteDance was the strongest realism option, Veo 3.1 handled cinematic motion well, and Kling was a solid third for stylized output. Newer models have landed on OpenRouter since, including Seedance 2.5, Kling 3.0, and Wan 3.0, and those have not gone through the same test. OpenRouter lets you swap between them with a single prompt change, so run your own scene through two or three before you commit. #### **How much does a Claude Code AI video cost?** Around $1.50 per 10-second clip on Seedance 2.0, which is what my test clip cost. Seedance is priced by video tokens, so higher resolutions and longer clips cost more, and every model prices differently. Veo 3.1 runs $0.40 per second with audio and Sora 2 Pro $0.30 to $0.50 per second, so both sit on the higher end. Add at least 10 to 15 dollars in OpenRouter credits before testing so you don't run out mid-generation. #### **Can Claude Code generate AI video with audio or captions?** Audio, yes. Seedance 2.0, Veo 3.1, Kling 3.0, and Sora 2 Pro all generate native sound through OpenRouter, and at standard resolution Veo 3.1 costs half as much per second with audio turned off. Captions are still a separate step. Add captions and your own music in an editor like CapCut or Descript, or use a Claude Code skill to overlay them in a follow-up step before posting. --- ## How to Use Any AI Model in Claude Code (OpenRouter) URL: https://ryandoser.com/claude-code-openrouter/ Markdown: https://ryandoser.com/claude-code-openrouter.md Published: 2026-09-30 | Updated: 2026-09-30 Categories: AI Tutorials, Claude Code > Learn how to set up OpenRouter in Claude Code to access GPT, Gemini, and other AI models from one API key. Step-by-step tutorial. This guide walks you through setting up **Claude Code OpenRouter** so you can get second opinions from GPT, Gemini, and dozens of other AI models without leaving your terminal. ### **How Claude Code OpenRouter Actually Works** Most people rely on a single AI model for everything. That approach leaves blind spots, especially for high-stakes work like [landing page copy or email subject lines](/best-ai-models-for-marketing/). [OpenRouter](https://openrouter.ai/) acts as a middleman between Claude Code and every major AI provider. One API key gives you access to GPT, Gemini, DeepSeek, Perplexity, and dozens more. No juggling 10 different API dashboards. No managing separate credentials for each provider. When I recorded this, I used the setup daily to cross-check marketing outputs against GPT 5.4 and Gemini 3.1 Pro. The results often surfaced recommendations that a single model missed entirely. Both models are still on OpenRouter, next to newer releases like GPT-6 Sol. *OpenRouter's model catalog gives you access to hundreds of AI models from a single API key.* ### **Setting Up Your OpenRouter API Key in Claude Code** Before OpenRouter rolled out, getting access to other AI models meant visiting Google AI Studio for Gemini credentials, then OpenAI's platform for GPT access, then repeating that process for every provider you wanted. OpenRouter collapses all of that into a single connection. Here's the OpenRouter API setup process: - Create a free account at openrouter.ai - Click Settings, then add credits ($5-$10 is plenty to start) - Go to API Keys and click Create - Copy the generated key Once you have the key, open Claude Code and tell it to save the OpenRouter API key in your APIs.env file. Storing credentials in an environment file is more secure than pasting raw keys into chat. This matters if you scale your setup or share configurations with a team. After that single connection, you can pull models from any provider OpenRouter supports. They add new options constantly, so you always have access to the latest releases. ### **Real Examples: Using GPT and Gemini Models in Claude Code** Talk is cheap. Here's how I actually use other AI models in Claude Code for real marketing work. #### **Landing Page CRO Analysis** I ran my [Claude Code Skills Stack](https://skills.ryandoser.com/) landing page through a crosscheck skill that queries GPT 5.4 and Gemini 3.1 Pro simultaneously. GPT scored the page 4.8 out of 10. Both models agreed on the biggest gaps: a product-first headline instead of benefit-first, zero testimonials, and no urgency. The synthesis from Opus 4.6 pulled the best insights from each model and gave me five specific fixes. Rewrite the headline around outcomes. Add three to five testimonials. Build in urgency. Reorganize sections by outcome category. Those fixes came from combining perspectives across three different AI providers. #### **Email Subject Line Testing** For my weekly newsletter, I generated subject lines with Claude Opus 4.6 first. Then I ran those through the crosscheck to get alternatives from GPT and Gemini. GPT suggested "Goodbye to My AI Tool Stack" with a predicted 49-52% open rate. Gemini offered "The Claude Feature Marketers Are Sleeping On." Neither model produced perfect output. But having three sets of options from different AI architectures gives me a broader pool to pick from. That kind of cross-referencing catches angles a single model would never surface on its own. *Claude Code synthesizing email subject line recommendations from GPT 5.4 and Gemini 3.1 Pro.* ### **Checking API Costs and Logs in OpenRouter** One concern with using Claude Code multiple AI models is cost management. OpenRouter makes this transparent. Click your profile icon, then select Logs to see every API call with timestamps and pricing. In my usage at the time, GPT 5.4 ran about 3 cents per request and Gemini 3.1 Pro roughly 4 cents. My [YouTube thumbnails and marketing images](/nano-banana-claude-code) also ran through OpenRouter, on Google's Nano Banana 2 model at about 7 cents per image. If you plan to scale this across multiple workflows, keep an eye on which models you call most frequently. The cheaper models work fine for brainstorming and initial drafts. Save the premium options for final quality checks where the extra cost justifies the output. ### **Why You Should Use Other AI Models in Claude Code** Every AI model has a different training dataset, architecture, and set of strengths. Claude writes excellent long-form content and follows [brand voice instructions](/claude-skills) better than anything else I've tested, and Opus 5.5 is the [Claude model I write with now](/best-claude-model-for-writing/). But GPT handles certain analytical tasks differently. Gemini brings a distinct perspective on technical topics. Running outputs through multiple models is like getting feedback from three senior marketers who trained at different companies. They catch each other's blind spots. For high-stakes deliverables like email campaigns, ad copy, or landing pages, that second opinion can be worth hundreds or thousands of dollars in conversion improvements. You could also add DeepSeek, Grok, or any other model available on [Claude Code's MCP ecosystem](/claude-code-mcps). The setup stays the same. One API key, multiple perspectives. ### **Can You Run Claude Code Itself Through OpenRouter?** Yes, and it is a different setup from everything above. The workflow in this post keeps Claude as the main model and calls GPT or Gemini for second opinions. The other option sends Claude Code's own requests through OpenRouter. [OpenRouter's official Claude Code guide](https://openrouter.ai/docs/cookbook/coding-agents/claude-code-integration) has you add three lines to your shell profile (for example `~/.zshrc`), with your OpenRouter key already saved as `OPENROUTER_API_KEY`: - `export ANTHROPIC_BASE_URL="https://openrouter.ai/api"` - `export ANTHROPIC_AUTH_TOKEN="$OPENROUTER_API_KEY"` - `export ANTHROPIC_API_KEY=""`, left empty on purpose to prevent conflicts Use your shell profile, not a project .env file, because the native Claude Code installer does not read .env files. Reload the profile or open a new terminal so the values take effect. If you were logged in with an Anthropic account before, run /logout once, relaunch, and confirm the connection with /status. Read the fine print before you switch. OpenRouter says this setup is only guaranteed to work with the Anthropic first-party provider, and that Claude Code is optimized for Anthropic models and may not work correctly with other providers. So for most marketers already paying for a Claude plan, the second-opinion setup above is the better use of OpenRouter. ### **Final Thoughts from Ryan** Setting up OpenRouter in Claude Code takes about five minutes and costs almost nothing to run. The payoff is access to every major AI model from a single terminal session. I use this daily for content creation, landing page optimization, and email marketing. If you're only getting opinions from one AI provider, you're leaving insights on the table. Try cross-checking your next important deliverable and see what surfaces. ### **Claude Code OpenRouter FAQs** #### **How much does OpenRouter cost to use with Claude Code?** OpenRouter bills by token usage, and every model has its own rate. In my use back in March, GPT 5.4 came to about 3 cents per request and Gemini 3.1 Pro to around 4 cents. At those rates, $5-$10 in credits covers somewhere between 125 and 330 requests. #### **Can I use OpenRouter and Claude's built-in models at the same time?** Yes. For the second-opinion workflow in this post, OpenRouter supplements your existing Claude subscription. Claude stays your primary model, and Opus 5.5 is the Claude Code default on every paid plan. OpenRouter adds access to GPT, Gemini, and other providers for cross-checking and second opinions. #### **What AI models are available through OpenRouter?** OpenRouter supports hundreds of models across every major AI provider. They continuously add new releases as they become available. You can browse the full catalog at openrouter.ai/models. #### **Is it safe to store my OpenRouter API key in Claude Code?** Store it in an environment file (APIs.env) rather than pasting it directly into chat. Environment files keep credentials separate from your conversation history and are a standard security practice for API key management. --- ## 7 Best Outrank Alternatives for AI SEO Optimization (With Pricing) URL: https://ryandoser.com/outrank-alternatives/ Markdown: https://ryandoser.com/outrank-alternatives.md Published: 2026-09-30 | Updated: 2026-09-30 Categories: AI Tool Reviews > Seven Outrank alternatives for AI SEO, priced from live rate cards with monthly billing, plus which ones still trade backlinks for you. Most of page one for **Outrank alternatives** is written by companies selling you one of the alternatives. I pulled the results on September 3, 2026 and checked each one: ContentMonk ranks ContentMonk first, RightBlogger ranks RightBlogger first, RankUp ranks RankUp first, and Outrank publishes its own roundup of its competitors. The exceptions are directory pages like G2, which rank without a horse in the race and without telling you much. I sell no auto-publishing SEO tool, so I have nothing to move you toward. What I do sell is the AI SEO work itself, which is why I care whether these things actually earn citations rather than just publishing volume. ### **Three Things Most of These Roundups Skip** Three things decide whether you should leave Outrank. A few reviews cover one or two of them. The vendor roundups ranking for this term mostly do not. The first is what its customers say. Outrank's Trustpilot profile sits at **3.7 out of 5 across 87 reviews**, 81 of them in the past twelve months. Trustpilot notes the company has no recent history of inviting reviews, and adds its own caveat that an uninvited pool may not be representative. Read it as what a self-selected group chose to say rather than a verdict on the customer base, and note that 87 reviews is a small sample either way. *Outrank's Trustpilot profile as captured September 3, 2026, when it read 3.3. It has since moved to 3.7. Note the 1-star bar and the reply rate on the right.* Compare that with the file Outrank publishes for AI assistants. Its [llms.txt](https://www.outrank.so/llms.txt), the plain-text brief a company writes so models describe it correctly, still ends its summary with "Rated 4.8/5 by users." Trustpilot said 3.3 the day I read both, and says 3.7 now. I covered how that gap developed in my [full Outrank review](/outrank-review/). The second is what the complaints are about. Read the one-star pool and it is barely about SEO at all. The themes that repeat most are billing and the difficulty of cancelling, sitting under a pricing page that says "Cancel anytime. No questions asked!" in bold. The third is the part that can cost you something a refund will not fix, and it deserves its own section. ### **The Backlink Question You Should Ask Every Tool on This List** Outrank's Backlink Exchange earns you credits for hosting links to other members and spends them getting links back. Google's [spam policies](https://developers.google.com/search/docs/essentials/spam-policies) name the mechanic almost word for word, listing "excessive link exchanges" and "partner pages exclusively for the sake of cross-linking" as link spam. The part that gets skipped: swapping tools does not necessarily swap the mechanic. Of the seven below, **four build links for you**. RightBlogger runs a Backlink Exchange on every paid tier. BabyLoveGrowth advertises "$800/mo in backlinks from 4,000+ partner sites" inside its base plan. Arvow puts Automatic Backlinks on its $169 Business tier rather than $69 Solo. SEObot builds backlinks to move domain rating, though it describes finding opportunities rather than a member-to-member exchange. So "I left Outrank because of the backlinks" is only true if you check the replacement. I have flagged it per tool below. ### **Outrank Alternatives Compared on Price and Article Volume** Every figure here was read from the live pricing page on September 3, 2026 with **monthly billing selected**, and rechecked on September 30, 2026, when ContentPen, Koala and Arvow had all changed. That distinction matters more than usual on this SERP. Most competing posts quote the annual rate with a "/month" suffix beside it, which is how RightBlogger gets described as $49 when month-to-month is $59, and how ContentPen appears as $79 when month-to-month is $99. | Tool | Best for | Paid plans start at (monthly) | Articles included | Own link network? | | BabyLoveGrowth | Matching Outrank feature for feature | $99/mo | 30/mo | Yes | | ContentPen | More articles than Outrank for the same $99 | $49/mo (Autopilot from $99) | 12/mo ($99 for 40) | No | | Byword | Trying auto-publishing without paying | $99/mo | 25/mo (5 free) | No | | RightBlogger | Bloggers who want tools, not just articles | $59/mo | Unlimited AI words | Yes | | Koala AI | The cheapest genuine entry point | $25/mo | 45,000 words/mo | No | | Arvow | Agencies running many client sites | $69/mo | 1,000 credits/mo (~10 per article) | Yes, from $169 | | SEObot | Founders who want zero involvement | $49/mo | 9/mo | Builds links, no exchange | For reference, Outrank is $99 a month for 30 articles, or $999 a year, which works out to $83.25 a month. ### **The Auto-Publishers That Actually Replace Outrank** These seven do what Outrank does: research, write, and push finished posts into your CMS without you touching them (on ContentPen, from the Growth plan up). They are ordered by how completely each one replaces Outrank, starting with the closest match, not by which one I would have you open first. Those are different questions, and the closer at the end answers the second one. #### **1. BabyLoveGrowth (Best for Matching Outrank Feature for Feature)** *BabyLoveGrowth leads with a 90-day money-back guarantee, which its Terms now include with narrow conditions.* The closest match to Outrank on this list, at an identical price for an identical article count. I reviewed it separately and the resemblance is not coincidental. Both sell 30 auto-published articles a month for $99 with backlinks bundled in. **Pros:** - Same 30 articles and $99 as Outrank, with a 3-day trial before you commit - A 90-day money-back guarantee, now written into its Terms, which Outrank does not offer - Tracks your brand across ChatGPT, Perplexity and Gemini, which Outrank does not do - Auto-publishes to WordPress, Shopify and eight more platforms **Cons:** - Bundles its own partner-site link network, so the Google exposure follows you over - The Reddit and Quora comment agents put your brand into threads on your behalf, which carries its own platform risk - The $247 struck-through anchor beside the $99 has been up for months, so treat $99 as the real price, not a deadline **Best for:** Someone who likes what Outrank promises and wants brand tracking and faster support replies. **Pricing:** Grow $99/month billed monthly. Scale $299/month. 25% off on annual billing. **Free trial:** 3 days, plus a 90-day money-back guarantee that pays out only if none of organic clicks, impressions or Domain Rating rises, after three paid months with every article published and publicly visible. **Bottom line:** The straightest swap if your complaint about Outrank was support rather than the link network. Read the guarantee's conditions before you count on it, because a rise in any one of three metrics voids it. Read my [BabyLoveGrowth review](/babylovegrowth-review/) before you buy either. #### **2. ContentPen (Best for More Articles Than Outrank at the Same Price)** *ContentPen's pricing page defaults to yearly billing. Annual takes 20 percent off, so the real monthly rates are about 25 percent above the numbers shown.* Run the arithmetic nobody on this SERP runs. For the $99 a month Outrank charges for 30 articles, ContentPen's Growth tier gives you 40, which is **about $2.48 per article against Outrank's $3.30**. On annual billing Growth drops to $79, or about $1.98 an article. One caveat, because these posts usually hide it. Cost per article is only clean between plans that count articles. RightBlogger sells unlimited words at $59 and Koala meters words, so either can undercut that figure depending on article length and model. Among plans that sell a fixed article count, ContentPen is the cheapest at Outrank's volume. **Pros:** - Cheapest per article at Outrank's volume among the plans that count articles - Advertises no link exchange, so you sidestep the exposure - Extra article credits can be bought as one-off packs when you run out mid-month - Publishes direct to WordPress and other content systems, with automatic internal linking **Cons:** - The pricing page opens on the yearly toggle, so the advertised numbers are not what you pay monthly - The $49 entry tier is only 12 articles, well short of Outrank's 30, and leaves out Autopilot, which starts on Growth - Unused articles do not roll over, so the allowance resets each billing cycle - Thin public review footprint next to the others here, so there is little independent signal **Best for:** Anyone who wants more articles for the same monthly bill. **Pricing:** Billed monthly, Starter $49 (12 articles), Growth $99 (40), Scale $249 (75), Agency $449 (150). Annual billing takes 20% off, which is where the $39, $79, $199 and $359 figures on its page come from. **Free trial:** Yes, 7 days on every tier, but a credit card is required to start it. **Bottom line:** The value pick if you want more articles than Outrank for the same $99, and it does it without asking you to host links for strangers. #### **3. Byword (Best for Trying Auto-Publishing Without Paying)** *Byword gives you 5 articles with no credit card, which is the cheapest way to judge output quality.* The most generous free look at the actual writing. Koala and RightBlogger both have free plans too, but they meter you in words, where Byword hands you five complete articles with no payment details, which answers the question a pricing table cannot. **Pros:** - Five complete articles free with no credit card required - Publishes its real prices in plain text, so there is no toggle to misread - Can be driven from an AI assistant like Claude if you ever want that, without you wiring anything up - Credits accumulate and never expire **Cons:** - Same $99 as Outrank for 25 articles instead of 30, so you pay more per piece - API access is gated to the $299 Standard tier - Advertises no backlink product, which is a drawback if that was why you bought Outrank **Best for:** Testing whether auto-generated articles are good enough for your name before spending anything. **Pricing:** Free for 5 articles. Starter $99/month for 25, or $83/month billed annually. Standard $299/month for 80. **Free trial:** Yes, 5 articles, no card. **Bottom line:** Worth starting here wherever you end up. Spending nothing to see the output quality is the most useful hour in this decision. #### **4. RightBlogger (Best for Bloggers Who Want Tools, Not Just Articles)** *RightBlogger bundles 80-plus tools around the autoblogging engine rather than selling articles alone.* The one currently ranking second for this keyword on its own blog, where it also ranks itself first. Worth saying plainly, because the product underneath is genuinely reasonable and the pricing it quotes for itself is the annual rate. **Pros:** - Unlimited AI words on every paid tier instead of a metered article count - States its monthly and annual prices side by side instead of making you hunt for the difference - 30-day money-back guarantee plus a 7-day trial with nothing due today - Nine content systems supported, plus a free plan to look around **Cons:** - Runs its own Backlink Exchange on all three tiers, same mechanic as Outrank - Solo is one connected site and no team seats - Publishing is capped at 5 posts per day per site, with 30 able to sit in the queue at once **Best for:** A blogger who wants a keyword tool, an SEO report and a writer in one subscription. **Pricing:** Solo $59/month month-to-month ($49 annual), Pro $89 ($69 annual), Agency $299 ($199 annual). Free plan available. **Free trial:** Yes, 7 days at $0 due today, with a 30-day money-back guarantee. **Bottom line:** Good value if you will use the wider toolkit, and the money-back guarantee is real. Just price it at $59, not the $49 its own post quotes. #### **5. Koala AI (Best for the Cheapest Genuine Entry Point)** *Koala AI now starts at $25 a month, still the lowest real entry price among these Outrank alternatives.* Twenty-five dollars gets you a working account with CMS publishing included, which makes it the cheapest way to keep a small site fed. It meters words rather than articles, so what you actually get depends on how long your posts run. **Pros:** - $25 entry tier that still includes WordPress, Shopify, Webflow and Ghost publishing - Advertises no link exchange, and KoalaLinks handles internal linking, not backlinks - API access on the entry plan, which most competitors gate much higher - Pulls live Amazon data, genuinely useful for affiliate sites **Cons:** - 45,000 words a month at $25 is roughly 20 to 30 articles, depending on length - Word metering makes cost per article harder to predict than a flat count - Longer articles push you to the $49 tier for 100,000 words, at which point the saving narrows **Best for:** One small site where a handful of posts a month is the honest requirement. **Pricing:** Starter $25/month (45,000 words), Professional $49/month (100,000), Boost $99/month (250,000). Annual billing saves 20%. **Free trial:** Free to start, no credit card, cancel anytime. **Bottom line:** The right answer for a small site that never needed 30 articles a month, which is more people than the category admits. #### **6. Arvow (Best for Agencies Running Many Client Sites)** *Arvow bundles white-label reports and an AI visibility tracker, aimed at agencies rather than solo sites.* Built for people managing sites for other people, with white-label reporting and Google Business Profile automation that nothing else here offers. **Pros:** - White-label SEO reports, which matters if you resell this to clients - Automates Google Business Profile posts and review responses, useful for local clients - Includes an AI visibility tracker alongside the writing - 150-plus languages supported **Cons:** - Automatic Backlinks sits on the $169 Business tier, not $69 Solo, and brings the same policy exposure as Outrank - Month-to-month is $69. The $39 everyone quotes is the yearly rate, and the page labels it "limited time," so do not treat it as permanent - Solo covers one website, so agency use starts at the $169 tier **Best for:** An agency that needs client-ready reporting more than it needs the cheapest articles. **Pricing:** Solo $69/month month-to-month or $39 on yearly. Business $169/month or $69 on yearly. Ultimate $449/month or $249 on yearly. **Free trial:** Account creation is free, and signup currently includes a 2-hour AI SEO course. **Bottom line:** The agency pick, provided you either leave the link exchange switched off or accept the same bet you were trying to leave. #### **7. SEObot (Best for Founders Who Want Zero Involvement)** *SEObot targets solo founders and states its $49 entry price on the homepage.* Aimed squarely at technical founders who want SEO to happen without them. It says so directly: it takes 100% of the work out of your way. **Pros:** - $49 entry, half Outrank's price - Runs automated fact-checking and an anti-hallucination pass in the pipeline, where Outrank's checking add-on is human editors at $1,399 a month - Re-links older articles monthly rather than only publishing new ones - Converts YouTube videos into articles **Cons:** - Nine articles at $49 is $5.44 each, the highest per-article price among the fixed-count plans here - Builds backlinks to raise domain rating without publishing how the links are secured, so ask before switching it on - No pricing page on the marketing site, so the tier ladder lives in a help-center article rather than beside the product **Best for:** A founder who wants a small number of checked articles and no dashboard time. **Pricing:** $49/month for 9 articles, $99 for 20, $199 for 50, per its help centre. No annual option is advertised. **Free trial:** No free tier. It offers a full refund on the $49 plan after your first article instead. **Bottom line:** Worth the per-article premium if an automated accuracy pass matters more to you than volume. Machine checking is not a human editor, and it can hand you false confidence, but the alternative here is no checking at all. ### **What 30 Articles a Month Does for AI Search** The new pitch across this whole category is not rankings, it is citations. Outrank says it gets you "recommended by ChatGPT." BabyLoveGrowth, ContentPen, Koala and Arvow all put getting cited by AI on the homepage. So it is worth saying what that looked like on my own site. This site logged **12.1K AI citations between February and August 2026** in Bing Webmaster Tools, across Microsoft Copilot and its partners, with no backlink budget behind it. Two caveats worth stating: that report only opened to the public on February 10, 2026, so the starting point is partly where measurement began, and a citation counts an appearance, not a recommendation. I am not selling you the tool that did it, because no tool did it. What I can say is what it took. Being the most specific, most checkable answer to a question someone actually asks an assistant did more work than anything else, and that is a research problem before it is a publishing problem. I cannot prove volume was irrelevant. I can say that publishing more was never the lever I reached for. So buy one of these for what it is. Thirty articles a month is a distribution engine, and none of these tools is a reason on its own to expect citations. Point it at genuine expertise you already have and it multiplies that. Point it at nothing and it multiplies nothing, faster and for $99 a month. One practical note, since every tool here upsells tracking. You can measure this for free. [Bing Webmaster Tools](https://www.bing.com/webmasters) reports AI citations across Copilot, and Search Console has a Generative AI report for Google's side. Both cover your own site only, with no competitor or prompt-level data, but that is where my numbers above came from and neither costs anything. The [charts behind those numbers](/ai-seo-consulting/) are public if you want to see the shape of it. ### **What About Surfer SEO, Frase and Jasper?** They appear on nearly every competing roundup for this keyword, and they do not belong in the ranked list above. [Surfer](https://surferseo.com/) and [Frase](https://www.frase.io/) are optimizers. You bring a draft and they tell you how to improve it against the results already ranking. [Jasper](https://www.jasper.ai/) is a brand-voice writing platform. All three are good at their jobs. Surfer and Frase can both push a finished piece to WordPress, so this is not about whether they connect to a CMS. It is that you start the work. None of them is built to wake up, pick a keyword and publish while you sleep, which is what most people are paying Outrank for. Recommending them to an Outrank refugee swaps a hands-off product for a hands-on one and calls it an upgrade. If you want optimizers rather than auto-publishers, I ranked those separately in my [roundup of AI SEO tools](/best-ai-seo-tools/). ### **Three Questions That Narrow This Fast** The same ones I work through on client builds, in this order. **Would I put my name on the output?** Answer this before any pricing question, because a cheap article you cannot publish costs more than an expensive one you can. It is also the only question here you cannot settle from a rate card, which is why the free tiers matter more than the discounts. **What is the real cost per article at my volume?** Divide the monthly price by the articles included at the tier you would actually buy, not the tier on the billboard. A $49 plan with 9 articles costs more per piece than a $99 plan with 30. **Does it trade or buy links on your behalf?** If it does, you have kept the exposure and only changed the logo. Earned mentions are a different thing entirely. Ask before you migrate, not after. ### **The Cheaper Move Than Any of These** Worth saying, because the whole category sells one thing and the money often belongs somewhere else. Pick a page that already makes you money. Buy three to five guest posts on sites that are relevant to your niche and actually rank. Wait for them to index, then point niche edits at those posts rather than straight at your site. Tiering links that way costs less than blasting everything at the target and gives you a buffer if a placement goes bad. Send real traffic through them too, not just link equity. That tiered approach is old practice in competitive money niches like loans and credit cards, and the logic holds up better than spraying 30 articles at a domain and hoping. Now the honest part, because I am not going to sell you a loophole. **Google's policy covers this too.** The same spam document names "buying or selling links for ranking purposes" and, specifically, "links with optimized anchor text in articles, guest posts, or press releases distributed on other sites." A paid link is compliant only when it is marked, with `rel="sponsored"` or `rel="nofollow"`, and a marked link does not pass ranking credit. Which is to say the version people actually buy, the followed one, is the same category of bet as an exchange. What changes is control. In an exchange you get whatever the network hands you, from sites you did not choose, published without a preview. Buying placements yourself means you see the site, its traffic and its relevance before you spend, and you can walk away from the bad ones. That is a better version of the same bet, not an escape from it. If you want no exposure at all, the answer is earned mentions and digital PR, which I break down in [my AI SEO strategy guide](/ai-seo-strategy/). ### **Where I Would Actually Put the $99** Take Byword's five free articles first and look hard at the output. If it clears the bar and you want Outrank's exact shape with better support, BabyLoveGrowth. If you want more volume for the same money without hosting links for strangers, ContentPen. If your site never needed 30 posts a month, Koala at $25 and put the difference into good placements. ### **Outrank Alternatives FAQs** #### **What is the best alternative to Outrank?** It depends on which part you are leaving. BabyLoveGrowth, the only one here I have used myself, matches Outrank almost exactly at $99 for 30 articles and adds a 90-day money-back guarantee with narrow conditions. ContentPen is cheaper per article, $99 monthly for 40 articles against Outrank's $99 for 30. Byword is the one to try first because five articles cost nothing. Read those last two as a pricing and feature assessment from their live rate cards rather than a field report, and none of these is hands-down better across the board. #### **Is there a free Outrank alternative?** Byword gives five full articles with no credit card, which is the most useful free offer here because it tests output quality. Koala AI and RightBlogger both have free plans, though they are limited enough to be trials rather than usable tiers. Koala's paid entry at $25 a month is the cheapest genuine option. I have not run any of those three myself, so treat this as a read of their published plans. #### **Why is Outrank's Trustpilot rating so mixed?** It sits at 3.7 across 87 reviews, and the negative ones are overwhelmingly about billing rather than SEO quality, with customers describing difficulty cancelling and support not replying. When I checked in September, Outrank had replied to 12% of its negative reviews, and Trustpilot notes it has no recent history of inviting reviews, which suggests the score is not a solicited average. #### **Are AI backlink exchanges safe?** Google's spam policies list excessive link exchanges and cross-linking partner pages as link spam, so the mechanic is named directly rather than being a gray area. Outrank, RightBlogger and BabyLoveGrowth run member-to-member exchanges, and Arvow adds automatic backlinks on its $169 Business tier. SEObot builds links without publishing how it secures them. If avoiding that exposure is why you are switching, ContentPen, Byword and Koala AI are the three here that advertise no link building at all. #### **How much does Outrank cost?** $99 a month or $999 a year for the All-in-One plan, covering 30 auto-published articles, keyword research and backlink exchange access. The add-ons climb fast: 60 articles adds $85, 90 adds $160, and the Human Curated Service that puts editors on every article before publication is $1,399 a month on top. *Disclosure: no affiliate links, and I am not a customer or partner of any tool here. I have used BabyLoveGrowth. The other six were priced from their live rate cards on September 3, 2026 with monthly billing selected, and rechecked on September 30, 2026. I sell an AI SEO course, not an auto-publishing tool. [Full disclosure](/disclosure/).* --- ## Rankability Review: The Best AI SEO Tool in 2026? URL: https://ryandoser.com/rankability-review/ Markdown: https://ryandoser.com/rankability-review.md Published: 2026-09-30 | Updated: 2026-10-09 Categories: AI Tool Reviews > Rankability now starts at $97/month with self-serve signup, but the free trial is still gone. Here is what changed in 2026 and who should buy it over Surfer or Ahrefs. [Rankability](https://www.rankability.com/?via=ryan-doser) is an AI SEO platform built for agencies that need content to get cited by ChatGPT and Claude, not just ranked on Google. This **Rankability review** covers the current pricing, the feature worth paying for, and the one change since I recorded my video that you need to know before you buy. Rankability gave me free access to test the platform for my video review. I was not paid for it, and I do earn a commission if you sign up through my link. Here is the part most reviews will not tell you. The tool I recorded is not the tool you buy today. Rankability rebuilt its pricing more than once this year and dropped the free trial I recommended in that video. I went back through the current site and help docs line by line to write this. **Update, October 9, 2026:** Rankability changed its offer again on October 7. When this review first ran on September 30, the pricing page sold one plan from $497 a month on a 12-month agreement, booked through a demo, with nine AI platforms. That plan is gone. There are now three self-serve plans, Starter at $97 a month, Agency at $297 and Agency Pro at $497, each covering 11 AI platforms. Monthly plans need no annual commitment and can be canceled in Billing. The pricing, comparison table, buying advice and FAQs below now reflect the new offer. My testing notes and the video are unchanged. ### **What Rankability Actually Does in 2026** Rankability positions itself around one job: create content that influences AI systems to recommend your clients. The homepage headline is "Create content that wins AI visibility." The workspace splits into Research, Create, Audit, Promote, and Track, with an AI advisor called Serena sitting across all of it. Serena chat is included in the plan, which matters more than it sounds like. ![Rankability homepage showing the Create content that wins AI visibility headline](/images/2026/08/rankability-review-homepage.jpg) Keep two things separate as you read the plans. Research platforms are the sources that inform a draft, while Track is the separate module that measures whether you got cited. That is a genuinely different product from the one in my video. Back then it was three features: keyword research, content optimizer, and content monitor. The optimizer is still the core. The platform grew around it. ### **Rankability Pricing: What It Costs Now** This is where the biggest change happened, and where most published reviews are out of date. As of October 7, 2026, Rankability sells three self-serve plans. The [pricing page](https://www.rankability.com/pricing) lets you pick a plan, pay monthly or yearly, and sign up without a sales call. A year costs the same as ten monthly payments, so annual billing saves two months. | | Starter | Agency | Agency Pro | | Monthly | $97 | $297 | $497 | | Annual (total paid per year) | $970 | $2,970 | $4,970 | | Content projects per month | 20 | 80 | 160 | | Tracked AI queries | 100 | 300 | 500 | | AI platforms | 11 | 11 | 11 | | Client workspaces and team members | Unlimited | Unlimited | Unlimited | | API, MCP and agency-branded reports | Included | Included | Included | | Onboarding | Self-serve setup | One team session | Team session plus campaign planning | | Gotch Inner Circle coaching | No | No | Annual plan only | Content projects and tracked queries are shared across all of your clients. Unlimited workspaces does not mean unlimited usage, so size the plan to your total client workload. The 11 platforms are ChatGPT, Google AI Mode, Google AI Overviews, Claude, Perplexity, Gemini, Grok, Microsoft Copilot, Brave AI, DeepSeek and Meta AI. Coaching has a catch worth knowing. Nathan Gotch's weekly Inner Circle calls come only with an active Agency Pro annual subscription, not with monthly Agency Pro or the cheaper plans. This lineup has changed fast. The Core, Scale and Advanced plans at $99, $299 and $799 sat on this page in August, and the one $497 demo-only package replaced them in September. One place the official surfaces still disagree. The pricing page says every plan gets all 11 platforms, while the help center's platform page still describes cheaper plans with fewer engines. Rankability's docs name Billing as the final word, so check it after you sign up. You will also find articles quoting $149 or $199 plans. Those come from an even older lineup. If you want to go deeper on how I run AI search and content systems day to day, I put together a free resource with my Claude Code skills, automation templates, and systems. Grab the **[AI Marketing Essentials Guide](/ai-marketing-guide/)** to follow along. ### **The Free Trial Is Gone, and That Changes the Advice** In my video I told you to take the 7-day free trial before committing. That advice no longer works. I checked this against the archive rather than assuming. Rankability's pricing page on September 29, 2025, two days after my video went live, carried a "Start Your Free Trial" button. Today that language is gone from the pricing page. When I searched the help center documentation in September, it returned zero mentions of a free trial, and the October pricing page still offers none. So the honest version of my recommendation is different now. The closest thing to a trial is one paid month of Starter at $97. Monthly plans can be canceled in Billing, and you keep access until the end of the billing period you paid for. Treat that $97 as the cost of the test. If a lower entry price matters more to you than the feature depth, [Surfer](https://surferseo.com/pricing/) starts at $59 a month. ### **The Content Optimizer Is Still the Reason to Buy** I said this in the video and I still believe it. The optimizer is the strongest thing Rankability does. You give it a target keyword and it analyzes the pages currently ranking, then scores your draft on relevance against them. Optimal is 70 and above. The score is a relevance measure rather than a quality grade. It reflects how semantically complete your page is against the pages already ranking. What I liked while testing was the granularity underneath the score. It surfaces the exact outline of every top-ranking competitor, broken down by H2 and H3, with their own score and word count beside it. That is a competitive research workflow, not just a writing assistant. I could see how the pages above me had structured the topic, and where my draft was thin by comparison. The brief that comes with it recommends a URL, title, meta description, and target word count derived from what actually ranks. The URL recommendations matched how I build URLs myself, which is a small signal that a practicing SEO designed this. ### **AI Search Tracking Is the Biggest Addition Since My Video** This did not exist when I recorded. Rankability's help center documents citation tracking across eleven AI answer platforms, including ChatGPT, Perplexity, Gemini, Claude, Grok, Copilot, DeepSeek, and Meta AI. ![Earlier version of the Rankability help center table listing supported tracking platforms and per-check credit costs](/images/2026/08/rankability-review-tracking.jpg) It captures whether you were mentioned, whether you were cited, and the sentiment attached. You can filter to citations only or mentions only per platform. The cost model is simpler than it was. The screenshot above shows an earlier version of the help center, which priced each platform in credits, with Gemini at 75 per keyword check and Google AI Overview at 10. That per-platform credit math is gone from the current plans. Now one saved query checked across your selected platforms uses one tracking slot. Starter includes 100 slots, Agency 300 and Agency Pro 500, all shared across clients. Local Pack tracking is the one that can still surprise you. One scan covers one keyword for one location on a grid of up to 5x5, a 7x7 grid uses two scans, and a 9x9 grid uses four. Starter includes 10 Local Pack scans a month, Agency 30 and Agency Pro 50. If you run local clients, a few large grids can use up the Starter allowance quickly. ### **Rankability Connects to Claude and Codex via MCP** Every paid plan includes API and MCP access, and the hosted endpoint means there is nothing to install locally. Work an agent does through the API or MCP draws from the same allowances as work done in the app. ![Rankability help center documentation for connecting to AI assistants with MCP](/images/2026/08/rankability-review-mcp.jpg) You connect Claude through OAuth as a custom connector, or Codex through streamable HTTP. The help center now tells developers to read the rate-limit headers on each response rather than plan around a fixed number per plan. This is the piece that fits how I actually work. If you already run SEO research through an assistant, I compared the [SEO MCP servers worth connecting](/best-seo-mcp-servers/) separately. One detail I appreciated in the docs: Rankability tells you to run a read-only verification prompt before letting an agent start billable work. That is a thoughtful default for a tool where an agent can spend your monthly allowance. ### **What the Founder Told Me About Who This Tool Is For** I interviewed Nathan Gotch on my channel and asked him directly what separates Rankability from every other AI SEO tool. His answer explains the product better than the marketing page does. He was blunt about the target market. Other tools want to be the next Ahrefs or Semrush and serve everyone, while Rankability is built for agencies specifically. His reason for that focus is the interesting part. He runs coaching calls twice a week for an academy where he says 95 percent of members are agencies, and product decisions come out of that feedback loop. He said they deliberately leave out vanity related things and fancy bells and whistles that do not move the needle for an agency. That is his framing, and the stripped-down feel of the tool matched it when I tested. He did not discuss pricing in that conversation, so this next part is my read rather than his. A tool built around agency pain has little reason to court hobbyists. Even the $97 Starter plan added in October is sold on client workspaces and branded reports, and dropping the free trial fits that same logic even if buyers dislike it. One thing he said stuck with me on the wider AI search debate. He argued that AI platforms perform retrieval through public search engines, so calling SEO dead means claiming search engines are not used for retrieval. ### **Rankability vs Surfer vs Ahrefs** These are the three tools people cross-shop, and the honest answer depends on what job you are hiring the tool for. | | Rankability | Surfer | Ahrefs | | Entry monthly | $97 Starter | $59 Discovery | $129 Lite | | Mid tier monthly | $297 Agency | $119 Standard | $249 Standard | | Users included | Unlimited | 1 to 10 by plan | 1, extra seats $40/mo | | AI answer tracking | 100 to 500 queries, 11 platforms | Yes, prompt-based | Yes, 5 prompts on Lite | | Backlink index | No, prospect lists only | No | Yes, industry leading | Surfer's monthly rates are $59 Discovery, $119 Standard, $219 Pro, and $359 Peace of Mind. Its pricing page defaults to annual, so the lower numbers you see first are yearly rates. Against Surfer, the entry price still favors Surfer, but by far less than before: $97 for Rankability Starter against $59 for Surfer Discovery. Team size narrows the gap for agencies, because every Rankability plan includes unlimited users and clients, so one subscription covers your whole writing team and every account. The content and tracking allowances are shared across all of them. Against [Ahrefs](https://ahrefs.com/pricing), it is not really a fair fight in either direction. Ahrefs has a backlink index and keyword database Rankability does not attempt to match, and Ahrefs Lite includes one user with additional seats at $40 each. I said it in the video and it still holds. If you mainly need keyword research and competitor analysis, buy Ahrefs. If that is the direction you are leaning, I weighed Ahrefs against the cheaper pay-as-you-go option in [DataForSEO vs Ahrefs](/dataforseo-vs-ahrefs/). If your bottleneck is producing and optimizing pages that get cited, Rankability is the better spend. Most agencies I know end up running one of each rather than choosing. I broke down how these tools compare across the category in my roundup of the [best AI SEO tools](/best-ai-seo-tools/). ### **Where Rankability Falls Short** The keyword research is the weakest module, and that has not changed. It works, but you get fewer metrics and less automatic long-tail expansion than a dedicated tool. During testing I had to apply a filter manually to surface longer-tail variants of a base keyword. Ahrefs hands you those automatically on the first search. The documentation lags the offer. The pricing page counts usage in plain monthly allowances, while parts of the help center still describe an older plan split with fewer AI platforms on cheaper tiers. Check Billing for what your account actually includes. There is also no native mobile app. It is browser-only, which is fine for agency work but worth knowing. And there is still no free trial. The cheapest way to see it for yourself is a paid month of Starter at $97, so you pay to find out whether it fits. ### **Who Should Actually Buy Rankability** This is built for agencies and consultants doing high-value SEO, and the plan design makes that obvious. If you charge clients real money for content that has to rank against serious competition, the optimizer plus AI citation tracking is a defensible line item. You can show a client whether they got cited in ChatGPT last month, across the major AI answer engines, which is a report most SEO tools still cannot produce. The unlimited users detail matters more than it looks. If you have three writers and an account manager, per-seat tools get expensive fast and Rankability does not. Skip it if you are a solo creator writing a few posts a month. Most of even the Starter plan will go unused, and a cheaper optimizer or a sharper [AI SEO strategy](/ai-seo-strategy/) will serve you better. Also skip it if you need backlink data. That is not what this tool is. If you are comparing agency SEO platforms at this price point, I put [Search Atlas](/search-atlas-review/) and [Adaptify](/adaptify-seo-review/) through the same test. Both sell to agencies and price very differently. ### **Final Notes from Ryan** Rankability was a good content optimizer when I reviewed it, and it has become a more serious platform since. The AI citation tracking is the addition that justifies revisiting it. If you want citation tracking at a similar price with the publishing done for you, [a $99 platform bundles it with auto-publishing and a link exchange](/babylovegrowth-review/), and the tradeoffs there are worth reading before you compare on features alone. There are [six more selling that same bundle](/outrank-alternatives/) at prices that are not always what the page says. [Nathan Gotch](https://www.rankability.com/blog/whos-the-ceo-of-rankability/) being the founder still matters to me. He is one of the few SEOs I genuinely respect, and the product decisions read like they came from someone who has actually run client work. Removing the free trial is a real downgrade for buyers, and I am not going to soften that. When this review first ran, the pricing had turned it into a demo call and a year-long commitment at $497 a month. The October self-serve plans fix most of that, since you can now start monthly at $97 without a call, but you still pay to test it. My honest take: if you run an agency and content optimization is your bottleneck, Rankability belongs on your shortlist next to Surfer. If you are still deciding whether SEO is a line item for you, this is not where you start. ### **Rankability Review FAQs** #### **How much does Rankability cost in 2026?** As of October 7, 2026, there are three self-serve plans: Starter at $97 a month, Agency at $297 and Agency Pro at $497. Paying yearly costs $970, $2,970 or $4,970, the same as ten monthly payments. Every plan includes 11 AI platforms, unlimited client workspaces and team members, API and MCP access, and agency-branded reports. Content projects run 20, 80 or 160 a month and tracked AI queries 100, 300 or 500, shared across clients. Monthly plans need no annual commitment. #### **Does Rankability have a free trial?** Not anymore. An archived copy of the pricing page from September 2025 shows a Start Your Free Trial button, and the current pricing page offers no trial. A help center search in September returned no results for one either. This is the single biggest change since my video review, where I recommended trialing before buying. The closest substitute now is one paid month of Starter at $97, which you can cancel in Billing. #### **Is Rankability better than Surfer SEO?** They win on different things. Surfer starts at $59 monthly for Discovery against $97 for Rankability Starter, so the entry cost still favors Surfer, though by far less than before. Rankability includes unlimited users and clients on every plan, which narrows the gap for an agency where several writers and account managers need their own logins. Choose on team size and whether AI citation tracking matters to your clients. #### **Can I connect Rankability to Claude or ChatGPT?** Yes, through a hosted MCP server that needs no local installation, and it is included on every paid plan. Claude connects as a custom connector over OAuth, while Codex uses streamable HTTP. API and MCP work draws from the same allowances as work done in the app. Serena, the built-in advisor you chat with inside the product, is included too. #### **What AI platforms does Rankability track?** Eleven, on every paid plan: ChatGPT, Google AI Mode, Google AI Overviews, Claude, Perplexity, Gemini, Grok, Microsoft Copilot, Brave AI, DeepSeek and Meta AI. For each one it records mentions, citations, and sentiment. One saved query across your selected platforms uses one tracking slot, and plans include 100, 300 or 500 slots. The help center's platform page still describes fewer engines on cheaper plans, so confirm in Billing what your account has. *Disclosure: some links in this post are affiliate links, specifically Rankability. If you buy through them I may earn a commission at no extra cost to you. Rankability provided free access to the platform so I could test it for my video review. [Full disclosure](/disclosure/).* --- ## Search Atlas Review: Is This SEO Tool Worth It? URL: https://ryandoser.com/search-atlas-review/ Markdown: https://ryandoser.com/search-atlas-review.md Published: 2026-09-30 | Updated: 2026-09-30 Categories: AI Tool Reviews > Search Atlas now starts at $79 a month billed annually, with OTTO included on one project. Here is what the ratings show and the one question nobody has tested. Search Atlas held a **4.0 on Trustpilot** across 337 reviews when I pulled the data in August, and read 3.9 across 359 when I rechecked on September 30. On the Shopify App Store it held a **1.8** at the same time, where 9 of its 12 ratings were one star. In that August pull it was the same company, same product, same period, opposite verdicts. Most reviews you will read quote one of those numbers and ignore the other. That is the interesting part of this **Search Atlas review**, because the two pools are not complaining about the same thing. What the Shopify reviewers describe is billing and app access. The Trustpilot pool is dominated by people rating the SEO platform itself. Two things about my position, up front. I sell a competing product, my [AI SEO System](https://seo.ryandoser.com/), which is a one-time $199 rather than a subscription and runs on the AI tools you already pay for. So weigh what follows accordingly. I earn nothing if you buy Search Atlas, which is also why I can be straight with you about it. And I have spent time inside Search Atlas and read its documentation and public review pools closely, but I have not run it on a client site across a full campaign. So I can tell you what it is, what it costs, and what its own pages commit to. I cannot tell you what it moved for me, and I am not going to pretend otherwise. ### **What Search Atlas Sells** Search Atlas is an SEO platform whose headline feature is OTTO, an agent that does not merely suggest fixes but deploys them. In the company's own words on its pixel page: "The OTTO Pixel is a single script that connects your website to Search Atlas. Once it's live, OTTO SEO reads your pages, fixes what's holding your rankings back, and deploys the changes straight to your site, on its own, across any CMS." That is a genuinely useful proposition if you are carrying technical debt you have no time to clear. Approval mode exists too, so the automation is optional: "Want to sign off first? Turn on approval mode to review every change before it goes live, and roll back anything, anytime." I have written before about why I tell clients not to let OTTO run unsupervised, in my roundup of the [best AI SEO tools](/best-ai-seo-tools/). I am not going to re-argue that here. This piece is about something the roundup did not have room for: what the review pools actually say, and what the vendor commits to in writing when you stop paying. ### **The Pricing, Then and Now** In August I had to render the pricing page, because Search Atlas injected its pricing with JavaScript and a plain fetch returned nothing. It has been rebuilt since I first wrote this, and the prices now appear in the page itself. On September 30, 2026 it showed four plans behind an annual toggle that saves 20%: - **Starter** is $79 per month billed annually ($950 a year), about $99 month to month, with 1 seat, 1 project and OTTO included. - **Growth** is $159 per month billed annually, about $199 monthly, with 3 seats, 2 projects and AI Visibility across ChatGPT, Gemini and Google AI Mode. - **Pro** is $319 per month billed annually, about $399 monthly, with 5 seats, 4 projects, Copilot and Perplexity added, and white-label reporting. - **Agency** starts at $999 per month billed annually, with 10 seats and 10 or more projects. *The four plans as captured on August 14, 2026, when the page had no annual toggle and OTTO sat on its own meter. Both have since changed.* The biggest change is OTTO. In August it was metered separately at $99 per site per month, so a $99 Starter plan became a $198 bill for a single site. The current page lists "Atlas Agent + OTTO SEO" inside Starter's one project and meters usage through a monthly budget of Universal Credits, 50,000 on Starter. OTTO on one site now costs the plan price itself. The billing display changed too. In August there was no annual toggle and the words "annual" and "yearly" did not appear on the page. It now defaults to annual billing, so check which toggle is active before you read a number. One August detail is gone with the old meter. The page then defined a Hyperdrive Credit as "1 HDC = $1" while selling 100 of them for $99. Hyperdrive Credits no longer appear on the pricing page. ### **The 4.0 and the 1.8 Are Measuring Different Things** Here is the distribution behind that 4.0, taken from Trustpilot's own published counts across all 337 reviews in my August pull. The profile has since moved to 3.9 across 359, so read the shares as that snapshot: | Rating | Count | Share | | 5 star | 221 | 65.6% | | 4 star | 15 | 4.5% | | 3 star | 4 | 1.2% | | 2 star | 13 | 3.9% | | 1 star | 84 | 24.9% | The two poles hold 90.5% of the pool. The entire middle, every 2, 3 and 4 star review combined, is 9.5%. There are 2.6 times more one-star reviews than the whole middle put together, and exactly 4 people out of 337 landed on the true midpoint. So the 4.0 is a poor summary of what is underneath it. Reviewers here mostly rated the product at one extreme or the other, and a rating near the middle is the rarest thing in the pool. Worth noting that 4.0 is Trustpilot's displayed TrustScore rather than a simple average of those counts, which works out closer to 3.8. Either way, **read the distribution before you read the score**, because the score sits in a band where almost no reviewer actually landed. One caution on what that does and does not tell you. Reviewers are a self-selected group, and people motivated to write are rarely the ones who felt neutral, so a hollow middle is partly a property of who bothers to post. It still tells you something useful: if you buy this, the experiences reported publicly cluster at the ends, and you should read both ends before deciding which is more likely to be yours. The Shopify App Store pool is small at 12 reviews, so treat it as a signal rather than a verdict. But 9 of the 12 are one star, and the complaints there are not about SEO quality at all. They are about billing and access. One merchant writes that they "subscribed and paid USD$199. THE APP STILL DIDN'T WORK. The app developer refuses to refund our money." Another reports being "charged $200 per month for 3 months before we noticed." A third reports a "410 Gone" error opening the app. *The same product on the Shopify App Store. The distribution bars tell the story faster than the average does, and the reviews beside them are about payment and access rather than rankings.* ### **What the One-Star Reviews Are Actually About** I read the negative pool rather than only counting it. Of the 84 one-star reviews, I was able to read 79, and I coded each for what it complained about. In that sample, support problems appear in roughly two thirds, billing and refund problems in roughly two thirds, and complaints about the SEO output itself in under half. Most reviews raise more than one, so those shares overlap rather than summing. That ordering is the useful part. Among the unhappy reviewers I read, the most common complaints are commercial and operational rather than "the SEO did not work." A representative billing complaint, from a reviewer in Australia in June: "I signed up for a 7 day FREE trial but they charged my account straight away." He goes on to say support "can't refund the charge because it was outside their 72 hour cancellation window." One reviewer draws the distinction explicitly while giving one star: "This platform has a ever-improving product, but their support makes it almost unusable at times." That is a customer telling you the software is getting better and the company around it is the problem. There is a fourth category I did not expect, and it is not a customer complaint at all. Several one-star reviews come from publishers on Search Atlas's own Publication Media marketplace saying they have not been paid for completed placements, with accounts deactivated and prices revised after publication. That is a supply-side problem, and it belongs in a different bucket from a customer review, but it is sitting in the same pool feeding the same average. ### **Read the Positive Reviews Too, Because They Concede the Same Points** The five-star reviews are not empty. The most substantive ones name features, name the competitors they left, and volunteer the friction. One customer of nearly a year describes managing four clients on the platform, says he moved because "tools like Ahrefs and SEMrush were expensive for a boutique agency," and then says outright: "There was definitely a BIG learning curve." He also volunteers that he had "double-payment issues" and that they "refunded me immediately." Another five-star reviewer, the only one in the pool making a hard numeric claim, says he "replaced 6 software programs" and increased "web rankings and SEO traffic by 137% year over year." I cannot verify that figure and neither can you, so treat it as what it is, one customer's report. What strikes me reading both poles is how much they agree on. The happy reviewers describe a steep learning curve, occasional bugs, and billing problems that got resolved. The angry reviewers describe a steep learning curve, occasional bugs, and billing problems that did not. They differ less on what the product does than on whether the friction around it got sorted out, and support is the thing that separates those two stories in most of the reviews I read. One more thing about the pool. Trustpilot displays a notice on the profile: "No recent history of asking for reviews. This company hasn't invited customers recently, so reviews may not be representative." That is Trustpilot's own hedge on its own number. It does not tell you which direction the pool is skewed, only that Trustpilot is not confident it is representative, which is a reason to read the reviews rather than the score. ### **Does Your SEO Survive Cancellation? I Could Not Find Anyone Who Tested It** This is the argument that comes up most often about Search Atlas, and it is worth getting right because both sides claim more than they have shown. The most-cited version comes from a six-month review published by a Canadian agency in March: "When you cancel your subscription, every optimization vanishes instantly." And the line that travels furthest: "You're not building permanent assets. You're renting temporary enhancements." Search Atlas's pixel page appears to answer this directly, under a heading that reads "Your Optimizations Stay Live. Always." But read what sits under that heading, because the supporting sentence is narrower than the headline: "Changing your OTTO plan doesn't affect your live optimizations or site updates." A bullet adds "Full control, even after pausing." **The word "cancel" does not appear anywhere on that page.** The promise there is scoped to plan changes and pausing. The stronger commitment does exist, but it lives somewhere else entirely, on the pricing page, in a single clause: "keep every edit even after cancellation." So the vendor does commit to it, in writing, on one page, in seven words, while the page built around the durability question uses a headline that says "Always" and then never addresses cancellation at all. Now the other side, because it has a bigger problem. That six-month test never tested cancellation. What the authors describe actually doing is checking how AI crawlers indexed a test site, reviewing 247 OTTO recommendations and implementing 180, tracking credit consumption for three months, measuring a 0.3-second page-load delay, and spending four hours troubleshooting Cloudflare. Nowhere do they report cancelling an account and inspecting the resulting HTML. Their cancellation claim is an architectural inference from client-side rendering, supported by one anonymous quote about "watching six months of work evaporate overnight." It is a reasonable inference. It may well be right. But it is an inference presented as a finding, and it is worth checking the article's other numbers rather than inheriting them: it describes Search Atlas plans as starting at $49 and scaling to $99 and $199, while the live pricing page runs $79, $159, $319 and from $999 billed annually. Either the figures are stale or they were wrong when published, and either way they are not the current rate card. Search Atlas, for its part, never states anywhere on the pixel page whether pixel-deployed changes are server-side or client-side rendered. The entire dispute turns on that detail and the vendor has not put it in writing in either direction. So the honest answer: **I could not find a published test of what happens to your optimizations when you cancel Search Atlas.** The vendor commits to persistence in one clause on its pricing page. Its most-cited critic argues the opposite from architecture rather than from an experiment. If this matters to your decision, and it should, ask Search Atlas for the answer in writing before you buy, and ask specifically about cancellation rather than pausing. ### **Who Should Actually Buy It** Take the real entry price rather than the headline one. OTTO on a single site now comes with Starter at $79 a month billed annually, or $950 a year. The platform is built to execute changes at volume, and Search Atlas is genuinely good at that. What it does not do is tell you which changes deserve to exist, and at that price the distinction is the whole decision. *The separate OTTO meter as captured on August 14, 2026, when it turned a $99 plan into a $198 bill for a single site. It has since been folded into the plans and no longer appears on the pricing page.* Think hard if you run a single site. That is a lot of platform for one property, and what you are buying is execution capacity rather than judgment about what to execute. It makes more sense if you run multiple client sites, you are consolidating away from Ahrefs or Semrush on cost, and you have patience for a real learning curve. If that is you, [Adaptify is the other platform worth pricing against it](/adaptify-seo-review/), though it starts at $499 for a single site. The most detailed positive reviews in the pool come from people in that position, and several of them say plainly that the curve was steep and they got through it. Whoever you are, do not buy it on a free trial expecting a clean exit. The complaint I saw repeated most in the negative pool came from people who believed they were trialling, found they had been charged, and then discovered the refund window had closed. Read the cancellation terms before you enter a card, not after. It is a habit worth keeping: [one competitor advertises a 90-day money-back guarantee whose written conditions are far narrower than the headline](/babylovegrowth-review/). Here is the comparison I would actually run if it were my site. Search Atlas with OTTO on one site is $950 a year billed annually, and at the end of that year you have paid for execution capacity and you are still subscribed. My [AI SEO System](https://seo.ryandoser.com/) is $199 once. It is not a platform and it does not deploy anything for you. What it is is the process I use to work out which fixes are worth making, packaged to run through Claude Code or Codex, which you are probably already paying for. You keep it whether or not you keep paying me, and there is no pixel on your site to think about when you stop. That is a genuinely different purchase and I am not going to tell you it does the same job. Search Atlas will publish and deploy at a volume no process document can match, so if that volume is your bottleneck, buy Search Atlas. If your bottleneck is knowing what deserves to be published in the first place, a subscription does not answer that question, and [an hour of consulting](/ai-seo-consulting/) answers it once, without a subscription. ### **My Verdict on Search Atlas** If you run your own site, no. You would be renting execution capacity to answer a question that is mostly judgment, and the tool will publish faster than you can decide what is worth publishing. Buy the judgment instead. If you run many client sites, it is a defensible yes, provided you read the billing terms before you enter a card. That is where the loudest complaints live in both review pools, and it has nothing to do with how good the SEO is. And the cancellation question stays open. The vendor commits to persistence in seven words on its pricing page, its critic argues the opposite from architecture, and neither has published a test. If you do buy, get that answer in writing first. If you would rather not have to ask the question at all, that is an argument for owning your process rather than renting a pixel that sits on your site. ### **Search Atlas FAQs** #### **Is Search Atlas legit?** Yes, it is a real platform with more than 350 Trustpilot reviews, a Shopify app, and a G2 profile. Legitimacy is not the issue. The issue is that its review distribution was extreme in my August pull: 65.6% five star and 24.9% one star, with only 1.2% at three star. The most common serious complaints are about billing, refunds and support responsiveness rather than about the SEO work itself. That pattern repeats across this category, and it is worth knowing that [one vendor publishes a rating for AI models that its own review profile does not support](/outrank-review/). I checked the [billing terms across seven of these platforms](/outrank-alternatives/) in one place. #### **How much does Search Atlas cost per month?** Plans are $79, $159 and $319 per month billed annually, with Agency from $999, and about $99, $199 and $399 month to month. OTTO, the automation the product is known for, is now included on Starter's single project, so the entry price for one site is the plan price. In August it was billed separately at $99 per site. #### **What happens to your SEO if you cancel Search Atlas?** I could not find a published test of this. Search Atlas's pricing page states you "keep every edit even after cancellation." Its OTTO pixel page carries the headline "Your Optimizations Stay Live. Always." but supports it only with a sentence about changing your plan, and the word "cancel" never appears on that page. The most-cited claim that optimizations vanish comes from a six-month review whose authors tested AI crawler indexing, OTTO recommendations, credit consumption and page speed, but did not report cancelling an account and checking the result. Ask for the answer in writing before you buy, and ask about cancellation specifically rather than pausing. #### **Why did Search Atlas rate 1.8 on Shopify but 4.0 on Trustpilot?** In my August pull, the two pools contained different populations reporting different problems. The Shopify pool was small at 12 reviews, and its complaints were almost entirely about billing and app access: paying and being unable to open the app, duplicate charges, and refused refunds. The Trustpilot pool was larger and contained many agency users rating the SEO platform itself. A merchant hitting a broken install path and an agency running client campaigns are not evaluating the same thing. #### **Is Search Atlas good for a solo operator?** Usually not. Entry for one site with OTTO is $79 a month billed annually, and what that buys is the ability to deploy changes at volume. On a single site the harder question is which fixes are worth shipping, which a subscription does not answer. The most detailed positive reviews come from operators running many client sites who consolidated several tools into it, which is a different problem from yours. A defined process you own, run through Claude Code or Codex, costs far less and does not stop working when you stop paying. That is what my [AI SEO System](https://seo.ryandoser.com/) is, at $199 once. ### **Sources and Method** Pricing figures were read from a rendered copy of searchatlas.com/pricing on 14 August 2026, because the page then injected prices with JavaScript and a plain request returned nothing, and rechecked on 30 September 2026 after the plans changed. Rating counts and the star distribution come from Trustpilot's own published figures for searchatlas.com on the same date, cross-checked against the structured data on the page. The Shopify figures come from the Search Atlas listing on the Shopify App Store, also read that day. Quotations from Search Atlas's pixel and pricing pages, and from the six-month review published by themarketingagency.ca, are verbatim from those pages as they stood on 14 August 2026. The Trustpilot score and review count were rechecked on 30 September 2026, when the profile read 3.9 across 359 reviews; the distribution table is the August snapshot. I did not run Search Atlas on a client site across a campaign, so nothing here is a performance test. --- ## Which Claude AI Model to Use (Stop Wasting Tokens) URL: https://ryandoser.com/which-claude-model-to-use/ Markdown: https://ryandoser.com/which-claude-model-to-use.md Published: 2026-09-30 | Updated: 2026-09-30 Categories: Claude Code > Which Claude model to use, explained like a payroll decision. Fable, Opus, Sonnet, and Haiku mapped to real roles, with the actual token costs. The fastest way to answer **which Claude model to use** is to stop reading benchmark charts and start thinking like a hiring manager with a payroll to protect. ### **Which Claude Model to Use, Framed as a Payroll Decision** Most model comparison articles give you the same thing. A spec table, a benchmark score, a shrug. You learn what the models are without learning anything about your own work, so you go back to running everything on the most expensive one because it feels safer. That instinct is what drains your usage limits by Tuesday afternoon. Here is the reframe that fixed it for me. Your models are not tiers on a pricing page. They are people on a team, and you are the one signing the checks. Once you see the lineup that way, the routing decision answers itself. Nobody pays a doctor to organize a filing cabinet. Yet that is exactly what you do every time you ask a frontier model to reformat a CSV. *The payroll in one picture. Each step down the stairs is a cheaper seat, so match the seat to the job.* #### **Fable is the founder** Fable 5.1 sets direction. Anthropic's [official model overview](https://platform.claude.com/docs/en/about-claude/models/overview) reserves it for demanding reasoning and long-horizon agentic work, and you bring it the hard architectural call, the messy strategic decision, the problem where you genuinely do not know the shape of the answer yet. It scopes the work and hands off the rest. You do not ask your founder to write the weekly recap email. You ask them what the company should be doing next quarter. #### **Opus is your $500-an-hour expert** Opus 5.5 is brilliant and priced accordingly. It is the specialist you bring in for the thing that actually matters, then release before the meter runs your budget dry. Real client work, a landing page that has to convert, copy a customer will actually read. That is Opus territory. It is also the default model in Claude Code on every paid plan, and [my Opus 5.5 writing test](/best-claude-model-for-writing/) shows how it compares on real writing rules. Not your morning summary. If you are a marketer rather than an engineer, this is the tier that earns its keep on positioning, offer copy, and campaign strategy. The rest of the week belongs further down the ladder, which is the practical half of [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) in the first place. #### **Sonnet is the solid $50-an-hour employee** Sonnet 5.5 is good at most things. It handles the broad middle of the job: drafting, working through problems in steps, writing code, the daily volume that makes up most real work. This is the hire that quietly does the bulk of your output. Most people underuse it because it lacks the prestige of the top tier. #### **Haiku is the $10-an-hour assistant** Haiku 4.5 is fast and excellent at simple checking. Classification, extraction, formatting, routing, is-this-thing-what-I-think-it-is. Anthropic's own [guidance on choosing a model](https://platform.claude.com/docs/en/about-claude/models/choosing-a-model) recommends Haiku for simple tasks and reserves the top tier for the most complex reasoning. Speed matters more than depth here, and Haiku has speed. #### **Codex is the contractor from a different agency** Codex, running GPT-6 Sol, sits outside your org chart entirely. That is the whole point. Hiring an outside contractor does not burn your own team's hours. I use it as a second set of eyes on writing. It reads a draft, tells me where the argument sags, and none of that comes out of my Claude budget. Different agency, separate invoice. ### **What the Cost Ladder Actually Looks Like** The analogy earns its keep only if the numbers back it. They do, though not in the order most people assume. Here is what Anthropic charges per million tokens, straight from the [official Claude API pricing page](https://platform.claude.com/docs/en/about-claude/pricing): | Model | Input | Output | The role it plays | | Claude Fable 5.1 | $10 | $50 | Founder | | Claude Opus 5.5 | $4 | $20 | Senior expert | | Claude Sonnet 5.5 | $2 | $10 | Core employee | | Claude Haiku 4.5 | $1 | $5 | Assistant | One correction worth making, because most people have this backwards. Fable is the priciest widely available seat in the building, at two and a half times the cost of Opus. Not the other way around. Opus is the second-most expensive model on the list, not the top of it. The spread that should actually change your behavior is Fable to Haiku. That is 10x on input and 10x on output. Run a batch of 500 classification jobs on Fable instead of Haiku and you paid a founder's rate to sort mail. One more distinction the pricing page will not make for you. These are API rates, billed per token. If you work inside a Claude subscription plan instead, you are spending against usage limits rather than a card, so the units differ. Either way the expensive model consumes your capacity faster. How much capacity you actually get depends on the plan, which I compared against OpenAI in [ChatGPT Pro vs Claude Max](/chatgpt-pro-vs-claude-max/). ### **How I Actually Route Work Across Claude Models** A framework is easy to write and harder to run. Here is the routing I use in a normal week: - Hard calls and planning go to the top - The bulk of the work runs in the middle - Mechanical checks drop to the bottom - Second opinions go outside the building That is the whole rule. The rest is knowing which bucket a task belongs in. *The shape that matters. Cost dips through the middle of the job and climbs back up for verification, because checking work is judgment and not clerical.* Planning and hard calls go to the top tier. When I am scoping a new system, deciding how a workflow should be structured, or working through something I have not solved before, I want maximum judgment. That is a small share of my total spend and where most of the payoff shows up. The work itself drops down a tier or two. Once the plan exists, the work is mostly mechanical. Drafting, editing, running the steps. Sonnet handles that volume at a fifth of the top-tier rate, and the quality gap on well-scoped work is much smaller than the price gap suggests. Verification climbs back up. This is the part people miss. Checking work is a judgment task, not a clerical one. I plan high, run the work cheap, and verify high again. If you do the whole loop on one model you either overpay for the middle or underthink the ends. Simple checks stay at the bottom. Does this file have the field I expect? Is this post over the character limit? Did the scan return clean? Haiku answers those in a second for pennies, and sending them to a top-tier model buys you nothing but a bigger bill. This is also the logic behind running [Claude Code agent teams](/claude-code-agent-teams/), where cheap sub-agents do the reading and the expensive one keeps the judgment. The common failure is defaulting upward on everything. It feels like insurance. It is really just paying a specialist to do intake paperwork, and you only notice once the capacity is gone. If you want the tactical version of this, I wrote up ten [Claude Code usage tips](/claude-code-usage-tips/) that cover the token math in more detail. ### **Where the Hiring Analogy Breaks Down** I would rather hand you the limits than pretend the frame is perfect. An employee learns. Models do not, at least not between sessions. Your $50-an-hour hire gets better at your business over six months. Sonnet starts fresh every time unless you give it the context yourself, which is why your prompts and files do the work a real onboarding would. Cheaper models are not simply worse. Anthropic positions Haiku 4.5 as near-frontier performance at its most economical price point, built for high-volume straightforward work, and the [Haiku 4.5 release](https://www.anthropic.com/news/claude-haiku-4-5) put it within reach of Sonnet 4 on coding at a third of the cost and more than twice the speed. It is not a junior version of the same brain. On the narrow work it was built for, the tradeoff you think you are making mostly does not show up. The pricing table also reflects raw token cost only. Fewer, better attempts from a stronger model can beat many cheap retries, so a model that gets it right on the first pass sometimes costs less than one you correct three times. I hit that line myself when [Claude Fable 5 launched](/claude-fable-5/), and my honest read was that it was overkill for 90 to 95% of my marketing and content work. ### **Ryan's Final Thoughts** Model selection is a management problem wearing a technical costume. Here is the part most people never accept: the price ladder is not a quality ladder. Paying more does not buy you a better answer on a task that was never hard. It buys you a slower, costlier version of the same answer, which means defaulting upward is superstition rather than insurance. Route by what the task actually demands. Plan at the top, work in the middle, check at the bottom, and send the overflow to a different agency entirely. ### **Which Claude Model to Use FAQs** #### **Which Claude model should I use for most tasks?** Sonnet 5.5 for the majority of daily work. It handles drafting, multi-step reasoning, and code generation at $2 per million input tokens and $10 per million output, which is a fifth of Fable's rate. Move up to Opus 5.5 for work a client will see, and up to Fable 5.1 for genuinely hard architectural or strategic calls. #### **Is Claude Opus worth the extra cost over Sonnet?** For a specific slice of work, yes. Opus 5.5 runs $4 input and $20 output versus Sonnet's $2 and $10, so you pay twice as much. That is worth it for novel problems, decisions with many competing constraints, and final quality checks. It is not worth it for drafting, summarizing, or formatting. #### **What is Claude Haiku actually good for?** Classification, extraction, formatting, routing, and simple verification. At $1 input and $5 output it is the cheapest model in the lineup, and Anthropic builds it for high-volume straightforward tasks where speed and price matter most. Use it for mechanical checks that do not need deep reasoning. #### **Should I use GPT alongside Claude models?** It helps for one practical reason. Running a GPT model through Codex bills against a separate account, so a second-opinion pass does not eat into your Claude capacity. I use it to critique drafts and catch weak arguments, then decide myself what to accept. Its read is input, not a verdict. There is more to that second account than a critique pass, and my guide on [pairing the two agents for marketing work](/claude-code-and-codex-together/) covers where each one earns its keep. #### **Does using a cheaper Claude model hurt output quality?** Not much, on tasks that fit the model. The quality gap tends to show up on open-ended reasoning and matters far less on well-scoped mechanical work. The bigger risk runs the other direction. Paying top-tier rates for routine jobs burns your capacity so fast that you have nothing left for the tasks that genuinely need judgment. --- ## 8 Best AI Marketing Consultants in 2026 (With Real Prices) URL: https://ryandoser.com/best-ai-marketing-consultants/ Markdown: https://ryandoser.com/best-ai-marketing-consultants.md Published: 2026-09-28 | Updated: 2026-09-28 Categories: AI Resources > The best AI marketing consultants in 2026, sorted by what it costs to start, with real prices and who each one is wrong for. These are the **best AI marketing consultants** you can hire in 2026, sorted by what it costs to get started, with the price each one publishes. My own name is here too, so read my entry with that in mind. ### **What Google Shows Instead of the Best AI Marketing Consultants** Search "AI consultants" and page one is enterprise names like BCG, IBM and Gartner. Search "best AI consultants" and you get firm directories. I pulled seven hiring searches on September 28, 2026. Not one page-one result was a list of individual people you could book a call with. Lilach Bullock, one of the eight below, found a similar gap in Google's AI answers when she [ran 47 prompts through Google's AI Mode](https://www.lilachbullock.com/google-ai-mode-ai-marketing-consultants-2026/). Most consultant pages make you book a call just to find out what the first step costs. ### **Best AI Marketing Consultants in 2026** To make this list, a person had to sell AI marketing help to businesses under their own name or a small practice they front, show AI-specific work in public, and be active in 2026. I checked 27 people and practices, and 11 passed. Three are search specialists and one sells enterprise advisory, so they get their own sections below. I held myself to the same three tests, and my entry uses the same format as everyone else's. Every price was read on each consultant's own offer page on September 28, 2026. The order runs from the least you have to commit to get started to the most, then the one who does not publish a price. It is not a quality ranking. | Consultant | What you buy | Least you commit to start | Best for | | Mark Schaefer | A one-hour marketing advice call | $250 per session | Owners who want a senior marketer's read on one decision | | Ryan Doser | Hourly consulting or monthly AI coaching | $500 per hour | Solo operators and small teams who want to build it themselves | | Lilach Bullock | AI audits, fractional CMO work and AI builds | $1,000 for the smallest engagement | Founders and service businesses | | Jonathan Mast | A monthly virtual Chief AI Officer | $1,500 for one month (agencies: $497 a month, 90-day minimum) | Small businesses that want an AI advisor every month | | Britney Muller | A live cohort course on AI for marketers | $1,750 per course seat | Marketers who learn by building a real project | | Nicole Leffer | AI training for a marketing team | $2,999 per team webinar | B2B SaaS marketing teams | | Trust Insights (Christopher Penn and Katie Robbert) | A 90-day AI roadmap for the whole company | $25,000 fixed fee | Mid-size companies with AI pilots but no plan | | Liza Adams | AI workshops and advisory for go-to-market teams | Not published | B2B marketing leaders rolling AI out to a team | *Least you commit to start, read on each consultant's own page on September 28, 2026. Check the live page before you buy.* #### **1. Mark Schaefer (One-Hour Advice Calls)** *Schaefer sells a single one-hour call, not a retainer.* Schaefer is a marketing author and speaker who sells a one-hour call called [Instant Marketing Advice](https://businessesgrow.com/instant-marketing-advice/). His page pitches it as access to "more than 40 years of global business experience." His AI angle comes from his book, *Audacious: How Humans Win in an AI Marketing World*. **Starts at:** $250 per one-hour session. **Best for:** an owner who wants an experienced marketer's opinion on one decision. **Watch out for:** this is broad marketing advice with AI as one lens. You leave with direction, not a working setup. #### **2. Ryan Doser (Hourly Consulting and Monthly AI Coaching)** *My three published options, from one hour to on-site days.* That's me. My [AI consulting page](/ai-consulting/) offers an hourly session, a monthly coaching plan called the [AI Concierge](/ai-concierge/), and on-site days with your team. The public proof is the teaching: more than 470 videos showing the work on a YouTube channel with 40.5K subscribers, and an AI marketing community of 2,000+ members. I also run AI content and SEO systems for clients on retainer. **Starts at:** $500 per hour. The AI Concierge is $999 a month for a 90-minute working call, VIP membership in my AI Marketing Insiders community and my three digital products. On-site days start at $5,000. **Best for:** solo operators and small teams who want to build the system themselves, with someone directing. **Watch out for:** the Concierge is coaching, not done-for-you. Anyone who wants the marketing taken off their plate should pick someone else. #### **3. Lilach Bullock (AI Audits, Fractional CMO, AI Builds)** *Bullock's offer page is aimed at founders and service businesses.* Bullock calls herself "that AI consultant who started in marketing." Her [work with me page](https://www.lilachbullock.com/work-with-me/) covers AI audits, fractional CMO work, training and done-for-you AI builds. She says she has 21 years in marketing and has partnered with Twitter, Dropbox and IBM. In a separate study, she ran the same prompts through six AI engines, 72 runs in all. **Starts at:** $1,000 for her smallest engagements, per her page. Scope and final price get set on a free 30-minute call. **Best for:** founders and service businesses that want AI built into lead generation and ads. **Watch out for:** her page covers both coaching and done-for-you work, so ask whether she or her team will do the build. #### **4. Jonathan Mast (Virtual Chief AI Officer)** *Mast prices his virtual Chief AI Officer service as a monthly subscription.* Mast runs White Beard Strategies and sells a [Virtual Chief AI Officer](https://whitebeardstrategies.com/virtual-chief-ai-officer/) subscription with up to six hours of consulting each month. Agencies get a separate program with two 90-minute mastermind sessions a month and his AI Prompting Mastery course for up to ten team members. **Starts at:** $1,500 a month. The agency program is $497 a month with a 90-day minimum. **Best for:** a small business looking for an AI advisor on call every month. **Watch out for:** the focus is AI across the whole business, not marketing alone. My [fractional Chief AI Officer breakdown](/fractional-chief-ai-officer/) covers when that kind of role is worth paying for. #### **5. Britney Muller (Cohort Course Plus Consulting)** *Muller's cohort course page, with the next start date and seat price.* Muller teaches [Actionable AI for Marketers](https://maven.com/britney-muller/actionable-ai-for-marketers), a live cohort course on Maven. Her own site describes her as an AI consultant and educator. The course page says she was previously at Hugging Face and has 11+ years in AI. It showed a 4.8 rating from 78 reviews when I checked. **Starts at:** $1,750 per seat, with the next cohort running October 6 to November 5, 2026. Consulting rates are not published. **Best for:** marketers who learn best by building a real project alongside a group. **Watch out for:** the published price buys a course, not one-on-one time. Ask directly if you want consulting. #### **6. Nicole Leffer (AI Training for Marketing Teams)** *Leffer publishes her team training prices, starting with a two-hour webinar.* Leffer trains B2B marketing teams on AI. Her [advisor page](https://nicoleleffer.com/ai-marketing-advisor/) says she began doing it full-time in early 2023, and it carries testimonials from the CMOs of Vimeo and SOCi. Her team packages are priced by the tool you use: $4,499 for ChatGPT, $5,499 for Claude or Gemini, and $7,499 for Copilot, each for up to 20 people. **Starts at:** $2,999 for a live two-hour team webinar. **Best for:** B2B SaaS marketing teams where everyone needs to level up at once. **Watch out for:** her page says the $2,999 webinar is not customized for your company. The tailored work starts at the tool packages. #### **7. Trust Insights (90-Day AI Roadmap)** *Trust Insights prints its fixed fee and timeline on the offer page.* Christopher Penn and Katie Robbert co-founded Trust Insights, a small analytics and AI firm. Their [AI Enablement Package](https://trustinsights.ai/ai-enablement-package/) is a fixed-fee, fixed-scope offer. For a fixed fee you get 90 days, four deliverables and a walkthrough call, including a role-by-role report on which tasks AI can take over. **Starts at:** $25,000 fixed fee. **Best for:** mid-size companies that already ran AI pilots and need a written plan. **Watch out for:** it covers the whole company, not just marketing, and it comes from a two-founder firm rather than one consultant. #### **8. Liza Adams (Workshops and Advisory for Teams)** *GrowthPath Partners runs AI workshops for go-to-market teams.* Adams runs [GrowthPath Partners](https://www.growthpath.net/engagements/), which helps go-to-market teams become "Human+AI" organizations through workshops, hands-on training and advisory. Her site features a case study of a cybersecurity marketing team that, by her count, built 211 AI teammates and kept 57 in daily use. **Starts at:** not published. The page offers a free consultation. **Best for:** B2B marketing leaders rolling AI out across a team. **Watch out for:** this is built for teams and leadership groups, not a solo owner. ### **How to Pick One of These AI Marketing Consultants** Price tells you where to start. It does not tell you who is good. The one rule I would not bend: only hire an AI marketing consultant who is a practitioner. That means someone running AI marketing work right now, in their own business or for current clients, who can show you real results from it. Skip anyone whose only proof is a course, a certificate or a slide deck about AI. Some entries here are stronger on this test than others, and each "Watch out for" line tells you where to press. Before you book any of these AI marketing consultants, run them through the [nine questions I would ask any AI consultant](/ai-consultant-for-small-business/), mine included. Two of them matter most with this group. First, ask what you will own when the work ends. Mark Kashef, who builds AI systems for clients, made the point well when I interviewed him. His test for anyone building for a client: can they move it off their own laptop, secure it, and explain it so a non-technical client can follow along? If not, he would build it in a visual tool like n8n that the client can audit and take over. Second, ask whether they build or only advise. A $250 call ends in advice and a $25,000 roadmap ends in documents, so my [consultant vs coach vs fractional CAIO breakdown](/ai-consultant-vs-ai-coach/) will help you pick the right kind of help first. For the rate ranges behind these numbers, [what AI consultants cost in 2026](/ai-consultant-cost/) goes tier by tier. ### **Only Care About Getting Named in AI Search?** If your problem is specifically that ChatGPT and Google's AI recommend your competitors, you want a search specialist rather than a general AI marketing consultant. Before you hire anyone, try the free first step Chris Panteli of Linkifi shared on my podcast. Ask ChatGPT why it recommended a competitor instead of you, then check its reasons against the sources it cites, as I walk through in [my breakdown of asking ChatGPT why it picked a competitor](/how-to-get-chatgpt-to-recommend-your-business/). Nathan Gotch and Aleyda Solis passed my research for this list, and both already sit on my list of the [best AI SEO experts](/best-ai-seo-experts/). Kevin Indig fits the same bucket. I also sell AI SEO consulting and sit on that list myself, so the same disclosure applies. ### **What About the Big Names?** Paul Roetzer's company, SmarterX, sells [executive AI advisory](https://www.smarterx.ai/advisory) for $250,000 a year, US only. That buys four in-person half-days, four one-hour virtual sessions and ten AI Mastery licenses. It is built for enterprise leadership teams, which is why it sits here and not in the list. ### **Why the Price Belongs on the Page** Seven of these eight put a number on their offer page, so you can size the first step before you ever get on a call. Start with the smallest step that answers your real question, and scale up only when the first one pays for itself. Book the hour before you sign the retainer. *Disclosure: I sell AI consulting, which makes me a competitor to most people on this list. I have no financial relationship with anyone else named here, and nobody paid or was asked to be included. [Full disclosure](/disclosure/).* --- ## Best AI for Marketing: 9 Top Models Tested on Real Jobs URL: https://ryandoser.com/best-ai-models-for-marketing/ Markdown: https://ryandoser.com/best-ai-models-for-marketing.md Published: 2026-09-28 | Updated: 2026-09-28 Categories: AI Tool Reviews > Best AI for marketing, tested blind: nine models wrote the same blog post and sales email. Grok 4.7 was the most consistent pick. I gave nine AI models the same three marketing jobs to find the **best AI for marketing** writing, and the most consistent winner was not the model I use every day. ### **Best AI for Marketing in 2026: The Results** Here is the short version from the latest round, run on September 28, 2026. Two blind judges ranked the writing jobs, and a scoring model rated the landing pages. - Most consistent writer: Grok 4.7. It was the only model both judges ranked in their top three on both writing jobs. - Blog posts: Grok 4.7, with Claude Opus 5.5, Claude Fable 5.1 and GPT-6 Sol tied right behind it. - Sales emails: a tie between Opus 5.5 and Grok 4.7. Kimi K3 matched their average rank but broke three rules in the brief. - Landing pages: no clear winner. Every redesign scored within 0.05 of the others on a zero-to-one scale. - Weakest: Gemini 3.8 Flash on the blog post, where it recommended two AI models from 2024 as current picks, and DeepSeek V4 Pro on the email. Claude Opus 5.5 is still my daily driver. That is a workflow choice, not a reading of this data, and I explain it at the end. The briefs and rules for these tests live in skill files, and I packaged the ones I use daily in my **[Claude Code Skills Stack](https://skills.ryandoser.com)**. Most "best AI for marketing" lists compare tools like Jasper, HubSpot and Copy.ai. Many of those tools run on the same few models underneath, so this page tests the models themselves. ### **Best AI for Marketing Test Rounds and What Changed** This page is a living benchmark. A new round runs whenever a major lab ships a new flagship model, and each round adds to the history below. - Round 2, September 28, 2026: added Gemini 3.8 Flash, Grok 4.7, DeepSeek V4 Pro and Kimi K3, then re-judged all nine models together. Grok 4.7 became the most consistent writer, and GPT-6 Sol's unchanged Round 1 email fell from first to a 5.5 average, so read every rank as relative to the field. - Round 1, September 24, 2026: five models (Opus 5.5, Fable 5.1, GPT-6 Sol, GPT-6 Astra and Muse Spark 1.3). Four blog posts tied at an average rank of 2.5, and GPT-6 Sol won the email by a nose. Round 3 runs on the next major flagship release. ### **How I Tested the Best AI for Marketing Writing** What makes this ranking different? Every model got the identical brief and was told not to browse, and the judges never saw a model name. The three jobs are real work from my business. A 500 to 700 word SEO blog post on "best AI models for marketing," a 120 to 180 word sales email for my AI SEO System, and a conversion redesign of that product's real landing page. *Every model gets the same brief. Code checks the rules, and two blind judges from rival labs rank the blog posts and emails.* A script checked each output against the brief for length, banned words and em dashes, and checked every number in the emails against the fact sheet. Then two blind judges ranked all nine blog posts and all nine emails, one from the Claude family and one running on GPT-6 Sol. The nine contestants were Claude Opus 5.5, Claude Fable 5.1, GPT-6 Sol, GPT-6 Astra, [Grok 4.7](https://docs.x.ai/developers/release-notes), Gemini 3.8 Flash, Meta Muse Spark 1.3, DeepSeek V4 Pro and Kimi K3. I ran every model outside Claude and OpenAI through [OpenRouter](https://openrouter.ai), and the four added on September 28 cost $1.24 in total. One disclosure matters. The four Claude and GPT models ran inside my own workspace, where they could read my general setup notes, while the other five saw only the brief. That setup could favor the Claude and GPT entries, and Grok still came out as the most consistent writer. Three of the new jobs also ran out of token budget while the model was still thinking, Gemini's and Kimi's blog posts and DeepSeek's email. I reran each once from the same brief with a higher limit and scored only the finished version. [Gemini 3.8 Flash](https://ai.google.dev/gemini-api/docs/changelog) is in the lineup because Google's newest Pro model is still a preview from February. The first five models ran on September 24 and the last four on September 28, from the same briefs, and all nine were judged together. ### **Blog Post Test: Grok 4.7 Topped the Average** Grok 4.7 was the only post both judges put in their top three. The Claude judge ranked it third, and the GPT judge ranked it first. | Model | Claude judge | GPT judge | Average rank | | Grok 4.7 | 3 | 1 | 2.0 | | Claude Opus 5.5 | 2 | 4 | 3.0 | | Claude Fable 5.1 | 1 | 5 | 3.0 | | GPT-6 Sol | 4 | 2 | 3.0 | | GPT-6 Astra | 6 | 3 | 4.5 | | Kimi K3 | 5 | 6 | 5.5 | | DeepSeek V4 Pro | 7 | 8 | 7.5 | | Meta Muse Spark 1.3 | 8 | 7 | 7.5 | | Gemini 3.8 Flash | 9 | 9 | 9.0 | That makes Grok 4.7 the best AI for marketing blog posts in this round. Opus 5.5, Fable 5.1 and GPT-6 Sol tied at 3.0 behind its 2.0 average. Grok wrote in short, confident lines and added guardrails a real marketer would use. One example: "Keep that pick for a month." The GPT judge called it "specific, memorable advice with strong editorial judgment." Its weak spot was a made-up personal detail, a claim that "most of my clips are 6 to 15 seconds." Meta Muse Spark 1.3 went further and invented a weekly team routine I do not have, which is why I never publish a draft without reading it. Fable 5.1 earned the top copy score from both judges, tied with Grok on the GPT side. That judge still ranked it fifth overall, saying its SEO advice "makes automation sound more automatic than it is." ### **Three Models Recommended AI That Is Already Outdated** Told not to browse, a model asked for the best AI for marketing can only answer from its training data. Three of the nine recommended outdated versions, even though the brief told them to name the model family whenever they were unsure a version was current. - Gemini 3.8 Flash picked "Claude 3.5 Sonnet" for copywriting and "GPT-4o" for data work. Both launched in 2024 and have been replaced several times since. - Kimi K3 called GPT-4o "a close second" for writing. - DeepSeek V4 Pro suggested DALL-E 3 for images inside ChatGPT, which now uses OpenAI's newer image model. *A verbatim excerpt from Gemini 3.8 Flash's post, with the two 2024 model names highlighted.* Gemini also claimed that "standard chat models struggle with search because they pull facts from static training data." ChatGPT, Claude and Gemini all search the web today, and both judges gave Gemini their lowest accuracy score of the round. The takeaway works for any AI tool. When a model recommends a product without searching first, check the release date before you pay for it. My breakdown of [which writing tools are just wrappers](/best-ai-writing-tools/) covers the markup side of that decision. ### **Sales Email Test: A Tie at the Top** Email is the job closest to revenue, and best AI for marketing lists rarely test it head to head. This test measured judge preference, not real sales. Each model got a fact sheet for my $199 AI SEO System and one rule above the rest: use only those facts. | Model | Subject line | Claude judge | GPT judge | Average | Rule breaks | | Claude Opus 5.5 | Is AI search naming you or a competitor? | 3 | 2 | 2.5 | None | | Grok 4.7 | How I got 12.1K AI citations | 2 | 3 | 2.5 | None | | Kimi K3 | how I got 12,100 AI citations in 6 months | 1 | 4 | 2.5 | Three | | GPT-6 Astra | Who does AI recommend instead of you? | 7 | 1 | 4.0 | One | | Claude Fable 5.1 | Is AI search skipping your website? | 4 | 6 | 5.0 | None | | GPT-6 Sol | Does AI search name you or a competitor? | 6 | 5 | 5.5 | None | | Gemini 3.8 Flash | How to show up in AI search | 5 | 8 | 6.5 | None | | Meta Muse Spark 1.3 | AI search is changing who gets found | 8 | 7 | 7.5 | None | | DeepSeek V4 Pro | Your site is invisible to AI search | 9 | 9 | 9.0 | None | Kimi K3 was the Claude judge's favorite email, but it broke three rules. It ran over the word limit, never used the phrase "AI search" the brief asked it to lead with, and rewrote my "12.1K" citations as "12,100," a precision the fact sheet never claimed. That leaves Opus 5.5 and Grok 4.7 as the clean winners, and I call it a true tie. Each judge ranked one of them above an email from its own family, so neither cross-family read breaks it. DeepSeek V4 Pro came last with both judges. "Your site is invisible" is exactly the fear-based hype my list tunes out. ### **Landing Page Test: No Clear Winner** Landing pages were the one job where no model looked like the best AI for marketing. None clearly beat my own page. *Phone views of four redesigns from the September 28 round. All four lead with the $199 one-time price and the $600-an-hour line from my original page.* Every page, including my live original, scored between 0.53 and 0.58 on "would a skeptical owner buy" from Jev, a scoring model on OpenRouter. That spread is too small to pick a winner, and no page was tested on real visitors. Three of the new pages also skipped a required part of the brief, a comment explaining their conversion choices. Landing pages stay my call, and I review them by eye before anything ships. ### **Each Judge Favored Its Own Family, Mostly** For the blog posts, the Claude judge ranked the two Claude posts first and second, and the GPT judge put the two GPT posts second and third. The bias is not absolute, since the Claude judge put Kimi K3's email first and no Claude email in its top two. If a best AI for marketing ranking uses a single AI judge, it may be measuring that judge's taste as much as the writing. I dig into why blind judges still pick their own family in my [Opus 5.5 vs GPT-6 breakdown](/opus-5-5-vs-gpt-6/). It is also why every draft I publish gets a second read from a model outside the family that wrote it, a setup I explain in [how I run Claude Code and Codex together](/claude-code-and-codex-together/). ### **What I Still Use, and When This Test Runs Again** [Claude Opus 5.5](https://www.anthropic.com/claude-opus-5-5) stays my daily driver, for workflow reasons more than test results. It tied for the email win, it placed second with the Claude judge on the blog post, and my whole workflow already runs on it, as I covered in [why I switched to Opus 5.5 for writing](/best-claude-model-for-writing/). Grok 4.7 is the model to watch in the next round. One run per model per job is a snapshot, not a verdict, so this best AI for marketing page gets a new round whenever a major model ships. Google says [Gemini 4 is coming "as soon as possible,"](https://9to5google.com/2026/09/24/google-says-gemini-4-release-is-coming-as-soon-as-possible/) and it goes into Round 3 once it ships. ### **Best AI for Marketing FAQs** #### **What is the best AI for marketing right now?** For marketing writing, Grok 4.7 was the most consistent model in my September 28, 2026 test, finishing in both blind judges' top three on the blog post and the sales email. Claude Opus 5.5 tied Grok for the email win, and no model clearly won the landing page test. Treat any ranking like this as a dated snapshot. #### **Is Claude or ChatGPT better for marketing?** It depends on who is judging. Claude Opus 5.5 and Fable 5.1 tied GPT-6 Sol at 3.0 for blog writing in my test, and Opus beat both GPT models on average rank for the sales email. A Claude judge favored the Claude posts and a GPT judge favored the GPT posts, so compare both judges before you trust any single winner. #### **What AI is better than ChatGPT for writing?** In my blind test, Grok 4.7 outranked both GPT-6 Sol and GPT-6 Astra on the blog post, and Claude Opus 5.5 and Grok 4.7 both outranked them on the sales email. GPT-6 Astra still got the GPT judge's first place for its email, so ChatGPT's models are close, not far behind. #### **Is Gemini good for marketing writing?** Google's Gemini 3.8 Flash was not, in this round. It finished last in the blog writing test with both judges, and the GPT judge flagged its dated picks of Claude 3.5 Sonnet and GPT-4o plus its missing video and SEO advice. Google's newest Pro model is still a February preview, so its standing could change quickly once Gemini 4 arrives. --- ## Opus 5.5 vs GPT-6: Best AI Model of 2026? URL: https://ryandoser.com/opus-5-5-vs-gpt-6/ Markdown: https://ryandoser.com/opus-5-5-vs-gpt-6.md Published: 2026-09-28 | Updated: 2026-09-28 Categories: AI Rabbit Holes > Opus 5.5 vs GPT-6 Sol vs Meta Muse on a real landing page and launch email, judged blind by two AI families. Here is the daily driver I kept. **Opus 5.5 vs GPT-6** became the question of the month on September 22, when Anthropic and OpenAI shipped Claude Opus 5.5 and GPT-6 Sol on the same day, so I put both against Meta Muse on the marketing work I actually do. ### **Watch Me Run Opus 5.5 vs GPT-6 on Real Marketing Work** This episode of AI Rabbit Holes is a livestream with Aaron Makelky, who teaches AI to people who don't write code and tests these models as hard as I do. It picks up a week after our [open source AI models episode](/open-source-ai-models/), where we ran a similar landing page test on cheaper models. Partway through, I pulled up [the side-by-side test I run every time a new model ships](/best-ai-models-for-marketing/). One landing page, one launch email, five models, no branding direction beyond the page itself. Aaron runs OpenAI's cheaper Luna models for his everyday background work, and I run Opus 5.5. The blind judges disagreed with me too, and that turned out to be the most useful result. If you want to build a model test like this for your business, my **[Claude Code Skills Stack](https://skills.ryandoser.com)** includes the Skill Creator I use to turn any repeat job into a reusable skill. ### **My Opus 5.5 vs GPT-6 Verdict for Marketing Work** My call is simple. Opus 5.5 stays my daily driver, and GPT-6 Sol is the model to test first if you pay API rates for high-volume copy. The tiebreaker is voice in my real setup. On the short blog post test, Opus 5.5 used one hypothetical "I'd" and zero soft contrast lines, while GPT-6 Sol used nine and three. Opus ran inside my workspace with my writing rules loaded, and Sol saw only the brief, so this is not a neutral count. It is how I actually run a daily driver, though, and Opus followed those rules with almost no hedging. Hedges and contrast lines are the first things I cut from any draft, so fewer of them means less editing before anything ships. Sol wins on cost. Its list rates are half of Opus 5.5's, and the judges' average put its launch email slightly ahead, so it deserves a real trial for volume work. The video title says Opus 5.5 blew me away, and that is about the jump from Opus 5, which I found hard to write with. That story lives in my [Opus 5 vs Opus 5.5 writing test](/best-claude-model-for-writing/). ### **Daily Driver vs Orchestration Model: Stop Asking for One Winner** Most model debates compare the wrong tier. The benchmark king is rarely the model you should run all day. My split sorts work models into two jobs. The orchestration model is the heavyweight, and right now that means Fable 5.1 or GPT-6 Astra. Use either one for daily work and you can burn through your plan's limit in an hour or two, depending on the plan. Aaron's framing is that this tier writes the plan or does the design work, then hands execution to something cheaper. A daily driver does the volume. For my solo operation that means packaging YouTube videos, writing emails and doing SEO work for clients, so it needs quality and token efficiency at once. Opus 5.5 is my number one daily driver right now. GPT-5.6 Sol held the slot before it, and Opus 4.8 before that. In my opinion, at least for my outputs, Opus 5.5 raised the quality bar over Opus 5 and got more token efficient too. Anthropic says [Claude Opus 5.5](https://www.anthropic.com/claude-opus-5-5) costs less per token than Opus 5 and uses fewer tokens per task, which it puts at a 40% drop in costs. *Two lanes for work models plus a third for personal assistants. Save the heavy models for planning, and pick the daily driver by testing it on the pages and emails you actually ship.* That split is why the Opus 5.5 vs GPT-6 question only matters for the daily driver slot. ### **Opus 5.5 vs GPT-6 on Paper: The Leaderboard and the Price Tag** The leaderboard and the price tag tell different stories, and they don't even feature the same GPT-6 model. OpenRouter's [Discover models page](https://openrouter.ai/discover) shows a frontier chart built on the Artificial Analysis intelligence index. *OpenRouter's frontier chart on September 24, 2026, the day we recorded. It lists one model per lab, so GPT-6 Sol does not appear.* When we recorded, Claude Opus 5.5 sat first at 58, with GPT-6 Astra and Qwen3.8 Max tied at 53. The headline read "Claude Opus 5.5 takes the frontier lead." Price flips the story. On the API, Opus 5.5 lists at $4 per million input tokens and $20 per million output, while [GPT-6 Sol](https://openai.com/index/introducing-gpt-6-sol-and-luna/) lists at $2 and $10 on OpenAI's standard tier. On list rates for uncached input and output, that makes Sol half the price of Opus 5.5 as of September 28, 2026. Cached and long-context rates differ, and both labs move prices often, so read the live pricing pages before you budget. ### **The Landing Page Test: Meta Muse Wrote the Standout Headline** The model I expected the least from wrote the line that stood out to me most. The page was my live landing page for The AI SEO System, which Opus 4.8 originally built. Five models got the same page and one instruction: make it drive as many conversions as possible. Opus 5.5 kept my screenshots and gave me a lime buy button that jumps off the page. My first reaction was that I liked it, apart from a few logo colors. GPT-6 Sol went darker and much shorter, 1,324 words against the original's 2,673, with only two testimonials. Then Meta's Muse model, the API version rather than the Muse app, opened with this. *The Meta Muse hero from the September 24 test. This headline is the line that jumped out at me first.* "Your buyers ask AI who to buy. Make sure it names you." That first sentence above the fold is what really stood out to me when I first scrolled the five pages. Aaron went further on the details. He liked the glow on the checkout button and the full-color client logos on a single line, calling a few choices "empirically better than Claude Opus 5.5." He added the qualifier himself: "I'm not going to say overall better." GPT-6 Astra drifted furthest off brand, which it also did in my previous round of tests. Every page was usable with a few tweaks. For landing pages, the Opus 5.5 vs GPT-6 gap in my test was small. ### **The Launch Email Test: My Eye Said Opus, the Judges' Average Said Sol** If the subject line misses, most people never read the rest of the email. So the second round was a short launch email for the same product, and I judged the subject line first. *Launch email drafts from GPT-6 Sol, Meta Muse and Opus 5.5. Sol and Opus landed on nearly the same subject line.* Opus 5.5 wrote "Is AI search naming you or a competitor?" and GPT-6 Sol wrote "Does AI search name you or a competitor?" Aaron spotted that Opus 5.5 vs GPT-6 Sol came down to almost the same line. Muse went with "AI search is changing who gets found." Aaron's read was that it doesn't open a loop in your brain, and I wouldn't use it. My pick was Opus, with Sol a super close second. Then my test handed all five emails to two blind judges, one Claude and one GPT, with the model names stripped out. Averaged across both judges, GPT-6 Sol won by a nose. It scored an average rank of 2.0, against 2.5 for both Opus 5.5 and Fable 5.1, and Muse finished last with both judges. ### **Why Blind AI Judges Still Pick Their Own Family** In my test, hiding the model names did not stop the judges from favoring their own side. The GPT judge ranked the two GPT emails first and second, even though the Claude contestants had my workspace rules loaded and the GPT contestants did not. The Claude judge did the same for the two Claude emails. A short blog post test in the same run split the same way, and both judges put Muse last there too. My best guess is house style. Each family seems to recognize its own voice even with the names removed, so a same-family judge flatters its own model. One more caveat on my setup. GPT-6 Astra ran at medium reasoning while Sol ran at high, and the Claude judge had my workspace context, so treat those two reads with care. The cross-family read is the one I trust most. The Claude judge's favorite GPT email was Sol, and the GPT judge's favorite Claude email was Opus 5.5. On this one email, Opus 5.5 vs GPT-6 Sol came down to half a rank, and my own pick went the other way from the judges' average. When a single model family grades a clear winner, treat the result with suspicion. That finding is why every draft Claude writes for me still gets a GPT review before it ships, the same pairing behind [using Claude Code and Codex together](/claude-code-and-codex-together/). ### **Where Meta Muse Actually Fits: Your Calendar and Errands** The Muse app is Aaron's territory, not mine. My test ran Meta's model through OpenRouter's paid API, and the app never went on my Mac. Meta launched the [Muse app](https://ai.meta.com/muse/) on September 8 as a personal agent with a free tier and a paid subscription, US only for now. Aaron uses it daily for errands, like turning a photo of a birthday party invite into a calendar event with a gift reminder. His warning is that you cannot see, change or bring your own model. Meta says Muse conversations are not shared with its ad systems, but a free agent inside WhatsApp and Meta's other apps still looks like a long game for the ad business to me. For the Opus 5.5 vs GPT-6 decision, Muse isn't necessarily a daily driver for marketing at all. It wrote one great headline, then finished last on the email and the blog post. ### **Build Your Own Opus 5.5 vs GPT-6 Test Before the Next Launch** Aaron's best advice from the episode was to build a skill around whatever you are best at judging. A designer tests design, and a marketer tests email copy. Mine is a slash command in Claude Code that runs every new model on the same landing page, email and blog post, then lays the outputs out on one local page. Keep that test portable as a markdown skill rather than a custom GPT. OpenAI retires custom GPTs on December 11, and I covered the move in [Claude skills vs custom GPTs](/claude-skills-vs-custom-gpts/). Run your test the week a model ships, grade it with a judge from a different family, and let your real pages and emails pick the daily driver. ### **Opus 5.5 vs GPT-6 FAQs** #### **Is Claude Opus 5.5 better than GPT-6?** It depends which GPT-6. On September 24, Opus 5.5 led OpenRouter's frontier chart over GPT-6 Astra on the Artificial Analysis intelligence index. Against GPT-6 Sol on marketing copy the result was close, so I keep Opus 5.5 as my daily driver because it follows my writing rules with less hedging in my own setup, and I would test Sol first for high-volume API work, where it costs less. #### **Is GPT-6 Sol cheaper than Opus 5.5?** Yes, by half on list rates for uncached input and output on the standard API. As of September 28, 2026, GPT-6 Sol listed at $2 per million input tokens and $10 per million output, against $4 and $20 for Opus 5.5. Anthropic says Opus 5.5 uses fewer tokens per task than Opus 5, so compare the cost of a finished job, not just the rate card. #### **Which AI model is best for marketing copy in 2026?** No single model won cleanly in my test, and each blind judge favored its own model family. Pick your daily driver by running the candidates on your own emails and pages, counting the edits each draft needs, and having a judge from a different family grade the results. #### **Is Meta Muse good for marketing?** Not as a copywriter, based on my test of Meta's Muse model through OpenRouter's API. It wrote the landing page headline I singled out, then finished last with both blind judges on the email and the blog post. The Muse app itself is a personal agent with a free tier, and Aaron's warning is that you cannot choose the model behind it. --- ## How to Start an AI Business Anyone Can Launch (Copy This) URL: https://ryandoser.com/how-to-start-an-ai-business/ Markdown: https://ryandoser.com/how-to-start-an-ai-business.md Published: 2026-09-25 | Updated: 2026-09-25 Categories: AI Rabbit Holes > How to start an AI business with no code: the two-call monthly offer Corey Ganim sells, what his clients pay, and how he found them. Corey Ganim's answer to **how to start an AI business** without writing code is a service: teach business owners to use Claude on two calls a month, for a monthly retainer. ### **Watch Corey Ganim Explain How to Start an AI Business** Corey came back on AI Rabbit Holes to walk through the offer he calls AI Concierge. His first episode covered the [$999 AI tools assessment that feeds this offer](/ai-audit-business/). Plenty of advice on how to start an AI business means building a software product. This episode takes the other road, a service you can sell with tools you already use. Corey's clients end up with Claude skills built around their own business. If you want to see what finished skills look like, my **[Claude Code Skills Stack](https://skills.ryandoser.com)** holds the ones I run for my own marketing work. ### **How to Start an AI Business Corey's Way, Step by Step** The steps below follow the order you would actually do them in. Every number is Corey's, from the episode or his own newsletter, unless I say otherwise. #### **Pick an industry you already know** I raised this in the episode, and Corey agreed. Someone with 20 years in law could run this for lawyers, an accountant for accountants, and I would pick marketing agencies and marketing departments. A shotgun offer for anyone makes results harder to deliver consistently. As I put it in the episode, industry experience is the moat most people have without realizing it, because a $20-a-month model still misses the nuances of a trade you have worked in. Corey admitted his own clients span financial services, info products, D2C, fintech and insurance, industries where he has little background. He spent nine years in e-commerce and said, mid-conversation, that an e-commerce version might let him charge more. His guess is that a former realtor selling to realtors could charge $3,500 to $4,000 a month, against his roughly $2,000 without that background. Treat that as his estimate, not market data. I run a smaller version of this myself, my [AI Concierge](/ai-concierge/), with a few clients on it. Most of my client work is marketing on the agency side. #### **Aim at owners who can pay** The buyer is an owner who is good at business and barely uses AI. Corey pitches his assessment to companies doing $500,000 to $10 million a year, and the monthly offer to bigger ones. His smallest concierge client does roughly $5 million a year in revenue. The largest is the CEO of a $150 million company, who pays him $2,000 a month. I added a point here during the episode. Owners at five, ten or twenty million dollars in revenue are the better fit, because the return is easier to measure and there is budget to spend. That gap between money and AI skill is wide. Across US businesses of every size, fewer than one in four (23.8%) told the Census Bureau's [Business Trends and Outlook Survey](https://www.census.gov/data/experimental-data-products/business-trends-and-outlook-survey.html) they used AI in the two weeks ending September 6, 2026. One of Corey's first clients was his financial planner, whose firm he estimates at seven or eight million dollars a year. She was not using AI at all, and his first two calls with her went to making her marketing assets look consistent in Claude. #### **Build one Claude skill for yourself** Corey's qualification bar is low on purpose. He says that if you have built one [Claude skill](https://support.claude.com/en/articles/12512176-what-are-skills) for yourself, you are qualified to sell this, because most owners have no idea where to start. That bar covers the sale. Delivering results for a $5 million company is the part to be honest with yourself about. If you have not built one yet, my guide to [creating your first Claude skill](/claude-skills/) covers four ways to do it. #### **Start with people who already know you** Corey's first six sales conversations were calls already on his calendar, including his financial planner and his insurance agent. He mentioned what he was working on, and they asked what it cost. For anyone without that network, his script is a text to five small business owners in your phone. Church, the gym, and the parents of your kids' friends all count. The message is short: you recently got into AI, found tools that might save the business time or money, and would like to spend 15 free minutes showing how they apply. Worst case they learn something about AI, and best case they leave with a real result. Of five texts, Corey expects two or three yeses. #### **Or host a free local meetup** His slower channel is an in-person meetup called AI for Business. He rented a coworking space for about $200 for two hours and posted it in local Facebook groups. About 25 people came to the first one. The format is 30 minutes of networking, a 15-minute demo, then 30 more minutes of networking. At the first meetup the demo was building a very simple Claude skill. Whoever runs the room becomes the AI person in town, and Corey calls it his best long-term channel for local clients, with a lead time of two to six months or more. #### **Turn a free call into a paid assessment** The free call covers one problem and one tool. If it lands, Corey offers the full AI tools assessment at $999. That assessment is a 45-minute interview that ends with three to seven off-the-shelf tools prescribed for the owner's problems. In Corey's telling, a good one leaves the owner wanting a guide. *The ladder Corey describes. A free win earns the paid assessment, and the assessment earns the coaching pitch.* #### **Pitch the monthly coaching** This is the AI Concierge offer itself, which Corey describes as done-with-you consulting. He meets the owner on a video call twice a month, for 45 minutes each time. On those calls he teaches the owner to use Claude and turns their manual processes into Claude skills. The owner does the clicking, while Corey tells them what to prompt and what to build. *Corey's opening slide. The $8,000 MRR line is his own figure, from five clients he signed in his first ten days.* #### **Price it, then cap it** Corey built the offer backwards from one question: what would need to be true for him to earn $1,000 an hour consulting on AI? Hourly Zoom calls, in his view, top out around $500 an hour, and few buyers pay even that. Two 45-minute calls add up to an hour and a half a month. At $1,500 a month that works out to $1,000 an hour of call time, and at $2,000 it is $1,333. *Corey's pricing slide, captured when we recorded in September 2026. It predates his $2,500 minimum, and the hourly figures count call time only.* The slide gives a beginner's ladder. Start at $1,000 a month and never less, then raise the price to $1,500 once two clients are paying $1,000. His own first clients came in at $1,200 to $2,000 a month. Per [his newsletter](https://corey-ganim.kit.com/posts/how-i-m-making-1-000-hour-as-an-ai-concierge), five of the first six people he pitched said yes, at $1,200, $1,500, $1,500, $1,800 and $2,000, which adds up to $8,000 a month. A yes rate that high told him he was cheap. He now quotes a $2,500 minimum, which is about $1,667 per call hour by my math. He gave three reasons for the raise: more confidence, testimonials and case studies from five months of this work, and the value of the time he buys back. His claim is that saving an owner five to ten hours over an engagement is worth tens of thousands of dollars a year to them. He caps the offer at six clients so the service does not slip. Here is the whole offer in one place. | Corey Ganim's AI Concierge offer | His numbers (September 2026) | | Calls | Two 45-minute calls a month, 1.5 hours total | | First five clients, signed in his first ten days | $1,200, $1,500, $1,500, $1,800 and $2,000 a month, $8,000 combined, from six pitches | | Current minimum | $2,500 a month | | Rate per call hour | $1,000 at $1,500 a month, $1,333 at $2,000 (call time only) | | Client cap | Six clients | | Assessment buyers | Companies doing $500,000 to $10 million a year | | Retainer buyers | Companies doing roughly $5 million to $150 million a year | Two caveats before you run those numbers on yourself. The hourly rate ignores prep, the intake review and messages between calls, and none of this is a promise of what you will earn. For context, my [rate card on what AI consultants charge](/ai-consultant-cost/) puts most monthly retainers at $2,000 and up. Corey's $2,500 minimum sits near the bottom of that range, for about an hour and a half of calls a month. The cap is worth copying before the price is. Six clients is nine hours of calls a month, and your calendar runs out long before demand does. #### **Deliver four things every month** Corey's offer has four pieces, and the last one is what keeps clients renewing. - An intake form that Claude builds for him through a form-tool connector. It surfaces the three tasks eating the owner's week, and no form means no first call. - Two 45-minute working calls every month. Call one gets the owner set up in Claude, and later calls build skills live on screen. - Unlimited messages between calls on [Voxer](https://www.voxer.com), a walkie-talkie style app. - A shared [Notion](https://www.notion.com) hub with everything built together, the call transcripts, and his contact details. *Corey's deliverables slide. His calls run in an audit-first order: fix the process, then automate it.* The hub is his renewal tool. The owner can see, on one page, everything the two of them have built together. My addition on the call was to put those transcripts to work. Feed them into the client's AI systems, and everything you covered becomes material their workflows can learn from. Corey took it a step further and said he would probably steal it. His version is one Claude Project per client that holds every call transcript, a brain for the engagement the owner can question between calls. ### **Why Owners Will Still Pay When Claude Gets Smarter** The obvious objection is that Claude will soon be good enough for owners to do this themselves. My answer on the call was that they could do it right now if they wanted to, because the models are already good enough. Corey's answer is the website. Claude can build a site in minutes that looks better than what $10,000 bought ten years ago, in his words, and people still pay for websites in 2026. His example buyer is a manufacturing shop owner who is excellent at his trade and has no interest in learning AI. Better models do not change what that owner wants, which is someone to show him the way. If you are still deciding how to start an AI business, begin with the owners in your phone and a trade you have worked in. ### **How to Start an AI Business FAQs** #### **How much does it cost to start an AI business?** For the service version in this post, very little. You need a paid AI subscription, roughly $20 a month at the entry tier, plus a calendar and a video call tool. If you host a meetup, Corey paid about $200 to rent a coworking space for two hours. The real cost is time: learning Claude well enough to build a skill, then finding the first client. #### **Do you need to know how to code to start an AI business?** Not for this model. Corey's clients learn Claude and build Claude skills, which are folders of instructions, scripts and resources rather than an app you build and sell. His bar for selling the service is having built one Claude skill for yourself. Building an AI software product is a different path, and that one usually needs engineering help. #### **How much should a beginner charge for AI coaching?** Corey's slide says to start at $1,000 a month, never less, then move to $1,500 once two clients are paying $1,000. He now quotes a $2,500 minimum after five months with five clients. His signal that you are too cheap is when nobody says no. Firms price monthly retainers higher, which the rate card linked above covers tier by tier. #### **Do AI consultants make good money?** Some do, and Corey's numbers are one person's results, not a benchmark. His call-time math reaches $1,000 to $1,333 an hour, but prep, intake reviews and messages between calls are unpaid hours on top. Only 23.8% of US businesses reported using AI in early September 2026, which is the skills gap this model sells into, yet income depends on finding owners who can pay. --- ## Claude Opus 5.5 Is the Best Claude Model for Writing (Finally) URL: https://ryandoser.com/best-claude-model-for-writing/ Markdown: https://ryandoser.com/best-claude-model-for-writing.md Published: 2026-09-23 | Updated: 2026-09-23 Categories: Claude Code > Opus 5.5 is the best Claude model for writing again. My side-by-side test against Opus 5, how I use it in my agency, and why switching was painless. After two months of babysitting Opus 5 drafts, **the best Claude model for writing** is an Opus again, and Claude Opus 5.5 is now my daily driver. I tested it against Opus 5 on my own writing rules before saying that. ### **Why Opus 5.5 Is the Best Claude Model for Writing Now** How often does a company call out its last model's writing on a launch page? Anthropic released [Claude Opus 5.5](https://www.anthropic.com/claude-opus-5-5) on September 22, 2026, and gave writing its own section. Their words: writing was "one of the most common areas of feedback we heard about Opus 5." They say the new model "puts the most important information up front, is less likely to use jargon or idiosyncratic phrases, and follows the writing rules you give it." That last clause matters most. A model that ignores your style guide costs you an editing pass on every draft. Anthropic also ran a research-report test where any invented figure or quote meant failure. 16 of 18 Opus 5.5 reports cleared its quality bar, and neither Fable 5.1 nor Opus 5 cleared it in any attempt. If you want the writing rules I hand every model before it touches a draft, I packaged them in my **[Claude Code Skills Stack](https://skills.ryandoser.com)**. *From Anthropic's launch page. Opus 5 opens with an em dash and an "isn't X, it's Y" swap, two habits my writing rules ban outright.* The Opus 5 answer starts with "The extra drop isn't the free tier," then an em dash, then "it's a regression." Opus 5.5 leads with the answer and the dollar amounts instead. ### **Opus 5 Was a Tragedy for Anyone Who Writes** Opus 5 shipped on July 24, 2026, and its writing is where my summer went sideways. By mid-August I widened a standing rule so every piece of writing a Claude model produced got a second read from GPT-5.6 Sol in Codex before it shipped. On my Skool live Q&A call on September 4, I said it plainly: "I'm starting to really hate Opus 5, if I'm being completely honest with you." I also said GPT-5.6 Sol had to "come in and clean up a lot of things." For most of the summer, the best Claude model for writing in my setup was really a pair: Opus 5 drafting, GPT-5.6 Sol cleaning up behind it. Eighteen days after that call, the upgrade landed. ### **My Opus 5 vs Opus 5.5 Writing Test** Opus 5 never broke my punctuation or word bans in this test. It kept breaking the paragraph rule, the one that makes a post readable on a phone. I could not find an independent writing test of Opus 5.5 yet, so I ran a small one on September 23, 2026. Same brief, same rules, five runs per model through Claude Code, scored by a script so the counting did not depend on my judgment. The brief was a 150 to 200 word LinkedIn post about AI subscription bloat. The rules were mine: no em dashes, no semicolons, no "it's not X, it's Y" swaps, a banned word list, and one or two sentences per paragraph. | Result (5 runs each) | Opus 5 | Opus 5.5 | | Runs that followed every rule | 0 of 5 | 4 of 5 | | Em dashes, banned words or swaps | 0 | 0 | | Paragraphs over two sentences | 10 | 1 | | Average cost per post in Claude Code | $0.41 | $0.28 | | Average time per post | 42 seconds | 34 seconds | Cost per post dropped by about a third on average, including Claude Code's own overhead. One unusually cheap Opus 5.5 run pulls that average down, so call it a quarter to a third. *Launch-day pricing per million tokens, as Anthropic listed it on September 22, 2026. Check the live rate before you budget.* Input and output run $4 and $20 per million tokens on Opus 5.5, against $5 and $25 on Opus 5. Anthropic says it also uses fewer tokens per task, so at default settings it costs 40% less than Opus 5 on typical workloads. This measures rule-following, speed and cost, not whether the ideas were better, and ten posts on one brief is a spot check. Rule-following is still the part that costs me editing time, so it is how I judge the best Claude model for writing. For a wider field, I later ran nine models from every major lab through [a blind test on real marketing jobs](/best-ai-models-for-marketing/). ### **Where Opus 5.5 Fits in My Solo Marketing Agency** I run a one-person marketing agency, and most of what I ship is writing. That makes picking the best Claude model for writing a real business decision for me. Since launch day, Opus 5.5 is my default for audience-facing writing like this: - Client SEO content, like blog posts for a dental IT client, built from that client's brand docs and my [Claude Code SEO workflow](/claude-code-seo/). - My own blog, including posts repurposed from my YouTube videos. - My weekly newsletter to about 7,000 subscribers, plus LinkedIn and X captions. - YouTube titles and descriptions, and research on podcast guests before I hit record. Each job has its own skill file, and every piece of writing gets a GPT-5.6 Sol critic pass in Codex. The rules flag problems, and I decide what ships. This post is the launch-day example. Opus 5.5 drafted it inside my blog skill, GPT-5.6 Sol critiqued it in Codex, and I sent it back for another round before it went live. ### **Where Opus 5.5 Still Loses** Being the best Claude model for writing does not make Opus 5.5 the best model for every job. In my [blind test against GPT-6 Sol and Meta Muse](/opus-5-5-vs-gpt-6/), Sol came within half a rank on a launch email at half the list price. *Anthropic's own benchmark table. GPT-6 Astra still takes business workflows and agentic scientific research.* On AutomationBench, the business workflow test built by Zapier, GPT-6 Astra scores 41.4% to Opus 5.5's 40.0%. That is the row closest to marketing ops, and OpenAI's model still edges it. For volume, Sonnet 5 keeps its spot. At $2 input and $10 output per million tokens, it costs half as much as Opus 5.5 for bulk first drafts, and my test did not cover it. My split: Opus 5.5 for anything a client or audience will read, Sonnet 5 for bulk drafts a second pass will clean up. Fable 5.1, at $10 input and $50 output, stays reserved for the hardest strategy calls. ### **Why Switching to Opus 5.5 Took Zero Rebuilding** The next time a new model becomes the best Claude model for writing, my output quality stays put, because everything that makes it good lives outside the model. Opus 5 was the stress test. When the model slipped, I bolted a GPT critic onto every draft with one rule change, and every skill file, brand doc and connection kept working untouched. I call that layer the harness: skills, context and connections. In plain terms, my voice rules and blog checklist as skill files, a folder of brand docs for each client, and connections to my email platform, my SEO data and my website. *The model is the plug. Skills, context and connections are the outlet, and the outlet is what you own.* When Opus 5.5 arrived, the [Claude Code model settings](https://code.claude.com/docs/en/model-config) made it the default on Pro, Max, Team and Enterprise plans once Claude Code is on version 2.1.280 or later. Nothing else needed an edit. Both agents sit in one VS Code window: the [Claude Code extension](https://code.claude.com/docs/en/vs-code) on one side, the [Codex IDE extension](https://learn.chatgpt.com/docs/codex/ide) on the other. I broke down that split in [why I run Claude Code and Codex side by side](/claude-code-and-codex-together/). A harness will not make a bad model good. It makes a bad model cheap to route around, which is the point of [building a model agnostic AI system](/reality-of-ai-in-2026/). ### **Opus Is Back in the Driver's Seat (For Now)** For now, Opus 5.5 is the best Claude model for writing, and it writes the way Opus should have written all summer. I will still swap it the week something better ships. For the full routing across Fable, Opus, Sonnet and Haiku, see my guide on [which Claude model to use for each job](/which-claude-model-to-use/). ### **Best Claude Model for Writing FAQs** #### **Is Claude Opus 5.5 better than Opus 5 for writing?** For following your writing rules, yes. Opus 5.5 held a two-sentence paragraph rule in four of five runs of my test, while Opus 5 missed it in all five. On Anthropic's research-report test, where one invented figure meant failure, Opus 5.5 cleared the quality bar 16 times out of 18 and Opus 5 never did. #### **Which Claude model is best for writing marketing content?** Use Opus 5.5 for writing a client or audience will read, at $4 input and $20 output per million tokens on launch day. Sonnet 5, at $2 and $10, costs half as much for bulk first drafts that get a second pass. Fable 5.1, at $10 and $50, is for rare high-stakes strategy work. #### **Did Claude get worse at writing?** Anthropic called writing "one of the most common areas of feedback we heard about Opus 5" and answered with a new model, Opus 5.5, rather than a patch. If Opus 5 is still pinned in your setup, update Claude Code and switch the model setting. Opus 5.5 needs Claude Code version 2.1.280 or later. --- ## OpenSEO Review: Is This Open Source Semrush Alternative Worth It? URL: https://ryandoser.com/openseo-review/ Markdown: https://ryandoser.com/openseo-review.md Published: 2026-09-23 Categories: AI Tool Reviews > Hosted OpenSEO resells DataForSEO data at a 28% markup. I priced comparable jobs direct in Claude Code to see what its $10 layer adds. In February, Google Ads data put US searches for "openseo" at 10 a month. In August the same estimate was 2,900. Its GitHub repository passed 20,000 stars in under seven months. **OpenSEO** is an open source SEO platform for keyword research, rank tracking, backlinks, site audits and AI visibility, with an MCP server built in. MCP (Model Context Protocol) is how an AI assistant such as Claude or Codex plugs into another tool and uses its data mid-conversation. The hosted version costs $10 a month. Almost all of its SEO data comes from DataForSEO, a pay-as-you-go data service I run every day inside Claude Code and Codex. OpenSEO's own GitHub page explains how the hosted service makes money: it charges "28% extra for every request we make to DataForSEO." So the useful question is narrower. What does the markup and the monthly fee buy you, and does an AI agent already connected to DataForSEO make that layer redundant? Where I stand: I have not used OpenSEO myself. This review works from OpenSEO's public code and live pricing pages, plus comparable requests I ran through my own DataForSEO account. I am a DataForSEO affiliate, and I sell a competing AI SEO product. ### **What OpenSEO Is and Who Builds It** OpenSEO is built by Ben Senescu, a former Klaviyo software engineer, and the company behind it is Every App, Inc. The code is MIT-licensed, which means anyone can use, modify or copy it for free. The repository was created in February 2026 and has shipped 37 releases since, the latest being v0.1.9 on September 17. For a buyer, "pre-1.0" means features, setup steps and pricing behavior can change faster than they would in a mature product. *The keyword research view, from OpenSEO's own feature page. The keyword numbers on this screen come from DataForSEO.* The web app covers the jobs most small teams buy Semrush or Ahrefs for. You can find keyword ideas, check a competitor's rankings and backlinks, track your own positions, audit a site, and look up how often AI assistants mention a brand. The homepage pitch has shifted toward agents. The headline reads "SEO made simple," followed by "Connect your favorite AI agent in 2 minutes." The MCP server exposes 57 tools, and ten packaged skills walk an agent through jobs like competitor analysis and link prospecting. You can run it two ways. Hosted, at openseo.so, for $10 a month. Or self-hosted for free, where you bring your own DataForSEO account and pay DataForSEO directly. For most marketers reading this, hosted is the practical choice. Self-hosting takes technical setup, and the simplest local version runs without a login, so it is meant for a private machine rather than the open internet. ### **Where the Data Actually Comes From** My starting assumption was that OpenSEO is a friendly screen over DataForSEO and not much else. For the third-party SEO numbers, that turned out to be right. OpenSEO's public code shows keyword ideas, search volume, live Google results, competitor rankings, backlinks, local results and AI mentions all requested from DataForSEO behind the scenes. OpenSEO does not collect that data itself. It does not hide this either. The homepage says it outright: "An SEO tool is nothing without quality data. That's why OpenSEO uses DataForSEO. But we also do much more." One more detail from its GitHub page: the DataForSEO link there carries OpenSEO's own affiliate code. So OpenSEO earns from DataForSEO signups the same way I do, and anyone recommending either path is sending money to DataForSEO. The "much more" holds up, and it is where my first read was too simple. Several pieces are OpenSEO's own work: - **Its own site audit crawler.** OpenSEO chose to build one rather than use DataForSEO's. Only the optional page-speed check goes to DataForSEO. - **Google Search Console and Google Analytics connections**, pulled straight from Google and free of credits. - **Memory between sessions.** Each project stores your business overview, goals and saved keywords, and your agent reads them when it starts work. - **Scheduled rank tracking with history**, plus saved reports you can share with a link. - **An in-app assistant called SAM**, currently in beta, which runs on an outside AI model rather than DataForSEO. So the fair description is a DataForSEO client with a workflow layer and its own crawler. The data is rented. The memory, scheduling and reporting are built. If you already have an AI agent connected to DataForSEO, you have the data half. The question is whether you need the other half. *Both routes draw on the same DataForSEO data. The difference is what sits in between.* ### **What the Direct Route Looks Like in Claude Code** I walked through the direct setup on my YouTube channel, using keyword research as the example. The written version lives in my guide to [keyword research in Claude Code](/claude-code-keyword-research/). The setup has three parts. A keyword research skill, which is a saved set of instructions telling Claude Code how you want the job done. A DataForSEO account connected through its MCP server. And a plain prompt, such as asking for 15 keyword ideas around a root topic. Claude Code comes back with a table of search volume, keyword difficulty, cost per click and intent. If some ideas are off-target, you say so and Claude revises the list, and you can update the skill so the fix sticks next time. The keywords you keep can go straight to a blog-writing skill in the same session. I run the same setup in Codex as well. In the video, a full keyword run, which can involve several requests, cost me roughly five to ten cents. The keyword research skill is the direct-route counterpart to OpenSEO's packaged skills, with one difference: it encodes your own process. The video also covers the upgrade path. Ahrefs Lite at $129 a month includes MCP access, and I still rate Ahrefs' keyword data above DataForSEO's. That ceiling on the underlying data applies to OpenSEO too, since it runs on DataForSEO. *Affiliate links below. [Full disclosure](/disclosure/).* If you want to try this route, [DataForSEO's free starting credit](https://dataforseo.com/?aff=245611) covers a few test runs before you deposit anything. ### **What $10 Buys Once the 28% Comes Out** There is one plan. The [OpenSEO pricing page](https://openseo.so/pricing) lists the Base Plan at $10 a month, and that $10 includes $10 of usage. There is no annual option. Prices below were checked on September 23, 2026. *One plan, $10 of usage included, and an estimator that prices each task.* The usage works like a prepaid balance. Each task draws it down, and the page's estimator prices the common ones: about $0.05 per keyword search, about $0.08 per backlink check, and about $1.09 per ChatGPT brand check, which the page calls "the expensive one." How the balance behaves matters as much as the price: - The included $10 resets every billing cycle, so whatever you do not use that month is gone. - Extra top-up credits "roll over indefinitely," but you still need an active subscription to spend them. - When credits run out, tasks return errors instead of billing you more. No surprise invoices, which I like. The free trial is $0.50 of credits, enough for roughly ten keyword searches. Take the 28% out and the $10 plan buys about $7.81 of DataForSEO requests. OpenSEO's billing code also charges SAM's AI model costs to the same credit pool, which the pricing FAQ does not mention. OpenSEO's pricing page compares itself this way: "Ahrefs' cheapest plan is $129/mo." That is Ahrefs Lite, its entry full suite. The live [Ahrefs pricing page](https://ahrefs.com/pricing) also lists a limited $29 Starter plan and a free tier, so the gap is smaller than the line suggests. Semrush sits in the same band as Ahrefs Lite. Its entry SEO plan is $139 a month, or $117.33 a month billed annually, on the [Semrush pricing page](https://www.semrush.com/prices/). Against either full suite, $10 is a very different purchase. The closer comparison is DataForSEO itself. ### **I Ran Comparable Jobs Straight Through DataForSEO** To see what the markup means in dollars, I ran requests matching OpenSEO's estimator tasks directly through DataForSEO in Claude Code, on my own account. DataForSEO reports the exact cost of every request, so the left column is what I was charged. | Task | DataForSEO direct (my charge) | OpenSEO's estimate | | Keyword research, 150 ideas | $0.03 | About $0.05 | | Backlink overview plus a year of history | $0.048 | About $0.08 | | One live Google results page | $0.002 | Part of rank tracking | | AI brand lookup, ChatGPT side (three requests) | $0.30 | About $1.09 | | AI brand lookup, Google side (three requests) | $0.32 | About $1.09 (same per-platform rate) | The whole run cost me about 70 cents. Adding OpenSEO's stated 28% to that exact run would make it about 89 cents. The estimates run higher than my charges because they assume typical result sizes, and my test brand returned very few rows. DataForSEO prices the AI brand data at about $0.10 per request plus a fraction of a cent for every mention returned. OpenSEO's pricing page labels its $1.09 a ChatGPT check, but its pricing code budgets that amount per platform, and every brand lookup covers both ChatGPT and Google. A brand with more mentions costs more. That cuts against my own starting position: **at small volume, the 28% markup is pocket change.** Nobody should skip OpenSEO to save 20 cents. Where the two differ more is how you pay. OpenSEO bills $10 every month and wipes the unused part. DataForSEO asks for a $50 minimum deposit, and [new DataForSEO accounts start with $1 of free credit](https://dataforseo.com/?aff=245611) to test first. That DataForSEO balance never expires. If your usage is $3 a month, OpenSEO still charges $10, while a $50 deposit at that pace lasts more than a year. Heavy users see the markup grow with every request instead. ### **What the AI Visibility Data Says About OpenSEO Itself** OpenSEO has two AI search features. Prompt Explorer runs one-off live prompts across ChatGPT, Claude, Gemini and Perplexity. The AI Visibility brand lookup reads DataForSEO's LLM Mentions database, a stored collection of ChatGPT and Google AI answers, and it is the one I ran direct above. For openseo.so, that database held zero ChatGPT answers and 13 Google AI answers. Running the same query for Semrush returned 3,224 ChatGPT mentions, so the query itself worked. Yet when I asked ChatGPT, Claude, Gemini and Perplexity about OpenSEO by name, with live web search on, all four identified DataForSEO as its data source and quoted its $10 price. That is a different test, since a named lookup only shows an assistant can research a brand when asked. The takeaway for a buyer: on a young brand, the brand lookup can read near zero on the task OpenSEO calls "the expensive one." Going direct returns the same stored result, since it is the same database. Check live answers too, which Prompt Explorer can run inside OpenSEO. One more detail for agent users: none of OpenSEO's 57 MCP tools cover AI visibility yet. It lives in the web app only, and scheduled prompt tracking is listed as coming soon on the public roadmap. ### **What OpenSEO Does Better Than a Raw DataForSEO Connection** **Rank tracking with history.** A DataForSEO connection answers "where do I rank right now?" and keeps no history of your tracked keywords. OpenSEO runs tracking on a schedule and stores the history, which an agent-only setup has to rebuild on its own. **A site audit you do not have to design.** Its crawler checks up to 10,000 pages on the paid plan. With DataForSEO alone you would pay per page for its site audit data and decide what to check yourself. **Memory your agent can use.** Saved business context, keywords and reports mean you do not re-explain your site every session. Shared report links, labeled "Made with OpenSEO," are easy to send to a client or teammate. **Less setup.** Connecting DataForSEO yourself means an account, a deposit, an MCP connection and knowing what to ask for. OpenSEO charges partly for making those decisions for you, and $10 is a smaller first step than a $50 deposit. **A screen for people who avoid terminals.** A teammate who will never open Claude Code can still use the web app. ### **The Weak Spots in a Young Tool** **One person writes nearly all of the code.** GitHub lists 19 contributors, but Ben Senescu accounts for the overwhelming majority of the work. That is normal for a young open source project, and it is also a risk if you build a client workflow on it. **Its backlink data can only be as complete as DataForSEO's.** In my [DataForSEO review](/dataforseo-review/) I noted its backlink data does not match the depth of Ahrefs' index, and OpenSEO inherits that gap along with the data. **"No subscriptions" only applies if you self-host.** The GitHub page lists "No subscriptions" as a reason to use it, while the pricing FAQ says "you need an active subscription in order to use OpenSEO." Both are true for different setups, but a buyer reading one page gets the wrong idea. **The name is crowded.** Google's AI Overview for "openseo review" currently summarizes employee reviews of an engineering firm called Openso. Perplexity mixed in two unrelated projects with the same name. The product in this review lives at openseo.so and [github.com/every-app/open-seo](https://github.com/every-app/open-seo). **Usage billing is hard to forecast at agency scale.** The estimator has a freelancer and agency preset, about $25 a month for 15 sites, but it sets AI brand checks to zero. At the estimator's $1.09 example, one ChatGPT brand check for each of ten clients would use more than the included $10 on its own. ### **OpenSEO vs the DataForSEO MCP in Claude Code** | | OpenSEO (hosted) | DataForSEO MCP, direct | | Cost to start | $10 a month, $10 of usage included | $50 minimum deposit, $1 free credit to test | | Data source | DataForSEO, plus a 28% markup | DataForSEO at list price | | Unused credit | Included credit resets monthly | Balance never expires | | Agent access | 57 MCP tools, no AI visibility yet | Broader access to DataForSEO's catalog, including AI mentions | | Rank tracking history | Built in and scheduled | Not included, you rebuild it | | Site audit | Own crawler, up to 10,000 pages | DataForSEO's audit data, priced per page | | Search Console | Built in, free | A separate free MCP, with its own setup | | Web interface | Yes | None, your agent is the interface | My own setup is the right-hand column, paired with the free Search Console server covered in my [SEO MCP servers roundup](/best-seo-mcp-servers/). If you have not connected an MCP server before, my guide to [setting up MCPs in Claude Code](/claude-code-mcps/) covers the process. For research, that combination covers what OpenSEO's data half does, without the monthly fee or the markup, and with more of DataForSEO's catalog in reach. If you already work inside an agent all day, the agent is the interface, and a second interface on top adds little for research. ### **Should You Pay for OpenSEO?** Pay for it if a Semrush or Ahrefs seat is out of budget and you want a dashboard for a small site. At $10 it is a low-risk way to find out whether you like working this way. It also makes sense when scheduled rank tracking and shareable reports matter more to you than raw data, or when teammates and clients need a screen to look at. Go direct instead if you already use Claude Code or Codex daily and are comfortable setting up a data connection. Add the free Search Console server, and you have the research side without the monthly charge. Be careful with the AI Visibility brand lookup on a young brand, for the reasons above. The dedicated trackers in my [AI visibility tools roundup](/best-ai-visibility-tools/) are the comparison to make before you spend on it. And leave self-hosting to people who already run their own servers. It saves the markup, but it adds a setup job most marketers do not need. ### **Where I Land on OpenSEO** OpenSEO is unusually open about its business. The GitHub page states the markup, and the homepage names the data source. That is more than most SEO tools tell you. It is also mostly a way of buying DataForSEO with a workflow wrapped around it. For a small business owner who values a dashboard and scheduled tracking, $10 a month is a reasonable price for that wrapper. For the marketers who read this blog, the practical choice is OpenSEO's MCP or DataForSEO's MCP, plugged into the same Claude Code or Codex. On that comparison, I still think you are better off connecting the [DataForSEO MCP](https://dataforseo.com/?aff=245611) directly. Three reasons, all from the numbers above. The direct connection reaches AI mention data that OpenSEO's MCP does not. You pay for what you use, with no $10 monthly floor wiping unused credit. And the balance never expires. For on-demand research, your agent already does the job. The clearest exception is rank tracking. If a scheduled ranking history is the job you are hiring for, OpenSEO does that for $10 a month without you building anything. ### **OpenSEO Review FAQs** #### **What is OpenSEO?** OpenSEO is an open source SEO platform built by Ben Senescu, a product of Every App, Inc., and released under the MIT license. It covers keyword research, rank tracking, backlinks, site audits and AI visibility, and it includes an MCP server for AI agents like Claude Code and Codex. Most of its SEO data comes from DataForSEO. The hosted version is at openseo.so. #### **Is OpenSEO free?** The code is free, and you can self-host it at no charge, but you still need your own DataForSEO account and pay DataForSEO for the data. The hosted version costs $10 a month. Its free trial includes $0.50 of credits, enough for roughly ten keyword searches. #### **How much does OpenSEO cost per month?** Hosted OpenSEO costs $10 a month for a single Base Plan that includes $10 of usage. The included credit resets each billing cycle, extra top-ups roll over, and tasks stop with an error instead of overbilling when credits run out. Checked on the live pricing page on September 23, 2026. #### **Does OpenSEO use DataForSEO?** Yes. OpenSEO says so on its homepage, and its public code requests keyword, search result, backlink, competitor and AI mention data from DataForSEO. According to its GitHub page, the hosted service charges 28% on top of DataForSEO's cost for every request. Its site audit crawler and its Search Console and Analytics connections are its own. #### **Is OpenSEO worth it?** For a small site on a tight budget, yes. It covers keyword research, rank tracking, backlink checks and site audits for $10 a month, against $139 for Semrush's entry SEO plan and $129 for Ahrefs Lite, though Ahrefs also sells a limited $29 Starter plan. If you already use Claude Code or Codex, connecting DataForSEO directly costs less at light usage. *Where this came from: OpenSEO's pricing and positioning come from its live site, its data sources, markup and MCP tools from its public GitHub code, and competitor prices from the Ahrefs and Semrush pricing pages, all checked on September 23, 2026. DataForSEO costs are charges on my own account that day. I have not used OpenSEO myself. I earn a commission on DataForSEO signups through my links, and I sell a competing AI SEO product. [Full disclosure](/disclosure/).* --- ## SaaS SEO Is Broken: Here's How to Make Money from AI Search URL: https://ryandoser.com/saas-seo/ Markdown: https://ryandoser.com/saas-seo.md Published: 2026-09-23 | Updated: 2026-09-23 Categories: AI Rabbit Holes > SaaS SEO that drives pipeline starts at the bottom of the funnel. Sam Dunning shows which pages rank on Google and get cited in AI search. **SaaS SEO** breaks when it starts at the top of the funnel, chasing traffic that AI search now answers on its own. ### **Watch Sam Dunning Break Down SaaS SEO That Drives Pipeline** This episode of AI Rabbit Holes is a conversation with Sam Dunning, founder of [Breaking B2B](https://www.breakingb2b.com/), an SEO and AI search agency for B2B software companies. Sam puts his data set at around 50 SaaS clients, and he is one of the [AI SEO experts I trust for revenue-first B2B work](/best-ai-seo-experts/). The centerpiece is a live teardown of one alternatives page that, when Sam showed it, ranked first on Google and was named in the AI Overview above it. If you want to build pages like that one yourself, my **[Claude Code Skills Stack](https://skills.ryandoser.com)** includes the listicle and research skills I run for clients. ### **When SaaS SEO Is Not Worth It Yet** Sam says his team turns away a lot of business, and bootstrapped founders are often the ones he tells are not a fit yet. One reason he gives is search demand. If you built a new kind of tool that nobody knows to look for, there is no captive market typing your category into Google or ChatGPT. Search, on Google or in an LLM, works best when buyers already know the solution exists and go looking for it. Crowded categories are the other trap. Pitch Sam a new CRM and his answer is to pick a narrower niche, because you would be up against Salesforce, HubSpot, Pipedrive and Close. Check whether real people search for your category before you pay anyone to rank in it. ### **Start With Sales Calls, Not a Keyword Tool** Plenty of SaaS SEO plans open a keyword tool on day one. Sam opens the CRM. His agency's onboarding form asks very little about SEO. It asks about the product and the dream client instead. - Which industries have you historically sold well into? - What is their most expensive problem, in their own words? - What do they cobble together in house before they buy, such as a Google Sheet? - What tipping point finally makes them evaluate software like yours? Sales and customer success call recordings answer all four. Sam's move is to connect the call recorder to Claude through MCP and query the pain points directly. From there, he pairs that research with Ahrefs or Semrush to find long-tail commercial terms with low difficulty. Both now run [SEO MCP servers you can connect to Claude](/best-seo-mcp-servers/). Those terms carry less volume. Sam's point is that they can rank quickly, which matters for a startup, and they bring in buyers who are already shopping. Top-of-funnel queries like "what is a CRM" are the opposite bet. You compete with 70 to 90 DR software brands, and AI search answers the question before anyone clicks. The keyword this post targets proves it. When I searched "saas seo" on September 23, 2026, Google showed an AI Overview defining the term before the first organic link. ### **The Bottom-of-Funnel Pages Most SaaS Sites Are Missing** Sam says many SaaS companies lack basic pages on their own site, then jump straight to link building, Reddit and LinkedIn. That gap is the first SaaS SEO fix he makes. His money keywords are what a dream customer types when they are ready to buy software like yours. These are the page types he builds first: - Competitor alternatives pages ("best [competitor] alternatives") - Direct comparisons, both you vs a competitor and competitor vs competitor - Best-of software lists in your niche - Pricing pages - Integration pages - Use case and ICP pages - Landing pages Before building any of them, Sam checks intent. Search the keyword, see whether Google ranks a best-of list, a comparison or a how-to, then build that format better than what already ranks. The mix depends on who you compete with. For the SaaS company I run SEO for, many of these are API and MCP pages, because that is where its competitors fight. Sam also prefers pages he controls. If an LLM is going to describe his client's product, he wants the source to be his client's page, not a frustrated Reddit thread. *Sam's order of operations. Customer research picks the keywords, and the keywords pick the page types.* ### **Anatomy of an Alternatives Page That Ranks and Gets Cited in AI Search** Nobody searches a competitor's name plus "alternatives" for fun. Sam's read is that the searcher is probably annoyed with a current tool, whether pricing went up, support dropped off, or a feature went away. That intent is why alternatives pages are a staple of his SaaS SEO work, and why he says they can drive demos. His example is from his client Fibbler, an ad attribution tool whose co-founder Adam Holmgren builds in public. *The results Sam showed on the recording: Fibbler named first in the AI Overview and ranked first organically. Results shift, so treat this as a snapshot.* Here is the [Fibbler page](https://fibbler.co/blog/zenabm-alternatives) Sam walked through, top to bottom, as it reads today: - A fixed sidebar call to action with the brand's pink lion and a free trial button - The target keyword in the H1 - A quick summary right under the title - A small "top three picks" table above the fold - A "Why Trust Us?" section - What ZenABM is, and why buyers look for alternatives - A full comparison table with ratings and pricing - A numbered list with Fibbler first, each tool showing its G2 rating and price - An FAQ at the bottom *The opening screen: keyword H1, quick summary, and the top three picks table.* Sam's reason for the quick summary is that it can get pulled into an LLM. I have noticed the same with tables placed early on a page, while long intros bury the part a model would lift. Sam finds the "why people leave" material in G2 and similar review sites, filtered to the reviews below five stars. My addition is the part AI cannot copy. Anyone can have a model rewrite the top three results, so the page needs context only you have, like a video, sales call quotes, or a diagram. #### **What it costs to crown yourself** Putting yourself at number one is fine, in Sam's view, as long as the rest of the list is a fair review of the other tools. The risk he flagged is publishing lists outside your lane, with ClickUp as the cautionary example. There is a second cost worth seeing. ZenABM published a [point-by-point response](https://zenabm.com/blog/fibblers-zenabm-alternatives-article-our-response) on April 4, 2026, disputing nine claims in Fibbler's article. *The verdict section of the Fibbler page, the kind of claim a named competitor can answer in public.* I am not taking a side on the API details. The lesson is that a page aimed at a named competitor is a public claim, and that competitor has a blog too. Self-promotion can also backfire inside the models. In an [Ahrefs experiment](https://ahrefs.com/blog/self-promotional-content-ai-seo-experiment/) published in July 2026, 43% of the AI answers that cited pages promoting its Ahrefs Evolve conference never mentioned the conference at all. I covered the formats side of this in my post on [how self-referencing listicles get picked up](/how-to-manipulate-ai-search/). What the Ahrefs data adds is the catch: a self-promotional page can earn the citation while the answer recommends someone else. The fix I use is in my [AI SEO strategy](/ai-seo-strategy/): keep the qualifying condition inside the same sentence as any recommendation, so a lifted chunk cannot travel without it. ### **How to Get Your SaaS Into AI Search Answers** Your pages exist. Now the job is finding where the models already look. Sam's method starts with a question. Ask ChatGPT or Claude one of your money prompts, then read the citations behind the answer. He says the usual suspects are listicles, your own site, competitors, and review sites like G2, Capterra and Software Advice. On Reddit, his words were "not so much Reddit at the moment, I don't think." Then you get onto those sources. Sam calls it barging your way into the LLMs. I ran that check for this topic across ChatGPT, Claude, Gemini, Perplexity and Google's AI Overview. Most cited sources were agency guides or best-of lists, while ChatGPT leaned on official documentation from Google, Bing and OpenAI. A three-week Linkifi study found a similar tilt toward lists. A core of 3% of sources, mostly directories and "best of" lists, got cited almost every day, as I cover in [Linkifi's study of which sources ChatGPT keeps citing](/how-to-get-chatgpt-to-recommend-your-business/). The assistants do not share one search index, which I broke down in [which search engine each AI actually uses](/what-search-engine-does-claude-use/). Breaking B2B was cited by Google's AI Overview and Perplexity. Its cited page is a best SaaS SEO agencies list, the exact page type Sam recommends, with Breaking B2B ranked first. Some of the readers checking those sources are now agents, because Claude can fetch pages on a buyer's behalf. Sam says most of his clients' traffic is still human. My split is simple: write for agents to get cited, and for humans to convert. ### **How to Measure SaaS SEO When Attribution Is a Mess** A buyer can ask an LLM about your category, forget about it for months, and then Google your brand name. Your analytics will call that a branded search. Sam's fix costs nothing. Ask "how did you hear about us?" on your forms, your signup flow and your demo flow, then ask again on the sales call. Besmir Bregasi, who works at an AI visibility company, named the same question as the most accurate measure in [my episode on how to track AI visibility](/how-to-track-ai-visibility/). His agency invests in [AI visibility trackers](/best-ai-visibility-tools/), naming Searchable and Promptwatch, but does not treat them as the verdict. Sam's problem is with what gets tracked. Many teams track every prompt under the sun, and few of those prompts come from buyers with real intent. Citations also move constantly. I dug into how much a single daily tracker run tells you in my [Searchable review](/searchable-review/). What Sam reports depends on the client. Larger companies care about share of voice. Startups and mid-market companies care about demos, signups, trials and booked calls. His leading indicators are money keyword rankings, visits to money pages, branded search and direct traffic. If those rise alongside self-reported AI mentions, he is generally pretty happy. ### **Where SaaS Buying Goes Next** Sam expects more SaaS to sell inside the LLM within a year, mostly low-ticket tools up to around $99 a month. If buyers stop visiting websites at all, the SaaS SEO pages worth owning are the ones that answer a ready buyer. SaaS is far from dead, as I argued in my conversation on [growing SaaS with YouTube](/how-to-grow-saas-with-youtube/). What is running out of road is the top-of-funnel playbook. ### **SaaS SEO FAQs** #### **Is SEO worth it for an early-stage SaaS company?** It depends on demand more than stage. If buyers already search for your category, low-difficulty bottom-of-funnel terms are winnable even for a young domain. If your tool creates a new category, there is little search demand to capture yet, which is one of the cases where Sam Dunning says a company is not ready for SEO. Check your category in Google and in ChatGPT before hiring anyone. #### **Should a SaaS company still write top-of-funnel blog posts?** Not first. Definition queries like "what is a CRM" pit you against software brands with 70 to 90 DR, and AI Overviews now answer them before the click. Build alternatives, comparison and pricing pages before any glossary content. My one caveat is YouTube, where I still see a lot of beginner-level opportunity on my own channel. #### **How do you get a SaaS product recommended by ChatGPT?** Ask the prompt your buyer would ask, open the cited sources, and get onto them. Check more than one assistant, because they disagree. When I ran the same SaaS SEO questions through ChatGPT, Claude, Gemini and Perplexity, ChatGPT leaned on official documentation from Google, Bing and OpenAI, while the others cited mostly agency guides and best-of lists. #### **How long does SaaS SEO take to show up in pipeline?** Longer than it takes to rank. A low-difficulty alternatives page can rank quickly, but a buyer who meets you in an AI answer may research for months before booking a demo, often by Googling your brand name. That delay is why Sam asks "how did you hear about us?" on forms and again on sales calls. --- ## Death of WordPress: My WordPress Alternative for Marketers URL: https://ryandoser.com/wordpress-alternative/ Markdown: https://ryandoser.com/wordpress-alternative.md Published: 2026-09-23 | Updated: 2026-09-23 Categories: Claude Code > WordPress still runs 40% of the web, but for solo marketers it is done. The WordPress alternative I use: Claude Code, Astro, GitHub, Cloudflare. The following article explains why WordPress is dying for marketers who run a site alone, and the **WordPress alternative** that runs this entire site instead. ### **Watch Me Build a Site on My WordPress Alternative** In this video I build a local service website from a fresh Claude Code chat to a live custom domain, with no page builder and no plugins. The stack has four parts, and I would put any solo marketer or small business on it today: - [Claude Code](/why-marketers-should-use-claude-code/) or Codex does the building, loaded with skills. - [Astro](https://astro.build/) is the web framework underneath. - GitHub stores every file and every version. - Cloudflare hosts it and deploys each change. The skills part matters more than people think. If you want the exact website designer and local SEO skills from this build, they live in my **[Claude Code Skills Stack](https://skills.ryandoser.com)**. *The second draft of the Des Moines Junk Removal demo site, built by Claude Code on Astro and running locally before launch.* ### **Is WordPress Dead? Not If You Count Websites** Let's be real about the numbers first. On September 23, 2026, [W3Techs](https://w3techs.com/technologies/details/cm-wordpress) reported WordPress on 40.2% of all websites and 58.8% of sites with a known CMS. Nothing that big is dead. And on camera I said the quiet part out loud: "I'm not saying WordPress is dead." My exact caveat was about teams. With a lot of non-technical people editing and polishing content, a CMS like WordPress is still better set up for that job. But those W3Techs numbers are a census of the whole web. They cannot tell you what to build your next site on. So here is my actual position. WordPress is dying for the reader I write for: the marketer, solo operator, or small business owner running a site alone. That reader never needed a database, a theme marketplace, and a stack of plugins. They put up with all of it because a fast, custom WordPress alternative they fully owned used to mean hiring a developer. ### **Astro Needed a Developer. Now the Developer Is an AI Agent** When I asked ChatGPT, Claude, Gemini, and Perplexity about Astro vs WordPress in September 2026, all four raised the same objection. Astro is fast, they said, but it needs a developer. That was true when a developer meant a person. For a WordPress alternative in 2026, the developer is Claude Code or Codex. You still review its plan and check the result. The agent handles the code itself. I do not write code. Every one of the 160-plus posts on this site is a plain file in a GitHub repo, managed through Claude Code, and I cover the full move in my [notes on leaving WordPress for Astro](/new-website-rebuild/). My site is not the only one. [Des Moines Septic](https://desmoinesseptic.com/), a local service site I built as a test, runs on the exact same stack. *The next sentence mentions a tool I have an affiliate relationship with and that is a client. [Full disclosure here](/disclosure/).* [Blotato](https://www.blotato.com/?ref=rdoser), the AI social media tool I do SEO for, runs on Astro and GitHub too, with Vercel handling the hosting instead of Cloudflare. *The stack after WordPress: describe the change, the AI builds it, GitHub saves it, and Cloudflare puts it live.* The real test is what happens when something breaks. In the video, my first push to GitHub failed with an error I did not understand. So I pasted the whole terminal message into Claude Code. It explained the failure in plain English and handed me the one command that fixed it. *Claude Code reading a pasted terminal error and explaining why the GitHub push failed, recorded May 28, 2026.* As I put it on camera, "A lot of this stuff is over my head." It did not matter, because I only had to describe the problem. That is the whole shift. An error on this stack goes straight back to the same assistant that wrote the code, with the full project open in front of it. ### **The Dead End Most People Take Instead** Plenty of people who quit WordPress walk straight into one of two traps. When I checked on September 23, 2026, Google's own AI Overview for "WordPress alternatives" steered beginners toward Wix. The first trap is the hosted site builder. [Wix's own help center](https://support.wix.com/en/article/exporting-or-embedding-your-wix-site-elsewhere) states plainly that a Wix site has to run on Wix's servers. You traded plugin updates for a landlord. The site looks finished, but you cannot pick it up and move it. The second trap is the vibe-coding platform: Lovable, Replit, Base44. My problem with them is where your context lives. My agent runs on my own machine, so my skills, brand files, and SEO rules carry over to every site I build. In a browser builder, that context sits on their platform, you pay in their credits, and the tool is tuned for app prototypes more than content sites that have to rank. To be fair, Lovable and Replit can sync your code to GitHub, and Base44 can on its Builder plan and up, so you can leave with your files. I break down where each of these builders fits in my [roundup of AI coding tools for non-technical users](/best-ai-coding-tools/). ### **Astro vs WordPress for a One-Person Marketing Team** Here is how Astro holds up as a WordPress alternative for the reader this post is written for, one person running the whole site. | Question | WordPress | Astro + AI agent | | Who builds it | You, a theme, and a page builder | An AI coding agent, from a plain-English request | | Where content lives | A database behind a dashboard | Plain files in your GitHub repo | | What ships to visitors | Whatever the theme and plugins load | Static pages, with only the JavaScript you add | | Upkeep | Core, theme, and plugin updates | No plugins, occasional dependency updates | | Best fit | Large teams, heavy WooCommerce stores | Solo marketers, local businesses, blogs | The hosting side is the easy part. [Cloudflare Pages](https://pages.cloudflare.com/) says every plan, free included, comes with unlimited sites, requests, and bandwidth, and the free plan allows 500 builds a month. Every change also leaves a trail. When Claude Code pushes a commit to GitHub, Cloudflare turns it into a new deployment on its own. *Cloudflare Pages listing each deployment next to the GitHub commit that triggered it, minutes after Claude Code pushed a fix.* If you want the click-by-click setup for GitHub and Cloudflare, my [step-by-step Claude Code website tutorial](/vibe-code-websites-claude-code/) walks through every screen. ### **Once You See the Light, You Don't Go Back** WordPress will keep running a huge share of the internet for years. It just stopped being the default answer for a marketer building alone. Owning the files, skipping the plugin treadmill, and fixing problems by describing them is a better deal. And after you run a site on this WordPress alternative for a month, going back to wp-admin feels impossible. ### **WordPress Alternative FAQs** #### **Is WordPress dead in 2026?** No, not by usage. W3Techs had WordPress on 40.2% of all websites on September 23, 2026. What is fading is the case for a solo marketer or small business to run it, because an AI coding agent now handles the developer work that used to push people toward a dashboard CMS. Large editorial teams are still a good fit for WordPress. #### **What is the best WordPress alternative for a small business?** If one person runs the site and it is mostly pages and a blog, Astro built by Claude Code or Codex, stored in GitHub, and hosted on Cloudflare Pages is my pick. If you need a big online store or a team of non-technical editors, a hosted platform or WordPress still makes more sense. #### **Is Astro better than WordPress for SEO?** For a solo marketer running a content site, Astro usually wins on the technical side, because it ships static pages with zero JavaScript by default, so they load fast without caching plugins. Rankings still come from content and links, so a well-built WordPress site can outrank a sloppy Astro one. Astro just removes the plugin bloat that drags many WordPress sites down. #### **Can I use Astro if I don't know how to code?** Yes, if an AI coding agent does the coding. You describe what you want, review the result, and paste any error back in so the agent can fix it. You still need to be comfortable reading its plan and pushing back when something looks wrong, which is a marketing skill more than a programming one. #### **Why not just use Wix or another hosted website builder?** Because the site stays on their servers. Wix's own help center says a Wix site cannot be hosted anywhere else, so leaving means rebuilding. Some newer AI builders now offer code export, so check that before you commit. With Astro and GitHub, every page is already a file you own, and you can switch hosts or AI tools without starting over. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## How to Use Open Source AI Models (Stop Wasting Money) URL: https://ryandoser.com/open-source-ai-models/ Markdown: https://ryandoser.com/open-source-ai-models.md Published: 2026-09-21 | Updated: 2026-09-21 Categories: AI Rabbit Holes > Open source AI models handle mid-level work at a fraction of frontier pricing. Here is where they win, where they lose, and how I route work. **Open source AI models** now handle a surprising amount of real work at a fraction of frontier pricing, and most people are still paying Opus rates to rename files. ### **Watch Me Test Open Source AI Models Against My Own Landing Page** This episode of AI Rabbit Holes is a conversation with Aaron Makelky, an AI consultant who has been running open models for years. Partway through, I pointed the three top-ranked open models at my real opt-in page and asked each one to redesign it. The results are further down, and they are not what the benchmark charts would lead you to expect. If you want the Claude Code setup behind tests like this one, my **[Claude Code Skills Stack](https://skills.ryandoser.com)** ships the same skills and systems I run daily. ### **Open Source vs Closed Source AI: What You Are Actually Choosing** Most comparisons frame this as a loyalty test. Pick a side, defend it. That framing is wrong, and neither of us runs a business that way. We both pay for frontier models and route the cheap work elsewhere. Aaron uses a right to repair analogy. Farmers bought John Deere equipment, then had to haul it back to the dealership for any repair. Closed models work the same way. To use OpenAI's desktop app, you use OpenAI's models. Worth getting the term right, because most roundups do not. Nearly everything sold as open source is really open weight, meaning the weights are published while the training data and code usually are not. That distinction changes the ownership question, not the quality question. You hold the blueprint, so the hosting and the bill are yours to decide. Frontier models still win on hard reasoning, layout work, and anything where a subtle mistake gets expensive. Open source AI models win on volume, price, and privacy. The skill is knowing which bucket a task belongs in before you spend anything. *The routing decision this whole post argues for. Ask it per task, not once per vendor.* #### **The local hosting question, answered honestly** Aaron's estimate is that 99% of people are not going to self-host a full-size model. He puts the hardware for running something like Kimi or GLM 5.3 at home around eight to ten thousand dollars in compute. Do that math against a $100 monthly subscription and the hardware rarely wins. Aaron and I ran the subscription side of that comparison in our episode on [whether a $100 plan is worth it](/chatgpt-pro-vs-claude-max/). My own Mac Mini and MacBook Pro are not enough for serious local work at scale either. Small local models are a different story. Aaron runs a 3GB Qwen vision model on a Mac desktop that renames his screenshots, offline. Twenty or thirty screenshots a day, each saved as a meaningless date string, become things like "Google Chrome Wells Fargo account September 14." That task is the whole argument in miniature. Bank statements should not travel to a frontier API just to get a filename, and that filename is not worth frontier rates. ### **Where to Run Open Source AI Models Without Buying Hardware** You have spent money on a model you cannot open anywhere. This is the gap nobody explains. [OpenRouter](https://openrouter.ai) is the middleman I use, and the pitch is simple. One account, one API key, hundreds of models. That key plugs into Claude Code, Codex, Cursor, or any IDE you already run. The alternative is a separate key from Z.ai, DeepSeek, and Moonshot, all managed in environment files. *The OpenRouter model table on the day of the recording, sorted by weekly tokens. Rates shift, so read the live page before budgeting.* Look at the input column on the day I captured this. GPT-5.6 Luna, OpenAI's cheaper tier, was listed at $0.20 per million input tokens. DeepSeek V4 Flash 0731 read $0.03 and GLM 5.3 Flash $0.075, though that one carries a visible discount badge, so treat it as a promo rate and not a standing price. Nemotron reads $0, because NVIDIA publishes a rate-limited free endpoint alongside the paid one. Three traps before you budget off any of this. Model names carry dated snapshots, so V4 Flash 0731 and the newer V4.1 Flash are different models at different prices. Open weights also get served by dozens of competing providers at different rates, so the headline number on a listing page is one provider's price rather than the model's price. And these figures move week to week. Every number here is a snapshot, not a quote, so read the live rate for whichever provider you actually select. At one prompt none of this matters. At a few million tokens a month of background work, it stops not mattering fast. Start with fifteen or twenty dollars of credits. Open models are cheap enough that a small balance lasts through a lot of testing. #### **Why I skip the discount portals** Portals like Kie.ai advertise steep discounts against the official rates on the same models. I avoid them, and this one is a hunch rather than a tested finding. Heavy discounting usually means distillation. A distilled model is a smaller, cheaper imitation of the original. It answers faster and costs less, and quality drops in ways that are hard to see until the work matters. Aaron reaches these models through [Hermes](https://hermes-agent.nousresearch.com/) instead, which holds his ChatGPT subscription, a Z.ai coding plan, and a portal of open models in one interface. He has since added Claude Max, and [our DevDay episode](/is-chatgpt-pro-worth-it/) covers why. His setup does one thing I want to steal. He fires a single prompt at DeepSeek, Kimi, and a frontier model at the same time, then reads all three answers side by side. Last I checked, Anthropic's own app will not do that with two Anthropic models. You open a second tab and paste the prompt again. Think about what that does to copywriting. Four cheap drafts of a subject line beats one expensive draft, every time. ### **The Best Open Source AI Models Right Now (And Who Ranks Them)** Picking a model from memory is how you end up using something that was current six months ago. Let the ranking decide instead. *Filtered to open source, this ranking draws on 8.1 million votes across 222 open source models.* The [Arena LLM leaderboard](https://arena.ai/leaderboard/text?license=open-source) ranks models by blind human preference across math, coding, and creative writing. Filter it to open source and you get a live answer instead of a guess. When we recorded, that filtered list read kimi-k3-max first, then glm-5.3-max, glm-5.3-flash, glm-5.2-max, and mimo-v2.5-pro. Now read the second column, because it is the most honest number on this page. The top open source model sits at overall rank 17 once closed models are back in the running. Hold onto that gap. These models are genuinely good and genuinely not the frontier, and both facts are visible in one screenshot. My own rotation is narrow. Kimi K3 and the GLM models get most of my open source work, with DeepSeek V4 for workhorse tasks. Plenty sit outside that rotation untested. MiniMax, most of the Qwen family, Tencent's Hunyuan, Mistral. Aaron has actually settled on one. GLM Flash has been his default for at least nine months, for background tasks rather than creative or strategic ones. His examples are deliberately boring. Pull this file up, run a search, draft this. Those tasks are hard to get wrong, and GLM Flash does them for almost nothing. One correction worth making, because we got this slightly wrong on the recording. Vision lives in the Flash line, not the main GLM 5.3 model, which is still text only. So if you need to hand a model a screenshot, check the modality before you pick the bigger number. ### **I Let the Leaderboard Pick Three Open Source AI Models and Tested Them** Benchmarks are votes on chat responses. They do not tell you whether a model can rebuild a page you actually use. So I did not pick the models. I handed over the leaderboard URL and told it to fetch the current top three, then test those. That is the part worth copying. Run this next quarter and the leaderboard hands you a different three, and the method still works. The target was my opt-in page for the free AI marketing guide, a deliberately simple page built to convert. *The test setup. Each model is mapped to its OpenRouter ID with its Arena rank, and all three redesigns render locally for review.* One detail surfaced immediately. Those max and flash suffixes do not map onto OpenRouter model IDs, so ranks two and three both resolve back to Z.ai GLM. Kimi K3 produced the most designed result. Editorial headline, floating proof cards, sticky navigation, the most visual personality of the three. It also mangled my branding at the top and rendered a crooked frame around my headshot. Aaron called the frame wonky, and he was right. Close, but not quite shippable. GLM 5.3 Flash came back plain. Black and white, almost no branding, nothing above the fold that grabs you. Which is roughly what a flash model should produce. Aaron noted he would rather ship a clean black and white page than a busy one chasing gradients, and for many opt-in pages that is the correct instinct. GLM 5.3 landed closest to usable. It underlined one phrase in the headline to pull the eye toward the offer, a real copywriting decision nobody asked it to make. Spacing problems remained. Usable with a few fixes is the fair verdict. These outputs sit roughly where the frontier models were six months to a year ago. That is the calibration to keep. A week later, Aaron and I ran the same kind of landing page test on the new frontier models in our [Opus 5.5 vs GPT-6 episode](/opus-5-5-vs-gpt-6/). Aaron put a sharper point on it, saying the GLM result looked like Opus 4.8 work, a model less than a year old. If you want the deeper version of this, I put six models including Qwen and MiniMax against a Claude-built homepage and logged what each run cost. That breakdown lives in my [open source model bake off for web design](/open-source-ai-web-design/). #### **A trick for making cheap models smarter** If you already pay for a frontier plan, you are sitting on an asset you are probably not using. Ask Fable 5.1 or GPT-6 Astra, in a high thinking mode, to write a skill markdown file capturing how it approaches a specific task. Then point a cheap open model at that file. The open model inherits some of the frontier reasoning without the frontier bill. It is not a one to one transfer and I would not claim it is, but it noticeably lifts output on repetitive work. This pairs with knowing your own model tiers, which I broke down in my guide on [which Claude model to use](/which-claude-model-to-use/). ### **When Open Source AI Models Are the Wrong Answer** Here is where I would not touch an open model. High-stakes creative and strategic work still belongs on frontier models. Marketing strategy, complex visual design, and anything a client sees first are not places to save three cents. Free models deserve particular caution. Aaron's warning is blunt, that they are free for a reason, they train on your data, and you cannot opt out. The same goes for code-named mystery models on these portals. A model listed under a codename with no stated lab is a lab testing compute and collecting data. Use those for side projects and throwaway agents, never for client data. Hosted open models carry a quieter version of the same issue. Aaron assumes his GLM prompts are being read somewhere, and he uses the model accordingly. Open weights do not mean private inference unless the weights run on your own machine. #### **The offline option nobody talks about** For genuinely sensitive work, there is a free path that skips the hardware question. [Google AI Edge Gallery](https://github.com/google-ai-edge/gallery) runs Gemma models directly on a phone, and it is now on the App Store and Google Play rather than a sideloaded file. The current build features the Gemma 4 family, with the smaller variants landing a couple of gigabytes. Google describes the app as in active development, so treat it as a preview rather than a finished product. Once a model is downloaded, turn off wifi and it still answers. It handles images too, so you can hand it a photo and ask about it. Aaron uses it on airplanes and for medical or banking questions. Nothing leaves the device, which is a different privacy guarantee than any subscription offers. Nobody would call it a great model. It is a decent one that works when nothing else does. ### **Route the Boring Work Somewhere Cheaper This Week** Open source AI models are rate limit insurance as much as a cost play. When a provider retires a plan or throttles you mid-project, a second lane matters. At real volume the math only points one way. Teams in China and elsewhere ship upgraded open models continuously, and more of them land free. So keep your frontier subscription for the work that earns it. Put fifteen dollars on OpenRouter and move your background tasks over this week. Spend the savings on whatever actually moves your business. ### **Open Source AI Models FAQs** #### **Are open source AI models as good as ChatGPT or Claude?** Not at the top end. On the Arena leaderboard, the best open source model ranks 17th overall once closed models are included. For mid and low-level knowledge work the gap rarely matters. In my landing page test, the open models produced results comparable to frontier models from roughly six months to a year ago. #### **What is the difference between open source and closed source AI?** Closed source means you rent access and the provider controls where it runs, so your data goes to their servers and your bill follows their pricing. Open weight means you can run the model anywhere, including on hardware you own. The difference is control and cost rather than automatic quality, and the top closed models still lead on benchmarks. #### **How much does it cost to run open source AI models?** Less than frontier pricing, though the number moves faster than most guides admit. The same open model is served by dozens of competing providers at different rates, and promotional discounts expire, so the headline figure on a listing page is one provider's price on one day. Budget from the live rate of the provider you actually select. #### **Can I run open source AI models on my own computer?** Small ones, yes. A 3GB vision model runs comfortably on a Mac desktop, and Google AI Edge Gallery runs Gemma models on a phone offline once you download one. Full-size open models need serious hardware that rarely pays for itself against a monthly subscription. #### **Are free open source AI models safe to use?** Treat anything free as public. Free tiers generally train on your inputs with no opt out, and free endpoints are usually rate limited versions of a paid model rather than a different product. Run side projects on them and keep client data, financial records and anything personal off them entirely. --- ## ChatGPT Pro vs Claude Max: Which $100 Plan Is Worth It? URL: https://ryandoser.com/chatgpt-pro-vs-claude-max/ Markdown: https://ryandoser.com/chatgpt-pro-vs-claude-max.md Published: 2026-09-17 | Updated: 2026-10-02 Categories: AI Rabbit Holes > Claude Max meters its flagship to half your week. ChatGPT Pro does not. Three head-to-head tests of Fable 5.1 against GPT-6 Astra. *Update, October 2, 2026: OpenAI's DevDay plan changes flipped my answer. For knowledge work, Claude Max is now the better $200 plan, and I explain why in [is ChatGPT Pro worth it after DevDay](/is-chatgpt-pro-worth-it/).* Six months ago I wrote a post about leaving OpenAI, and Claude ran nearly all of my work. Today my stack is split. **ChatGPT Pro vs Claude Max** stopped being a question about which model is smarter and became a question about how much of the good model you actually get to use before your plan cuts you off. That shift is why I quietly moved a chunk of work back to OpenAI over the last few weeks. I'm not deleting anything. I still pay Anthropic, Fable is still the best model I own, and [what I said six months ago](/switch-from-chatgpt-to-claude/) was true when I said it. But the math changed, so I changed with it. Since then I ran GPT-6 Astra and Claude Fable 5.1 head to head on three real jobs: a landing page that already makes money, a local service brand built from one prompt, and 17 scanned pages turned into long-form writing. Here is the full breakdown, starting with the three tests and every screenshot from them. For the everyday tier below those two flagships, my [blind test of Opus 5.5 vs GPT-6 Sol](/opus-5-5-vs-gpt-6/) covers which model to run all day. Short version: Fable wrote better, Astra delivered more per prompt, and the plan math decided it rather than the models. The rest of this post is why. ### **I Ran Astra and Fable Head to Head on Real Marketing Work** Before any of the plan math matters, you need to know whether the model you're rationing is worth rationing. So I put Astra and Fable 5.1 on the same three jobs, with the same prompts, on the same afternoon. The results are in the video above, where I went through them with Aaron Makelky. Aaron is an AI consultant who pays for no Anthropic subscription at all, reaching Claude models through OpenRouter and Cursor instead, and he is the same person I went through [Grok Bot's rate limits](/is-grok-bot-worth-it/) with a week earlier. He pushed back hard enough to change how I'd answer the buying question, and we landed in different places, which is the useful part. #### **Test 1: Redesign a Landing Page That Already Makes Money** Every time a new model ships I give it the same first job, because I have a page with real revenue attached to it and I know exactly how it performs. My Claude Code Skills Stack page has brought in over $20,000. The current version was built by Opus 4.8. The prompt was deliberately thin. I gave each model the live URL and said: make a better landing page designed to get more conversions. Nothing about brand, nothing about colors. Fable 5.1 stayed on brand almost perfectly. Aaron picked out the specifics: it toned down the gradient, which is normally something you get unless you prompt against it, pushed more contrast into the CTA buttons, and made the testimonial cards more visually appealing. Nothing crazy, but the big takeaway is that it truly stayed on brand and iterated the original rather than replacing it, which is what you want when brand consistency matters. Astra ignored my brand entirely. Different colors, my logo and full name added at the top, and a completely different approach to the product widget. It also came back noticeably shorter and more condensed than Fable's version. My honest reaction was that I liked it. Aaron went further and argued the plainer version would convert better, on the theory that a visitor is not grading your gradient, they are deciding whether to click. Neither of us has numbers on that yet, and he was the first to say the only way to settle it is a test. That is the part worth taking away. If I am a plumber in Des Moines, I do not care whether my landing page is an award winner. I care whether the phone rings. Off-brand is a tradeoff I will take if the numbers justify it, so this one goes into an A/B test rather than straight into production. #### **Test 2: Build a Local Service Brand From One Prompt** The second test was messier on purpose. It has been raining hard in Des Moines and basements have been flooding faster than the plumbing companies can keep up, which made me wonder whether there was a [rank-and-rent opportunity](/rank-and-rent-seo/) sitting there. So I gave both models one paragraph: I'm starting a local service business for flooded basement cleanup and restoration, give me a company name, ICP, brand guide, and a front-end homepage design. I named the city and pointed at a reference site. That was the entire brief. I ran them side by side in VS Code, Claude Code in one pane and Codex in the other. Worth saying plainly because it confuses people: you do not need either company's desktop app to use these plans. Both run inside one IDE, which is [how I actually work](/claude-code-and-codex-together/). Fable gave me a homepage. My read was that it was fine and forgettable. Placeholder images where the photos should be, a logo I would not keep, and nothing that would embarrass you in front of a client. Serviceable. Aaron was harsher, and he caught details I had skimmed past: an orange eyebrow label too low-contrast to read, five steps crammed above the fold, and colored pills whose text centering was visibly off. His words were that it looked vibe-coded and low-effort, and that a plan charging $100 or $200 a month should nail that on the first pass rather than making you go back and say "now fix this." Looking at it again, he is right and I had graded it on a curve. Astra returned something closer to a starter kit. It gave me the brand concept, a full brand guide with a named color palette, the homepage, and a hero image it generated itself with ChatGPT Images, without being asked. Then it produced a second design iteration nobody requested. Aaron's read was that the palette looked more refined and modern than Fable's harsh orange and navy, and that the named "action orange" actually carried through into the CTA button and the headline. A toolkit for building the site rather than a site with placeholders in it. That cuts both ways, and I want to be fair to Fable here: this was a bare-bones prompt with almost no context. Given a real harness with skills and brand foundations behind it, Fable produces excellent work. I [rebuilt ryandoser.com](/new-website-rebuild/) with a combination of Opus 4.8 and Fable 5, and I still like that design. A one-paragraph prompt tests how much a model does unprompted. It does not test its ceiling. #### **Test 3: 17 Scanned Pages, One Long-Form Draft** Aaron's own test is the one that reframed the cost question for me, because it is the only one that measured something other than output quality. He took 17 handwritten pages scanned into a PDF and asked for a long-form piece built from his actual ideas. Three things stacked in one job: ingest the PDF, OCR handwriting accurately, then write at length without inventing filler. The result matched what I had seen all afternoon. Fable won on quality and it was not close: better structure, and a genuinely good hook nobody asked it for. Then the other half. Fable was slow enough that just reading the PDF took longer than Astra needed to finish the entire job end to end. It burned more tool calls and more credits to get there. Which surfaces a mistake I see constantly in these comparisons. People compare price per token and stop. Compare price per task instead, because a model that burns fewer tokens and finishes faster can be cheaper on the actual job even at the same headline rate. You do not care what a token costs. You care what the landing page cost. That matters more here than usual, because the headline rates are identical. I assumed Fable was the pricier model and checked it while writing this up: both Fable 5.1 and GPT-6 Astra run $10 per million input tokens and $50 per million output tokens at standard rates. Same number on both sides. So at standard rates the sticker price is a wash, and what separates them is how many tokens each one burns to finish and how long you wait. On the PDF job that gap favored Astra clearly. Both halve those rates for batch work, and Astra adds a few modes Fable does not have, so name the mode before you quote either one a price. ### **What Actually Changed at OpenAI** OpenAI has made one of the great comebacks in this space. Three things moved, and none of them are the "INSANE update" kind. #### **GPT-6 Astra Landed on the Pro Plan** Astra reached general availability on September 4. The part most write-ups get wrong: GPT-6 Pro, powered by Astra, sits in the main chat only on the Pro plans, Business Premium and Enterprise. Plus users get Astra inside ChatGPT Work and Codex, not in the standard model picker. So the flagship is genuinely what the $100 buys. #### **GPT-5.6 Sol Got Good Enough for Content Work** Sol is the model I use most now, and it does the unglamorous jobs well: drafting, editing, tearing a draft apart, arguing with my own angle. My read is narrow and about one job. For drafting and editing marketing content, Sol got good enough that I stopped reaching for Opus by reflex. The metering point is not just mine, either. Authority Hacker built their September 4 episode around the same question, comparing the two on design, writing and computer use, and then on *"how much of either model your plan lets you use before it cuts you off."* They flagged the same Fable 50% cap this post is about. #### **ChatGPT Images 2.5 Took Over My Image Work** OpenAI shipped ChatGPT Images 2.5 on September 8, with two API models, Flare and Sunburst. What matters to me is practical: transparent backgrounds, better single-element edits, and holding a subject's face steady across a reference photo. That is most of my thumbnail and diagram workflow, and it replaced what I covered when [ChatGPT Images 2.0](/chatgpt-images-2-0/) shipped. ### **The $100 Question** Both companies sell a $100 plan and both sound identical on the surface. They are not, and the difference is how each one meters its best model. ChatGPT Pro at $100 gives you 5x Plus usage. Claude Max starts at $100 and gives you 5x Pro usage. Same price, same-sounding multiplier, and the two baselines are not the same size to begin with. One more wrinkle on the Claude side that is easy to miss: those multipliers describe the rolling 5-hour session window, not the weekly ceiling. Weekly limits do not scale by the same factor, so moving from Max 5x to Max 20x does not quadruple what you can do in a week. Since the weekly number is the one that actually stops you, read 20x as a burst allowance rather than a weekly one. The deals differ, and it comes down to one sentence in Anthropic's own support docs: on Max you can use **up to 50% of your weekly usage limits on Fable models**. Fable is the model you are paying for. It is metered to half your allowance. | Plan | Price | Stated usage | Flagship access | What is metered | | ChatGPT Pro | $100/mo | 5x Plus | GPT-6 Pro in main chat | Standard plan limits | | ChatGPT Pro | $200/mo | 20x Plus | GPT-6 Pro in main chat | Standard plan limits (new signups paused) | | Claude Max | $100/mo | 5x Pro, per 5-hour session | Fable, capped | Fable at 50% of weekly limits | | Claude Max | $200/mo | 20x Pro, per 5-hour session | Fable, capped | Fable at 50% of weekly limits | The figures in that table are what the two companies published as of September 17, 2026, and this is a fast-moving corner of the market. Check both pricing pages before you buy anything. There is a second change worth separating out, because it is easy to mix up with the Fable cap. On September 14 Anthropic replaced a temporary 50% boost to **Claude Code** weekly limits with a permanent 25% increase, and that change is now in effect. That is Claude Code specifically, not your chat usage, and it has nothing to do with the Fable cap above. Run the arithmetic. If your baseline is 100, the boost put you at 150, and the permanent raise puts you at 125. That is roughly 17% less than what heavy Claude Code users lived on through the summer. Anthropic is correctly calling it a permanent increase over the original baseline. It is also a cut from what you had before September 14. Both things are true. One caveat before anyone goes shopping: OpenAI paused new sign-ups to the $200 Pro tier on September 10. Existing subscribers are unaffected and the $100 tier is still open. So the $200-versus-$200 comparison is academic right now if you are not already in. ### **Which Jobs I Moved and Which Ones Stayed** Forget which model is better and ask which job goes where. **Stayed with Claude Code and Fable:** building and running systems. Client site work, the cron publisher, skills, anything touching a repo. The skill files themselves are portable, as you will see in a minute. What keeps me here is the execution environment around them, which is the piece I would actually have to rebuild. **Moved to GPT-5.6 Sol:** drafting, editing, and red-teaming content. First drafts, tightening, and having a second model attack a piece before it ships. This is high-volume work, and high-volume work is exactly what you don't want metered to half your week. **Moved to ChatGPT Images 2.5:** thumbnails, featured images, and the diagrams in posts like this one. Subject preservation is the reason. Getting my own face to stay consistent across a reference photo was the job I kept redoing, and that is the thing 2.5 fixed. **Stayed on OpenRouter:** open-source model pulls. DeepSeek, Kimi, GLM when a job is cheap and bulk and does not need a frontier model. That runs under $50 a month and I covered the setup in my post on [using OpenRouter inside Claude Code](/claude-code-openrouter/). Aaron and I went deeper on [which cheap models actually hold up](/open-source-ai-models/) in a later episode. I put numbers on that gap a while back. I rebuilt my homepage with Opus and then ran the same task through five open-source models, and the spread was not close. Kimi was the most expensive of them at roughly 30 cents, while GLM came in near two cents. Running it on the frontier models would have cost several times more. Quality was not equal either, which is the point. Frontier models earn their price on work that needs them, and most bulk jobs do not. One ChatGPT feature genuinely changed how I work and almost nobody mentions it. The desktop app runs on a Mac or PC, you pair your phone to it, and you drive that session from anywhere. Mine runs on a Mac Mini that keeps working while I am not at my desk. The catch is real: if that machine sleeps or drops off the network, remote access stops. There is no magic, just a paired session. But it clears a bar most agent tooling does not for a non-technical marketer. I wrote about why you should [avoid OpenClaw](/avoid-openclaw/) and looked at [Hermes AI agents](/hermes-ai-agents/) for a specific automation job, and both are more setup than a QR code and a machine you already own. Notice the pattern. The expensive, careful, system-level work stayed. The high-volume repeatable work moved to the plan that does not ration the flagship separately. ### **The Case For Not Paying Anthropic At All** I pay for both plans. Aaron pays for one, and it isn't Claude's. Since I'd rather show you a real disagreement than pretend the buying decision is obvious, here is his argument in full. His position is that Fable is the only thing on Claude Max worth having, and that one model does not carry a $100 subscription when you can only spend half your allowance on it. Everything else in the lineup he considers a non-factor for his work. Stack the constraints and you can see the shape of it. Half your weekly limit is the ceiling on the model you upgraded for. There's a 5-hour rolling session window on top of the weekly one. And a Claude subscription still generates no photos or illustrations, so that job leaves the ecosystem no matter what. Claude does build diagrams, charts and interactive visuals, and Claude Design handles mockups and decks, but none of that replaces an image model. #### **Two Things We Got Wrong On Camera** Both of these were arguments against Claude, which is the direction I was already leaning, so they are exactly the kind of error that slides through unchallenged. I checked them against both companies' documentation after we recorded. Correcting them here rather than quietly dropping them. I said you have to be on a Max plan to touch Fable. You don't. Per [Anthropic's own support docs](https://support.claude.com/en/articles/15424964-claude-fable-models-on-your-plan), Fable 5 and 5.1 are available on every paid plan including Pro at $20, but on Pro they run on usage credits rather than your included allowance. The 50% ceiling is what's bundled into Max specifically. So the honest version is narrower than what I said: Max doesn't buy you access to Fable, it buys you included Fable usage, capped at half your week. We also both got the data question wrong. Aaron said he can't opt out of Anthropic retaining his prompts. You can, under [Settings then Privacy](https://privacy.claude.com/en/articles/12109829-how-do-i-change-my-model-improvement-privacy-settings), and OpenAI has the same switch under [Settings then Data Controls](https://help.openai.com/en/articles/5722486). What Anthropic does publish is the retention math: up to five years de-identified if you leave it on, 30 days after deletion if you turn it off. I could not find OpenAI publishing a matching figure, so treat the comparison as unresolved rather than settled in either direction. Either way, go turn the setting off. #### **The Argument That Survives Checking** Ask what each company has optimized for since January. His read is that Anthropic's models got better and also got more expensive, used more tokens, and gated more behind higher plans, so the bill climbed at least as fast as the output did. The Fable cap and the Claude Code limit change earlier in this post are both evidence for that. OpenAI spent the same period getting more work out of the same money, while everyone was still making fun of ChatGPT for business use. I don't fully agree with where Aaron lands. But the framing is right, and it is the question I'd ask before renewing anything: is this company optimizing for my output or for my bill? There's a real counterweight, though, and it's the thing his framing understates. A subscription is not only a model, it is the environment you run it in. My repos, my client work, and my publishing systems all execute through Claude Code, and Fable is still what I reach for on the highest-stakes single outputs. Aaron is optimizing for cost per unit of work, which is the right call when your work is not tied to one environment. Mine is. Those are two honest positions producing two different answers, which is why this question has no universal one. ### **The Cross-Check Habit That Matters More Than The Model** One workflow tip is worth more than any benchmark in this post. I run GPT-5.6 Sol on high reasoning effort as a gatekeeper. Whatever produced the work, Fable, Opus, or an open-source model, Sol gets the last look before anything ships. For genuinely high-value work like a landing page or a technical SEO change, I'll spend Astra on that final vet instead. Cross-check your output against at least two models, three if your token budget allows it. Models fail in different directions, and the second one catches what the first was confident about. Everything in this post about which plan to buy matters less than whether you actually do this. ### **Where Claude Still Wins** First, Fable is still the best model I own. Not "was." Is. When I need the highest-quality single output and I am willing to spend limits on it, that is the one I reach for. Second, Claude Code is still home base. My skills, my systems, my client work all live there. A model being marginally better somewhere else does not beat the system you have already built, which is the whole argument I made for [running Claude Code and Codex together](/claude-code-and-codex-together/). Third, design. Authority Hacker ran a one-shot design test across Astra, Fable 5.1 and Opus on the same prompt, and their read has consistently put Claude ahead on front-end design. Their conclusion isn't "drop Claude" either. It is that you have to decide whether the frontier model is worth the money or whether the step below it fits your plan comfortably. ### **Why the Switch Cost Me an Afternoon** Here is the part I did not expect. Moving this much work between two vendors took an afternoon. Not because I'm fast. Because almost none of my work lives inside a chat window. It lives in skills, which are plain markdown files that load into Claude Code or Codex. Prompt, rules, examples, guardrails, all in text. So moving a job from one vendor to another was mostly pointing a different tool at the same files. The system was portable because it was never tied to a model in the first place. That is the same reason I package these as the [Claude Code Skills Stack](https://skills.ryandoser.com), and it is the single most useful thing I can tell you here. The models matter, as three tests just showed. What does not matter is which company you happened to build on. If a pricing change at one vendor can strand your entire workflow, you don't have a workflow, you have a subscription. So here is where I actually stand. I pay for both $100 plans and I reassigned the work between them. I haven't downgraded Max, I'm only considering it. I'm eyeing the $200 ChatGPT tier and haven't moved. None of that is urgent, because nothing I built is locked to either one. If Anthropic loosens limits next month, the work moves back the same afternoon. ### **ChatGPT Pro vs Claude Max FAQs** #### **If I can only afford one, which should I buy?** Buy on the job that eats most of your week. If that is writing, editing and images, ChatGPT Pro at $100 gets you more usable output because flagship access is not separately metered. If it is building and running systems inside a repo, Claude Code is worth the cap and nothing else is close. #### **Is GPT-6 Astra better than Claude Fable 5.1?** Not on writing quality, in my testing. Fable wrote better long-form copy and stayed on brand when Astra did not. Astra was faster, burned fewer tokens to finish, filled in work I had not asked for, and generates images natively. If you want the single best output and can wait for it, reach for Fable. If you want more finished work per hour, Astra. #### **Do Astra and Fable 5.1 cost the same on the API?** At standard rates, yes. Both run $10 per million input tokens and $50 per million output tokens, and both cut that in half for batch work at $5 and $25. Where they diverge is the extras: Astra adds a flex tier, a premium fast tier at $20 and $100, and higher pricing above 272K of context. Anthropic does sell a fast mode, but it covers Opus rather than Fable. So the base rates match and the difference in what you pay comes from how many tokens each burns to finish the job. #### **Do you need Claude Max to use Fable?** No. Fable 5 and 5.1 are available on every paid Claude plan including Pro at $20, but on Pro they run on usage credits rather than your included allowance. What Max buys is included Fable usage, capped at 50% of your weekly limits. Free is the only tier with no Fable access at all. #### **What is the Claude Fable 50% limit?** On the Max plan, Anthropic's support docs state you can use up to 50% of your weekly usage limits on Fable models at no extra cost. Fable is the flagship, so half your weekly allowance is the ceiling on the model you upgraded for. A separate 5-hour session window resets on its own schedule alongside the weekly limit. #### **What happened to Claude Code limits on September 14?** A temporary 50% increase to Claude Code weekly limits expired on September 13 and a permanent 25% increase replaced it on September 14. Against the original baseline that is a raise. Against what heavy users had over the summer it is about 17% less. This applies to Claude Code, not to chat usage, and it is separate from the Fable 50% cap. #### **Can I still buy the $200 ChatGPT Pro plan?** Not as a new subscriber as of September 10, when OpenAI paused new sign-ups to that tier. Existing subscribers are unaffected and the $100 Pro plan is still available. #### **Does this comparison change if I never generate images?** Yes, and it gets closer. Images are a whole category moving to OpenAI, so take that out and you are weighing drafting volume against system work. If you build more than you write, staying on Max alone is defensible. --- ## AI Consultant vs AI Coach vs Fractional CAIO: Which One You Actually Need URL: https://ryandoser.com/ai-consultant-vs-ai-coach/ Markdown: https://ryandoser.com/ai-consultant-vs-ai-coach.md Published: 2026-09-07 Categories: AI Resources > Three roles, three price tiers, one decision. What each does, who it fits, and four questions that pick the one your business needs. If you are asking **should I hire an AI consultant**, the honest answer is that you might be shopping in the wrong category. There are three different roles being sold to business owners right now, they run from under $500 a month to $25,000 a month, and most owners cannot tell them apart. So in September 2026 I ran a small experiment. I asked ChatGPT and Perplexity, both with live web search on, the same question a non-technical owner would ask: which of these should I hire first? Both landed in the same place. Start with a coach. That is the tier I sell, so treat my answer with the suspicion it deserves and read the four questions below before you take anyone's word for it, mine included. That is one snapshot, not a law. Ask again next month and it could shift. But it is worth knowing what your customers are being told when they ask. Perplexity put it as "pick an AI coach first if you are still deciding where AI fits." ChatGPT said "if you're just getting started, have a small team, and mainly need education, quick wins, and guardrails, hire an AI coach first." Two systems, different source sets, same answer. Here is the problem with that advice. Perplexity also noted that the coaching category has no strong universal price. Individual firms do publish rates, as you will see below, but they are so far apart that the category number is meaningless. So the assistants point owners at a category, then hand them no way to judge what a fair price inside it looks like. Below is what each of the three roles actually does, what each one costs according to firms that publish their rates, and the four questions that decide which one you need. My own numbers are in here too, including where I am the wrong hire. Once you have settled on a consultant, there is a separate list of [questions that tell an operator apart from a repackager](/ai-consultant-for-small-business/). ### **The Three Roles Are Selling Three Different Things** The category names are close enough to sound interchangeable. They are not. What separates them is who ends up holding the work when the engagement ends. #### **An AI coach builds the capability in you** You sit down together, you do the work, and you keep the skill. njin.co, one of the few firms that publishes a full ladder across all three roles, defines it plainly: ["An AI coach teaches. Their job is to build capability in you or your team."](https://njin.co/resources/blog/ai-coach-vs-consultant-vs-agency) The output of a coaching month shows up as something you can now do in your business that you could not do last month, and you can do it again without calling anyone. #### **An AI consultant assesses and recommends** A consultant looks at your business, finds where AI fits, and hands you a plan or a built system. njin.co's version: "An AI consultant assesses and recommends. They come in, look at your business, identify where AI can make a difference and give you a plan." The output is a document or a working system. Whether the knowledge stays after they leave depends entirely on how the engagement was run. #### **A fractional CAIO owns AI across the company** This is a part-time executive, not a project. They own strategy, governance, vendor selection, and budget across multiple departments. Applied AI Leadership, which [publishes its rates for the role](https://appliedaileadership.org/blog/how-much-does-a-fractional-chief-ai-officer-cost), frames the cost comparison against mid-market salary benchmarks rather than against a small business budget. The output is a portfolio and a set of policies. It is a management function, not a build. Notice what separates them. A consultant hands you a fish. A coach teaches you to fish and then leaves you with the rod. A fractional CAIO takes over the fishery. And the fourth option most owners are also weighing, an agency, just runs the pond for you, which I come back to below. All four are legitimate. They just leave you in very different places when the money stops. ### **What Each One Costs, From Firms That Publish Rates** Most of this category quotes a range and asks you to book a call. These four publish actual numbers, so they are the ones worth quoting. **Coaching.** njin.co lists $500 to $3,000 a month, with outcomes visible in four to twelve weeks. My own [AI Concierge](/ai-concierge/) sits in this tier at $999 a month, and its limits are written out below. [useai.coach publishes $495 a month](https://useai.coach/pricing/) for what it calls "AI Coach on Call," cancel anytime, no minimum term, alongside a separate $4,500 flat fee for a four-week first build. Both figures sit below what the same firms charge for a scoped consulting engagement. **Consulting.** [Palavir publishes $150 to $400 an hour](https://palavir.co/blog/ai-consulting-small-business-cost), $5,000 to $30,000 for a single automation project, and $1,500 to $5,000 a month for an ongoing advisory retainer. njin.co puts a scoped engagement at $3,000 to $20,000 and up. I broke the full consulting ladder down separately in [what AI consultants actually cost](/ai-consultant-cost/). **Fractional CAIO.** Applied AI Leadership says retainers "cluster between $10,000 and $25,000 per month," with $15,000 as the most common anchor in 2026. I went deeper on that role in my breakdown of [how the fractional Chief AI Officer model works](/fractional-chief-ai-officer/). This next part cuts against my own interests. useai.coach's $495 is real, standalone, and cancellable. If price is your only filter, that is cheaper than what I charge and I am not going to pretend otherwise. What you compare after that is what a month actually contains. Mine is 90 minutes one-on-one with me on a screen share, building the thing in your own accounts, plus VIP access to my community and all three of my products. Compare that against whatever the cheaper option puts in front of you, and if theirs is the better fit for where you are, take it. ### **The Fourth Option: Just Hiring an Agency** Everything above compares three ways of buying advice. Most owners are weighing a fourth thing at the same time: hiring an agency to just do the marketing. It is the one where the work is most likely to still be someone else's job a year from now, which is either the whole appeal or the whole problem. The published numbers overlap the tiers above more than you would expect. [Arc Intermedia publishes](https://www.arcintermedia.com/services/consulting-technical/marketing-ai-consulting/) $150 to $500+ an hour, $5,000 for a focused project up to $100,000 to $500,000+ for enterprise programs, and monthly retainers "often starting near $2,000/month and scaling to $50,000+/month." That $2,000 floor lands inside the consulting advisory range already quoted above, and just above the $2,000 starting point I use in [what AI consultants actually cost](/ai-consultant-cost/). The tiers do not stack in a neat price ladder. What separates them at the same monthly number is what you are buying, not what you are paying. [First Movers draws the line](https://firstmovers.ai/ai-marketing-consultant/) more usefully than the price does: "A company or agency usually sells you the output on a retainer, while a consultant builds the capability inside your business and hands it over." That is the actual fork. You are choosing between renting the result and owning the machine. #### **The case for just buying the outcome** When you do not want to learn this. That is a legitimate position, and it is the honest dividing line between an agency and everything I sell. If marketing is not where you intend to build a personal skill, and you would rather buy the outcome and spend your attention elsewhere, an agency is a reasonable purchase and the other three tiers are probably a detour. #### **The risk to raise in the sales call** The month you stop paying. If the agency built the workflows, prompts, and context documents on their side, that is what leaves with them. You keep the results they produced and lose the machine that produced them. That is question four again. A fractional CAIO has the same answer and is openly sold that way, so you know going in. With an agency it is worth asking directly, because a monthly retainer does not advertise what it leaves behind. ### **Four Questions That Decide It** Skip the category names. Answer these four about your own business. If two of them point different directions, question two wins, because who has to run the thing in six months outlives any single project. #### **1. Do you know what you want AI to do yet?** If you can name the specific workflow, you have a scoping problem and a consultant can solve it. If you are still at "everyone says I should be using this," you have a judgment problem, and no amount of building fixes that. This is the question both assistants were answering when they said coach first. #### **2. Who has to be able to run it in six months?** If the answer is you or someone on your small team, buy the thing that transfers the skill. If the answer is a vendor and you are fine with that, buy the build. Both are reasonable. Choosing the build and then expecting the skill is where owners get burned. #### **3. How many departments are involved?** One workflow is a project. Several departments with competing requests, vendor decisions, and a policy question is a management function. That is the honest trigger for a fractional CAIO. Before you get there, you are buying executive overhead for a problem that has not arrived. #### **4. What happens the month after you stop paying?** This is the one nobody asks in the sales call, and it is the most useful of the four. If the answer is "everything stops," what you bought was access rather than capability. Sometimes that is the correct purchase, and a fractional CAIO is openly sold that way. Just make sure you chose it on purpose instead of discovering it in month seven. ### **Where the Category Advice Falls Down for Small Owners** One of the better-argued pieces on this question comes from Perceptive Analytics, on [hiring a consultant versus building in-house](https://www.perceptive-analytics.com/should-we-hire-an-ai-consultant-or-build-an-in-house-team/). Its direct answer is good: hire a consultant when you need a working system fast and have not yet proven where AI creates value, then build in-house once you have proven use cases. But read who it is written for. Operations leaders, CTOs, and founders with technical authority. It assumes you follow data environments, production systems, and deployment methodology. And it never offers coaching as a third option at all. Its framing is consultant or in-house team. That is the actual gap. If you run a ten-person company and cannot evaluate a model deployment plan, "hire a consultant or build a team" is not a menu you can order from. Both options require you to already know what you are buying. To be fair to the consulting model, that same piece makes the right point about knowledge transfer: a well-run engagement "documents the system, transfers ownership, and trains your team so the knowledge doesn't leave when the consultant does." That is a real thing good consultants do. It is just not the default, and it is not what you get by accident. ### **Where My Own Offer Sits, and Who It Is Wrong For** I sell the coaching tier. My [AI Concierge](/ai-concierge/) is $999 a month, month to month, limited spots, by application. It is one 90-minute one-on-one working call a month on a screen share, where we set up a real improvement in your business live, in your own accounts. VIP membership of my community and all three of my digital products come with it. It is coaching and direction. It is not done-for-you. I say that early because it disqualifies people, and it should. Who it is right for: an owner or founder who can make a 90-minute call each month, wants to end up able to run this without me, and has one part of the business that is genuinely costing them time right now. Knowing which area hurts is enough. If you had already scoped the exact workflow and just wanted it built, question one would send you to a consultant instead, and it should. If you are not technical, that is fine. Most of the owners I talk to are not. Who it is wrong for: if you want your marketing run for you, buy the agency tier from someone, not me. If you have one bounded question rather than something you want to build a habit around, a single session at my hourly rate answers it faster and costs you less. And if you need a guarantee of a specific revenue number, nobody in this category can honestly give you one, including me. I also publish the other two options rather than pretending coaching wins every time. Hourly consulting with me is $500 an hour, and on-site work starts at $5,000. All three sit on my [AI consulting page](/ai-consulting/). If the four questions above point you at a build rather than a coaching engagement, take that answer. ### **The Sequence Most Small Businesses Should Actually Follow** Both live AI answers landed on roughly the same order, and on this one they are right. Start with coaching only while you are still figuring out where AI fits, not as a default. Two or three months is usually enough to find the real bottleneck, because the first thing you think is the problem is usually not. My [90-day implementation plan](/how-to-implement-ai-in-business/) walks through how to do that part yourself. Move to a scoped consulting project once you can name the specific workflow and want it built properly. Add a fractional CAIO only when AI stops being a project and becomes a standing management function across several departments. Most small businesses never reach that point, and that is not a failure. The mistake is buying the expensive tier first because it sounds more serious. Paying for executive oversight before you have decided what you want done just buys you a more expensive version of the same confusion. If the four questions pointed you at coaching and you want to do that with me, the [AI Concierge](/ai-concierge/) runs by application. You tell me what is eating your week, I tell you honestly whether a monthly working call fixes it or whether you want one of the other two. I have talked people out of it before. If you would rather sit across a table for that conversation, I am [based in Des Moines](/ai-marketing-consultant-des-moines/) and work with businesses around Iowa. ### **Should I Hire an AI Consultant FAQs** #### **Is a consultant the same as a coach?** No, and the difference is who holds the work at the end. A consultant assesses your business and hands you a recommendation or a built system. A coach works alongside you so the capability stays with you and your team. A consultant is measured by the deliverable. A coach is measured by what you can do without them. #### **How much does an AI coach cost?** Published rates run from $495 a month at useai.coach up to $3,000 a month at the top of njin.co's coaching tier. My own AI Concierge is $999 a month, and you can see [how it compares with seven other consultants' published prices](/best-ai-marketing-consultants/). Rates spread this wide because the category has no standard unit, so compare what a month actually includes, and how many hours of it are with the person you are hiring, rather than the headline number. #### **Do I need an AI consultant if I am not technical?** Often not as your first hire. A lot of consulting content assumes you can already evaluate a technical plan, which is the thing a non-technical owner cannot do yet. Asked this directly in September 2026 with live search on, both ChatGPT and Perplexity pointed a non-technical small business owner at coaching first. Once you can name the specific workflow you want built, a consultant becomes the right buy. #### **When is a business too small for a fractional CAIO?** Applied AI Leadership, one of the few firms publishing rates for the role, states no minimum company size and no typical client size at all. So headcount is the wrong test. The real one is whether several departments are making competing AI decisions that need a single owner. If AI is still one workflow in one part of the business, you are buying executive overhead you do not need yet. #### **Should I hire an AI consultant or a marketing agency?** Start with capacity, not preference. If the work genuinely needs more hands than you have, coaching will not fix that and an agency is the honest answer. If the shortage is judgment rather than hours, meaning you could get it done but cannot tell whether it is any good, an agency will happily fill the gap and you will still not be able to grade the output. Price will not settle it either way: Arc Intermedia starts agency retainers near $2,000 a month while njin.co puts a full agency engagement at $5,000 to $15,000+, and consulting advisory retainers run $1,500 to $5,000 in between. #### **Is an AI marketing consultant cheaper than an agency?** Often, but not always, and the ranges overlap. Arc Intermedia puts agency retainers as starting near $2,000 a month, which sits inside the $1,500 to $5,000 advisory-retainer range Palavir publishes for consulting. njin.co, quoted earlier in this post, puts a full AI agency engagement higher at $5,000 to $15,000+ a month. So the honest answer is that a consultant is usually cheaper than a full-service agency retainer and roughly the same price as an agency's entry tier. What you are actually choosing between at the same monthly number is output versus something you keep. #### **What questions should I ask before hiring any of them?** Ask what you will be able to do yourself when the engagement ends, who owns the accounts and the setup, and what happens the month after you stop paying. That last one separates a capability from a rental faster than any credential check. Disclosure: this post has no affiliate links. The firms and prices quoted are competitors I am citing as sources, and I sell a coaching offer in the same category, which I have named and priced openly above so you can weigh it against them. I also run a marketing agency myself, solo, so the section on agencies is written by someone inside that category rather than outside it. See my full [disclosure](/disclosure/). --- ## 8 Best Instagram DM Automation Tools in 2026 (Ranked) URL: https://ryandoser.com/best-instagram-dm-automation-tools/ Markdown: https://ryandoser.com/best-instagram-dm-automation-tools.md Published: 2026-09-07 Categories: AI Tool Reviews > I priced eight Instagram DM automation tools off their live rate cards and found the constraint that decides whether any of them work for you. Before you pick from the **best Instagram DM automation tools**, there is one thing worth knowing about the lists you have already read. I fetched the seven pages currently ranking for this search. Every single one was published by a company that sells a DM automation tool. All seven put their own product at number one. That is not a scandal. Vendors are allowed to write about their own software. But it does mean the ranking you are looking at is a sales page wearing a listicle costume. ### **The Two Meta Rules That Decide What You Can Send** This is the part almost nobody covers, and it matters more than any feature comparison. You cannot message whoever you want on Instagram, and the two rules that decide what you can send are not the same rule. Most articles in this category blur them together. The first governs comment-to-DM, which is the funnel almost everyone buys these tools for. It runs on an API Meta calls Private Replies, and its documented limits are strict: your app "can send this private reply within 7 days of the creation time of the comment," and under the heading Limitations, "Only one message can be sent to the commenter." One message. Not a sequence. If that person does not follow the account, your reply lands in their Request folder rather than their inbox, which is worth knowing before you judge your open rates. The second governs actual conversations. Once someone sends you a DM, Meta opens what it calls the Standard Messaging Window, defined in its documentation as "the 24 hour time period in which you are allowed to send a message to a person." After that the door shuts, and the only escalation is the Human Agent tag, which "allows a business representative to *manually* respond to a person's messages within a 7-day period." Manually is doing real work in that sentence. Two more limits before you buy anything. Message tags "may not be used to send promotional content, including but not limited to: deals, offers, coupons, and discounts." And Sponsored Messages and One-Time Notifications, the two escape hatches Facebook Messenger gets, are both unavailable on the Instagram Messaging API. Here is why that matters for your shortlist. Every compliant tool on this page is fenced in by those same rules, and none of them can sell you around it. Six of the seven ranking pages I read assert that using the official API keeps you safe, and not one links to the Meta documentation that says so. When a tool markets "unlimited DMs," it is selling unlimited *replies to people who contacted you first*. Cold outreach at scale is not something anyone here can legally offer, and a vendor implying otherwise is telling you how it treats the rules. ### **What to Put in the One Message You Get** The rules above have a practical consequence almost nobody writes about. If your only guaranteed send is a single reply to a comment, that one message has to do the whole job, and the reply that works looks different from the one most people set up. Three things I would change about a default setup. First, put the link in the first message rather than asking them to reply for it, because a reply is the thing you cannot count on. Second, if the person does not follow you the message lands in their Requests folder, so write the opening line to survive being seen in a preview with no context. Naming what they asked for beats "Hey there, thanks so much for commenting." Third, treat the follow gate honestly. It asks people to follow before the link unlocks, which does lift follower counts, and it also adds a step between a warm commenter and the thing they asked for. On a small account where every lead matters, sending the link immediately usually beats gating it. The one genuine way to earn more messages is to get a reply. A reply from them opens the 24-hour window, which is why asking one specific, easy question at the end of that first message does more for your funnel than any feature on any pricing page here. ### **How I Checked the Pricing** Every price below came off the vendor's live pricing page on September 6, 2026, with monthly billing selected. That last part is not a formality, and it is the same check I run when I price [social media automation tools](/social-media-automation-tools/) for the publishing side. ManyChat's pricing page loads on the annual toggle by default and prints annual rates with a "/mo" suffix beside them. Read it quickly and you will write down $14 a month for Essential. The real monthly price is $17. I clicked the toggle on every page here and captured both states, which is also how I caught that the widely repeated "ManyChat starts at $14" figure floating around this category is the annual number. One boundary, stated plainly. Blotato is the only tool on this list I run every day, including the DM automations, and I have an affiliate and client relationship with them that you should weigh. The other seven I have not used. I priced them from their live rate cards and read their documentation, and I have flagged in each entry where a claim comes from a vendor's own marketing rather than from something I verified myself. ### **The Best Instagram DM Automation Tools at a Glance** | Tool | Best for | Starts at (monthly) | What it meters | Free plan | | Blotato | Running DMs and publishing from one AI agent | $29/mo | 1,000 active contacts/mo | No, 7-day trial | | ManyChat | Deep visual flow building across four channels | $17/mo | 250 active contacts, then per contact | Yes, 25 contacts | | ReplyRush | The most DM volume per dollar once you pay | $10/mo | 7,500 DMs sent/mo | Yes, 1,500 DMs | | InstantDM | Flat unlimited pricing with an MCP server | $9.99/mo | Nothing, no contact or DM meter | Yes, 500 credits | | CreatorFlow | Creators who want one clean price and no math | $15/mo | 5,000 DMs per workspace/mo | Yes, 500 DMs | | LinkDM | Managing several Instagram accounts at once | $19/mo | DMs sent, 3 accounts on Pro | Yes, 1,000 DMs | | Inro | Treating DM contacts as a CRM list | From EUR 12.99/mo | Activated contacts, on a sliding scale | Yes, 100 contacts | | Meta Business Suite | Finding out whether you need to pay at all | Free | Nothing | Yes, entirely free | ### **The 8 Best Instagram DM Automation Tools** Ranked for a creator or small business owner who wants comment-to-DM working this week without getting their account restricted. #### **1. Blotato (Best for running DMs and publishing from one AI agent)** I put [Blotato](https://www.blotato.com/?ref=rdoser) first for a reason that has nothing to do with it being the best DM flow builder, because it is not. ManyChat wins that. I rank it first because it is the only tool here that ends the separate-vendor problem: my comment-to-DM automations and the posts that generate those comments run through the same key, and the DM triggers fire from a rule my AI agent wrote. The automation model is comment-received or message-received as a trigger, keyword filtering on top, then a reply with up to three link buttons, an optional follow gate and an optional email capture. That is the comment-to-DM funnel every tool here sells, and it is the one I actually use. I went deeper on the rest of the product in my [full Blotato review](/blotato-review/). **Pros:** - DM automation, comment replies, publishing to nine platforms and analytics behind one key and one bill - Native MCP server, so Claude or another agent can build and fire automations without a dashboard - Flat monthly price that does not climb per contact the way ManyChat's does - Follow gate and email capture built into the automation rather than sold as an add-on **Cons:** - DMs and comments work on Instagram and Facebook only, so no WhatsApp or TikTok inbox - Active contacts are capped at 1,000 a month on Starter, and a person reached through two connected Pages counts twice - The flow builder is a rules engine, not ManyChat's visual canvas - No free plan, and generating an API key ends the 7-day trial and starts billing immediately, which is a trap for exactly the developer audience the product courts - Publishes no annual dollar figures, only a vague "save about 17%", which is the same pricing vagueness I just criticized elsewhere on this page **Best for:** Someone already publishing through an AI agent who wants the DM layer on the same key. **Pricing:** Starter $29/mo (20 social accounts, 1,000 active contacts), Creator $97/mo (40 accounts, 6,000 contacts), Agency $499/mo (100 accounts, 15,000 contacts). Monthly billing. Blotato says annual saves about 17% but publishes no annual dollar figures. **Free trial:** 7 days, card required, and it covers everything except the API. **Bottom line:** The pick if Instagram and Facebook are where your DMs happen and you want them on the same key as your publishing. Outside that, it is the wrong tool, and the WhatsApp gap is not something I can talk you around. #### **2. ManyChat (Best for deep visual flow building across four channels)** *ManyChat appeared on all seven ranking pages I checked, the only tool that did.* [ManyChat](https://manychat.com/) is the default for a reason. It showed up on all seven competing lists I pulled, and it is the only tool in this category with that kind of gravity. The flow builder is genuinely the most capable one here. It covers Instagram, WhatsApp, TikTok and Messenger, and ManyChat lists itself as a Meta Business Partner. What earns it second rather than first is the pricing shape. ManyChat bills on active contacts, which its page defines as "a real person you interact with during a monthly billing period... One person = one Active Contact for the month." Cross your included count and you do not get shut off, you get charged: $0.10 per extra contact on Essential, dropping to $0.004 on Advanced. A viral reel is a billing event. **Pros:** - The deepest visual flow builder in the category, and the least likely to hit a wall you cannot design around - Four channels including WhatsApp and TikTok, which no other tool on this list matches - A real free plan for 25 contacts, plus a 14-day trial on paid tiers - Overage is metered rather than a hard stop, so automations keep running when you spike **Cons:** - Essential and Pro cap you at 2 and 3 connected channels - Contact-based billing charges you most in the month a post actually performs - The pricing page opens on annual billing, so the number you write down is rarely the one you pay - No first-party MCP server as of September 2026, so agent access means the REST API **Best for:** Creators running multi-step DM funnels who need WhatsApp or TikTok alongside Instagram. **Pricing (monthly billing):** Free $0 for 25 contacts, Essential $17/mo for 250, Pro $39/mo for 2,500, Business $99/mo for 7,500, Advanced $199/mo for 25,000. On annual those become $14, $29, $69 and $139 a month. **Free trial:** Yes, 14 days on paid plans, plus a permanently free tier. **Bottom line:** If your funnel is complicated or your audience lives on WhatsApp, ManyChat is worth the premium and the metering. Run the contact math at your actual monthly reach before you commit, not at today's. #### **3. ReplyRush (Best for the most DM volume per dollar)** [ReplyRush](https://www.replyrush.com/) sells more DM volume per dollar than anything else here. Ten dollars buys 7,500 DMs a month, and $25 buys 40,000 across three accounts. It meters DMs sent instead of people reached. At high volume with a small audience that is cheaper than contact-based billing, and at low volume with a large audience it is worse. Worth noting the free tier withholds Comment Auto Reply and the follow gate, so the thing most people came for sits behind the $10 plan. **Pros:** - 1,500 free DMs a month, though the free tier is a volume sample rather than a way to test comment-to-DM - Covers Instagram and Facebook, with multiple accounts from the Boost tier up - Priced in USD and INR, which is rare and useful outside the US **Cons:** - Comment auto reply and the follow gate are not in the free tier - No annual option at all, so no discount for committing - Smaller company than ManyChat, and I have not run it myself - Its Meta Business Partner status is the company's own claim, which I did not verify against Meta's directory **Best for:** High reply volume on a small budget, once you know the tactic works for you. **Pricing:** Free (1,500 DMs, 1 IG and 1 FB account), Lite $10/mo (7,500 DMs), Boost $25/mo (40,000 DMs, 3 accounts each), MAX $100/mo (400,000 DMs, 5 accounts each). Monthly only. **Free trial:** Not needed, there is a permanent free plan. **Bottom line:** The $10 tier is the cheapest serious volume on this page. Do not mistake the free plan for a trial of the real thing, because comment-to-DM and the follow gate both sit behind the paywall. #### **4. InstantDM (Best for flat unlimited pricing)** [InstantDM](https://instantdm.com/) takes the opposite position to ManyChat on the only axis that matters at scale. There is no contact meter and no DM meter. Legend Pro is $9.99 a month with unlimited automations at a 750-per-hour ceiling, though the plan table marks contact access on that tier as limited and reserves unlimited contacts for Trendsetter at $24.99. It also ships an MCP server exposing 22 tools on Instagram's official API, which makes it the only tool besides Blotato here that an AI agent can drive natively. InstantDM says the free trial includes API and MCP access, while its plan table puts ongoing API access on the $24.99 tier. Worth confirming which applies to you before you subscribe. **Pros:** - MCP server plus API access and webhooks on the $24.99 tier - Free forever plan with 500 credits a month and no card required - States plainly that it uses no browser bots, no scraping and never asks for your password **Cons:** - The annual toggle on its pricing page does not change the displayed prices, so annual pricing is unverifiable - Its llms.txt headlines "$9.99/month flat" and omits the higher tier, which is marketing rather than a rate card - Two tiers only, so there is little room to grow into - Instagram-focused, with none of ManyChat's channel spread **Best for:** High-volume creators who do not want a bill that tracks their reach. **Pricing:** Free forever (500 credits/mo), Legend Pro $9.99/mo (unlimited automations at 750/hr, limited contact access), Trendsetter $24.99/mo (unlimited contacts plus API access, webhooks and safety modes). **Free trial:** Yes, 7 days with no card, and a permanent free tier underneath it. **Bottom line:** If your posts spike unpredictably, flat pricing removes the one variable you cannot forecast. Below a few hundred contacts a month a metered plan is usually cheaper, so this is a bet on your ceiling rather than your average. Get the annual price in writing from support before committing. #### **5. CreatorFlow (Best for one clean price and no math)** [CreatorFlow](https://creatorflow.so/) is the tidiest pricing story in this roundup. Three tiers, DMs per workspace, and an llms.txt rate card that matches the live page figure for figure. After a day of vendor pages contradicting themselves, that consistency counts for something. It is also the tool that says the honest thing out loud. Its own compliance page notes that the official API "carries a lower risk of account restrictions than unofficial methods, but no tool can eliminate that risk." Every other vendor here implies safety is a solved problem. **Pros:** - Free plan includes comment-to-DM and story replies rather than withholding them - DM top-up packs are one-time purchases that never expire - Lists itself as a Meta Tech Provider, and is honest in writing about residual risk **Cons:** - Two Instagram accounts on Pro, five on Growth, so agencies outgrow it fast - Instagram only, with no Facebook inbox - 14-day trial requires a payment method up front - Trustpilot score of 3.8 rests on only 13 reviews, which is thin either way **Best for:** A solo creator who wants one number on the invoice and no metering to track. **Pricing:** Free (500 DMs, 1 account), Pro $15/mo (5,000 DMs, 2 accounts), Growth $30/mo (10,000 DMs, 5 accounts). Annual works out to $12 and $24 a month. **Free trial:** 14 days on paid plans, card required, plus a free tier. **Bottom line:** The clearest pricing here and a free tier that includes the feature you want. The five-account ceiling is the thing that will eventually move you. #### **6. LinkDM (Best for several Instagram accounts at once)** [LinkDM](https://www.linkdm.com/) gives you three Instagram accounts on a $19 plan, where CreatorFlow gives two and ReplyRush's comparable tier is $25. If you run a couple of brands, that ratio is the argument. It says it has been a certified Meta Business Partner since 2021, which is the longest tenure claimed by anyone here. One caution from reading its pricing page carefully: the monthly view says 25,000 DMs a month, while the yearly view relabels the same figure as per account. Those are different products. Ask before you buy. **Pros:** - Meta Business Partner since 2021, per the company - Free plan with 1,000 DMs a month - Platinum+ scales to 10 accounts and 300,000 DMs for $99 **Cons:** - Its monthly and yearly views describe the DM cap differently, which needs clarifying before purchase - Instagram only - The jump from $19 to $99 leaves no middle tier - I have not run it, and the partner status is the company's own claim **Best for:** Someone running two or three Instagram accounts who does not want to pay per seat. **Pricing:** Free (1,000 DMs, 1 account), Pro $19/mo (3 accounts), Platinum+ $99/mo (10 accounts). Annual runs $182 and $832 a year. **Free trial:** Free plan rather than a trial. **Bottom line:** The multi-account value pick. Confirm what the DM cap actually means on your plan before you hand over a card. #### **7. Inro (Best for treating DM contacts as a CRM)** [Inro](https://www.inro.social/) is the one tool here that treats your DM list as a database rather than a message queue. Segmentation, enrichment and CRM actions are the product, and the pricing follows that: you pay for activated contacts on a curve that scales with usage. The detail I like is that manual DMs you send yourself do not count toward the quota. Only contacts touched by automation or CRM actions do. It also prices in euros, so a US buyer is exposed to the exchange rate. **Pros:** - Contact segmentation and enrichment that no other tool here offers - Manual DMs do not consume quota, only automated and CRM actions do - Free tier of 100 activated contacts - Lists itself as a Meta Tech Provider, and states compliance with GDPR and the EU AI Act **Cons:** - Publishes no price list between the EUR 12.99 entry and the EUR 1,249 annual plan, so you have to run its calculator to learn your own cost - Its annual plan is discounted against a list price, not against the monthly entry point - The heaviest tool here for someone who just wants comment-to-DM **Best for:** Businesses whose Instagram inbox is a sales pipeline that needs segmenting. **Pricing:** Free (100 activated contacts), Pro from EUR 12.99/mo for 500-plus activated contacts, Annual Pro EUR 1,249/yr for 10,000-plus contacts (listed against EUR 1,800). Managed service from EUR 200/mo. Inro does not publish the tier prices between those points, it gives you a calculator instead. **Free trial:** Free tier rather than a trial. **Bottom line:** Overkill for a link-in-DM funnel, and the right call if you are qualifying leads in the inbox and need to know who they are. #### **8. Meta Business Suite (Best for finding out if you need to pay at all)** Four of the seven ranking pages I read include [Meta Business Suite](https://business.facebook.com/business/tools/meta-business-suite), and they are right to. It is free, it is first-party, and it does saved replies, greeting messages and simple automated responses without a third-party app touching your account. It will not build a keyword-triggered comment-to-DM funnel with a follow gate. That is the actual line between this and everything above it. But plenty of people paying $17 a month are using about this much functionality. **Pros:** - Free, with no tier to outgrow - Handles Instagram and Facebook inboxes together - No third-party tool sits between you and Meta's own policy enforcement **Cons:** - No keyword-triggered comment-to-DM automation - No follow gate or email capture - The interface is built for support, not funnels - No API or agent access for building your own logic **Best for:** Establishing your baseline before paying anyone. **Pricing:** Free. **Free trial:** Not applicable. **Bottom line:** Spend a week here first. If the only thing you miss is auto-DMing people who comment a keyword, you now know exactly what you are buying and why. ### **How to Choose an Instagram DM Automation Tool** These are the questions I work through on every client build, and they sort this category faster than any feature grid. - **What does the bill track?** Contacts reached, DMs sent, or nothing at all. This single choice decides your cost at scale more than the headline price does. - **What happens on your best day?** Model the bill on a post that outperforms by 10x. Contact-based plans charge you most exactly when something works. - **How many accounts, honestly?** Account caps, not features, are what move people between tiers here. - **Do you need a channel beyond Instagram?** WhatsApp and TikTok narrow this list to one tool immediately. - **Is this a fifth vendor or part of something you already run?** If you already pay for publishing, adding a separate DM subscription deserves a reason. Blotato keeps a [feature matrix of which Instagram DM tools also publish](https://www.blotato.com/blog/instagram-automation-tools), which answers that question in one column. - **Does the vendor tell you the truth about risk?** Anyone promising cold DM outreach at scale is describing something the API does not permit. ### **What About Chatfuel and the Enterprise Inbox Tools?** Two names you will see elsewhere are deliberately not ranked above. [Chatfuel](https://chatfuel.com/) appeared on six of the seven lists I checked, so leaving it out is a real choice. It has moved toward WhatsApp-first lead qualification and sales attribution, pitched largely at agencies, which is a different job than the creator comment-to-DM funnel this post is about. If your sales happen on WhatsApp, look at it properly. Respond.io, Trengo, SleekFlow and Wati sit in the same bucket. They are customer support platforms that happen to include Instagram, built for a team working a ticket queue rather than a creator running a funnel. ### **Start With the Rules, Not the Tool** The comparison that actually matters here is not which flow builder looks nicest. It is what your bill does when a post takes off, and whether the vendor was straight with you about the rules everyone is operating inside. Run Meta Business Suite for a week. If the gap you feel is keyword-triggered DMs, pick from the eight above based on what your bill tracks, and you will not overpay for a canvas you never open. If you want the publishing side running the same way, I wrote up how I [run social media through Claude Code](/claude-code-social-media/). ### **Instagram DM Automation FAQs** #### **Can you automate DMs on Instagram?** Yes, and Meta supports it officially through the Instagram Messaging API. What you cannot do is send cold DMs at scale. Automation is limited to replying to people who contacted you first. A comment on your post lets you send one private reply within 7 days, and once someone DMs you, you get a 24-hour window to respond. #### **Is there a free automation tool for Instagram DMs?** Several. ReplyRush gives you 1,500 DMs a month free, LinkDM gives 1,000, CreatorFlow gives 500 including comment-to-DM, and Inro covers 100 activated contacts. ManyChat's free tier is 25 contacts. Meta Business Suite is free but does not do keyword-triggered comment-to-DM, so it is a baseline rather than a replacement. #### **What are the best Meta-verified automation tools for Instagram DMs?** Meta runs two separate programs and vendors are not always precise about which they hold. ManyChat, ReplyRush, LinkDM and InstantDM describe themselves as Meta Business Partners. CreatorFlow and Inro list themselves as Meta Tech Providers. Every tool in this roundup runs on Meta's official API rather than browser bots, which is the distinction that actually protects your account. #### **How much does Instagram DM automation cost?** Entry pricing runs from $9.99 to $29 a month, but the meter matters more than the headline. ManyChat bills per active contact starting at $17 monthly for 250 contacts, then charges overage. ReplyRush, LinkDM and CreatorFlow bill by DMs sent. InstantDM charges a flat $9.99 with no meter. Model your bill on a post that outperforms by 10x before you pick. #### **Will Instagram ban me for using DM automation?** Using a tool built on Meta's official API carries far less risk than a browser bot that asks for your password, and every tool here uses the official API. CreatorFlow puts it accurately on its own site: the official API "carries a lower risk of account restrictions than unofficial methods, but no tool can eliminate that risk." What gets accounts restricted is unsolicited bulk messaging, which the API does not permit anyway. *Disclosure: the Blotato links here are affiliate links and Blotato is also a client of mine, so I may earn a commission at no extra cost to you. Blotato is the only tool on this list I use. The other seven were priced from their live rate cards on September 6, 2026, and I have no relationship with any of them. [Full disclosure](/disclosure/).* --- ## How to Implement AI in Business When You Are Not Technical URL: https://ryandoser.com/how-to-implement-ai-in-business/ Markdown: https://ryandoser.com/how-to-implement-ai-in-business.md Published: 2026-09-07 Categories: AI Resources > Pick your first AI task by what you would tolerate being done badly, not by what takes longest. A 90-day plan for an owner with no team. Most guides on **how to implement AI in business** tell you to find your most repetitive task and start there. That is the wrong first filter, and it is why so many owners stall in week six. The better question is which task you would tolerate being done badly. AI output needs checking. If a job is one you cannot bring yourself to hand to a new employee on their first week, you will not really hand it to software either. You will hover over it, re-do it yourself, and quietly stop opening the tool. The task that survives is the one where a rough first draft is genuinely useful to you, even when it is wrong. That single reframe is most of the difference between a habit that sticks and one that does not, and I have not seen it in any of the guides ranking for this phrase. ### **Why the Standard Advice Does Not Fit a Business Your Size** I checked the page-one results. Microsoft, IBM, MIT Sloan and Harvard Business School are all there, and to be fair to them, most do tell you to identify the problem before picking a tool. IBM's first step is defining goals. Microsoft's is use-case identification. The problem is who they are talking to. IBM's guide assumes you can convene a cross-functional review board and hire data scientists. Microsoft's assumes a portfolio of use cases to rank by value and effort. That is sound advice for a company with departments. If you are the owner, the operations manager and the person who answers the phone, there is no portfolio to scan and no committee to convene. There is just your week. It also assumes the hard part is choosing correctly. For an owner, the hard part is that the choice has to survive a bad Tuesday. Worth naming what the research says actually stops people. The Bipartisan Policy Center found in a [December 2023 survey of 498 firms](https://bipartisanpolicy.org/report/small-businesses-matter-navigating-the-ai-frontier/) that cost was the most significant barrier, at 55%. A Service Direct report found that among owners who do *not* use AI, 62% gave reasons that came down to [not understanding the benefits](https://servicedirect.com/resources/small-business-ai-report/). Different years and different groups, so I am not going to stack them into a league table, but together they say the two things standing between an owner and AI are price and not being able to picture the point. The plan below is built to kill the second one first, because it is free to do, and because price sorts itself out once you can see what you are buying. If you would rather pay someone to shortcut it, the [nine questions I would ask an AI consultant](/ai-consultant-for-small-business/) are worth reading before you do. ### **Days 1 to 14: Build the Two-Column List** Do not download anything yet. For two weeks, keep a running list of every task you personally do more than twice. Not what your business does. What *you* do, with your own hands, that eats your evenings. Give each task two columns. First, how long it takes you. Second, whether you would let a capable new hire do it badly for a fortnight while they learned. Picking the right task off that list is the thing I most often end up doing with owners in the [AI Concierge](/ai-concierge/). The 90 days below cost nothing to run though, so do that first, before paying anyone. Me included. The second column is the one that picks your task. Sort by it, not by the clock. A ninety-minute job you would never hand over is a worse starting point than a twenty-minute job you would, because the first one you will take back and the second one you will keep. By day 14 you want one task selected. One. Writing customer emails, drafting quotes, summarizing calls, turning a job into an invoice description. Something language-heavy that you can check in ten seconds. ### **Days 15 to 45: Get One Task Working Properly** Now open a tool. Use the free tier of [Claude](https://claude.ai) or [ChatGPT](https://chatgpt.com). You do not need a paid plan to find out whether this works for you, and you should not buy one until you know. Do the task the way you always do. Then do it again with the tool. Compare the two, and time both. The important part is what happens next, and it is the part almost every guide skips. When the output is wrong, do not accept it and do not give up on it. Tell the tool exactly what was wrong and ask again. Then save the version of your instructions that finally worked. That saved instruction is the actual asset. Not the tool, not the subscription. It belongs in a note on your desktop where you can paste it again next week. Owners who quit at this point usually quit because they judged the technology on its first answer. The first answer is a starting position. By day 45 you should be able to say a real number. Not "it saves time." Something closer to "this took me forty minutes on Tuesdays and now takes twelve." ### **Days 46 to 75: Make It Survive a Bad Week** This is the stretch where the novelty is gone and nothing is forcing you to keep going. Two things make a habit stick here. First, attach the task to something already in your calendar rather than relying on remembering. If you draft quotes on Monday mornings, the saved instruction lives in the Monday morning block. Second, write down what the tool is not allowed to touch. Client financials, anything with personal data in it, anything going out the door without your eyes on it. Owners skip this because it feels like paperwork for a company of three, then hesitate over every single use because they never settled the question. Settling it once removes the friction. If the task has not stuck by day 75, the honest read is usually that you picked the wrong task, not that AI does not work for your business. Go back to your day-14 list and take the next one down. ### **Days 76 to 90: Add the Second Thing, or Stop** You have earned exactly one decision here. If the first task is running without you thinking about it, pick a second from the same list and repeat the cycle. Not five. One. If it is not running, stop adding. Adding a second tool on top of a first one you are not using is how owners end up paying for four subscriptions and using none, and how a business that told a survey it used AI last year says no this year. Stopping is a legitimate outcome at day 90. A business that tested AI on one workflow, measured it honestly and concluded it was not worth it right now is in a better position than one that bought a stack on enthusiasm. You can revisit in six months with everything you learned. If it worked and you want to go further, that is the point where [choosing between a coach, a consultant and a fractional CAIO](/ai-consultant-vs-ai-coach/) starts to matter. ### **What This Plan Deliberately Leaves Out** No automation platform. No connected apps, no [Zapier](https://zapier.com) or [Make](https://www.make.com) workflows, no agents. Those are legitimate tools, but they are day-180 work, and putting them in a beginner's first 90 days is a large part of why beginners quit. No AI strategy document. You cannot write a useful one before you have run a single task, and the ones written beforehand are guesses dressed up as plans. No tool comparison. You are not choosing a platform in your first 90 days. You are finding out whether this fits how you actually work, and the free tiers answer that question well enough. ### **Ryan's Final Thoughts** If you take one thing from this, make it the second column. Sort your week by what you would let someone else do badly, not by what takes longest, and your first AI task picks itself. That is the whole trick. Get one visible win you can point at on a Tuesday, and the second one is easy. The tool question answers itself. If you run this and get stuck, or you want someone to look at your day-14 list and tell you which task to start with, that is what the [AI Concierge](/ai-concierge/) is. One 90-minute call a month at $999, by application, and I have talked people out of it before when a free afternoon would have done the same job. ### **How to Implement AI in Business FAQs** #### **How do I implement AI in my business if I am not technical?** Start with one language-heavy task you already do every week, like drafting customer emails or quotes, and run it through the free tier of ChatGPT or Claude alongside your normal method for a few weeks. You do not need to build anything or connect any systems. The technical work people picture, automations and integrations, comes much later and is not required to get value. The skill you are actually learning is writing clear instructions and checking output, which is not a technical skill. #### **How long does it take to implement AI in a small business?** Getting one task working reliably takes about 45 days at a realistic pace, and making it a habit takes another 30. Ninety days is enough to have one workflow genuinely running and an honest measurement of what it saved you. It is not enough to have AI running across the whole business, and plans that promise that are setting you up to abandon it. #### **Why do so many small businesses stop using AI?** Usually because of the task they picked, not the tool. Owners tend to start with whatever eats the most time, and those jobs are often the ones they are least willing to let anyone else touch. So every output gets re-done by hand, the tool stops saving anything, and it quietly goes unused. Starting with a task where a rough draft is genuinely useful avoids that, even if the time saved looks smaller on paper. #### **Do I need to pay for ChatGPT or Claude to start?** No, and you should not until you have proof it helps. The free tiers are enough to test whether one task works, which is the entire goal of the first 90 days. Buy a subscription when you have a number showing what the task saved you, not before. #### **What is the first thing a business owner should automate with AI?** The first thing should not be automated at all, it should be assisted. Pick a repetitive writing task where you can judge the output in seconds, like a customer reply or a quote description, and keep yourself in the loop reviewing every one. True automation, where something runs without you looking at it, is a later decision that should only follow a task you already trust. Some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use or would recommend regardless. See my full [disclosure](/disclosure/). --- ## Is Grok Bot Worth It? (Rate Limits & Workarounds) URL: https://ryandoser.com/is-grok-bot-worth-it/ Markdown: https://ryandoser.com/is-grok-bot-worth-it.md Published: 2026-09-07 | Updated: 2026-09-07 Categories: AI Rabbit Holes > Is Grok Bot worth it? You are buying three products with nearly the same name, and most people use one of them. The rate limits and the workaround, explained. Whether **Grok Bot** is worth it comes down to one thing nobody puts in the demo videos. It runs out of weekly usage faster than almost anyone expects, and the fix is a machine you are already paying for and probably never opened. ### **What Grok Bot Actually Is** Aaron Makelky paid full price for Grok Bot the week it launched, back when the cheapest door was $200 a month. Nobody sponsored him and nobody gave him a discount code. He came on the podcast to walk through what he actually got for it, where the limits stop him, and the part of the subscription almost nobody opens. That matters, because he came on AI Rabbit Holes with the unglamorous version of this product rather than the demo version. Entry has since fallen to $20, and his verdict barely moved. Imagine Slack, except none of your colleagues are human. You get a sidebar of AI bots, you drop them into channels, and you hand them jobs. Each bot is a non-human employee working a task or collaborating with another bot. It is single player, but it feels multiplayer. The part that earned the attention is where it runs. There is no Mac mini to buy, no VPS to rent, no config file to babysit. It runs in the cloud on xAI's own machine, with apps for macOS, Windows, Linux, iPhone, and Android. Aaron runs it across macOS, iPhone, and Linux, and turning off every device he owns does not stop it. That is the real tradeoff against driving your own machine remotely, which is how I [run ChatGPT on a Mac Mini from my phone](/chatgpt-pro-vs-claude-max/), where a sleeping Mac does stop the session. Want to build systems like this without the subscription? My [Claude Code Skills Stack](https://skills.ryandoser.com) gives you the skill files I run my own business on. *Aaron's bots run a morning stand-up with no human message in the thread. Personal details blurred.* ### **The Grok Bot Rate Limit Workaround Nobody Advertises** Your subscription includes a cloud virtual machine, and unlike other hosted agent products, you can click into it and drive it yourself. You get a browser you control and a terminal you can type into. Codex, Cursor Agent, Antigravity, and Grok CLI all run on it. *Codex running inside Grok Bot's cloud VM, browsing the live web in the window behind it.* That detail is also the rate-limit workaround. Grok Bot stays in charge and hands the actual coding job to an agent running in that terminal, which draws on that agent's usage instead. Aaron walks through the whole thing in under three minutes here. He is direct about what this is not. Grok Bot still spends its own allowance on prompting and orchestration, so the trick stretches the limit rather than removing it. Watch the ceiling too. Once a weekly allowance is gone, usage spills onto your account's on-demand spend, and there is no Grok Bot specific cap to stop it. Aaron enforces the split with standing instructions on his top-level bot. It handles the conversation between the other bots, but any actual building happens in the VM terminal. He pushed it further than most, putting the machine on his Tailscale network behind an exit node. It browses as if it were sitting in his house, moves files straight to his laptop, and prints his schedule on his home printer each morning. That is a box in a data center driving hardware in his office. Now put that against the price. On the $40 Teams tier, Grok Bot is one of three things you are paying for. Cursor's cloud agents and Grok CLI in the terminal are the other two, and Aaron rates both higher. He calls Grok CLI the best command-line tool available right now, and it has no desktop app yet, so almost nobody who bought the bundle has tried it. Most buyers use only the first of the three, hit a wall, and conclude the product is broken. ### **The Naming Problem That Costs People Money** Aaron kept circling back to the reason people feel cheated. Cursor, Grok, and Grok Bot are three different products with nearly the same name. In his experience they do not spend from one shared bucket. You can exhaust Grok Bot for two days, open the Grok app running the same underlying model, and keep working. Read the fine print before you build a budget on that. [Cursor's own documentation](https://cursor.com/help/grok-bot/plans) states that Grok Bot usage is metered on your Cursor account rather than on Grok or X, and that linking a SuperGrok or X Premium+ subscription grants usage on that same account instead of creating a second meter. So the vendor describes one meter where a heavy user describes separate ceilings. Treat the documentation as the thing that governs your bill and Aaron's experience as the thing that governs your afternoon. The lesson survives the disagreement either way. People buy this thinking they bought one product, use a third of what they paid for, and call the whole thing a scam. ### **The Price Drop Changed the Number, Not the Verdict** Those launch-day doors were a $200 Cursor Ultra plan or a $300 SuperGrok Heavy plan. [Cursor's pricing page](https://cursor.com/pricing) now lists Grok Bot access on Individual Pro at $20 a month, with bigger allowances on Pro+ at $60 and Ultra at $200. Teams Standard runs $40 per user. xAI's [August 26 announcement](https://x.ai/news/grok-bot-more-plans) is the one that opened it up, confirming Grok Bot is included with all SuperGrok, Cursor Pro, and Cursor Teams plans. Check that date against anything you read elsewhere. xAI's own FAQ page still lists a narrower set of eligible plans that starts at Cursor Pro+, so the cheapest door is easy to miss. So the sticker price fell by roughly 90%, and cheap entry makes the limits bite sooner rather than later. On the highest tier available, Aaron still hits weekly limits. His words: "I don't know anybody, even for personal stuff, that could go beyond moderate usage right now." There is also no free tier to fall back on. [Cursor's own documentation](https://cursor.com/help/grok-bot/plans) describes the trial as a usage credit with a 7-day window, not an ongoing free plan. That credit runs out on the entry tiers before you finish setting up a system worth running, which is why Aaron calls the free-access marketing "a little bit deceiving." ### **Who Grok Bot Is Actually For** Aaron sorts the agent market into a pyramid. At the top sit the roughly 0.1% who are true developers and love to hack on things, and that group runs OpenClaw. Below them, about 5%, are people comfortable in a terminal who want to control their setup, which is Hermes territory. Everyone else is the actual market. They want more than a texting agent but they are never opening a config file. Grok Bot is built for that third group, and if you are stuck deciding between chat, cowork, code, and a desktop app, this is where it does its best work. Connecting a tool means clicking a sign-in box inside the chat, not pasting an API key into a config file. Aaron connected a personal Gmail and a work Gmail that way, and each one took a click. If you are still deciding which assistant to commit to at all, my breakdown of [which Claude model to use](/which-claude-model-to-use/) covers the same decision on the Anthropic side. *Each bot gets a name, a color, a shape, and a description. Aaron's Chief of Staff is the only purple cloud.* He hates the term best practices for a tool that has existed a few weeks, so he says be intentional instead. Shape and color carry meaning in his sidebar. The Chief of Staff is the only purple cloud, project managers are triangles, and single-job specialist bots stay hidden. He messages a manager, and the manager delegates down to the worker bots. It works the way middle management works. #### **What That Looks Like on Real Work** The example he showed is one I know the manual version of, because it is this podcast. He hands a recording to his bots and asks them to lay the intro and outro music, move the ad read to a specific spot, and publish it. They pull the right track, find the right project in Descript, write the show notes and the timestamps, and push the episode to Transistor. He puts the finished work at about 95% and still listens before anything ships. The video side of the show now runs through my own Claude Code skills. I broke down [how Claude Code edits my podcast episodes](/ai-video-editing/), including what still breaks. One rule of his is worth copying. His bots may draft anything and send nothing. A draft can sit in his Gmail, but no message or post leaves his ecosystem without him. That is the right default for any agent holding your logins. ### **Where the Lock-In Hurts** Here is the part that would keep me away. You are locked inside the xAI model ecosystem with no way out. You cannot call an OpenAI model, an Anthropic model, or an open-source one. That much you might expect from a first-party product. The frustrating part is narrower. You cannot even choose between xAI's own models. You cannot see which model is running and you cannot change it. Right now it is Grok 4.6, but whether it is the fast variant and what thinking level it uses are both invisible. That breaks a habit anyone managing usage builds early. Running your heaviest model for every task burns limits fast, so you delegate the small jobs to a cheaper one. None of that is possible inside Grok Bot, which makes the rate limits worse than they need to be. The one thing that would stretch a quota is the one control the product withholds. For the non-technical majority this is a feature, not a flaw. My problem with the trade is that it is permanent, because every other agent tool I run lets me start simple and take the controls later. ### **Will Grok Bot Still Matter Next Year** Aaron says yes, with a catch that undercuts the yes. Grok Bot was the first agent product he saw handle multiple Gmail connectors cleanly, and a competitor shipped the same feature within about five days. Copying now moves faster than filming and publishing a video about the new thing. My own read is harsher, and twelve months out it would surprise me if this still matters. OpenAI launched its own always-on agent, dots, on September 29, and Aaron's first take on it is in [our post-DevDay ChatGPT Pro verdict](/is-chatgpt-pro-worth-it/). *The two highest-view results promise money and superlatives. Neither mentions rate limits.* The deeper problem is who xAI sells to. Cursor's brand was built for developers, there is no Cursor for marketers or for sales, and by Aaron's estimate the overwhelming majority of users are coders connecting to GitHub. #### **Consider Where You Are Reading the Hype** There is a reason the sentiment you see skews positive, and it has nothing to do with the product. xAI owns X, so the loudest venue for Grok Bot opinion is a channel the manufacturer controls. The same pressure exists where I publish. If I wanted a video to travel on YouTube, the cynical play would be covering Antigravity, because Google owns both the tool and the algorithm deciding who sees the video. That is an incentive worth naming, not an accusation that anyone rigged a feed. Read any verdict on Grok Bot, including this one, knowing who benefits from it. Aaron's answer to the noise is the useful one. He seeks out the people posting that they are stuck and rate-limited, because troubleshooting from real users beats a demo where everything works. ### **My Honest Verdict on Grok Bot** If you already live in Claude Code or Codex, tune this out. It will not do your work, and Aaron said so plainly. The exception is narrow. Remote sessions on Claude and Codex can be fussy, so a simple interface while you are away from your desk has some pull. If you are not technical and you manage a real digital footprint, a podcast, a site, a channel, this is the most approachable agent product available. A busy family juggling calendars fits too. For collaborative teamwork, no. Each user gets an isolated machine and cannot reach anyone else's, so Aaron's single-player description holds even on Teams plans. Aaron's closing principle is the one worth keeping regardless. Be model agnostic and be tool agnostic. He keeps his skills backed up in GitHub rather than trapped inside whichever tool he is using. Build your agent team so you can port it out when you cancel, because you will cancel something eventually. That is why I keep my own workflows in [Claude Code for marketing work](/claude-code-for-marketing/) rather than a vendor's walled garden. The tool changes. The system should survive it. You can follow Aaron at [aaronmakelky.com](https://aaronmakelky.com) or on X, where he posts practical Grok Bot troubleshooting rather than hype. ### **Grok Bot FAQs** #### **How much does Grok Bot cost?** Grok Bot access starts at $20 a month through Cursor's Individual Pro plan, with bigger allowances on Pro+ at $60 and Ultra at $200. Cursor Teams Standard is $40 per user per month, and SuperGrok plans also qualify. At launch the only doors were roughly $200 to $300 a month, so the entry price has fallen sharply since then. #### **Is Grok Bot free?** No. Grok Bot has no free tier and requires a paid Cursor plan or a linked SuperGrok or X Premium+ subscription. Cursor's documentation describes the trial as a usage credit with a 7-day window rather than an ongoing free plan, so the credit can run out before you finish setting anything up. Budget for a subscription rather than planning around free access. #### **How do you get around Grok Bot's rate limits?** Use the cloud virtual machine that comes with your subscription. Aaron's approach is to keep the conversation in Grok Bot and run the actual building through coding agents in the VM terminal, which in his testing drew on usage separate from his Grok Bot allowance. Cursor does document the ceiling: once a weekly allowance is gone, usage continues on your account's shared on-demand spend, and no Grok Bot specific cap is published. #### **What is the difference between Cursor, Grok, and Grok Bot?** They are three different products sold under nearly the same name, which is the single biggest source of buyer confusion. Cursor is the coding environment, Grok is xAI's chat assistant and model family, and Grok Bot is the agent workspace where you run a team of bots. Aaron's experience is that running out in Grok Bot does not stop you using the Grok app on the same model, while Cursor's documentation states that Grok Bot usage is metered on your Cursor account rather than on Grok or X, and that linking SuperGrok or X Premium+ does not create a second meter. Treat the documentation as the thing that governs your bill and the day-to-day behavior as the thing that governs your afternoon. #### **Is Grok Bot better than Claude Code or Codex?** Not for daily work, and not for anyone already comfortable in those tools. Grok Bot wins on simplicity and on running in the cloud without setup. Claude Code and Codex win on model choice, control, and cost per unit of work. See Who Grok Bot Is Actually For above for the full breakdown. #### **Does Grok Bot work for teams?** Only in a limited sense. Teams plans give each person their own seat, but xAI's documentation states each user's work runs in a dedicated microVM and that one user cannot reach another user's computer. Colleagues do not share a workspace or each other's bots, which is what Aaron means by single player. Combined with rate limits, that rules out most collaborative business use. --- ## How to Rank in ChatGPT in 2026 (Tested by AI Search Expert) URL: https://ryandoser.com/how-to-rank-in-chatgpt/ Markdown: https://ryandoser.com/how-to-rank-in-chatgpt.md Published: 2026-09-06 Categories: AI Resources > I asked ChatGPT to recommend a local plumber and logged every source it cited. None of them were Google Business Profiles. Here is what it actually reads. Every guide on **how to rank in ChatGPT** opens with the same instruction: optimize your Google Business Profile. I wanted to know whether that was true, so I tested it. In September 2026 I asked ChatGPT, with live web search on, to recommend the best plumber in Des Moines. It named five companies and cited fifteen sources. Not one of them was a Google Business Profile. I ran it again for HVAC companies in Omaha. Sixteen citations, same result. Zero Google Business Profiles. Both runs were live web searches, and I logged every URL the model returned rather than reading the summary it gave me. The full source lists are below so you can check them against your own. Two queries on one day is a small sample, and the mix will move if you ask next month. It is also two more than the guides ranking for this question appear to have run. Every one of them tells you to start with your Google Business Profile, and that instruction pointed at something ChatGPT did not cite either time I checked. One correction before we go further, because it changes what you are aiming at. There is no ranking to win here. Answers are generated fresh per request, so what you actually influence is how often you get named across many asks, which is a rate rather than a position. I have written separately about [why "ranking" in ChatGPT is the wrong mental model](/ai-search-myths/), and everything below is aimed at moving that rate. Working out where you stand is the kind of thing I do with owners inside the [AI Concierge](/ai-concierge/). The test at the end of this post costs nothing though, so run that before paying anyone, me included. ### **What ChatGPT Actually Cited** Here is the full source list from the Des Moines plumber query, because the specifics matter more than the summary. Six directory-style pages: Expertise.com, ThreeBestRated, TrustAnalytica, ProLp, Houzz, and ServiceAgent, the last of which runs its city directory as a front for an AI phone product it sells to those same companies. Three Reddit threads, all from r/desmoines. One PDF of CITYVIEW's "Best of Des Moines" reader poll, sitting on a Squarespace CDN. Google data reached that answer exactly once, and secondhand. ChatGPT quoted "4.8 stars from 2,708 Google reviews" for one company, but it read that figure off a directory page rather than from Google. The Omaha run repeated the shape with a different cast: ServiceAgent, ConsumerAffairs, BestProsInTown, Expertise.com, Forbes Home, and one r/Omaha thread. It also cited Orbital, which is worth pausing on. Orbital is not a consumer directory at all. It is a business-to-business sales intelligence platform that sells contact data on small business owners to vendors, and its own page says plainly that it "is not a consumer directory and is not optimised for booking appointments." A homeowner looking for an HVAC company got handed a slice of a sales prospecting database. That is a useful reminder that the model is matching pages, not vetting the purpose of the site it found them on. *What the model reached for both times I asked. The profile you were told to optimize was not among the sources it cited.* ### **Why the Google Business Profile Advice Persists** It persists because it used to be the whole game, and because it is still correct for a different question. Your Google Business Profile genuinely does drive Google's own surfaces. It feeds Maps, the local three-pack, and Google's AI Overviews. [Google's own local ranking documentation](https://support.google.com/business/answer/7091?hl=en) names three factors, relevance, distance, and prominence, and that machinery runs on profile data. Neglect your profile and you lose Google, which is still where most of your customers are. So the advice is not wrong. It is answering "how do I rank in Google's local results" and being sold as an answer to "how do I rank in ChatGPT." Those turn out to be different questions with different levers. Read Google's own definition of prominence closely and it points the same direction anyway. Google says prominence is based on "how many websites link to your business and how many reviews you have." Even inside Google's model, a large share of the signal lives on other people's websites. ### **What OpenAI Documents, and What It Does Not** OpenAI's [web search documentation](https://developers.openai.com/api/docs/guides/tools-web-search) mentions real-time third-party feeds the model can pull from, and gives three examples of how they are labelled in the response: sports, weather, and finance. There is no local business feed on that list. No Google Business Profile integration, no Maps connection, no directory partnership. An absence in documentation does not prove no such connection exists, and I want to be honest about that. But it lines up with both probes and suggests the mechanism: with no dedicated local data source, the model searches the open web and cites whatever comes back. That means directories, forums, and local press. I put the question to Perplexity with live search on as a cross-check. It drew the same line, saying there is "no verified basis here to claim it directly reads the underlying GBP backend as an exclusive source." ### **The Uncomfortable Version of This Finding** Here is the part that makes people wince, and it is the reason this work is harder than the checklists suggest. Almost none of the pages ChatGPT cited are pages you own. You do not control Expertise.com's rankings. You cannot publish to r/desmoines without a real account and real history there. You cannot vote yourself into CITYVIEW's reader poll. That inverts the usual SEO instinct. The standard move is to write another page on your own site. On this specific problem, another service page is not where the leverage is. Owned pages still do real work, they make you verifiable and they convert the visit once it happens. They were simply not what either answer was built from. The Omaha run produced the sharpest illustration of this. One of ChatGPT's cited authorities was [John Henry's own blog](https://www.jhlincoln.com/best-hvac-companies-omaha-ne/), a "Top HVAC Companies in Omaha" list published by an HVAC company that ranked itself number one on it. ChatGPT cited it as a source and passed the ranking along. That cuts both ways. A competitor's self-published listicle became evidence in an AI recommendation. There is a real opening there, with a line worth drawing. An honest comparison that names competitors and says where you lose is legitimate content and always has been. A list that exists only to crown yourself is the thing readers and models will eventually learn to discount, and it is not what I am suggesting you publish. ### **Where to Actually Spend the Effort** Rank the work by whether the target page is one ChatGPT already cites. That single filter reorders the usual checklist. Get into the aggregator directories first. Expertise.com, ThreeBestRated, ConsumerAffairs, and the vertical-specific ones for your trade were cited repeatedly across both cities. A three-week Linkifi study points the same way. Directories and "best of" lists made up 61% of all citations and were among the stickiest sources, which I break down in [how to get ChatGPT to recommend your business](/how-to-get-chatgpt-to-recommend-your-business/). Check how each one actually works before you reach for a card, because they differ more than you would expect. ThreeBestRated states flatly that it never accepts payment for listings or rankings. Expertise.com runs its provider portal free. ConsumerAffairs does sell a paid partner programme. So the work here is mostly qualifying rather than purchasing, which is slower and cannot be shortcut with budget. Read each directory's own terms before assuming a cheque moves you. Be genuinely present in your city's subreddit. Reddit was cited in both runs, and r/desmoines threads several years old still surfaced. This is the one nobody wants to hear, because you cannot buy it and you cannot rush it. An account that shows up only to promote itself gets removed by moderators, and a removed thread cites nothing. Chase local press and reader polls. The CITYVIEW citation was a PDF of a magazine's "Best of" issue. Your city has an equivalent, it has a nomination window, and almost nobody in your trade is working it. Then fix your own site, which still matters and now sits fourth. The [wider AI SEO strategy I run for clients](/ai-seo-strategy/) goes deeper on the on-page side. Clear service pages, a real location page, LocalBusiness schema, and plain answers to the questions customers actually ask. When a directory or a journalist goes to verify you, this is what they read. It is the substrate for everything above it rather than the lever itself. *Order the work by what gets cited, not by what you control.* ### **How to Test This for Your Own Business** Do not take my two queries as your answer. Run your own, because your city and trade will differ and this shifts month to month. Open ChatGPT with web search enabled and ask it the way a customer would: best [your service] in [your city]. Then ask it to list every source it used. Do the same in Perplexity and in Google's AI mode. Run it more than once, and vary the wording. Try it as "who should I call for [problem] in [city]", start each attempt in a fresh chat so the last answer does not colour the next, and note whether you were named at all before you worry about where you placed. Five runs across a couple of phrasings will tell you far more than one will, which is the same discipline I am holding myself to with two. A podcast guest's tracking dashboard showed why that matters: [the same prompt ranked his brand anywhere from #1 to #8 inside one week](/how-to-track-ai-visibility/). A bigger version of this test, with four assistants across two cities, [put 250 AI recommendations up against Google Maps](/research/does-chatgpt-recommend-local-businesses/), and the four rarely listed the same business first. Now read the citation list rather than the recommendation. Which directories appear? Which forum threads? Is there a local publication in there? Are you in any of them? Re-run it quarterly and log what you see, because the rate only means anything as a trend. Paid [AI visibility trackers](/aiclicks-review/) automate this, though run it by hand first so you know what the number is made of. That list is your starting dataset, and it is specific to you in a way no guide can be. If you would rather work through yours with someone, that is most of what I do as an [AI marketing consultant in Des Moines](/ai-marketing-consultant-des-moines/). ### **How to Rank in ChatGPT FAQs** #### **Does my Google Business Profile affect whether ChatGPT recommends me?** Indirectly at most. In two probes across two cities, ChatGPT cited zero Google Business Profiles, and OpenAI documents no local business data feed. Your profile still drives Google Maps, the local three-pack, and Google's AI Overviews, so keep it accurate. Just do not expect it to be the lever that moves ChatGPT. #### **What does ChatGPT actually read when recommending a local business?** In my testing, aggregator directories like Expertise.com, ThreeBestRated and ConsumerAffairs, city subreddit threads, local publication "best of" lists, and occasionally a competitor's own ranking blog post. Google review counts showed up only as figures quoted inside those directory pages. #### **How long does it take to show up in AI recommendations?** It depends on the surface you target rather than on any waiting period. A directory listing can appear within weeks of approval. Local press runs on annual nomination cycles. Genuine forum presence takes months because the account needs real history. Anyone quoting you a fixed timeline is guessing. #### **Can I pay to be recommended by ChatGPT?** Not directly, and be careful with anyone selling that. Some directories ChatGPT cites do sell paid partner programmes, ConsumerAffairs among them. Others refuse payment entirely: ThreeBestRated says it never accepts payment for listings or rankings. There is no payment that places you in the answer itself, so treat any vendor promising an AI ranking as selling something they do not control. #### **Is ranking in ChatGPT worth the effort for a local business?** Only if your customers are asking AI for recommendations, and you can find that out by asking them how they found you. For most local businesses Google is still the larger channel by a wide margin. The work above is worth doing because it also improves your Google prominence, since Google counts third-party links and reviews too. Treat AI visibility as a second return on the same effort, not as a replacement for local SEO. Some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use or would recommend regardless. See my full [disclosure](/disclosure/). --- ## AI Consultant for Small Business: 9 Questions to Ask First URL: https://ryandoser.com/ai-consultant-for-small-business/ Markdown: https://ryandoser.com/ai-consultant-for-small-business.md Published: 2026-09-05 Categories: AI Resources > Nine questions to vet an AI consultant, the red flags that end the call, and the three of nine my own offer fails. Hiring an **AI consultant for small business** has a structural problem nobody selling the service will mention. Almost every guide teaching you how to vet one was written by someone who wants the job. I checked, once, on one day. In September 2026 I asked Perplexity, with live web search on, how a small business owner should vet an AI consultant. It returned twenty sources. Every one of them was a consulting firm, an agency, or a marketplace selling access to consultants. The closest thing to an independent voice was a personal site writing honestly about red flags, and it ends with a booking link for the author's own practice. That is one snapshot, not a law. Ask next month and the mix will shift. But it is worth knowing that when you go looking for help choosing, the help is mostly selling. I am not outside that either. I sell an [AI Concierge](/ai-concierge/) at $999 a month, so I carry the same conflict as everyone else on that page. The difference is that I am going to hand you the questions that would disqualify me, and then tell you where they land. ### **Almost Nobody Is Actually Using AI Yet** Start here, because it reframes the entire purchase. [Goldman Sachs surveyed 1,256 small business owners](https://www.goldmansachs.com/pressroom/press-releases/2026/small-businesses-embrace-ai-but-need-training-and-support-to-fully-harness-it) in early 2026 and found 76% report currently using AI. That number gets repeated constantly in sales decks. Now the measured figure. The [SBA Office of Advocacy](https://advocacy.sba.gov/2025/09/24/ai-in-business-small-firms-closing-in/), using Census Bureau Business Trends and Outlook Survey data, found that **8.8% of small businesses actually use AI to produce goods or services**, up from 6.3% six months earlier. Those two are not measuring the same thing. One is owners saying they use AI. The other is firms using it in production, counted by the Census Bureau. The gap between them is where most AI consulting gets sold. What it means for you: you are not late, and urgency is the oldest lever in the room. ### **What an AI Consultant Actually Does for a Business Your Size** The category covers wildly different work, and the confusion is expensive. At the small end, the job is picking two or three workflows worth automating and getting them running. Lead intake. Quote drafting. Support triage. Nothing exotic. At the large end it is data infrastructure, model selection, and governance, which is real work you almost certainly do not need at eight employees. The distinction that matters is whether the person builds or only advises. An advisor leaves you a document. An implementer leaves you a running system. Both are legitimate, they are not interchangeable, and the price gap between them is not proportional to the value gap for a small operator. If you are still deciding which category you need at all, I broke the three roles apart in [AI consultant vs AI coach vs fractional CAIO](/ai-consultant-vs-ai-coach/). This post assumes you have landed on a consultant and are now trying to pick one. ### **Nine Questions That Separate Operators From Repackagers** Ask these in a first call. You are not testing technical depth. You are testing whether they have shipped anything for a business like yours. #### **1. What would you look at first in my business, and why that?** A real answer asks about your process before naming a tool. If the first substantive noun out of their mouth is a product name, you have your answer. #### **2. Show me two systems you built for a company under 50 people that are still running today.** Still running is the load-bearing part. Anyone can demo a build. Fewer can point at something that survived six months of a real team using it. #### **3. Do you implement, or only advise?** Both answers are fine. An unclear one is not. If they advise only, ask who builds it and what that costs, because that number belongs in your budget now rather than in a surprise next month. #### **4. What will I have in writing at the end of phase one?** You want a named deliverable and a date. "A roadmap" is not a deliverable. "A working lead-intake automation connected to your CRM, live, by October 15" is. #### **5. What would you tell me not to automate?** The best question on the list. Anyone who has done this work answers fast and specifically, usually about judgment calls or anywhere being wrong is expensive. Someone who cannot name a single thing has never hit the limits. #### **6. Who owns the accounts, the workflows, and the data when we are done?** The answer should be you. Work built inside a consultant's own accounts is a bargaining chip against you at renewal. Ask where it lives before, not after. #### **7. Do you earn anything if I buy the tools you recommend?** Affiliate revenue and partner commissions are common and not automatically disqualifying. Undisclosed ones are. The answer tells you whether the tool recommendation is advice or distribution. #### **8. What happens when it breaks?** Automations break. Models change, an API deprecates, a form field gets renamed. Ask what maintenance costs. No answer means you are buying something with a shelf life nobody quoted you. #### **9. Can I talk to a client who is roughly my size?** Not a logo wall. A phone call with an owner whose business is shaped like yours. Enterprise case studies say nothing about working inside your constraints. ### **The Red Flags That Should End the Call** Some answers are not weak, they are disqualifying. **A discovery phase longer than two weeks.** Past that point you are paying to educate someone about your own business. **No fixed-scope option at all.** If nobody will commit to a defined deliverable at a defined price, the engagement has no floor and no ceiling. **A branded proprietary framework.** Methodology names exist to make a process feel bigger than it is. The work is picking workflows and building them. **Vague data handling.** If customer data touches a model, you need a concrete answer on where it goes, how long it is kept, and whether it trains anything. **A team you have not met.** Meeting a senior partner in the sale and juniors in delivery is the oldest move in consulting. **Promises about transforming your entire business.** The realistic outcome of a first engagement is two or three workflows running better than they did. ### **What This Costs at Each Level** [Iternal Technologies](https://iternal.ai/ai-consulting-for-small-business) lists $100 to $300 per hour for advisory, $2,500 to $10,000 for a fixed-scope quick win, and $1,500 to $8,000 a month for a fractional retainer. It also notes tooling runs $20 to $50 per user per month on top, which most quotes leave out. [The AI Consulting Network](https://www.theaiconsultingnetwork.com/blog/ai-consulting-small-businesses-cost-how-it-works) publishes a higher ladder: $2,000 to $8,000 for a readiness assessment, $8,000 to $25,000 for strategy and roadmap, $15,000 to $50,000 for a pilot implementation. It puts most small firms in the $10,000 to $50,000 range and says positive ROI typically arrives in four to eight months. Both are honest about their own pricing. Notice the shape though. The assessment tier runs $2,000 to $8,000 and produces a document. Paying that to be told which workflows to automate, before anything is automated, is the most common way this goes wrong at small scale. Get two or three quotes, starting with a [shortlist of AI marketing consultants who post their prices](/best-ai-marketing-consultants/), before you accept any of these as the going rate. My own [breakdown of what AI consultants charge](/ai-consultant-cost/) runs higher at the hourly end because it samples independent operators rather than firms. ### **The Case for Not Hiring Anyone Yet** The strongest version of this advice: a lot of small businesses should not hire anyone this quarter. If your processes are not written down, a consultant's first act is writing them down at consulting rates. If your data is scattered across three tools nobody trusts, automation makes the mess faster rather than smaller. Run the arithmetic before the sales call. Hours a week you would save, times a loaded hourly cost, times 26. If that is not at least double the project cost, it does not clear. One caveat on where you look for that person. Several of the results you get for a city search are national firms running a page for your city, so check the address before you assume the top result is nearby. I wrote up what that looks like [on my own market's page one](/ai-marketing-consultant-des-moines/). The [SBA's own guidance](https://www.sba.gov/business-guide/manage-your-business/ai-small-business) makes the same point: start small, test cheap tools, see what adds value. One person, one workflow, one month. One distinction matters here, because "do not hire anyone" is too blunt. If that month produces nothing because you could not tell which workflow was worth the effort, that is a judgment gap, and an hour with someone who has seen fifty of these is cheap. If it produced nothing because nobody had time to sit down and do it, that is a capacity gap, and coaching will not fill it. If you are not sure which one you have, my [90-day plan for implementing AI without a technical team](/how-to-implement-ai-in-business/) is the cheapest way to find out. Buy advice for the first problem and hands for the second. ### **Now Disqualify Me With the Same Nine** Fair is fair. Here is where I fail my own list. My Concierge is $999 a month for one 90-minute call. That is coaching, not implementation. **I fail questions two, three and four.** I cannot show you two client systems still running, because what I have built is my own operation. I advise, I do not build. And what you leave with is a recording and notes, not a working automation wired into your CRM. On question seven, I earn affiliate revenue on some tools I mention, disclosed at the bottom of every post here. Where I hold up is question five. Most of what I actually do on those calls is talk people out of automating things. Which points at the real fork. If you want the work handed to you finished, hire an implementer and run all nine questions on them hard. If you would rather understand your own stack well enough to direct it, that is a different purchase with a different list, and the question to ask is whether they teach or just do. I sell the second kind, so weigh that accordingly. ### **AI Consultant for Small Business FAQs** #### **How much does an AI consultant cost for a small business?** Published rates run $100 to $300 an hour for advisory work, $2,500 to $10,000 for a fixed-scope project, and $1,500 to $8,000 a month on retainer. Those are firm rates; independent operators often start higher per hour, closer to $150 to $350. Firms quoting the higher ladder put most small businesses in the $10,000 to $50,000 range for a first implementation. Tooling is usually separate, around $20 to $50 per user per month. #### **What is the most important question to ask an AI consultant?** Ask what they would tell you not to automate. Anyone who has done the work has a specific answer involving judgment calls or high-cost exceptions. Someone who cannot name anything has never hit the limits of the tools they are selling. #### **Do small businesses actually need an AI consultant?** Most do not need one yet. Census Bureau data puts actual small business AI use at 8.8%, so there is no adoption emergency. If your processes are undocumented or your data is scattered, fix that first, because a consultant will otherwise bill you consulting rates to do it. #### **How do I tell a real AI consultant from someone repackaging ChatGPT tips?** Ask for two systems they built for a company under 50 people that are still running today. Demos prove nothing. Something a real team has used for six months without abandoning it is the only durable signal, and repackagers cannot produce one. #### **What are the biggest red flags when hiring an AI consultant?** A discovery phase longer than two weeks, no fixed-scope option, a branded proprietary framework, vague answers about where your data goes, and promises to transform your whole business. A realistic first engagement improves two or three workflows. Some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use or would recommend regardless. See my full [disclosure](/disclosure/). --- ## How Much Does an AI Consultant Cost in 2026? (My Rates Included) URL: https://ryandoser.com/ai-consultant-cost/ Markdown: https://ryandoser.com/ai-consultant-cost.md Published: 2026-09-04 Categories: AI Resources > AI consultants charge $150 to $1,000 an hour and $2,000 to $30,000 a month. Here is what each price tier actually buys, with my own rates published. Wondering **how much does an AI consultant cost** in 2026? Independent consultants run $150 to $350 an hour, fixed projects land between $5,000 and $75,000, and monthly retainers run from $2,000 up to $30,000 for an executive-level engagement. Those numbers are easy to find. What is hard to find is a straight answer about what each one actually buys you, and that is the part that decides whether you overpay. I went through the guides currently ranking for this question. A few of them do publish their own prices, which is more honest than the category gets credit for. Most quote a market-wide range whose top end is five to seven times its own floor, and leave you to book a call to find out where you land. Below is the market rate card, what each tier really gets you, and my own prices sitting in the same table as everybody else's. ### **Why a $150 to $1,000 Range Is a Useless Answer** Read a few of these guides and you will notice the same shape. A very wide range, a list of factors that influence cost, and a contact form. The range is wide because the work genuinely is different at each end. An independent consultant improving your intake process and McKinsey running an enterprise transformation are not the same job, and pretending one number covers both is how you end up with "$150 to $1,000+ per hour" as an answer. But the vagueness serves the seller too. A published price lets you disqualify them before a sales call. A range lets them find out your budget first. You are not trying to learn the industry. You are trying to work out what your problem should cost and whether the person quoting you is being reasonable. So here is the table those guides should have led with. ### **The 2026 AI Consulting Rate Card, Tier by Tier** Every market price below comes from a published rate card I opened myself, and where sources disagree I have used the more conservative band and said so underneath. The last three rows are my own rates. Sources are linked under the table. | What you are buying | 2026 market price | What it actually gets you | | Independent consultant, hourly | $150 to $350/hr | Strategy calls, audits, tool selection, light setup help | | Boutique firm, hourly | $250 to $500/hr | A small team, deeper technical work, defined deliverables | | Big 4 or MBB, hourly | $500 to $1,000+/hr | Enterprise scope, governance, a name your board knows | | Fixed project, small | $5,000 to $25,000 | One automation or readiness assessment, 4 to 6 weeks | | Fixed project, strategy and roadmap | $25,000 to $75,000 | Company-wide plan, use case mapping, no build | | Monthly retainer, advisory | $2,000 to $5,000/mo | 5 to 10 hours a month of guidance on call | | Monthly retainer, managed | $5,000 to $25,000/mo | Active development, reporting, someone owning the systems | | Fractional Chief AI Officer | $3,500 to $30,000/mo | An executive owning AI strategy across departments | | Monthly coaching (what I do) | $999/mo | One 90-minute working call where we set it up together | | My hourly rate | $500/hr | One problem, one session, a plan you execute | | My on-site day rate | From $5,000 | I come to you, your team in the room | Sources for the market rows: [Leanware](https://leanware.co/insights/how-much-does-an-ai-consultant-cost), [Alice Labs](https://alicelabs.ai/en/insights/ai-consulting-pricing-2026), [Bosio Digital](https://bosio.digital/articles/ai-consulting-cost-guide), and [Tavoko](https://www.tavoko.com/guides/ai-consulting-cost). My own rates are on my [AI consulting page](/ai-consulting/), where they have been all along. Credit where it is due: a few firms do post their own numbers rather than a market range. HeyBRB lists a [£499 assessment](https://heybrb.ai/blog/ai-consulting) and prices each service underneath it, and AI Essentials states [$10,000 to $15,000](https://aiessentials.us/blog/how-much-does-it-cost-to-hire-an-ai-consultant-for-my-small) for a typical small business project. You may not want either offer, but you can tell in ten seconds whether it fits your budget, which is the whole job of a price. ### **Hourly Only Makes Sense When You Have One Question** Hourly is the cleanest way to buy advice and the worst way to buy change. *What an hour costs at each tier, and where my own rate sits.* It works when you have a specific decision in front of you. Which tool should we standardise on. Is this vendor quote reasonable. Why did our first AI project stall. You pay for the answer, you get the answer, you go execute it. If you are still working out [whether a consultant is even the right role to hire](/ai-consultant-vs-ai-coach/), settle that before you pick a rate. Where it falls apart is implementation. At $250 an hour, every question you ask between sessions has a meter running, so you stop asking. The work slows down, then stops, and six weeks later you have a very good document and nothing running. I charge $500 an hour for this and I still tell people it is the wrong purchase when what they actually need is momentum. If your problem is that nothing is getting done, buying hours does not fix it. ### **What a Fixed-Price Project Hides** Fixed pricing feels safest because the number is knowable up front. A small automation build runs $5,000 to $25,000, and a strategy engagement runs $25,000 to $75,000. Two things are worth knowing before you sign one. The first is that a strategy engagement often produces no working software at all. You are buying a roadmap. That is a legitimate purchase for a company with the internal team to execute it, and a waste of money for an owner who was hoping to walk away with something running. The second is dependency. A good vendor hands over documentation and trains someone on your side, and plenty do. Where it goes wrong is the build that ships without either: it runs beautifully until it breaks or your business changes, and then you are back on the phone at their hourly rate. Bosio Digital, one of the firms ranking on this term, puts the hidden costs at [20 to 40 percent](https://bosio.digital/articles/ai-consulting-cost-guide) on top of the fee, and this is a chunk of where that goes. Ask one question before any fixed-price build: when this is finished, who on my side can change it? If the honest answer is nobody, budget for the support contract too, because you will be needing it. ### **The Retainer Floor Is Higher Than Most Owners Expect** This is where the sticker shock lives. Continuing help from an AI consultant realistically starts around $2,000 a month and the useful tier is closer to $5,000. *The three monthly shapes. The difference is who does the work, not just the price.* Three independent rate cards land on the same floor. Leanware puts essential advisory at $2,000 to $5,000 for 5 to 10 hours a month. Bosio publishes the identical band. Tavoko quotes $2,000 to $5,000 for small businesses, rising to $5,000 to $15,000 once you are mid-market. Alice Labs skips the advisory tier altogether and starts its managed operations at $5,000. You will occasionally see lower numbers, and they are worth understanding rather than dismissing. WellHandled advertises monthly support at [$750 to $2,500](https://wellhandled.ai/blog/how-much-does-an-ai-consultant-cost), but read what it attaches to: that is optional support after a $4,500 to $15,000 done-for-you implementation, not standalone advisory. The Expert Roster, a directory tracking what providers publish, puts the retainer span at [$199 to $5,600 a month](https://theexpertroster.com/pricing) across the 83 firms in its index that disclose pricing. That $199 is the bottom of a range, not a product you can go and buy. So the cheap end exists. It is mostly maintenance on something you already paid to have built. For an owner who wants ongoing help getting AI working in the first place, $2,000 to $5,000 a month is the real number, and that buys you 5 to 10 hours of somebody's attention. ### **Where My $999 Sits and Who It Is Wrong For** My [monthly AI coaching](/ai-concierge/) is $999, which puts it under the advisory floor on every rate card above. Be careful with that comparison though. Ninety minutes at $999 is not a bargain hourly rate, it is a higher one. What changes the math is that you also get the community, the products, and a month of context I am holding for you rather than rebuilding every call. You get one 90-minute call a month. We get on a screen share, pick whatever is costing you the most time or business, and set it up live in your own accounts. I direct, you drive. Between calls you have my community, and my three products are included. It costs less than a managed retainer because you are the one clicking. I bring the direction, the diagnosis and the live help while we build it, and you keep the hands on your own accounts. If what you actually want is to hand the problem over and check in monthly, that is the $5,000 and up managed tier in the table, and you should buy that instead of this. What you get for the lower price is that the skill stays in your business. You can change what we built when your business changes, which is the failure mode of the done-for-you build above. So here is who this is right for. You run the business, you would end up owning whatever we set up anyway, and you would rather understand it than outsource it. You have 90 minutes a month and a little time between calls. You are not looking for a department, you are looking for the person who has already worked out which tools are worth your time. If that is you, the [Concierge application](/ai-concierge/) takes a couple of minutes and there is no call to sit through first. It is also wrong for you if you cannot make the call. Ninety minutes a month plus a bit of time in between is the whole mechanism, and skipping months stalls it. ### **What Actually Moves the Price** Two engagements with the same job description can differ by 10x, and it is rarely about consultant quality. Company size matters more than owners expect. Tavoko prices the same [fractional Chief AI Officer](/fractional-chief-ai-officer/) role at $3,500 to $8,000 a month for a small business and $8,000 to $30,000 for a mid-market company. Same job title. The difference is how many people have to agree before anything ships. Then there is who is doing the work. A $1,000-an-hour firm is not ten times better than a $150-an-hour independent at improving your follow-up emails. At that price you are paying for bench depth and a name nobody gets fired for picking, which is worth real money to a company that needs it and nothing at all to one that does not. The last one is whether you want to keep the capability. Handing it over costs less of your time now and more money later. Learning it costs more attention now and leaves you less dependent afterwards. ### **How to Work Out Your Own Number** Three questions get you close, in this order. First, what is the problem actually costing you? Not the tools, your hours. If a task eats six hours a week, that is a real number to price against, and it is often larger than the fee that would fix it. Second, do you want it done or do you want to be able to do it? This is the honest fork. Done means a project or a managed retainer starting around $5,000. Able means coaching, which costs less because you supply the labour. Third, does this need to keep working after they leave? If yes, whoever you hire has to be teaching somebody on your side, and you should ask them how they plan to do that before you sign. That is one of [nine questions worth putting to a consultant before you pay anything](/ai-consultant-for-small-business/). An owner who answers those three honestly usually finds the right tier is a level below where the sales conversation was heading. ### **Take the Rate Card Into the Sales Call** Use the table as a check on whatever quote you get. If a number lands far outside these bands, ask what makes your situation different, and take a real answer seriously. If they will not give you any number until you have sat through a discovery call, that is information too. And if the tier you land on is monthly coaching rather than a retainer, my prices are on [the consulting page](/ai-consulting/) and you can [apply for a Concierge spot](/ai-concierge/) without talking to anyone first. ### **AI Consultant Cost FAQs** #### **What does an AI consultant do?** An AI consultant works out where AI can move a number in your business, then either builds it or teaches your team to. In practice that means auditing workflows, choosing tools, setting up automations, and training staff. The title covers everything from a solo advisor fixing one process to an enterprise firm running a company-wide transformation, which is why published rates run from $150 an hour to over $1,000. #### **What is the typical hourly rate for AI consultants?** Independent AI consultants typically charge $150 to $350 an hour, a band Leanware, Alice Labs and Bosio Digital all publish independently. Above that the sources diverge: Alice Labs puts boutique firms at $250 to $500 while Bosio puts them at $350 to $650, and Big 4 or MBB work runs $500 to $1,000 or more. The same hourly figure buys very different work depending on the tier it comes from, so compare the deliverable rather than the rate. #### **How much does an AI consultant cost per month?** Monthly retainers start around $2,000 for advisory work covering 5 to 10 hours a month, and run $5,000 to $25,000 for managed engagements where someone is actively building and maintaining your systems. A fractional Chief AI Officer runs $3,500 to $8,000 a month for a small business and up to $30,000 for mid-market. Monthly coaching, where you do the work with direction, costs less: mine is $999 a month. #### **Are AI consultants worth it for a small business?** It depends on whether your bottleneck is knowledge or capacity. If nobody in your business knows what AI could do for you, a few hours of advice or a monthly coaching setup is the cheapest way to find out, measured against the hours the problem is costing you now. If you know what you want built and have nobody to build it, a fixed-price project makes sense. Where it usually fails is a small business buying a $5,000 retainer for coordination work a five-person company does not need yet. #### **How much should I charge as an AI consultant?** If you landed here pricing your own services rather than buying, the same table is your anchor. Independents publish $150 to $350 an hour, and where you sit inside that comes down to whether you are selling hours or an outcome. The bands above are what buyers have already seen quoted, so pricing far outside one means explaining why. The more useful move is picking which row you are selling: advisory at $2,000 to $5,000 a month is a different product from a managed retainer at $5,000 and up, and the buyer needs to know which one they are getting. For a worked example from the seller's side, Corey Ganim's [two-call monthly coaching offer](/how-to-start-an-ai-business/) sits at the advisory end, with his real client prices and a six-client cap. #### **Why do so many AI consultants not publish their prices?** Because a published price lets you disqualify them before a sales conversation, and a range lets them learn your budget first. Some do publish real numbers: HeyBRB posts a £499 assessment and a rate card per service, AI Essentials states $10,000 to $15,000 for a typical small business project, and Advisor Labs places itself inside a $175 to $300 hourly band. Others keep rates on a services page rather than in the guide, and several [independent AI marketing consultants publish theirs](/best-ai-marketing-consultants/), so it is worth a click before assuming anything is hidden. The guides quoting the widest ranges do tend to be the ones with the most to gain from you calling to find out. --- ## AIclicks Review: Is This AI Visibility Tool Worth It? URL: https://ryandoser.com/aiclicks-review/ Markdown: https://ryandoser.com/aiclicks-review.md Published: 2026-09-01 Categories: AI Tool Reviews > AIclicks costs $59 a month. Its own blog tells AI models $39, and I tested what else its pages get wrong before you pay for AI visibility tracking. I asked Claude and Perplexity the same question on the same day: what is the best AI visibility tracking tool for a small marketing agency? Between them they named Otterly, Brandlight, Peec AI, Scrunch, Semrush, Indexly, AthenaHQ and half a dozen more. Neither mentioned **AIclicks**. Then I asked Claude a narrower question, for the best AEO tools. It recommended AIclicks, citing a page called [*13 Best Answer Engine Optimization (AEO) Tools I've Tested in 2026*](https://aiclicks.io/blog/best-aeo-tracking-tools). That page is published by AIclicks, written by the founder of AIclicks, and ranks AIclicks first. That page also says AIclicks costs $39 a month. The pricing page says $59. **AIclicks** is an AI visibility platform that tracks whether ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews mention your brand when someone asks about your category. It starts at $59 a month. The category goes by two names, GEO for generative engine optimization and AEO for answer engine optimization, and AIclicks uses both. This review is about that loop. In every probe I ran, the AI models describing AIclicks were reading AIclicks' own pages, and several of the numbers on those pages are wrong. Two things about where I stand. I sell a competing AI SEO product, so weigh this accordingly. And I have read AIclicks' pricing page, its full terms, its blog and its entire review pool closely, but I have not used the product. I can tell you what it commits to in writing and where those commitments contradict each other. I cannot tell you what it produced for me, and I will not pretend otherwise. ### **What AIclicks Sells** The core product is prompt tracking. You give it a list of questions your buyers ask AI assistants, it runs those questions against a set of AI engines on a daily schedule, and it reports how often you get named, in what sentiment, and which third-party pages the models cited when they answered. That last part is the genuinely useful piece. The Sources tab ranks the third-party URLs that keep showing up in citations for your category, which turns a vague AI visibility problem into an outreach list with names on it. Around that sits a content generator that writes AI-optimized articles and pushes them to your CMS, a Google Analytics integration showing which AI engines send real traffic, and a recommendations tab. That traffic check matters more than it sounds. Chris Panteli of Linkifi said on my podcast that some of his finance clients get far more visits from X than from ChatGPT, a point I cover in [testing the way your customers actually find you](/how-to-get-chatgpt-to-recommend-your-business/). The company is based in Vilnius, Lithuania, founded by Rokas Stankevicius, Andrius Stockunas and Matas Kibildis. Its homepage claims 1,000+ businesses and 400+ agencies. It has not disclosed any funding round. Worth noting what the demo dashboard on the homepage is actually showing. The account on screen is aiclicks.io itself, and the engine split is lopsided: 710 sessions from ChatGPT against 23 from Claude over thirty days. That is the company's own data, and it is a fair picture of how uneven AI referral traffic is right now. ### **How AIclicks Wins AI Citations, and What It Teaches Them** Start with the mechanism, because everything else in this review follows from it. Models reward whoever publishes clear, structured, confident pages about a category. AIclicks publishes a lot of them: a blog, a pricing page, case studies, and a plain-text file called llms.txt written specifically so AI models can read its plan details. In every probe that returned anything about AIclicks, those were the pages the assistants cited. When ChatGPT described AIclicks for me, it cited aiclicks.io/pricing six separate times. It reported the G2 rating as 4.9 while sourcing that number to AIclicks' own pricing page rather than to G2, and it reported the Trustpilot score as 4.5 when the live page says 4.4. Four probes on one day is a small sample and I am not claiming it measures anything precisely. It does show the loop clearly enough that you can check it yourself in about five minutes. AIclicks is explicit about the strategy in [its own case study](https://aiclicks.io/case-studies/aiclicks-story-from-zero-to-a-top-mentioned-brand-in-chatgpt-in-3-months): "We set up our G2 profile early and actively worked on building our review presence... Every new review adds a fresh signal that AI models can reference." That is smart marketing and I would not condemn it. The problem is what happens when the pages doing the teaching are out of date. The founder-written listicle prices AIclicks at "$39/month, with a full refund if you're not satisfied." The live pricing page says $59, and an archived copy from April 22, 2026 shows the same $59, so this is not a price that changed last week. The refund is real, but it is capped at seven days on a first subscription, which "if you're not satisfied" does not convey. On the listicle itself, AIclicks is ranked first out of thirteen. The byline does say "Rokas Stankevicius, Founder @ aiclicks.io," so the relationship is there for a careful reader. What is missing is a plain statement near the ranking that the author owns the tool he put at number one, and any methodology behind the word "Tested" in the title. So a page that AI models cite when describing AIclicks quotes a price the live pricing page does not list. Ask an assistant what AIclicks costs and you may be told $39. The monthly plan is $59. That is one wrong number. The next two sections are the rest of them. ### **Pricing, Verified on September 1, 2026** Four tiers on the [pricing page](https://aiclicks.io/pricing). Starter is $59 a month for 30 tracked prompts and 3 AI engines. Pro is $189 for 150 prompts and 4 engines. Business is $499 for 300 prompts and 6 engines. Enterprise is quote-only. Annual billing takes up to 29% off, according to the toggle on the pricing page. The trial is 3 days. The plan cards show a trial button on all three self-serve tiers, while the FAQ on the same page says the trial covers Starter and Pro and that Business comes with a demo instead. The engine allowance works differently than most people expect, and the pricing page is clear about it. You do not get 3 engines plus the rest later. You *choose* 3 from a list of eleven, and the other eight stay greyed out until you upgrade. So on Starter you might pick ChatGPT, Gemini and Perplexity, and you are blind to Google AI Overviews, Claude, Copilot, AI Mode, Grok, Meta, DeepSeek and Mistral. For a lot of buyers that is fine. For anyone whose customers use Google, it means the answer box with the widest reach is the one you cannot see until $189. ### **The Same Page Gives Two Different Answers** Look at the screenshot above. The Starter plan card says **Websites you can add: 1**. Scroll down the same page to Compare Plans and the Starter column says **Websites: 3**. Same page. Same plan. Same visit. One number is wrong and a buyer has no way to know which. You can check it yourself on the [live pricing page](https://aiclicks.io/pricing). The [llms.txt file](https://aiclicks.io/llms.txt) sides with the table and says 3 websites. It also says Starter includes 10 AI-optimized articles a month and Pro includes 20. The live pricing page says 5 and 15. These are not rounding differences. Buy Starter expecting three sites and ten articles and you may get one site and five. To be fair about the cause, this reads like a stale file nobody updated after a plan change rather than anyone trying to mislead. But llms.txt exists for exactly one purpose, which is telling AI models what AIclicks offers. It is currently teaching them a website count and an article count the pricing page disputes, on top of the price the blog gets wrong. ### **The Trial Terms Are a Third Disagreement** The pricing FAQ says "No credit card required to start." Section 3.1 of the [binding terms](https://aiclicks.io/terms-and-conditions), last updated August 24, 2026, says "A valid payment method is required to start a trial," and that the subscription begins automatically when the trial ends unless you cancel. Here the evidence favors AIclicks. Three reviewers who went through signup all report a genuine no-card trial, and two of them sell competing tools, which makes a flattering error less likely. The marketing is probably right and the terms clause is probably boilerplate. Worth a glance at signup anyway, since the contract reserves a right the marketing does not mention. ### **Three Days Is Not Enough Time to Evaluate This Kind of Tool** This is the practical objection, and it matters more than the contradictions. AI visibility data is noisy. The same prompt returns different sources on consecutive runs, so no single reading tells you much. An April 2026 [arXiv study](https://arxiv.org/abs/2604.07585) measured this across 4,044 consecutive-day pairs and found cited sources overlap only 34% to 42% from one day to the next. A ZeroRank dashboard a guest showed me on my podcast captures the same thing at small scale: [one prompt's answers cited anywhere from 4 to 9 sources across five runs in a week](/how-to-track-ai-visibility/). Which means a 3-day trial gives you roughly three daily readings of a number that swings hard from one day to the next. You will learn that the dashboard loads and the charts render. You will not learn where your visibility is heading. The competing reviewer at [SaaSInsight](https://www.saasinsight.io/reviews/aiclicks) put it more bluntly than I would: "Three days is not really a trial." [Scrunch](https://www.scrunchai.com/pricing) offers seven days without a card, and most tools in this category offer more. I go deeper on why day-to-day AI citation numbers cannot be trusted in my [AI search myths](/ai-search-myths/) breakdown, and the same sampling problem applies to [Searchable](/searchable-review/) and every other tracker. ### **Almost Every Review Ranking for This Tool Has a Stake in It** I went through the review pool that ranks for this tool, and this was the finding I did not expect. [Trakkr](https://trakkr.ai/reviews/aiclicks-review) rates it 4.2 and states plainly, "Trakkr is our own product; that bias is named." EchoWi discloses the same thing: "EchoWi sells AI visibility measurement, so AIclicks is a competitor." CheckThat is built by an agency that sells AI visibility tracking and offers to track AIclicks for you. That pattern is the category norm rather than a quirk of this one product, and I [counted how often these vendors put themselves in their own top three](/best-ai-visibility-tools/). AIToolRush rates it 8.9 out of 10 and discloses affiliate commissions. SaaSInsight rates it 3.5 and discloses affiliate funding. That is five of the six most visible reviews, and not one is a disinterested party. [Marketraa](https://www.marketraa.com/tools/aiclicks/) was the only one I found with no disclosed financial stake either way, and it rates AIclicks 7.8 out of 10. To be consistent, I am on that list too, which is why I would weigh my read against the others rather than instead of them. One of these deserves a specific warning. AIToolRush claims extensive hands-on testing and reports citation-accuracy figures to the percentage point. It also states AIclicks costs $49 a month with a 14-day no-card trial and up to 250 prompts on Starter. The live pricing page says $59, three days and 30 prompts. When a review gets the published pricing wrong in every particular, its hands-on claims are worth less. ### **The Ratings Are Real, and the Sample Behind Them Is Small** [G2](https://www.g2.com/products/aiclicks/reviews) shows 4.9 stars from 55 verified reviews. That is a genuinely strong score and I have no reason to doubt it. It is also a small base that moved fast, since an independent snapshot on August 7, 2026 recorded 4.8 from 30 reviews. Worth knowing what that compares to. [Profound](/profound-review/), the tool most often named as the alternative, carries a review base large enough that G2 reports it differently in different places, with counts from the low hundreds to over a thousand all in circulation. [Otterly's own review base](/otterly-ai-review/) sits closer, at 54. A rating built on 55 reviews is a different kind of number from one built on several hundred, and the larger one is far harder to move. [Trustpilot](https://www.trustpilot.com/review/aiclicks.io) is thinner still, at a 4.4 TrustScore from 10 reviews, every one of them five stars. The score sits below its own reviews' average because Trustpilot discounts small and clustered samples, and the platform notes the company "hasn't invited customers recently." I have no reason to think any of these reviews are fake. My point is narrower: 65 total ratings across two platforms is an early-stage sample, and the confident 4.9 on the homepage rests on it. ### **What AIclicks Genuinely Does Well** I have spent a lot of words on contradictions, so let me be clear about the parts that hold up. The Sources tab is the best idea in the product. Knowing which third-party pages drive citations in your category, ranked by frequency, is the difference between guessing and having a list. Most trackers show you that you are losing. This one points at where the citations come from. The engine limits are displayed unusually plainly. Greying out the engines you do not get, right on the comparison table, is more upfront than most vendors manage, even though the limit itself is restrictive. Publishing monthly response counts at all is rare. Most vendors in this category will not tell you how many times a day they check a prompt, and AIclicks publishes a number you can at least do arithmetic against. It is worth checking that number, and the reviewer at [EchoWi](https://echowi.ai/blog/aiclicks-review/) did it first. On Pro and Business the published totals match what the plan's own prompts, engines and daily schedule would produce. On Starter they do not. AIclicks advertises about 1,860 more responses a month than its own Starter limits add up to. There is a plausible innocent reading, which is that Starter runs each prompt more than once a day. If so it is the better-sampled tier, and AIclicks should say so, because right now the one tier whose numbers do not reconcile is the one most buyers start on. And the refund is real and in writing. Section 4.8 grants a full refund within seven days of your first payment, once per customer, on a first subscription only. That beats a promise on a landing page, and it is more than several competitors in this category commit to. ### **Where It Falls Short** No white-label reporting and no native multi-client workspace. For an agency that wants to hand clients a branded report, that is a real gap, and AIclicks markets hard to agencies. The Starter tier is thin in a way that matters, and every reviewer who looked closely landed in the same place on it. Integrations are gated. Google Analytics, the API and the connector that plugs AIclicks into AI assistants all sit behind Pro. The analytics connection is what turns visibility into actual traffic numbers, and on Starter you cannot have it. Security paperwork is not published. I could not find a SOC 2 report, single sign-on support, or GDPR documentation, which is the sort of thing a larger client's procurement team asks for before signing anything. ### **Who Should Buy It and Who Should Skip It** Buy it if you are a small brand or solo marketer who wants a straightforward read on whether ChatGPT and Perplexity mention you, plus a prioritized list of sources to chase, and $189 a month fits your budget. Buy it if you are an agency that reports inside your own deck and does not need white-label output. Skip it if you need client-facing branded reports, because that feature does not exist. Skip it if Google AI Overviews is your priority and $59 is your ceiling, for the reason above. Skip it if your compliance team needs a SOC 2 report. And skip trackers generally if what you want is to know which changes earn citations. A tracker tells you where you stand rather than what to change, and no tool can guarantee placement in an AI answer. Anyone promising that is selling you something. ### **My Verdict on AIclicks** AIclicks is a real product from a real company solving a problem worth solving. If I were buying in this category on a small budget, it would make my shortlist. It would not make it at $59. That tier is enough to see whether you like the dashboard, and not much more. What I keep coming back to is the pattern rather than any single error. A company selling accurate measurement of what AI says about brands is not keeping its own numbers straight, and I watched ChatGPT repeat one of them back to me as fact. I read that as carelessness rather than anything worse. It stands out because catching this exact category of mistake is what the product is sold to do. The cheapest test I know in this category takes about a minute: compare what an AI assistant says a tool costs against what its pricing page says. When those two numbers disagree, that says something about how carefully the vendor manages the exact problem it wants to sell you. ### **AIclicks Review FAQs** #### **How much does AIclicks cost per month?** AIclicks costs $59 a month for Starter (30 tracked prompts, 3 AI engines), $189 for Pro (150 prompts, 4 engines) and $499 for Business (300 prompts, 6 engines), plus a quote-only Enterprise tier. Annual billing takes up to 29% off, and the trial is 3 days. Figures read off the live pricing page on September 1, 2026. AIclicks' own blog still quotes $39, so prices you see elsewhere are often stale. #### **Is AIclicks legit?** Yes. AIclicks is a real company operating from Vilnius, Lithuania, founded by Rokas Stankevicius, Andrius Stockunas and Matas Kibildis, serving a reported 1,000 brands and 400 agencies. It holds 4.9 on G2 from 55 verified reviews and 4.4 on Trustpilot from 10. Its terms include a written seven-day refund on a first subscription. The caveats are about maturity rather than legitimacy: the review pool is small, it has disclosed no funding, and its published numbers contradict each other across surfaces. #### **How many AI engines does AIclicks track?** Eleven, but no self-serve tier gives you all of them. You choose 3 on Starter, 4 on Pro and 6 on Business from a list that includes ChatGPT, Gemini, Perplexity, Google AI Overviews, Claude, Microsoft Copilot, Google AI Mode, Grok, Meta, DeepSeek and Mistral. Unselected engines stay greyed out until you upgrade, and only Enterprise includes all of them. #### **Does AIclicks require a credit card for the free trial?** The pricing page says no credit card is required, and reviewers who went through signup confirm that. Section 3.1 of AIclicks' binding terms says the opposite, that a valid payment method is required and the subscription starts automatically when the trial ends. The marketing is probably right in practice, so just confirm at signup which one applies to you. #### **What is the best alternative to AIclicks?** The trackers AI surfaces name most often are [Profound](/profound-review/), [Otterly](/otterly-ai-review/), Peec AI and Scrunch, and Profound carries a far larger review base than either of the cheaper options. All of them read the same volatile AI answers, so compare them on how many times a day they check each prompt and how long the trial runs, rather than on dashboard features. If you need white-label client reporting, rule out AIclicks first, because it does not offer it. I cover the wider category in my [best AI SEO tools](/best-ai-seo-tools/) roundup. *How I sourced this: AIclicks prices, plan limits and terms were read off its live pricing page, its llms.txt and its full terms on September 1, 2026, with historical pricing checked against an April 22, 2026 archive. Quotes from other reviewers come from their own published pages. G2 blocks automated access, so its rating is quoted as G2's own pages state it. The four AI probes used Claude Sonnet 4.5, ChatGPT and Perplexity Sonar with live web search confirmed in each response, and four probes are a small sample reported as such. I have not used AIclicks myself, and I sell a competing AI SEO product. [Full disclosure](/disclosure/).* --- ## 7 Best AI Visibility Tools in 2026 (Priced and Ranked) URL: https://ryandoser.com/best-ai-visibility-tools/ Markdown: https://ryandoser.com/best-ai-visibility-tools.md Published: 2026-09-01 | Updated: 2026-10-09 Categories: AI Tool Reviews > Seven AI visibility tools priced off their live rate cards, plus what I found when I checked who actually writes the rankings you are reading. Before I rank a single one of the **best AI visibility tools**, you should know who wrote the other rankings you have been reading. Twenty-two roundups rank these tools on Google and inside AI assistants. I fetched all of them and checked who published each. Of the ones Perplexity cited when I asked it to rank the category, fourteen were written by companies that sell a tool in it. All fourteen put themselves in their own top three. Thirteen put themselves at number one. Not one vendor-published roundup ranked itself below third. ### **The Rankings You Are Reading Were Mostly Written by the Vendors** Search *best ai visibility tools* right now. The second organic result is a page on Profound's own website, and Google's snippet for it reads "Profound is the best all-in-one LLM visibility tool." That is the vendor's own sentence, served to you as the answer. *Google's snippet for the second result quotes Profound calling itself the best tool in the category.* Scroll down and Alhena ranks at ten with a list that opens "1. Alhena AI Visibility." Frase ranks a spot above with a list that opens with Frase. When I pulled the results on September 1, three vendors were buying ads on the query too. I talked through whether any of this category is worth paying for with an AI search expert, which is worth watching before you spend anything. I asked Perplexity the same question with live search on. It ranked Frase first and cited Frase's own page as the reason. It pulled twenty sources, eighteen of which I could open, and fourteen of those eighteen were vendors ranking themselves. That leaves four of Perplexity's eighteen written by someone with nothing to sell here. Across the wider set of twenty-two roundups I checked, seven publishers sell no tool in the category. So I threw the vendor-written ones out and counted again using only those seven: Zapier, Position Digital, Marketer Milk, Unite.AI, The Rank Masters, Business.com and Rankmax. Two take affiliate money and three are agencies selling AI search services, so none is perfectly clean, but none sells a tracker, which is the specific conflict here. Go read them yourself if you want to check my arithmetic, because that set is what the ranking below is built on and each tool's count sits next to its name in the table. The recount surprised me twice. Peec AI turns up in every single one, and Semrush climbs rather than falls, which is the reverse of what I expected from stripping out vendor pages. ### **So Why Should You Trust This List** I sell a $199 AI SEO System. That means I sell into this category, so I have left my own product out of the ranking entirely. Putting it here would be the exact move I just spent four hundred words criticizing, and no amount of disclosure would fix that. It gets no entry and no number. The second thing matters more. Of the seven tools here, I have used exactly one. Rankability gave me free access to test for my video review, and I earn a commission if you sign up through my links, both of which you should weigh. The other six I have not touched, so for them this post cannot tell you which is nicest to work in, and I am not going to pretend otherwise. What I do have is the other side of this work. AI search visibility is my [consulting practice](/ai-seo-consulting/), and this site went from zero to 12.1K AI citations in six months without a paid tracker on it. Bing Webmaster Tools recorded those citations, and Search Console's Generative AI report showed the Google side. Hold onto that fact while you read the prices below. What it can tell you is what each one costs, what the entry price actually includes, and which ones the disinterested sources name. That is the whole basis for the order below: how many of the seven independent roundups list each tool, ties broken by the cheaper honest entry point, with one exception I flag where it appears. Four of these companies have also been through a longer desk review on this site, where I read their contracts, docs and review pools. Desk reviews, not field reports. ### **Every Number in the Table Below Is a Sample** These tools do not measure your visibility. They sample it. An AI answer is generated fresh each time, so the same prompt asked twice in the same hour can name different brands in a different order. When I asked Perplexity for the best AI visibility tracking tools twice, a few minutes apart while writing an earlier post in this series, the first answer named thirteen tools and the second named ten, with only nine common to both. The same thing showed up in [my field test of AI local business recommendations](/research/does-chatgpt-recommend-local-businesses/): when 12 answers were rerun, about four in five of the businesses from the first run appeared again. So a tracker that checks your prompts a few times a day is taking a handful of draws from something that keeps moving. That is genuinely useful for [spotting a large shift over months](/how-to-track-ai-visibility/). It is close to meaningless for the week-to-week number on the dashboard, and every vendor here sells you the dashboard. Read the prices below as the cost of a sampling budget, not the cost of an answer. It is also why the engine count matters more than the price: a tool watching three engines is sampling three of the places your buyers actually ask. ### **What These Tools Cost, at a Glance** Every figure below was read off the vendor's live pricing page or its own published rate card on September 1, 2026, with monthly billing quoted wherever both options exist. Profound and Rankability were rechecked on September 30, 2026, after both changed their pricing, and Rankability again on October 9, 2026, after it moved to self-serve plans. | Tool | Independent lists naming it | Best for | Starts at | Engines at entry | | Peec AI | 7 of 7 | Marketing teams that want the one tool every independent list names | $95/mo | Pick 3 of 6 | | Profound | 6 of 7 | Enterprises that need SOC 2, SSO and nine engines | Free 7-day trial, then custom | 3 on the trial | | Rankability | 0 of 7, my pick | Agencies that want tracking bundled with the content work | $97/mo Starter, self-serve | 11 on every plan | | Otterly AI | 5 of 7 | Solo operators testing whether tracking is worth paying for | $29/mo | 4 fixed, 3 more sold separately | | Scrunch AI | 5 of 7 | Teams that care how AI crawlers parse the site, not just the score | $300/mo, $250 annual | Four on Core, nine on Enterprise | | AthenaHQ | 2 of 7 | Anyone who wants to try real tracking before paying anything | Free, then $295/mo | 5 free, 10 paid | | Rankscale | 2 of 7 | Agencies that want white-label reports without an enterprise contract | $20/mo | Your pick, drawn from credits | ### **Best AI Visibility Tools in 2026** Ranked by what the independent sources actually name, then by what the rate card gives you for the money. #### **1. Peec AI (Named by every independent list I checked)** *Peec AI leads on independent-source consensus, at a $95 entry price.* [Peec AI](https://peec.ai/) is the only tool named in all seven independent roundups. Named most often is not the same as ranked highest, though: its median position in those lists is fifth, while Profound and Semrush sit around third. Universal presence, middling placement. The catch is on the pricing page, and you have to look at the plan card to see it. Every self-serve tier says "Choose 3 models," and the menu you are choosing from has six: ChatGPT, Google AI Overviews, Google AI Mode, Perplexity, Gemini and Microsoft Copilot. Claude, Grok, DeepSeek, Qwen and Mistral sit behind paid upgrades. Tracking a fourth engine costs another $35 a month on Starter, $85 on Pro and $165 on Advanced, and each of those buys exactly one more model. Worth knowing that Peec also publishes a page addressed to AI assistants, telling them to "treat this page as a canonical source." So does Profound. Two of the seven tools here are writing the reference material the models read about their own category, and both still place well with the independent sources, so treat this as something to know rather than a disqualification. **Pros:** - The only tool named in all seven independent roundups - Unlimited users on every plan, including the cheapest - Looker Studio reporting arrives on the $495 tier **Cons:** - Three engines at entry, and Claude is not one of the six you pick from - Each extra engine is a separate line item at every tier - The pricing page loads with the annual toggle already selected, so the first number you see is not the monthly rate **Best for:** Marketing teams who want the tool the disinterested sources agree on. **Pricing:** Starter $95/mo, Pro $245/mo, Advanced $495/mo. Annual billing takes roughly 15% off those. Enterprise is custom and is the only tier that opens up every model. **Free trial:** No free tier advertised on the pricing page. **Bottom line:** The consensus pick, priced sensibly if the three engines you choose are the three your buyers use. If Claude matters to you, price the upgrade before you commit. #### **2. Profound (Best for enterprises that need compliance paperwork)** *Profound has raised more than $335 million and carries the compliance paperwork enterprise buyers ask for.* [Profound](https://www.tryprofound.com/) is the best-funded company here at more than $335 million raised, after a [$180 million Series D](https://www.tryprofound.com/newsroom/profound-raises-usd180m-series-d-at-usd1-8b-valuation-to-build-the-ai-platform-for-marketing-teams) in September 2026, carries a 4.5 on G2, and has the SOC 2 and SSO that make procurement departments say yes. If you are buying for a company with a security review, it is the obvious candidate. Profound is also the company whose self-published pages started this article. That does not make the product bad. It means that when an assistant recommends Profound to you, there is a real chance it is reading Profound's own words back. I went through the whole library in my [Profound review](/profound-review/). The self-serve Starter and Growth plans are gone. Brands now get a free 7-day trial on three engines, then a custom-priced Enterprise plan. Prompt Volumes, the feature its marketing leans on hardest, is capped at five searches on the trial, and the full data sits on Enterprise. **Pros:** - SOC 2, SSO and the compliance answers enterprise buyers need - Up to nine engines on the enterprise tier - Best funded, which matters when you are betting on a vendor surviving **Cons:** - No published paid price for brands, so past the trial you are talking to sales - Full Prompt Volumes search data is enterprise-only - Publishes its own competitor rankings, which assistants then cite back **Best for:** An enterprise team whose procurement process asks for a SOC 2 report. **Pricing:** Free 7-day trial with 50 prompts run daily across three engines, then Enterprise at a custom price. A self-serve Agency Growth plan is mentioned without a published price. **Free trial:** Yes, seven days, free. **Bottom line:** On paperwork and engine coverage it is the strongest fit for a company with a security review, bought with clear eyes about how it markets itself. #### **3. Rankability (The one tool on this list I have actually used)** *Rankability rolls mentions, citations, recommendations and sentiment into one client-ready score.* **Update, October 9, 2026:** On October 7, Rankability replaced the single $497 demo-only plan this entry described in September with three self-serve plans from $97 a month, each covering 11 AI platforms. The pricing, engine and plan details below reflect that change. My take on the tool has not changed. [Rankability](https://www.rankability.com/products/tracker/) is the exception to this list's method. The independent roundups do not name it yet. It is here because it is the only entry I have personally run, documented in my [Rankability review](/rankability-review/), and because what its plan bundles is different in kind from the trackers above. Tracking is one wing of a whole agency platform. The tracker follows mentions, citations, recommendations and sentiment, rolls them into a single visibility score, and sits beside content optimization, site audits, publishing and client portals in the same workspace. The tools above measure the problem. This one also ships what you fix it with. Engine coverage is broad, and it no longer depends on the plan. Every plan includes 11 platforms: ChatGPT, Google AI Mode, Google AI Overviews, Claude, Perplexity, Gemini, Grok, Microsoft Copilot, Brave AI, DeepSeek and Meta AI. Tracked queries run 100, 300 or 500 by plan, shared across clients. Claude is included, which Peec and Otterly both charge extra for. **Pros:** - All 11 AI platforms on every plan, including Claude - API, hosted MCP access, and unlimited clients and users - Content optimization, audits and publishing bundled with the tracking **Cons:** - The independent lists have not caught up with it yet - Pricing has changed twice since this list first ran - Tracked queries and content projects are shared across all clients, so unlimited workspaces does not mean unlimited usage - No free trial **Best for:** An agency that wants the tracking and the fixing in one subscription. **Pricing:** Starter $97/mo, Agency $297/mo, Agency Pro $497/mo. Paying yearly costs $970, $2,970 or $4,970, the same as ten monthly payments. Self-serve signup, and monthly plans need no annual commitment. **Free trial:** No. **Bottom line:** It is back to something you can test for $97 a month without a sales call, and it is still the only entry here I can vouch for from use. #### **4. Otterly AI (Best for solo operators testing the category)** *Otterly's $29 entry plan covers four AI engines, with three more sold separately.* At $29 a month [Otterly](https://www.otterly.ai/) is the cheapest tracker here that most people will actually stay on. Rankscale's $20 tier and AthenaHQ's free plan are both cheaper, and both are thinner. Five of the seven independent roundups name it, and like Peec it has never published one of its own. It has the same engine problem in a different shape. Four engines come with every plan. Claude, Gemini and Google AI Mode are add-ons at every tier, including the $489 one. Add all three to the $29 plan and you are at $76. Add them to the top self-serve plan and you are at $1,226, which is more than the $1,000 its own Enterprise tier starts at. I went through the whole structure in my [Otterly AI review](/otterly-ai-review/). **Pros:** - Cheap enough to test the category without a budget conversation - Unlimited team members on all plans - Seven-day trial with no card required **Cons:** - Fifteen prompts on the entry plan is a small sample - Three of the seven advertised engines cost extra at every tier - Its own pricing page and help centre disagree on country coverage, one says 50 and the other 65 **Best for:** One person who wants to see real data before spending real money. **Pricing:** Lite $29/mo, Standard $189/mo, Premium $489/mo, Enterprise from $1,000/mo. Annual billing takes 15% off. **Free trial:** Yes, seven days, no card. **Bottom line:** A sensible first paid step, as long as you read the engine list before you read the price. #### **5. Scrunch AI (Best for teams fixing how AI reads their site)** *Scrunch has repositioned around how AI agents read your site rather than pure score tracking.* [Scrunch](https://scrunch.com/) is the one tool here that treats monitoring as the starting point rather than the product. It audits how AI crawlers actually read your pages and what they can pull from them, which is closer to work you can act on than a share-of-voice number. The bigger context is ownership. [Sitecore acquired Scrunch in June 2026](https://www.sitecore.com/company/newsroom/press-releases/2026/06/sitecore-acquires-scrunch-to-help-brands-influence-discovery--and-buying-decisions), and a month later the company announced a repositioning around what it calls an Agent Experience Platform, writing that this is ["no longer just a part of our product, but the product itself."](https://scrunch.com/blog/agent-experience-platform/) Monitoring and citations are still there. Worth knowing you are buying into a Sitecore integration rather than an independent roadmap before you sign an annual deal. One warning on the price. Scrunch's own surfaces disagree about what the entry plan even is. The pricing page sells a Starter plan at $250 a month billed annually, $300 month to month, with 350 prompts. The company's own FAQ still describes a Core plan at $250 with 125 prompts, and one of my two pulls of the pricing page returned that older card. Whichever you see, the $250 headline is the annual rate for brands. Month to month is $300, and agencies start at $500. **Pros:** - Site diagnostics and crawler analysis, not just a visibility score - Named in five of the seven independent roundups without ever publishing one - Seven-day free trial on the entry plan **Cons:** - The most expensive month-to-month entry in this roundup at $300 - Two different rate cards are live at the same URL right now - Acquired by Sitecore in June, so the product you buy may not be the product in a year **Best for:** A team that already believes it has a problem and wants to find the cause. **Pricing:** For brands, $300 a month or $250 on annual billing. Agencies start at $500 and Enterprise is custom. Four AI engines on the entry plan, nine on Enterprise. **Free trial:** Yes, seven days. **Bottom line:** The only one here whose output is site fixes rather than a score, priced for teams that have already decided this matters. #### **6. AthenaHQ (Best for trying real tracking at no cost)** *AthenaHQ is the only tool here with a genuine free tier rather than a time-limited trial.* [AthenaHQ](https://www.athenahq.ai/) has the only real free tier in this roundup. Not a seven-day trial, an actual free plan with 300 credits, five engines and unlimited members. If you want to see what this data looks like before forming an opinion, start here. The gap between free and paid is the widest in the category. Starter is $295 a month, and API access and extra credits are add-ons billed on top of that, which the page states twice. Its metering is at least the clearest of anyone's: one credit equals one AI response. **Pros:** - The only free plan in this roundup, not a time-limited trial - The clearest metering here, one credit is one AI response - Ten models on Starter, including Grok, DeepSeek and Meta AI **Cons:** - The jump from free to $295 skips every middle price point - API access costs extra on top of the subscription - Only two of the seven independent lists name it, the joint-lowest here **Best for:** Anyone who wants to look at their own numbers before deciding whether to buy anything. **Pricing:** Essential free with 300 credits, Starter $295/mo with 3,600 credits, Enterprise custom. Annual takes 17% off. **Free trial:** A free plan rather than a trial. **Bottom line:** The independent lists barely mention it, but it is the only one that lets you look at your own numbers before deciding anything, and that is worth an afternoon. #### **7. Rankscale (Best for agencies that need white-label reporting)** *Rankscale puts white-label reports and API access on a $385 plan rather than behind a sales call.* Most tools in this category make you talk to sales before you can put your own logo on a client report. [Rankscale](https://rankscale.ai/) puts white-label options and a REST API on its $385 Growth plan, which for a small agency is the difference between billing for this work and not. It also has the cheapest way in of anything here. An Essentials tier starts at $20 a month, though you have to scroll to the plan comparison table to find it, because the three cards at the top of the page start at $99. It meters in credits rather than prompts, and the page is honest about what that means. The Pro plan includes 1,200 credits and says you can track up to 4,800 answers, then adds "depends on which engines you select." More engines, fewer prompts. It is the same trade as everyone else, just priced in a different unit. **Pros:** - White-label reports and API access without an enterprise conversation - Unlimited search terms on every tier - Seven-day Pro trial with no charge until day seven **Cons:** - Credits make the real cost harder to predict than a flat prompt count - The cheapest tier is hidden below the three headline cards - Smaller review base than the tools above it **Best for:** A small agency that needs to hand clients a branded report this quarter. **Pricing:** Essentials from $20/mo, Pro $99/mo, Growth $385/mo, Enterprise $780/mo. Yearly billing saves 15%. **Free trial:** Yes, seven days on Pro. **Bottom line:** The only rate card here that puts white-label and an API below an enterprise contract, if you can live with budgeting in credits. ### **Two Tools I Reviewed That the Consensus Does Not Name** I have published full reviews of Searchable and AIclicks, so leaving them off needs an explanation. Searchable appears in none of the seven independent roundups, and in none of the twenty-two once you add the vendor-written ones back. It starts at $125 a month, and the sampling math is the reason I would not start there anyway, which I worked through in my [Searchable review](/searchable-review/). AIclicks appears in none of the seven either. It turns up twice across the wider set: once in its own blog post ranking itself first, and once at seventeenth of eighteen inside Profound's roundup. It also quotes two different prices for itself on two of its own pages, which is the subject of my [AIclicks review](/aiclicks-review/). Neither is a scam, and neither absence says anything about whether the software measures well. It says the disinterested sources are not naming them, which is the only thing my method can see. Rankability is missing from those lists too, and I ranked it anyway. The difference is that I have run Rankability and can vouch for it directly, and I cannot say that about these two. ### **What About Semrush, Ahrefs and the Big SEO Suites?** Here is the part of my method I like least, shown rather than buried. Semrush is named in six of the seven independent roundups, which ties it for second with Profound, and its two best placements are first-place finishes from agencies with no software to sell. [Ahrefs Brand Radar](https://ahrefs.com/brand-radar) is named in four. By the count I built the ranking on, Semrush belongs in the top three. I left both out because neither is a thing you can buy on its own. They are features of an SEO suite, so the real question is whether you already pay for the suite. If you do, switch the AI visibility features on before you spend a dollar in the table above, because your marginal cost is close to zero. If you do not, the subscription costs more than every tool here and you would be buying a suite to get an add-on. That is a judgment call about purchase shape, not quality, and you are entitled to disagree with it. I cover where the suites fit in my roundup of the [best AI SEO tools](/best-ai-seo-tools/). ### **How to Choose One Without Reading Another List** These are the questions I would ask on any client build, in this order. - **Which engines do your buyers actually use?** Referral data in your analytics is a starting point, though it undercounts badly because most AI answers never produce a click. Ask a few customers where they looked. Then buy the tool that covers those engines, not the one with the highest count. - **How many prompts do you genuinely need?** Most people need fewer than they think. Fifteen well-chosen prompts beat a hundred vague ones. - **What does one extra engine cost?** Every tool here rations engines somehow. Price the configuration you will actually run, not the headline tier. - **Can you act on the output?** A score that goes down tells you nothing you can fix. Site audits and citation sources do. - **Will you still open it in month three?** This is the one that decides whether the subscription was worth it, and nobody asks it before buying. ### **Where I Would Actually Start** Before you buy anything, check the two reports you may already have. Search Console's Generative AI report shows your impressions in Google's AI Overviews and AI Mode, and Bing Webmaster Tools counts your citations across Copilot and Bing's AI answers. That is first-party data from the engines themselves rather than a vendor running prompts at them, and it costs nothing. Neither shows competitors or individual prompts, which is the gap the paid tools fill. Never looked at this data before: AthenaHQ's free plan, this week, for nothing. Want a paid tracker and your buyers live in ChatGPT and Perplexity: Otterly at $29. Running client work: Rankscale white-labels without a sales call. Procurement needs a SOC 2 report: Profound, and the decision was never really yours. Run an agency and want the measuring and the fixing on one bill: Rankability, from $97 a month with self-serve signup, which I have used myself. Buying one tool for a team and you want the safest consensus choice: Peec AI, at $95 with three engines. It is first on this list because the disinterested sources agree on it, and I would rather hand you that than my own preference about software I have not used. And if none of those sound worth $29 a month, run your ten most important prompts yourself and keep the answers in a spreadsheet. Given how much these answers move, that is a spot check and so is a cheap subscription. No vendor list will ever tell you that. ### **Best AI Visibility Tools FAQs** #### **What are AI visibility tools?** AI visibility tools track whether ChatGPT, Perplexity, Google AI Overviews and similar engines mention your brand when someone asks about your category. They run a set of prompts on a schedule, record which brands and sources each answer names, and chart your share over time. The work is also sold as GEO or AEO. #### **How much do AI visibility tools cost?** Published entry pricing runs from free to $300 a month. Otterly starts at $29, Rankscale at $20, Peec AI at $95, Scrunch at $300 monthly for brands, AthenaHQ has a free tier before its $295 plan, and Rankability starts at $97. Profound offers a free 7-day trial and quotes paid plans through sales. Watch the engine limits, because most tools include only three or four AI engines at the entry price and sell the rest separately. #### **Are AI visibility trackers accurate?** They are directionally useful and precisely unreliable. AI answers change between identical runs minutes apart, so any single number is a sample rather than a measurement. Most tools check each prompt only a few times a day, which is far below what published research suggests you need. Treat large moves as signal and small ones as noise. Linkifi measured that churn over three weeks. Two answers to the same question asked on the same day shared only 40% of their sources, as I cover in [Linkifi's AI visibility volatility study](/how-to-get-chatgpt-to-recommend-your-business/). #### **Is there a free AI visibility tool?** Start with two free reports before any free tool: Search Console's Generative AI report shows your impressions in Google's AI Overviews and AI Mode, and Bing Webmaster Tools counts your AI citations across Copilot. They cover your own site only. Among trackers, AthenaHQ has the only free plan here, with 300 credits and five engines, and Ahrefs runs a free checker for one-off lookups. #### **Do I need an AI visibility tool at all?** Only if you will act on what it tells you. If a falling score would change what you publish next month, a tracker earns its price. If it would just make you anxious, check your own prompts by hand once a month and spend the money on the content that actually gets cited. *Disclosure: Rankability gave me free access to test and pays me a commission on signups, and it is the only tool here I have used. I sell a competing AI SEO product and left it off this list. All pricing checked September 1, 2026, with Profound and Rankability rechecked September 30, 2026, and Rankability again on October 9, 2026. [Full disclosure](/disclosure/).* --- ## Otterly AI Review: What the Entry Plan Leaves Out URL: https://ryandoser.com/otterly-ai-review/ Markdown: https://ryandoser.com/otterly-ai-review.md Published: 2026-09-01 | Updated: 2026-09-30 Categories: AI Tool Reviews > Otterly AI review: what the entry plan really covers, which AI engines cost extra, and why the tool's own homepage oversells what you get. Otterly starts at $29 a month with unlimited team members and no sales call. That is the number on every roundup, and for most shoppers it is the whole first impression. What the number does not tell you is which AI engines you are buying. Otterly includes four on every plan. Claude, Gemini and Google AI Mode are rented separately, at every self-serve tier, including the $489 one. So $29 is either a bargain or an opening bid, depending on whether the engines you care about are in the four or the three. That question runs through this entire review. **Otterly.AI** is an AI visibility tracker. You give it a list of questions your buyers might ask an assistant, it runs them daily, and it reports whether you got mentioned, who got mentioned instead, and which pages got cited. It starts at $29 a month. The category answers to two names, AEO for answer engine optimization and GEO for generative engine optimization, and Otterly uses both. My conflict, stated up front. There is a competing AI SEO product with my name on it, and no affiliate arrangement here in either direction. What I did and did not do: I read the pricing page, the security page, the referral terms and the April 2026 subscription contract, and I pulled the review pool. I have not run Otterly on a client campaign. So this is a review of what the company commits to in writing, not a report on what it produced for me. ### **The Four Engines You Get, and the Three You Rent** Every plan on Otterly's [pricing page](https://otterly.ai/pricing) tracks the same four AI search engines. ChatGPT, Google AI Overviews, Perplexity and Microsoft Copilot. Claude, Gemini and Google AI Mode are add-ons. Not on the cheap plan only. On every self-serve plan, including the $489 one. To Otterly's credit, the plan cards say so. Under each price sits the line "Claude, Google AI-Mode, Gemini as extra Add-ons," and the little row of engine logos above it shows four marks, not seven. Otterly's [help centre](https://help.otterly.ai/pricing-of-otterlyai) is blunter still, describing the three as "available as paid add-ons on all plans." Someone reading either page carefully will not be surprised. The add-on prices scale with your plan, which is the part worth slowing down for. On the $29 Lite plan, Gemini is $9 a month and Claude is $29. On Premium, the same two are $149 and $439. So a solo marketer who wants all seven engines pays $76 a month rather than $29. That is a real price for a real product, and it is more than two and a half times the number on the tin. The Premium version of that math is stranger. Add all three engines to the $489 plan and you land at $1,226 a month, which is above the "starting from $1,000/month" figure Otterly prints on its own Enterprise card. At the top of the self-serve range, buying the add-ons costs more than starting an enterprise conversation. None of this is hidden and none of it is fraud. It is a packaging decision, and cheap entry pricing with paid expansion is how most software gets sold. I am flagging it because the headline number is what people quote, and on this product the headline number describes a narrower purchase than most buyers think they are making. ### **Where the Marketing Stops Matching the Rate Card** The pricing page is honest. The homepage is not, and they are the same website. Under the main headline sits this sentence: "Get your brand mentioned, and your website cited on ChatGPT, Perplexity, AI Overviews, AI Mode, Gemini, and Copilot." Six engines, no qualification, three of which no plan includes. Further down, a feature section lists all seven with Claude added. An FAQ answer says marketing teams get "citation tracking across six AI platforms." The listing Otterly supplies to G2 names all seven the same way. And the footer sitting on every page of the site, the pricing page included, reads: "For ChatGPT, Google AI Overviews, Google AI Mode, Gemini, Perplexity, Copilot, and Claude. All in one place." On the pricing page, that footer sits directly below a table charging up to $439 for Claude. The pricing FAQ then asks "Are there any hidden fees?" and answers "No, we believe in transparency. All fees are clearly outlined in our pricing plans, and there are no hidden charges." Read narrowly, that answer is defensible. The fees really are on the page, in a table, with numbers. Read the way a shopper reads it, right after being told seven engines come in one place, it is doing work it should not be doing. I want to be precise about the accusation, because it is narrower than it sounds. Nobody is overcharged against the published rates and nothing is buried in a contract. The rate card is complete and public, which is more than several competitors manage. The gap sits between two pages of one website. A buyer who reads the homepage and stops there budgets $29 and needs $76, and finds out later than they should have. ### **Outsiders Got Otterly More Right Than Otterly Did** The add-on structure is well documented, and not by me. [Geoptie](https://geoptie.com/blog/otterly-ai-review) published a piece called "Otterly AI Review 2026: Is the $29 Plan Enough?" and [SE Ranking](https://visible.seranking.com/blog/otterly-ai-review/) printed the full add-on table, both before I opened the pricing page. [AI Peekaboo](https://www.aipeekaboo.com/blog/otterly-ai-review) quotes part of the range and [That Marketing Buddy](https://thatmarketingbuddy.com/pricing/otterly-ai) flags the engines as add-ons without pricing them. Worth saying plainly, because a review that claims a scoop it does not have is its own kind of marketing. Note too that SE Ranking sells SEO software, so "independent of Otterly" is the only independence on offer here. What interests me is which of Otterly's descriptions travels. Ask an assistant what the entry plan really costs and you tend to get a careful answer. Gemini laid out the base plan, added the two engine add-ons, and volunteered that the real cost runs "more than double" the sticker. Claude covered the same ground and added the $99 charge for another hundred prompts. Both cited outside reviews rather than Otterly's marketing pages. I should be exact about what that does and does not show, because the obvious reading is too flattering to me and too hard on Otterly. Otterly publishes the accurate version itself, on the pricing page and in its [help centre](https://help.otterly.ai/pricing-of-otterlyai), which states plainly that the three engines are "available as paid add-ons on all plans." Those facts are there for anyone who opens the page. What is happening is narrower and more interesting. Otterly's marketing pages and its rate card tell different stories, and the account of the product that circulates is assembled by outsiders. On this tool, the version they assembled matches the rate card. Compare that with [Profound](/profound-review/), which has published a library of reviews and rankings covering itself and its rivals, and had an assistant hand one of those pages back to me as evidence. Profound built material designed to be quoted, and it is being quoted. Otterly published a rate card and a help centre and left the judging to other people, and it came out fine. Profound's outcome was engineered. Otterly's was not, and it still landed closer to the truth. A vendor gets a vote on how it is summarized, never the deciding one, and the size of that vote has less to do with budget than with what other people bother to write down. ### **The Answer That Went the Other Way** The correction is not reliable, and one probe showed me how it fails. I asked ChatGPT for the best affordable AI visibility tool for a solo marketer or small agency. It put Otterly first, at "$29 per month," and praised it for "transparent pricing." It listed the four base engines accurately and never mentioned that three more cost extra. Then it compared that $29 against Rankscale at "around €20 per month" tracking "over 17 AI engines, including Claude." All four probes ran on one day with live web search switched on, and I checked that search actually fired in each response. Four readings, reported as four readings. That comparison is not like for like, and nothing in the answer says so. One price covers four engines, the other reportedly covers seventeen, and they are lined up as though the only difference is the money. One more detail from that same answer, offered as a caution about the whole category rather than a knock on Otterly. Among its sources for a competing tool's pricing, ChatGPT cited a SoundCloud page for a DJ set recorded at a music festival, apparently because the artist's name resembled the product's. That is what the citation layer under these recommendations can look like on a normal day. ### **What Otterly Gets Right** I have spent a lot of words on one gap, so here is the case for the product. Unlimited team members on every plan, starting at $29. That is genuinely unusual. [Profound](/profound-review/) no longer publishes a paid self-serve price for brands at all, so past its free trial a brand team is in a sales conversation. A five-person team can share Otterly's cheapest plan. Daily tracking on every tier, no upsell. Multi-country support is listed on every plan including Lite, which matters more than it sounds, because a brand selling in three countries is looking at enterprise contracts elsewhere in this category. The pricing page puts that at 50-plus markets and the help centre says 65-plus, so take the smaller number to the meeting. The company is Austrian, and for some buyers that matters more than any feature. OtterlyAI GmbH is registered in Persenbeug, the application data sits in Amazon's Frankfurt data centre, and Otterly publishes both a data processing agreement and a list of every outside service it hands your data to. If your legal team asks where the data lives, someone can answer in specifics. Worth reading that page carefully, though. The security certifications listed there belong to Amazon's data centres rather than to Otterly, and Otterly says so plainly instead of borrowing the credit. Its own SOC 2 audit, the one buyers usually mean when they ask, is still described as on the roadmap. Monitoring data also sits in Virginia rather than Frankfurt. It is also bootstrapped, with no venture funding on record, which cuts both ways. There is no investor clock forcing a pivot, and there is no war chest either. Against a competitor that has raised $155 million, that is a genuine risk to weigh rather than a point in anyone's favor. The ratings are strong and the sample is small but real. A 4.7 from 54 reviewers on [G2](https://www.g2.com/products/otterlyai/reviews) and a 4.8 from 55 on [OMR Reviews](https://omr.com/en/reviews/product/otterly-ai). Its Trustpilot profile is empty and unclaimed, so ignore anyone citing it. The Gartner recognition is real too. Otterly was named in Gartner's [Cool Vendors in AI for Marketing](https://www.gartner.com/en/documents/7103630), published 24 October 2025, one of five vendors. Otterly's own headline flips the title to "Cool Vendors for AI in Marketing," which is sloppy rather than dishonest, and Gartner does not endorse the vendors it names. ### **What the Reviewers Complain About** The critical reviews cluster in two places, and neither is about the add-ons. The first is capacity. One G2 reviewer, writing in euros, said the jump to the Standard tier "feels like a bit of a stretch for a small agency's software budget," while "the entry-level Lite tier doesn't provide enough capacity to comfortably support a growing workload." Fifteen prompts is the constraint. That is fifteen questions you get to watch, total, and a brand with three products in two markets will burn through them immediately. The next stop is a 6.5x price increase, or $99 for another hundred prompts, which lands you near Standard anyway. The second complaint is the one I would take most seriously. A reviewer wrote that "it's not always clear what specific actions should be taken based on the findings. At this price point, I would expect more concrete guidance and strategic recommendations rather than just reporting and tracking." That is the honest ceiling on this entire product category, and it is not Otterly's fault. G2's own tags echo it, with learning curve the most frequently tagged drawback. ### **One Clause Worth Reading Before You Pay Annually** Annual billing is advertised at 15% off, which takes Lite to $25 a month and Standard to $160. Premium lands at $422, closer to 14% than 15%. The contract also has a catch that interacts badly with the add-ons. Section 5.6 of the April 2026 terms says: "The CUSTOMER is not permitted to decrease its Subscription Plan level or reduce the number of limits of their subscription during an active Subscription Term." Downgrading later needs written notice at least thirty days before the term ends, and the same section adds that "no credits or refunds will be issued for underused subscriptions." Put that beside a $300 annual Claude add-on and the risk is clear enough. Buy an engine on an annual plan, discover in month two that your buyers never ask Claude anything, and you own it for the year. My read is to start monthly, learn which engines actually matter for your category, and switch to annual once you know what you are locking in. The discount is not worth guessing for. ### **Who Should Buy It** Buy it if you are a solo marketer or small team who mainly cares about ChatGPT and Google AI Overviews, and you want a cheap way to find out where you stand. At $29 with unlimited seats and a rating built on real reviews, it is an easy first tracker to justify. Buy it if you have a team of four or more and every competitor keeps quoting you per seat. Unlimited members on a $29 plan is the strongest thing on Otterly's rate card. Buy it if you need to show a lawyer where your data lives, with the caveat below that monitoring data sits in Virginia while the application sits in Frankfurt. That is a clearer answer than most competitors give, not a blanket EU guarantee. Skip it if Claude or Gemini is where your buyers actually are, unless you price the add-on first and are comfortable with the real total. Skip it if fifteen prompts will not cover your products and markets, and $189 is not in your budget. That gap is where most people will bounce. And skip trackers altogether if what you actually want is to know which change earned you a citation. No tool in this category can tell you that reliably, because the same question returns different sources on different days. I go further into that in my [AI search myths](/ai-search-myths/) breakdown. ### **My Verdict on Otterly AI** Otterly is a good product with a pricing page I trust and a homepage I do not. If I were picking a first AI visibility tracker for a small team, it would be on my shortlist on the strength of unlimited seats, daily tracking and a $29 door. The reviews are consistent, the criticism is mild and specific, and the company answers the boring questions about data residency that most of its competitors dodge. What I keep coming back to is how cheap the fix is. Otterly built a clear rate card and then wrote top-of-funnel copy that tells a wider story, and one qualifier in five places would settle it. Add "add-ons available" beside that engine list and the objection disappears. And leaving it has a cost Otterly cannot see from the inside. Three of the four assistants I asked reached for outside reviewers and passed the add-on caveat along. The fourth reached for the advertised starting price and recommended Otterly on a comparison the reader had no way to check. Which of those two answers a buyer gets is not something Otterly controls. It wrote an accurate rate card and then wrote marketing that talks over it, and the version a shopper hears now depends on whether the source in front of them worked from the prices or from the pitch. The practical version for you is short. Before you buy anything in this category, open the rate card and count what your plan actually includes, then hold it against the headline. On this one the two disagree, and the rate card is the half worth trusting. ### **Otterly AI Review FAQs** #### **What is Otterly AI?** Otterly.AI is an AI visibility tracker built by OtterlyAI GmbH in Persenbeug, Austria. You give it prompts your buyers might type into an AI assistant, it runs them daily, and it reports whether your brand is mentioned, how you compare against competitors, and which links get cited. Every plan covers ChatGPT, Google AI Overviews, Perplexity and Microsoft Copilot, with Claude, Gemini and Google AI Mode sold as paid add-ons. Pricing starts at $29 a month. #### **How much does Otterly AI cost per month?** Lite is $29 a month for 15 tracked prompts, Standard is $189 for 100, and Premium is $489 for 400. Enterprise is quote-only, starting from $1,000 a month. Annual billing is advertised at 15% off, bringing the three self-serve tiers to $25, $160 and $422. Claude, Gemini and Google AI Mode cost extra on every tier, which takes the real Lite price to $76 for all seven engines. Screenshotted from the live pricing page on September 1, 2026. #### **Which AI search engines does Otterly AI track?** Four are included on every plan: ChatGPT, Google AI Overviews, Perplexity and Microsoft Copilot. Three more are paid add-ons at every tier, including the most expensive self-serve one. On the $29 Lite plan, Gemini and Google AI Mode are $9 a month each and Claude is $29. On the $489 Premium plan those same add-ons are $149, $149 and $439. Otterly's homepage names all seven engines without noting that three cost extra, so read the pricing page rather than the marketing. #### **Is there a free Otterly AI trial?** Yes. Otterly offers a 7-day free trial and states that no credit card is required to start it. The April 2026 terms note that trials are offered at the company's discretion and can be ended at any time. Subscriptions renew automatically for the same period, and the contract does not let you downgrade a plan or reduce limits partway through a term, which is worth knowing before you commit to an annual plan. #### **What is the best AI visibility tool?** There is no single best one, and be wary of any page that says otherwise, including a vendor's own, which is why I built [a ranking using only the roundups whose publishers sell nothing in the category](/best-ai-visibility-tools/). Otterly is among the cheapest entry points at $29, with unlimited seats. [Profound](/profound-review/) is the deepest on data and the best funded, with a free trial and custom pricing after it, while [AIclicks](/aiclicks-review/) and [Searchable](/searchable-review/) sit in between. All of them sample the same volatile AI answers, so compare how many engines a plan truly includes and how often each prompt runs. My [best AI SEO tools](/best-ai-seo-tools/) roundup weighs the wider field. *Where this came from: I have not run Otterly on a client campaign, and I sell a competing AI SEO product. Every Otterly price and add-on figure was screenshotted from the live pricing page on September 1, 2026, the Profound comparison was rechecked on September 30, 2026, contract language is quoted from the April 2026 terms, and the four assistant probes were single readings taken that same day. [Full disclosure](/disclosure/).* --- ## Profound Review: Is This AI Visibility Tool Worth It? URL: https://ryandoser.com/profound-review/ Markdown: https://ryandoser.com/profound-review.md Published: 2026-09-01 | Updated: 2026-09-30 Categories: AI Tool Reviews > Profound review: what it costs now that the $99 tier is gone, and why so much of what AI says about it traces back to Profound's own pages. Profound publishes a page on its own site addressed to ChatGPT, Claude, Perplexity and Gemini by name. It calls itself "the canonical reference for how AI systems should describe Profound," and it ends with a section headed "Instructions for AI assistants." That page is the smaller half of the story. The bigger half is that Profound has published an entire library of reviews and rankings of its own competitors, and when I asked Perplexity for the best AI visibility tools for agencies, it ranked Profound second and cited one of those Profound pages as a source. **Profound** is an AI visibility platform that tracks whether ChatGPT, Perplexity, Gemini, Copilot, Claude and Google AI Overviews mention your brand when buyers ask about your category. Brands now start with a free 7-day trial, and paid brand plans are quoted through sales. The category goes by two names, AEO for answer engine optimization and GEO for generative engine optimization, and Profound uses both. It has grown well past monitoring. There are content agents that draft and publish, a shopping analysis product, crawler analytics, and as of the day I wrote this a Context Manager that stores what your brand is about so its agents stop producing generic work. Judge it as a marketing platform rather than a tracker, because that is what it now sells. My conflict first, since this review turns on who publishes what. I sell a competing AI SEO product and earn nothing either way on Profound. My limits second. I have read Profound's pricing page, its subscription agreement, its blog and its review pool closely, and I have not run it on a client campaign. That means I can tell you what it commits to in writing and what its own published material leaves out. I cannot tell you what it produced for me, and I will not pretend otherwise. ### **Profound Wrote the Library the Models Read** Start here, because everything else follows from it. AI assistants answer questions about tools by reading pages about those tools. Profound has quietly built a large body of pages about its own category, including pages that judge its rivals. I pulled its sitemap and counted. Profound publishes ten reviews of competing products, fourteen "Profound vs" comparison pages, and four roundups of the best tools in its category. That is twenty-eight pages judging the competition, all written by the competition. The reviews are titled the way an independent review would be. "AthenaHQ Review: Does it offer competitive AI visibility?" One is headlined [Writesonic Review: What its AI visibility suite gets wrong](https://www.tryprofound.com/blog/writesonic-review-what-its-ai-visibility-suite-gets-wrong). Another is [AthenaHQ Review: Not the best for enterprises](https://www.tryprofound.com/blog/athenahq-review-not-the-best-for-enterprises). They open in the first person. The AthenaHQ piece begins "I tested AthenaHQ to see if the platform's prompt tracking, citation monitoring, and actionable recommendations live up to the marketing claims." Every one of them ends at the same destination. The AthenaHQ review closes with a section called "When to choose an AthenaHQ alternative like Profound." The Peec review closes with "When to consider a Peec alternative like Profound." None of this is hidden, exactly. The byline reads "Nick Lafferty, Founding Marketing Engineer," and the pages sit on tryprofound.com. A careful reader will work it out. Sitting alongside that library is the page I opened with, the one telling assistants how to describe the company. It runs past 1,600 words on funding, customers, products and ideal buyers, and the only dollar figures in it are the amounts Profound has raised. The material aimed squarely at models skips what the product costs. What is missing is a plain line near the verdict saying the company publishing this review sells the product it recommends instead. ### **The Detail That Makes This Worth Writing About** On its own I would file all of that under ordinary competitive marketing. Every vendor talks its own book. What turned it into the subject of this review is the standard Profound applies to everyone else. In its [roundup of eighteen AI visibility tools for agencies](https://www.tryprofound.com/blog/best-ai-visibility-tools-for-marketing-agencies), Profound ranks itself first. The weakness it lists for AthenaHQ is that "prompt volume relies on an undisclosed model." For Writesonic, it is that "data methodology and validation aren't clearly disclosed." Profound is marking competitors down for failing to disclose their methods, on a page that never plainly states next to its own number one ranking that the publisher is the product being ranked. Its own entry names one weakness: Profound is "overkill for teams that only want a lightweight visibility score." That is the shape of a strength wearing a weakness costume, sitting on a page where real defects are named for everyone else. Read the pages as marketing and they are good marketing, with real criticism in them rather than a smear and a pivot. Read them as reviews, which is how they are titled and how a search result presents them, and the question of who grades whom on what becomes harder to wave away. There is a neat illustration of where this leads. Profound's roundup places [AIclicks](/aiclicks-review/) seventeenth out of eighteen. AIclicks publishes its own roundup of thirteen tools, written by its founder, which places AIclicks first and leaves Profound off the list entirely. Two vendors, two pages that read as editorial, two self-flattering answers. A reader who checks the domain can see what is going on. The problem is what happens when an assistant lifts the ranking out of the page and hands you the conclusion without the letterhead. ### **Does the Library Actually Get Read?** This is the part I could test rather than assert. I ran three probes on one day with live web search switched on, confirmed it came back on in each response, and that is a small sample I am reporting as a small sample. I asked Perplexity to rank the best AI visibility tools for marketing agencies in 2026. It placed Profound second and listed Profound's own eighteen-tool roundup among its sources. I cannot tell you the page caused the ranking, and I am not going to claim it did. What I can tell you is that a page Profound wrote about who the best tools are turned up as evidence in an answer about who the best tools are. Then I asked ChatGPT what Profound costs. It answered $99 for Starter and $399 for Growth, and cited Profound's pricing page. Both numbers were right at the time. It got the billing period wrong, describing both as billed annually when they were the monthly rates, but the prices themselves matched the page. Then I asked a question Profound has not written a page for. I asked how Peec AI and Scrunch compare to Profound. ChatGPT told me Profound "starts at $499 per month for the Standard Plan." There is no $499 tier and no plan called Standard. It had pulled that from a third-party comparison site rather than from Profound, and the real entry price then was $99. The contrast is the useful part. The answer that leaned on Profound's own pricing page got the prices right. The answer that leaned on a third-party comparison invented a tier. You can repeat the whole thing yourself in about five minutes. ### **What $99 Bought, and What Replaced It** **Update:** Profound has since taken Starter and Growth off its [pricing page](https://www.tryprofound.com/pricing). Brands now see two options: a free 7-day trial that runs 50 prompts daily across ChatGPT, Gemini and Google AI Overviews, and a custom-priced Enterprise plan that tracks up to nine answer engines. The page also mentions a self-serve Agency Growth plan without publishing its price. The breakdown below is the rate card as it stood on September 1, 2026, kept because it is still what most reviews quote. On September 1, 2026, the pricing page listed three plans. Starter was $99 a month. It tracked ChatGPT and nothing else, covered 50 prompts, analyzed 1,500 responses a month, and included one seat. Growth was $399 a month for three answer engines, 100 prompts, 9,000 responses and three seats. Enterprise was quote-only and went up to nine engines with SSO and SOC 2. The yearly toggle gave two months free, which brought Starter to $82.50 a month and Growth to $332.50. Prompts ran daily on every tier. The seat count was the line most buyers hit first, and it was easy to miss. Starter gave you one seat. Growth gave you three. Profound's own pricing FAQ said that if you had more than three people on your team, you belonged on a custom enterprise plan. So there was no published self-serve plan that fit a four-person marketing team. Now there is no published paid plan for brands at all, and every brand past the trial is in a sales conversation. One oddity worth flagging because it affects what you will read elsewhere. On September 1 the pricing FAQ still asked "Should I use Lite or Enterprise?" while no plan called Lite appeared anywhere on the page. A reviewer at [Analyze AI](https://www.tryanalyze.ai/blog/profound-ai-review) says Profound used to publish a Lite plan at $99. That reads like a renamed tier and a stale FAQ rather than anything worse, but it is the sort of leftover that keeps wrong numbers circulating. One practical warning, because the prices in circulation do not agree. [Rankability](https://www.rankability.com/blog/profound-ai-review/) and [Generate More](https://generatemore.ai/blog/my-profound-ai-search-visibility-review-for-saas-/-tech) both matched the September rate card at $99 and $399. [Analyze AI](https://www.tryanalyze.ai/blog/profound-ai-review) says in one place that pricing runs "from $399 to custom enterprise only" and lists $99, $399 and custom in another. And one number gets repeated wrongly: Rankability's $337 is the average across the thirty-plus tools it studied, not what Profound charges. Open the pricing page and read the current plan cards before you trust any figure in a review, mine included. ### **What Profound Is Genuinely Better At** I have spent a lot of words on the publishing operation, so let me be clear about what holds up. This is a serious product, and on data it is the deepest offering I found in the category. Prompt Volumes is the real differentiator. Most trackers ask you to guess which questions your buyers ask an assistant, then monitor your guesses. Profound sells you the questions, drawn from what it describes as a panel of consented real conversations, with intent and demographic breakdowns underneath. Worth noting the size of that panel is described inconsistently on Profound's own pages, as hundreds of millions of conversations in one place and more than 1.9 billion prompts in another. Those may count different things. I would ask which is which before signing. In the screenshot above, typing a single word returns matching queries with volumes attached. That is a keyword tool for AI conversations, and I have not found another tool in this category offering the same thing at the same scale. Read the comparison table carefully before you get excited about it, though. On the September rate card, Prompt Volumes searches were listed as None on Starter and None on Growth, and custom on Enterprise, with Growth getting a narrower "relevant keywords" view. The feature I just called the best reason to choose Profound was not something either self-serve plan actually included. Agent Analytics is the second piece. It reads your server logs to show which AI crawlers visit your pages and how often, which is the one number in this whole category that is counted rather than sampled. A crawler either hit your server or it did not. A prompt result is a sample of something that changes daily. The company is well capitalized, which matters mainly because this category is full of tools that may not outlive their seed round. Profound has raised more than $335 million across five rounds, most recently a [$180 million Series D](https://www.tryprofound.com/newsroom/profound-raises-usd180m-series-d-at-usd1-8b-valuation-to-build-the-ai-platform-for-marketing-teams) co-led by Sequoia Capital and Kleiner Perkins in September 2026 at a $1.8 billion valuation. It publishes SOC 2 Type II compliance and carries a 4.5 on G2. Funding buys runway rather than product quality, so weigh it as staying power and nothing more. And Profound tracked daily on every tier, including the $99 one, which several competitors reserve for higher plans. The free trial runs daily too. Be careful with the review counts quoted for it, though. G2 reports numbers at more than one level, so figures between roughly three hundred and eleven hundred all circulate as if they measured the same thing. The 4.5 rating is consistent wherever you look. The number of reviewers behind it is not, so treat any specific count you see as unreliable. ### **The Limits You Should Price In** The entry point is now a trial, not a plan. It covers ChatGPT, Gemini and Google AI Overviews for seven days, and anything ongoing goes through a sales quote. The trial is single language and single region, so anyone selling in two countries is on the enterprise path from day one. And the honest structural limit, which applies to Profound and every competitor equally. A tracker tells you where you stand. Pinning down which change earned a citation is far harder, because the same prompt returns different sources on different days, so you need repeated readings over time rather than a number you can point at. I go deeper on that in my [AI search myths](/ai-search-myths/) breakdown. That volatility is measured, not a hunch. An April 2026 [arXiv preprint](https://arxiv.org/abs/2604.07585) on measuring AI search visibility found results vary enough across runs and days that a single reading tells you very little, which is why I treat every number in this category as a distribution rather than a fact. A guest on my podcast showed it on his own dashboard, where [a single prompt's rank swung between #1 and #8 across five days](/how-to-track-ai-visibility/). ### **Who This Is Actually For** Buy it if you are an enterprise brand or a large agency, you need prompt demand data nobody else sells, and a quote-only contract is normal for how you purchase software. Buy it if crawler-level analytics matter to you, because that is the most defensible thing in the product. Treat the free trial as a look around rather than a full program. Seven days on three engines will tell you whether you like the tool more than it will tell you where you stand across AI search. Skip it if you are a solo marketer or a small agency on a budget. Cheaper trackers cover more engines for less, and the features that make Profound worth its price sit on the enterprise plan. Skip it if you want a published self-serve price, because brands now go through sales for anything past the trial. And skip trackers generally if what you actually want is to know which changes earn citations. No tool can guarantee placement in an AI answer, and anyone promising that is selling you something. ### **My Verdict on Profound** On paper Profound is the strongest product in this category and the one I would expect to still be here in three years. If I were buying AI visibility monitoring for an enterprise brand, it would be on the shortlist and probably at the top of it. I have not run it, so read that as a judgment about what it commits to, not about what it delivered for me. What I keep turning over has nothing to do with the software. The best-funded company in AI visibility has concluded that the way to win AI visibility is to publish the reference library yourself, then point the models at it. Marketing your own product is not the problem, and I would not call this cheating. Every vendor talks its own book, and Profound does it better than anyone else in the category. The part I would push back on is narrower and it is fixable in one line. These pages are titled as reviews, structured as reviews, and rank in search as reviews, while marking competitors down for methodology they do not disclose. A sentence next to the verdict saying who published the page and what they sell would cost Profound nothing and settle the whole objection. Until that sentence exists, the confident answer you get when you ask an assistant which AI visibility tool to buy may be resting, in part, on pages the winner wrote about itself. So the cheapest test I know takes about two minutes. Ask an assistant to recommend a tool in any category, then look at what it cited. If most of the sources were published by the tool that won, the recommendation may still be right. You just have not had it confirmed by anyone else yet. Expect directories and roundups in that list. In Linkifi's three-week study, 12 of the 18 sources ChatGPT cited almost every day were directories or "best of" lists, as I cover in [the sources ChatGPT keeps coming back to](/how-to-get-chatgpt-to-recommend-your-business/). ### **Profound Review FAQs** #### **How much does Profound AI cost per month?** Profound no longer publishes a paid price for brands. You can start with a free 7-day trial that runs 50 prompts daily across ChatGPT, Gemini and Google AI Overviews, and ongoing tracking is a custom-priced Enterprise plan covering up to nine engines with SSO and SOC 2. The $99 Starter and $399 Growth plans that were on the pricing page on September 1, 2026 are gone, and a self-serve Agency Growth plan is mentioned without a published price. #### **Is Profound AI legit?** Yes. Profound is the trading name of Cooper Square Technologies, founded in New York in August 2024 by James Cadwallader and Dylan Babbs. It has raised more than $335 million across five rounds, most recently a $180 million Series D at a $1.8 billion valuation, holds a 4.5 rating on G2, and publishes SOC 2 Type II compliance. My reservations are about how it markets itself, not whether the company or the product is real. #### **What is Profound AI?** Profound is an answer engine optimization platform that monitors how AI assistants describe your brand. It tracks whether ChatGPT, Perplexity, Gemini, Copilot, Claude and Google AI Overviews mention you when buyers ask about your category, shows which sources those answers cite, sells demand data on what people actually ask assistants, and reads your server logs to show which AI crawlers visit your site. #### **How much has Profound raised?** More than $335 million across five rounds, according to Profound's own published company information and its September 2026 announcement. A seed round from Khosla Ventures, a $20 million Series A led by Kleiner Perkins in June 2025, a $35 million Series B led by Sequoia in August 2025, a $96 million Series C led by Lightspeed in February 2026 that valued the company at $1 billion, and a $180 million Series D co-led by Sequoia and Kleiner Perkins in September 2026 at a $1.8 billion valuation. Note that some third-party reviews attribute the Series B to the wrong investor. #### **What is the best alternative to Profound?** That depends on which limit pushed you away. If price is the blocker, [Otterly at $29 a month](/otterly-ai-review/) covers four engines at a published price, though three more are paid add-ons there, and [AIclicks](/aiclicks-review/) is another cheap entry point. If going through sales is the blocker, look at tools with published self-serve plans. If you want the prompt demand data, it sits on Enterprise, so you are comparing enterprise contracts. I cover the category in my [best AI SEO tools](/best-ai-seo-tools/) roundup. *How I sourced this: I have not run Profound on a client campaign, and I sell a competing AI SEO product. Prices and plan limits were read off the live pricing page on September 1, 2026, and the plan change was read off it on September 30, 2026. The AI probes are three readings on one day, not a measurement. [Full disclosure](/disclosure/).* --- ## Searchable Review: Is This GEO Tool Worth the Cost? URL: https://ryandoser.com/searchable-review/ Markdown: https://ryandoser.com/searchable-review.md Published: 2026-09-01 Categories: AI Tool Reviews > Searchable starts at $125 a month for GEO tracking. Its own numbers work out to 3 AI answers per prompt per day, and the research says what that buys. I asked Perplexity to name the best AI visibility tracking tools twice, three minutes apart, same model, same wording. The first answer named 13 tools. The second named 10. Only 9 appeared in both, and **Searchable** was in neither. Treat that as a demonstration rather than a gotcha. It is the measurement problem the entire category sells into, surfacing in the four minutes it took to run it. **Searchable** is an AI visibility platform that tracks whether ChatGPT, Perplexity, Google AI Overviews and other AI engines name your brand when someone asks about your category. It starts at $125 a month. The work goes by two labels, GEO for generative engine optimization and AEO for answer engine optimization, and this post uses AEO because that is what Searchable calls it. It is a real, well-funded product that does several things well. This review is about what its own published numbers say it can and cannot see, which is the part no other review on page one has worked out. Two things about my position, up front. I sell a competing AI SEO product, so weigh what follows accordingly. And I have read Searchable's pricing page, its terms, its documentation surfaces and its review pool closely, but this is a desk investigation rather than an extended hands-on test. I can tell you what it commits to in writing and what its numbers imply. What it produced for me is something I cannot tell you, and I am not going to pretend otherwise. ### **What Searchable Sells** Searchable is an AEO platform. AEO means answer engine optimization, which is the practice of trying to get your brand named inside AI-generated answers rather than in a list of blue links. If you have ever wondered whether ChatGPT recommends you when someone asks for a tool like yours, that is the question this category exists to answer. The product has three parts. It monitors where your brand shows up across AI engines, it analyzes why, and it generates content aimed at getting cited. The monitoring is the real product. You give it a list of prompts your buyers might type, it runs those prompts against AI engines on a schedule, and it reports whether you were mentioned, where you placed, which competitors appeared alongside you, and which sources got cited. The company is young and well capitalized. Searchable operates out of New York and London, launched in late 2025, and [announced a $14 million raise led by Headline at an $85 million valuation](https://www.prnewswire.com/news-releases/searchable-secures-14m-from-headline-at-85m-valuation-as-ai-reshapes-how-customers-are-searching-and-buying-302774547.html) in May 2026, reporting $2 million in revenue in four and a half months and close to 1,000 customers. That growth is real and it is fast. It also means the product has existed for less than a year, which matters here because a measurement tool has had little time to build a track record you can check. ### **The Pricing, and Why Three Sources Disagree** I read Searchable's pricing from three of its own surfaces on September 1, 2026. They do not tell the same story, so here is what each one says. The live pricing page renders three plan cards with a monthly and yearly toggle: | Plan | Monthly | Tracked prompts | AI answers analyzed/mo | Site audits/mo | | Pro | $125 | 100 | 9,000 | 200 | | Scale | $400 | 500 | 45,000 | 1,000 | | Enterprise | $999 | 1,250 | 112,500 | 3,000 | There is a fourth Custom tier sold through sales, and the page offers 20% off for annual billing, which puts Pro at $100 a month and Scale at $320. Both self-serve tiers show a 14-day free trial. *Searchable's plan cards, captured September 1, 2026. Pro and Scale are self-serve; Enterprise routes to sales. Note the project limits in each column, because they do not match what the company tells AI models.* Look at the project counts in that screenshot. Pro includes **1 project** and Scale includes **10**. Searchable's machine-readable pricing file states "Unlimited projects" for both, and the structured data embedded in the pricing page itself says "all paid tiers include unlimited projects." So the same page disagrees with itself, and both machine-readable versions are the generous one. That matters more than a naming mismatch. A project is a brand or site you track, so a marketer who reads the agent-facing file and expects to cover several clients on the $125 plan is in for a surprise at signup. Now the disagreements. Searchable's machine-readable pricing file and its `llms.txt`, the files written specifically so AI models can read them accurately, list only two plans. They show Professional at $125 and Scale at $400, and state that pricing "starts at $125/month." Neither mentions the $999 Enterprise tier that the live page renders. Neither mentions the annual discount. The plan names do not match either. The markdown file calls the entry plan "Professional." The rendered page calls it "Pro." The two surfaces also disagree about which plan is most popular, with the live page badging Scale while the markdown file badges the entry tier. To be fair, this reads like a fast-moving startup mid-revision rather than a company hiding its rates, and every number above is published somewhere on its own site. But the irony lands in Searchable's own product category: the files it maintains so AI models describe it correctly are the files that are out of date. When I asked Perplexity what Searchable costs, it returned a tidy table with a $50 Starter tier, a $999 Enterprise tier, and a claim that Pro "could reach about $575/month with all available engines enabled." Sorting out which were true took longer than it should have. The $999 is real, and it is the tier Searchable's own machine-readable files omit. The $50 Starter was a genuine plan in early 2026 that has since been retired. The $575 is the one with no basis I could find on any Searchable surface, live or archived. So the models are doing something subtler than inventing prices. They are blending a vendor whose surfaces disagree, retired tiers nobody marked as retired, and an unsourced figure, then presenting the result in a confident table. ### **The Number That Actually Decides This Purchase** Searchable publishes both a prompt count and an answer count for every tier. Pro tracks 100 prompts and analyzes 9,000 AI answers a month. The page also says prompts run daily. Divide it. 9,000 answers, across 100 prompts, over a 30-day month, works out to 3 AI answers per prompt per day. The same ratio holds on all three tiers: Scale is 45,000 over 500 prompts, Enterprise is 112,500 over 1,250. Three answers per prompt per day, every time. So the question becomes how those 3 answers are spread across engines. Searchable's compare table lists 9 available engines with "select in onboarding," and the plan card reads "100 tracked prompts / model," while the SEO copy on the same page describes Pro as covering ChatGPT, Google AI Overviews and Perplexity. Track those three engines, which is what the pricing copy describes for Pro, and the budget works out to one answer per prompt per engine per day. Be careful about what that division does and does not establish. Searchable does not publish a definition of an "AI answer analyzed," so I am reading it as a collected response rather than some internal processing unit. Nor is there any indication that dropping engines buys you repeat runs on the ones you keep. What the arithmetic does establish is an average. The published allowance works out to about 3 answers per listed prompt per day, and if those are split evenly across the three engines its Pro copy names, that is roughly one per engine per day. The page does not confirm how answers are actually allocated, so treat this as the scale of the sampling rather than a spec. Hold that ceiling in mind, because there is now published research on precisely how many runs it takes to measure this reliably. ### **What the Research Says a Single Daily Run Is Worth** In April 2026, Julius Schulte, Malte Bleeker and Philipp Kaufmann published ["Don't Measure Once: Measuring Visibility in AI Search (GEO)"](https://arxiv.org/abs/2604.07585). They ran four campaigns across four AI engines over a 45 to 46 day window, plus a second dataset of prompts submitted simultaneously to separate model randomness from real change. Two caveats, since I am holding everyone else in this post to a conflict standard. It is a preprint, not a settled industry standard, and the lead author is affiliated with a company in this space, Aurora Intelligence, disclosed in the paper. Its data and code are published, which is more than any vendor dashboard offers. Their findings are blunt. Cited sources overlapped only 34% to 42% between consecutive days, so roughly 65% changed from one day to the next. Much of that variation persisted in repeated runs inside a 24-hour window, which points at the models themselves rather than at the news cycle. Then they calculated the thing the dashboards do not report: how many runs per prompt per day you need before the number means anything. | Runs per prompt per day | Average error bars at that sample size (95% confidence) | | 1 | ±0.724 | | 3 | ±0.369 | | 7 | ±0.158 | | 8 | ±0.121 | Their conclusion, quoted exactly: "Practitioners should therefore use at least 7 runs per prompt per day for brand visibility monitoring, and at least 8 runs when source-level coverage matters." Read the first row again. At one run per day the error bars are ±0.724 on a rate that can only range from 0 to 1, so a reading of 30% visibility could sit almost anywhere. Those are the study's average figures at each sample size, not a fixed bar stamped on any one score. Searchable's three-engine configuration lands you around that top row. So on any given day, a per-prompt visibility reading here is not a number I would act on, by this paper's threshold. Here is the part that rescues the category, and leaving it out would mislead you. The same paper found that stacking those thin daily readings works: error falls below 0.10 at a 10-day rolling window and below 0.05 at 24 days, and it recommends "rolling aggregation over two to four weeks." That changes the verdict. One run a day cannot tell you where you stood yesterday. Thirty stacked up can tell you roughly where you stand this month, and that is a real thing to buy. Searchable does not publish how it aggregates or displays its scores, so I cannot tell you whether the dashboard leans on the daily reading or the monthly trend. That is the question I would put to their sales team before paying. And none of this is a Searchable-specific accusation. Most tools in this category publish no run counts at all, so Searchable is being scrutinized here for the unusual act of publishing enough to be checked, which is a point in its favor. ### **A Second Study Reached the Same Place** Rand Fishkin published a study through SparkToro on [AI inconsistency in brand recommendations](https://sparktoro.com/blog/new-research-ais-are-highly-inconsistent-when-recommending-brands-or-products-marketers-should-take-care-when-tracking-ai-visibility/) in January 2026. 600 volunteers ran 12 prompts through ChatGPT, Claude and Google's AI a combined 2,961 times. His headline finding: there is a "<1 in 100 chance that ChatGPT or Google's AI, if asked 100X, will give you the same list of brands in any two responses." On ordering, he found "it's more like 1 in 1,000 runs before you'd see two lists in the same order." His verdict on the tooling is the sentence to keep. "Any tool that gives a 'ranking position in AI' is full of baloney." He is careful to say what does work: "Visibility % across dozens to hundreds of prompts run multiple times is a reasonable metric." Linkifi saw the same churn in the sources ChatGPT cites, and also found that real change is slow, with a fitted half-life of about 35 days. That makes a monthly review more useful than a daily one, as I explain in [Linkifi's three-week ChatGPT source study](/how-to-get-chatgpt-to-recommend-your-business/). Keep that in mind for the dashboard screenshot further down. Its Position Distribution panel reports exactly the metric Fishkin is describing, broken out by position and rounded to the percentage point. I am not accusing Searchable of anything unusual here, because every tool in this category ships that panel and buyers ask for it. It is worth knowing that the most confident-looking number on the screen is the one with the least support behind it. That distinction is the whole game, and it is more useful than a blanket dismissal. Aggregate visibility across many prompts and many runs is measurable. A position number for a single prompt is not. My own two Perplexity runs three minutes apart, with 9 of 14 tools surviving between them, are a sample size of two and prove nothing on their own. They just happen to match what two rigorous studies found at scale. ### **A Perfect Score Still Would Not Tell You What It Earned** Suppose a vendor solved the sampling problem tomorrow and handed you a flawless visibility number. You still would not know what any of it was worth, and running the prompt more times does not fix that. I put that to [Charles Floate](https://www.youtube.com/@CharlesFloate) on an episode of AI Rabbit Holes. He is an 18-year SEO veteran who was until recently CMO of the link-building platform PressWhizz, so he has had to report search results to paying clients at scale. His answer was that a mention producing no click leaves nothing to trace. "Unless you're being cited and getting that click, there's not going to be a direct attribution." Where there is a click, he does not trust the usual analytics stack to catch it either: "Server logs is going to be the only way that you're going to get accurate 100% numbers of how many referrals." And logs still stop at your front door. Someone hears your brand in ChatGPT, googles it, arrives and buys, and "that attribution is very, very difficult to do." That has a specific consequence for how you read what Searchable puts on screen. In the dashboard shot further down, next to Position Distribution, sits a panel labeled **Decision Journey**, subtitled "Mention rate by funnel stage" and showing 68.4% at Learn, the top-of-funnel stage. Read the label carefully, because the panel is not tracking anyone's journey. It is sorting your tracked prompts into funnel stages and reporting how often you get mentioned in each. That is a legitimate thing to measure and a useful cut of the data. It is not the buyer's path, and on a no-click mention no outside tracker can reconstruct that path. His recommendation lands where the arXiv paper lands, from the opposite direction: watch trends, not single readings. Track whether you surface more across a cluster of queries, watch whether unattributed traffic and your actual sales move with it, and treat the alignment as evidence rather than proof. "We can try and do rough estimates," as he put it, while noting that "it's becoming less and less of an attribution game." My own view, which I gave him on the call, is that the most useful AI attribution most businesses can run is also the cheapest: a "how did you find us?" field at checkout or lead capture. Self-reported answers are unreliable in a specific way, since a buyer who first heard about you in ChatGPT may well type Google. But it is one of the few inputs that comes from the buyer rather than from a model, which is not something a visibility dashboard can offer at all. Besmir Bregasi, who works at an AI visibility company himself, ranked that same question above every dashboard when we talked about [how to track AI visibility](/how-to-track-ai-visibility/). ### **Where Searchable Is Genuinely Good** I have spent a lot of words on the measurement ceiling, so let me be equally direct about what this product does well, because some of it is better than the category norm. The answer-level evidence is the best thing here. Searchable lets you open the actual AI response behind any score, showing the mentions, the citations, the cited domains and the competitors named in that specific answer. That is the correct response to the reliability problem: if the aggregate score is noisy, let people read the raw answers. *Searchable's dashboard, from its own marketing site. The Position Distribution panel on the right is the metric worth reading carefully, for the reasons the research above explains.* That dashboard also shows the tension in this product. The panel labeled Position Distribution reports what share of AI answers put each brand at position one, two, three and beyond, to the percentage point. Hold that thought, because a position number for a single prompt is the exact metric the research above says cannot be measured reliably. The seven-day window in those charts is also shorter than the window that research recommends. Reviewers consistently praise speed to first insight. Several describe getting usable findings within minutes of signing up, and one 5-star reviewer, a founder responsible for product and growth, wrote that he "got great insights that I could implement within minutes of signing up." Accessibility for non-technical users comes up repeatedly and looks like a real differentiator. One reviewer described being able to "ask the agent questions and get further information when I don't understand," which is a fair summary of what the product is optimizing for. That matches who this tool is for. It is built for a marketer who wants a dashboard and a recommendation, not a practitioner who wants raw data. The query fanout feature is the one I would actually want. It shows the follow-up queries AI platforms generate around your category and lets you promote them into tracked prompts. That is closer to real research than most of what this category ships. Even its competitors concede the product is focused and fast to set up. Search Atlas, which sells a rival platform and discloses that clearly, credits Searchable's "single-purpose design" and notes its scoring "ranks findings by impact and severity rather than presenting a flat list." ### **The Review Pool Is Thinner Than the Rating** Searchable holds a 4.1 on Trustpilot across 16 reviews as of September 1, 2026. That is a real rating and I am not going to argue it down. It is worth understanding what 16 reviews can and cannot tell you. All 16 are labeled unprompted, meaning nobody was invited to leave them. That is normally a credibility plus, and Trustpilot itself notes the company "hasn't invited customers recently." The distribution is 88% five-star with one 2-star and one 1-star. Eleven of the 16 landed between mid-December 2025 and early February 2026, right after the profile was claimed, and only three have appeared in the six months since. There is a pattern in who wrote them. Ten of the 16 reviewers have exactly one Trustpilot review to their name, ever. The two reviewers with substantial review histories are both critics. I cannot prove anything from that and I am not going to try. A launch cluster of enthusiastic early adopters is exactly what a good launch looks like. It is also what a founder network looks like. Sixteen reviews cannot distinguish between those two, which is the actual point. The more useful split is what the reviews are about. The positive ones lean heavily toward onboarding and first impressions, several explicitly describing the first minutes after signup. The two critical ones are the two that read most clearly as sustained daily use, though 16 reviews are far too few to conclude that happy customers lack it. The most recent review on the profile is the 1-star, from August 2026: "The content editor breaks EVERY TIME you put in the EEAT info, and it hallucinates a schema instead of using it... Over all, it has the feel of 'it compiles, ship it'. Customer service gets back to you days later." The 2-star, from January, describes a billing problem: "despite canceling my subscription, it still attempts to charge my card, and I am unable to remove my card details." Searchable has not publicly replied to either one, which is a miss on a profile with 16 reviews where every response would be visible. Searchable also has a G2 profile, where Google's snippet reports a 4.8 from just under 100 reviews. G2 blocks automated access, so I could not open it. Searchable's own site shows G2 badges but publishes no rating, and the third-party pages repeating the figure disagree on the count, so treat it as unconfirmed. ### **Almost Nobody Reviewing This Product Is Neutral** Search for "searchable review" and the results are a case study in why this category is hard to research. The number two organic result is [Profound's review of Searchable](https://www.tryprofound.com/articles/searchable-review). Profound sells a competing AI visibility platform. Below it sits [Search Atlas's review](https://searchatlas.com/blog/searchable-ai-review/), and Search Atlas sells a competing SEO platform. Then [Radarkit's](https://radarkit.ai/blog/searchable-ai-review/), also a competitor. Search Atlas discloses its position clearly, with the review authored by its founder. Radarkit does not disclose. The one review that reads as genuinely independent, with real screenshots and hands-on detail, is by an SEO consultant who discloses in the post that he is a paid Special Advisor to Searchable Limited. He deserves credit for the disclosure. The review contains no criticism at all. There is also a Trustpilot profile ranking on page one for a completely different company called Searchable Inc, holding a 2.9. If you are researching this purchase and land there, you are reading about an unrelated business. So a buyer searching for an honest read on this product finds competitors, an advisor, and the wrong company. That is the gap this post exists to fill, and it is also why I am telling you plainly that I sell something adjacent. ### **What the Terms Say About Reviews Like This One** Two things in [Searchable's terms](https://www.searchable.com/terms) are worth reading before you sign up. They live on two different surfaces, which is worth noting on its own. The summary version of the acceptable use policy prohibits using the service "for competitive analysis of Searchable." The full legal terms go considerably further than that summary suggests. They prohibit customers from publicly publishing "any benchmark, comparison, or competitive analysis of the Service against any other product or service without Searchable's prior written consent," with a carve-out for good-faith internal evaluation and confidential benchmarking shared with your own advisors. So you can compare Searchable to a rival privately, but publishing that comparison needs permission first. Plenty of enterprise contracts carry the same clause. It is still worth knowing, both because it sits on a product whose entire function is competitive analysis and because it is the clause to read if you planned to publish your own results. The second is the affiliate program, and it is worth knowing about before you weigh any recommendation of this tool, mine included. Searchable's [affiliate page](https://www.searchable.com/affiliates) offers "30% recurring for life," rising to "40% recurring for life" at 10 active paying referrals, on a 90-day cookie with no application step. On a $400 Scale plan, 30% is $1,440 a year for as long as that customer stays, and it does not stop. That is a generous, permanent, no-friction incentive attached to every recommendation of this product on the internet. It is a completely normal program and I am not suggesting anything improper about it. It is a standing reason to check who is paid by whom before trusting a recommendation in this category. I am not in that program and earn nothing if you buy this. One footnote on sourcing, since it is the same failure this post keeps documenting. Searchable's machine-readable terms summary still describes the older program, paying "for 12 months" and requiring that "all promotional content must be pre-approved." The live affiliate page contradicts both, promising commission for life and stating "no approval needed." I went with the live page. ### **Does It Work on Searchable's Own Site?** This is the test I run on every AEO tool, because the company selling AI visibility should be the best-positioned company in the world to have it. Here are the three probes from the top of this post, laid out. | Surface | Tools named | Searchable named? | | Perplexity, run 1 | 13 | No | | Perplexity, run 2, three minutes later | 10 | No | | Claude with web search | 17 | No | Zero for three, across 40 tool slots. Profound, Peec AI, Otterly, Scrunch, Ahrefs Brand Radar and SE Visible appeared repeatedly. Searchable did not appear once. Be precise about what this proves. Three probes on one day from one location is a small sample, I ran the category query rather than a branded one, Searchable ranks fine in classic Google search, and the company is barely nine months old. It also sells monitoring rather than guaranteed inclusion, so no promise has been broken here. Read it as a reminder that a well-funded company built to win AI recommendations has not yet won them in its own category, which is the honest measure of how hard this problem is. ### **Who Should Actually Buy Searchable** **Buy it if you are a marketer who needs to start somewhere and wants a guide rather than a spreadsheet.** This is the honest sweet spot, and the reviews praising accessibility for non-technical users are describing a real strength. If the alternative is typing prompts into ChatGPT and screenshotting the results, a structured tool with an agent that explains itself is a genuine upgrade. At $125 a month, or $100 annually, that is a defensible line item. **Buy it if you will actually read the answer-level evidence.** The feature that survives the reliability critique is the one that shows you raw AI responses. If you will open those, look at which domains got cited, and use that to decide what to publish next, you are using the part of this product that works. If you will only glance at the dashboard score, you are buying a number with wide error bars. **Buy it if you are an agency that needs a client-facing deliverable.** Scale at $400 gives you white-label reports and 500 prompts. Be honest with your client about what the number means, and it is a legitimate reporting layer. **Skip it if you want a precise position number for a specific prompt.** That number does not exist reliably at any price, from any vendor, and the research above is why. Buying a tool will not create it. **Skip it if what you actually need is judgment about your own site.** Searchable does ship recommendations and audits, so the gap here is not in the product. A tool scoring your pages still cannot replace knowing why a page earns a citation in the first place. That is the gap I built [my AI SEO System](https://seo.ryandoser.com/) to close, for $199 once rather than $125 a month. I am obviously biased here, so treat that as a disclosure rather than a recommendation. ### **My Verdict on Searchable** Searchable is a competent, well-designed product that is honest enough to publish the numbers that undermine its own category's central promise. I mean that as a compliment and as a warning at the same time. Reviewers consistently describe a clean interface and fast onboarding, the answer-level evidence is the right feature to build, and non-technical marketers clearly find it usable in a way they do not find raw data usable. If that describes you, the $125 tier is not a bad purchase. What you cannot buy here, or anywhere else right now, is daily precision. Sampling at this rate produces a reading whose uncertainty swallows it, and that is a property of AI systems rather than a flaw in this company's engineering. Every competitor charging you more has the same problem and most of them do not publish enough for you to catch it. What you can buy is direction, which the research says arrives once you stack two to four weeks of those thin readings together. That is a genuinely useful thing to own, and it is worth $125 a month to some businesses. Just know that it is what you are buying. So the practical advice is the same whether you buy this or not. Watch the monthly trend rather than the daily position, read the actual AI answers instead of the score, and treat any single-day movement as noise until several weeks agree with it. If a vendor will not tell you how many times a day it samples each prompt, ask. That one question separates a measurement tool from a dashboard, and it is the question I would lead with on any sales call in this category. ### **Searchable Review FAQs** #### **How much does Searchable.com cost per month?** Searchable costs $125 a month for Pro (100 tracked prompts, 1 project), $400 for Scale (500 prompts, 10 projects) and $999 for Enterprise (1,250 prompts), plus a Custom tier through sales. Annual billing takes 20% off, so Pro is $100 a month and Scale is $320. Both self-serve tiers include a 14-day free trial. Figures read off the live pricing page on September 1, 2026; Searchable's own machine-readable files list only two plans and omit the $999 tier, so prices quoted elsewhere are often stale. #### **Are AI visibility trackers accurate?** Directionally yes, precisely no. An April 2026 arXiv study found cited sources overlap only 34% to 42% between consecutive days, and that a single daily run carries an average uncertainty of ±0.724 on a rate bounded between 0 and 1. It recommends at least 7 runs per prompt per day for a reliable daily figure, but also found that a 10-day to four-week rolling window does reach stable estimates. So monthly direction is measurable and any given day is not. Rand Fishkin's SparkToro study agreed: aggregate visibility percentage is reasonable, while "any tool that gives a 'ranking position in AI' is full of baloney." More on [which AI search metrics hold up](/ai-search-myths/). #### **Does Searchable's Decision Journey panel show what a mention earned you?** No, and read its label closely. The panel is subtitled "Mention rate by funnel stage," so what it reports is how often you get mentioned across the tracked prompts you have sorted into each stage. It is not following anyone through a journey, and it is not measuring revenue. An AI mention that produces no click leaves no referrer, so there is nothing for any tracker to attribute. Charles Floate, formerly CMO of PressWhizz, told me on [this AI Rabbit Holes episode](/google-ai-search-guidelines-exposed/) that server logs are the only accurate record of referrals when a click does happen, and that the journey from AI recommendation to branded search to purchase is "very, very difficult" to reconstruct. Read the panel as a shape, not a ledger, and put a "how did you find us?" field at checkout if you need the revenue answer. #### **How many times does Searchable check each prompt?** Three times a day at most, and Searchable is unusual in publishing enough to work that out. Pro tracks 100 prompts and analyzes 9,000 AI answers a month on daily tracking, which is 3 answers per prompt per day; the same ratio holds on Scale and Enterprise. Across the three engines its Pro copy names, that is one answer per prompt per engine per day. The company does not define an "AI answer analyzed," so treat 3 as a ceiling. It sits below the 7 daily runs the research recommends, though aggregating over 10 days to four weeks does reach stable estimates. #### **Is Searchable legitimate?** Yes. Searchable is a real company operating from New York and London that raised $14 million led by Headline at an $85 million valuation in May 2026, reporting roughly 1,000 customers. It holds 4.1 on Trustpilot across 16 unprompted reviews. A 4.8 G2 rating is widely quoted, but G2 blocks automated access and the sources repeating it disagree on the count, so treat that one as unconfirmed. The caveats are about maturity: it launched in late 2025 and the review pool is small and clustered around launch. #### **What is the best alternative to Searchable?** The trackers AI surfaces name most often are [Profound](/profound-review/), Peec AI, [Otterly](/otterly-ai-review/) and Scrunch, and [AIclicks](/aiclicks-review/) is the cheaper entry point at $59 a month. Every one faces the identical sampling problem, so compare them on how many runs per prompt per day they disclose rather than on dashboard features. If what you need is knowing which changes earn citations, a tracker is the wrong purchase and you want a process instead. No tool can guarantee AI placement, so treat any vendor promising it as a reason to walk. Be careful whose ranking you trust here too, because [most roundups of this category are written by the vendors being ranked](/best-ai-visibility-tools/). I cover the category in my [best AI SEO tools](/best-ai-seo-tools/) roundup. *How I sourced this: pricing, plan limits and terms were read off searchable.com's live pricing page, its /api/md/pricing markdown endpoint and its llms.txt on September 1, 2026, and the three surfaces disagree as described above. Terms are quoted from two surfaces that differ: the full legal contract at searchable.com/terms for the benchmarking clause, and Searchable's machine-readable terms summary for the affiliate program, which the legal contract does not cover. Trustpilot ratings and review text were read the same day; G2 blocks automated access, so its rating appears here only as Google displays it. The variance test used Perplexity Sonar and Claude Sonnet 4.5 with live web search confirmed in each response, run on September 1, 2026, and three probes are a small sample reported as such. The retired $50 Starter tier is reported from third-party reviews published in early 2026 and archived copies of the pricing page, not from anything live. Research citations come from arXiv 2604.07585 read in full as a PDF, and SparkToro's published study. Charles Floate is quoted from my AI Rabbit Holes interview with him, embedded above and published in full on [this post](/google-ai-search-guidelines-exposed/); his remarks are about AI search attribution generally and he was not asked about Searchable, which is not mentioned in that conversation. I have not run Searchable on a client campaign. I sell a competing AI SEO product and I am not a Searchable affiliate, both of which are disclosed above. [Full disclosure](/disclosure/).* --- ## 9 AI Agents for Content Creation That Actually Publish (Tested) URL: https://ryandoser.com/ai-agent-for-content-creation/ Markdown: https://ryandoser.com/ai-agent-for-content-creation.md Published: 2026-08-31 | Updated: 2026-09-30 Categories: AI Tool Reviews > No AI agent can post to your accounts by itself. Nine agents compared on what actually decides it: which ones publish unattended once a layer is connected. Every list of the best **AI agent for content creation** grades on what the agent can write. This one grades on something harder to fake: whether it can put a finished post on a real account while you are somewhere else. The honest answer is stranger than a ranking. Not one of these nine can reach your accounts through a platform API on its own, so each needs a second piece bolted on to hold the tokens. Exactly one, Manus, sidesteps that by driving a browser you are already logged into, which is its own kind of fragile. That second piece decides whether an agent is useful to you, and it is the thing nobody else is grading. Mine is [Blotato](https://www.blotato.com/?ref=rdoser), which is a client of mine, gives me a comped account, and pays commission on the link. I run two of these daily, Claude Code and Blotato, with Codex open beside them. Every week one long-form YouTube video becomes posts across six platforms that I never manually publish. The other six agents I assessed against what each vendor ships and documents, not months in the seat, and I say which is which. ### **Why Can't an AI Agent Post on Its Own?** An agent that writes is a writer. An agent that publishes is a system. To put a post on your LinkedIn, something has to hold an OAuth token for that account, survive the token expiring, and handle the platform rejecting the post. That is account plumbing, and none of these agents ships with it. They call out to something that has it. *The agent decides what to say. A separate publishing layer does the saying.* So each agent below is judged on three things: can it publish through a real platform API, can it run on a schedule with nobody watching, and does it read a durable file that holds your voice. ### **Best AI Agents for Content Creation in 2026** | Agent | Best For | Publishes Unattended | Brand Voice Memory | Starting Price | | Claude Code | Terminal users wanting scheduled posting | Yes, over MCP | Skill file on disk | $20 Pro, $100 Max | | Claude Cowork | Agent work without a command line | Yes, over MCP | Persistent instructions | Needs a paid Claude plan | | ChatGPT | Marketers who already draft there | Yes, Developer mode, web only | Chat memory, weaker | $20/mo | | Codex | A second agent beside your first | Yes, over MCP | AGENTS.md file | Included with ChatGPT | | Cursor | Developers who live in the editor | Yes, over MCP | Project rules file | Free, $20/mo Pro | | OpenCode | Choosing your own model per task | Yes, over MCP | Config file | Free, open source | | Gemini CLI | Learning agent work at zero cost | Possible, more wiring | Context file | Free | | Manus | Browser tasks a coding agent skips | Partly, browser-driven | Task memory | Limited free tier, $20/mo Pro | | OpenClaw | Self-hosters accepting the security load | Possible, you maintain it | Local config | Free, plus your model spend | #### **1. Claude Code** *Claude Code runs in your terminal and reads files directly off your machine.* This is what I run most days. [Claude Code](https://claude.com/product/claude-code) reads and writes files on your machine, which is the whole reason it wins here. My brand voice is not a prompt I retype, it is a markdown skill file on disk that gets read before every run, so post four hundred sounds like post one. Publishing happens over MCP and a scheduled job runs it while I am on a walk. The catch is comfort and cost: it is a terminal, and to live in it you want the $100 Max plan. #### **2. Claude Cowork** *Cowork gives you scheduled agent tasks without touching a command line.* Same engine, no terminal. [Cowork](https://claude.com/product/cowork) runs scheduled tasks and connects to publishing tools over OAuth, which makes it the pick for anyone who wants agent work without typing commands. What you give up is the local machine and the ability to script your own multi-step job. For most solo marketers that trade is worth making, and I compared the three Claude surfaces in [Claude AI vs Cowork vs Code](/claude-ai-vs-cowork-vs-code/). #### **3. ChatGPT** *ChatGPT connects to publishing tools through MCP in Developer mode.* The pragmatic pick, because it is where most marketers already write. [ChatGPT](https://chatgpt.com/) reaches external tools through MCP in Developer mode, so the drafting you already do there can end in a published post. Setup is buried in a security setting most people have never opened, it is web only, and OpenAI documents Developer mode across Pro, Plus, Business, Enterprise and Education, so confirm your plan allows a connector to write rather than only read. #### **4. Codex** *Codex reads an AGENTS.md instructions file before it does any work.* [Codex](https://developers.openai.com/codex/) is my second seat. I keep it running beside Claude Code in VS Code and use it as a second opinion on whatever the first one produced, which catches more than you would expect. It ships its own skills workflow and reads an AGENTS.md file, so the voice-memory story is real. I still reach for Claude Code first, but that is preference rather than a capability gap. #### **5. Cursor** *Cursor earns its spot only if you already work inside this editor.* [Cursor](https://cursor.com/) earns its place because developers already live in it, not because it is good at content. If your day is spent in that editor, having the agent that writes your release notes also publish them removes a context switch. For a marketer with no reason to open a code editor, this is the wrong tool. It is a coding environment that happens to publish. #### **6. OpenCode** *OpenCode is open source and lets you point any provider's model at a task.* [OpenCode](https://opencode.ai/) is the open-source entry, and its pitch is model freedom: connect Claude, GPT, Gemini or anything else, and switch per task. It documents MCP servers properly, so the publishing path is there. The trade is that you are assembling the setup rather than being handed one. Worth it if you resent being locked to a single provider, and unnecessary if you do not. #### **7. Gemini CLI** *A personal Google account gets 1,000 Gemini CLI requests a day at no cost.* [Gemini CLI](https://github.com/google-gemini/gemini-cli) is what I would hand someone who wants to find out whether any of this is for them before spending money. A personal Google account gets 60 requests a minute and 1,000 a day. The publishing story is thinner and the ecosystem younger, so expect to wire more yourself. OpenCode is free too, but this is the gentler start if you have never run an agent before. #### **8. Manus** *Manus drives a browser, which covers tasks a terminal agent cannot reach.* [Manus](https://manus.im/) is the odd one out here, and that is why it is worth knowing. It runs tasks in a browser rather than a terminal, so it reaches things with no API at all. Browser Operator uses your existing logins, so it can post to a site that has no API at all. That is real reach a terminal agent does not have. It is also the least predictable option here, because a browser session breaks in ways an API call does not, and Manus asks you to authorize each one. Good for research and web work feeding your content, shakier as the thing you leave running unattended. #### **9. OpenClaw** *OpenClaw is self-hosted, which puts its security burden entirely on you.* On paper the most autonomous option: self-hosted, cron-driven, agent runtime under your control. I have never self-hosted anything, so treat this as a read of the research rather than a field report, and I wrote a fuller case in [why you should avoid OpenClaw](/avoid-openclaw/). Scanning by [Censys](https://censys.com/blog/openclaw-in-the-wild-mapping-the-public-exposure-of-a-viral-ai-assistant/) found 21,639 publicly reachable instances in January 2026, with [later counts past 40,000](https://www.infosecurity-magazine.com/news/researchers-40000-exposed-openclaw/). Most still required a token, so exposure is not the same as an open door, but a one-click remote-code-execution flaw, CVE-2026-25253, was patched in early 2026. All of that is manageable. The managing is now your job. ### **What Every Agent Here Still Needs** You have four ways to close the publishing gap. Write the API integrations yourself, which is free until a platform rotates its auth. Route through an automation platform like Zapier or Make. Use a developer-first social API such as [Ayrshare](https://www.ayrshare.com/), or self-host [Postiz](https://postiz.com/). Or point the agent at a hosted layer. Mine is Blotato: nine platforms, 36 MCP tools, $29 a month flat rather than climbing per connected account. Flat pricing is the actual argument, and I ran that math in [Blotato vs Buffer](/blotato-vs-buffer/). Where it is not the answer matters more. Analytics covers eight of the nine platforms because LinkedIn returns no metrics. Comments and DMs are Instagram and Facebook only, so if replying everywhere is the job, look elsewhere. The 7-day trial also excludes the API, so an agent workflow means starting the subscription rather than trialing it. ### **How I Connect Claude Code to Blotato** Three pieces, and the order matters. A skill file holds the voice, an MCP connection gives the agent a way to publish, and Claude Code sits between them. The full walkthrough is in my guide to building a [Claude Code social media manager](/claude-code-social-media/). What surprised me is how little the agent matters once those are in place. The voice lives in the file and the publishing lives in the MCP server, so the agent in the middle is the most replaceable part of the whole setup. ### **Pick the Agent You Will Actually Open** Comfortable in a terminal, want the strongest version: Claude Code with a skill file. Terminal is a dealbreaker: Cowork. Already drafting in ChatGPT daily: stay there and stop shopping. I spent far too long picking the agent and not nearly long enough writing the skill file. The agent was never the bottleneck. The instructions were. I send one email a week on what is working in AI marketing. [You can join here](https://ai-insider-tips.kit.com/79fe0f3bb2). ### **AI Agent for Content Creation FAQs** #### **Which AI agent is best for content creation?** Claude Code, if you are comfortable in a terminal, because it reads a brand-voice skill file from disk on every run and publishes over MCP. Claude Cowork is the better pick without a command line, and ChatGPT is the pragmatic choice if that is already where you draft. The agent matters less than the skill file you give it. #### **Can an AI agent post to social media by itself?** No. An agent decides what to post but cannot hold the OAuth tokens for your accounts. It needs a publishing layer, either your own API code, an automation platform, or a hosted social API such as Blotato or Ayrshare. Once connected, the agent can publish unattended on a schedule. #### **What happens when an AI agent posts something wrong?** Plan for it, because it will. Keep a human approval step for anything reputationally risky and keep posting permissions narrow enough that a bad run is embarrassing rather than expensive. Check whether your publishing layer caps daily posts, because a cap is what limits the blast radius of a runaway loop. #### **What does a full AI content agent stack cost?** Budget two line items. The agent runs from free on Gemini CLI, through a $20 ChatGPT or Claude Pro plan, up to $100 for Claude Max. The publishing layer is separate and starts around $29. Running my own stack as the example, that is $49 a month on a Pro plan and $129 if you move up to Max. #### **How do I keep an AI agent writing in my brand voice?** Put the voice in a file the agent reads every run rather than a prompt you retype. A markdown skill file covering tone, platform formatting and a few real examples works across Claude Code, Cowork and Codex. That file is what keeps post four hundred sounding like post one. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## 6 Ayrshare Alternatives and What They Actually Cost URL: https://ryandoser.com/ayrshare-alternatives/ Markdown: https://ryandoser.com/ayrshare-alternatives.md Published: 2026-08-31 | Updated: 2026-09-30 Categories: AI Tool Reviews > Ayrshare starts at $149/month for one profile. What six alternatives really cost, where each one wins, and when switching is a mistake. Every page ranking for **Ayrshare alternatives** right now is published by a company selling one. Upload-Post, Zernio, bundle.social, Outstand and Blotato all have a page telling you to switch to them, and Ayrshare has its own pages telling you why its competitors are not real APIs. I priced all of them against each other in my roundup of [the best social media APIs](/social-media-api/). I counted. On page one there is exactly one source with nothing to sell: a Reddit thread. So here is mine, and I will tell you my conflicts before I tell you anything else. [Blotato](https://www.blotato.com/?ref=rdoser) is a client of mine, my account there is comped, and links to it below are affiliate links. I have no relationship with Ayrshare or with any other tool in this post. The second thing you should know is where my knowledge stops. **I have never been an Ayrshare customer.** I have never paid that $149, so I cannot tell you how their support responds or how their uptime feels at scale. What I can do is read pricing pages carefully, and I run a competing tool every day, which means I know exactly which questions to ask of one. Everything below is sourced from vendor documentation, and I say so where a claim is theirs rather than mine. The specific thing I bring to this is the shape of the workload. I publish through an MCP server from inside Claude Code rather than through a dashboard, and I do the same for client accounts, which means the questions I ask a social API are not the ones a review site asks. Not "does it have a nice calendar," but: how many calls does one post actually cost me, does the tool return an error my agent can act on or just a 500, and does the bill move when a client adds three accounts in a week. Those are the questions that decide whether a tool survives contact with an agent, and they are the ones I have organized this post around. What those vendor pages will not give you is the number that actually drives this decision, stated plainly, plus the cases where switching away from Ayrshare is a mistake. ### **The Number That Starts Every Ayrshare Conversation** [Ayrshare's pricing](https://www.ayrshare.com/pricing/) begins at **$149/month for the Premium plan, which includes one social profile.** Launch is $299/month for up to 10 profiles. Business starts at $599/month for 30 profiles, with tiered per-profile rates above that ($8.99 each for profiles 31 to 100, $3.49 for 101 to 500, $2.49 past 500). Enterprise is custom. Every plan includes API access and unlimited team members, and Ayrshare covers 14+ networks. One customer connecting Pinterest, Bluesky, YouTube, Reddit, X and TikTok still counts as a single profile, which is the detail people miss when they compare it to per-account tools. That profile definition is the whole design. Ayrshare is built for a company embedding social publishing into its own product on behalf of many customers. A profile is a customer, not an account. If that is your architecture, the pricing is coherent. If you are one person with eight accounts, you are paying $149 for a structure built for somebody else's problem. That is the mismatch driving most of the searches for this keyword. One thing worth knowing before you write the price off, because it changes how you can evaluate this: there is now a **28-day free trial, but only on the Launch plan.** Premium, Business and Enterprise are billed at signup with no trial at all. That is a long runway to test an API against your own workload, longer than almost anything else in this category. It also means the honest way to try Ayrshare is to start on the $299 tier and drop down at day 28, rather than starting on the $149 one. *Ayrshare states the rule plainly on its own pricing page: multiple networks still equal one profile.* Run that out before you dismiss the price. One person with eight accounts pays $149 where Zernio charges $36 for the same connections, so the price looks indefensible. Flip to a product serving two hundred customers and it inverts. Ayrshare bills those at $3.49 per profile on its Business tier, and each of those profiles can hold a customer's whole set of networks, while a per-account tool charges for every single connection every customer brings. That is precisely the buyer it was designed for. ### **Which Buyer Are You? Answer This Before You Compare Anything** The entire decision turns on one question, and it is not about features. **Are you publishing for yourself, or for your customers?** If it is for yourself, almost every tool below beats Ayrshare on price and you should skip straight to the cheap end. If it is for your customers, inside your own product, then only Ayrshare and bundle.social are genuinely designed for what you are doing, and the cheap per-account tools will betray you at scale. Two follow-ups narrow it further. Do you need a free tier to evaluate? Upload-Post and Zernio give you a permanent one without a card, Ayrshare gives you 28 days on its Launch plan, and Blotato gives you a 7-day trial that excludes the API. And do you need content created or only delivered? Every tool here except Blotato is a pipe, so if your agent still needs something upstream writing the posts, count that service in the price before you compare. ### **Ayrshare Alternatives, and What Each One Costs You** I have ordered these by the situation they fit rather than by preference. All figures below are monthly-billing rates taken from each vendor's live pricing page. Where a page opened on annual billing, I switched it to monthly first, which changes the number on Upload-Post. | Tool | Entry price | Billing unit | Free tier | Built for | | Ayrshare | $149/mo | Per customer profile | 28-day trial, Launch only | Multi-tenant products | | Upload-Post | $24/mo Basic | Per profile | Yes, 2 profiles | Widest platform list | | Zernio | Free, then $6/account | Per account | Yes, 2 accounts | Developers starting small | | bundle.social | $100/mo Pro | Per organization | Yes, 3 teams and 20 posts | Multi-tenant SaaS | | Postiz | $29/mo cloud, or self-host | Per channel tier | Self-host free | Owning the stack | | Blotato | $29/mo | 20 accounts flat | 7-day trial, no API | Agent writes and publishes | | Outstand | $19/mo, 3,000 posts | Per post published | No, accounts are free | Many accounts, low volume | Every tool in that table ships an MCP server, so agent compatibility is not the thing separating them. The billing unit is. ### **The Bill at 1, 10 and 50 Connected Accounts** When I checked page one on August 16, 2026, not one of the ranking pages worked this out, which is strange, because the bill at your actual account count is the thing people are trying to find. So here it is. Connected accounts across the top, monthly billing, worked from each vendor's published rates that day. | Tool | 1 account | 10 accounts | 50 accounts | What moves the bill | | Outstand | $19 | $19 | $19 | Posts, not accounts | | Zernio | $0 | $48 | $168 | Each account added | | Upload-Post | $0 | $50 | $147 | Profile tier | | Postiz cloud | $29 | $39 | $99 | Channel tier | | Blotato | $29 | $29 | $499 | Plan tier, flat inside it | | bundle.social | $100 | $100 | $100 | Publishing volume | Read across a row rather than down a column. The cheapest option changes twice on the way from one account to fifty, and the whole race is settled by six. Zernio and Upload-Post are both free at one or two accounts. Zernio takes it alone from three, at $6. From six accounts onward Outstand is cheapest and simply stays there, because a flat $19 stops competing with a curve that keeps climbing. Blotato is flat at $29 up to 20 accounts, then $97 to 40, then $499 for Agency, which its help docs cap at 100 accounts even though the pricing page omits that number. Landing just past a tier boundary is where its pricing hurts most. Postiz is the cheapest of the per-channel options at 50. Ayrshare is missing from that table on purpose. Its unit is the customer profile, not the connected account, so putting it in the same column would compare two different things. Priced its own way: **$149 for one profile, $299 for ten, $599 for thirty.** A customer on six networks still counts as one profile, which is the detail that makes the comparison unfair in both directions. #### **1. Upload-Post, the Cheapest Real Free Tier** *Upload-Post counts profiles, and the free tier covers two of them without a card.* [Upload-Post](https://www.upload-post.com/#pricing) has the most generous entry point here. The free plan gives you 2 profiles and 10 uploads a month with no credit card, covering Instagram, LinkedIn, YouTube, Facebook, X, Threads, Pinterest, Reddit and Bluesky, though not TikTok. Paid runs Basic at $24/month for 5 profiles, Professional at $50 for 25, Advanced at $147 for 75, and Business at $438 for 225. Annual billing drops those meaningfully, and extra profile slots are available as add-ons. It reaches 20+ platforms, including Discord and Telegram. Its pricing page says 22 while its own machine-readable docs say 20+, so I am citing the number both surfaces agree on. One cost that does not show up on the plan card: posting links on X is a $19/month add-on, because the base service strips URLs. Compare Advanced at $147 for 75 profiles against Ayrshare's Premium at $149 for one. Those are different products with different guarantees, but that gap is why this page exists. #### **2. Zernio, If You Want to Start Free and Scale by Account** *Zernio starts at zero and climbs with every account you connect.* [Zernio](https://zernio.com/pricing) gives you your first 2 accounts free with no card, then charges per account on a graduated scale: $6/month each for accounts 3 to 10, $3 each for 11 to 100, and $1 each past 101. Every feature is on every account, with nothing gated behind a tier. It covers 16+ social platforms plus 7 ad networks and ships a hosted MCP server. At five accounts you pay $18/month, at twenty you pay $78. If those numbers are the reason you are here, [the Zernio alternatives math](/zernio-alternatives/) covers the crossover points. One caution, and I wrote a whole post about it. Zernio markets itself with a claim about having 40x faster rate limits than a competitor, and that number does not hold up against the documentation. I walked through the arithmetic in [a full breakdown of Zernio](/zernio-review/). The tool is good. Read its comparison pages skeptically. #### **3. bundle.social, for Multi-Tenant SaaS** *bundle.social bills per organization, so connected accounts stay uncapped on paid plans.* [bundle.social](https://bundle.social/) targets the same buyer Ayrshare does: a product team embedding social publishing for many end users. It advertises flat pricing without post counting, unlimited users and accounts, plus SDKs, a CLI and an MCP server. I have not run bundle.social in production either, so this is a read of its rate card rather than a field report. Pro is $100/month for 10,000 posts, Business is $400/month for 100,000, and the free plan caps at 3 teams and 20 posts a month. Connected accounts are uncapped on both paid plans, which is the entire point. Onboarding a customer with forty Instagram profiles changes your bill by nothing. If you are evaluating Ayrshare for a multi-tenant app rather than for yourself, this is the closest architectural substitute on the list and belongs in your shortlist alongside it. #### **4. Postiz, If You Would Rather Own the Server** *Postiz caps at $99 for 100 channels, the lowest hosted ceiling in this roundup.* [Postiz](https://postiz.com/pricing) is open source and self-hostable for free on your own infrastructure. Its cloud plans run $29/month for 5 channels, $39 for 10, $49 for 30 and $99 for 100, all with unlimited posts. Self-hosting removes the subscription and replaces it with responsibility. I priced that tradeoff properly in my [breakdown of what running it yourself actually costs](/postiz-alternatives/). You handle deploys, upgrades, and getting your own platform app approvals, which is the part people underestimate. I get into why that trade bites in my [Postiz comparison](/postiz-vs-blotato/). #### **5. Blotato, If You Want the Agent to Write It Too** *Affiliate and client relationship, disclosed above and at the bottom. [Full disclosure here](/disclosure/).* *Blotato's plans are flat, so the bill holds steady until you cross a tier.* [Blotato](https://www.blotato.com/?ref=rdoser) is $29/month flat for up to 20 connected accounts across 9 platforms, with API access on the entry plan and a hosted MCP server. This is the one I use daily, and I use it because it generates the post and the image rather than only delivering them. The honest limits: 9 platforms is the smallest list in this roundup, there is no free tier, and generating an API key ends the 7-day trial and starts billing immediately. If you came specifically to test the API, plan on buying the first month rather than trialing it. #### **6. Outstand, If Your Account Count Is the Problem** *Outstand charges for posts rather than accounts, so connections are free at any number.* I have not run [Outstand](https://www.outstand.so/) in production, so treat this as documentation analysis rather than a field report. It earns its place because it is the only tool here that bills on a different axis entirely. The base plan is $19/month including 3,000 posts, then $0.007 per post to 10,000 and $0.005 beyond that. Connected accounts and seats are unlimited and free on every plan. That inverts the problem this whole page is about. If your bill hurts because you keep adding accounts, a tool that does not charge for accounts is the structural answer rather than a cheaper version of the same shape. The tradeoff is that heavy publishing volume is now the thing that costs you. It covers 12 platforms, four of which (X, Google Business Profile, Vimeo and Reddit) need your own API credentials, and it ships a 28-tool MCP server. ### **When Ayrshare Is Still the Right Answer** No roundup on page one will tell you this, because none of them benefit from it. Stay with Ayrshare if you are publishing on behalf of many customers inside your own product. The per-profile model, the official platform partnerships, and unlimited team members on every plan are built for exactly that, and the cheaper per-account tools get expensive fast once every customer needs their own set of connections. Stay if you need its specific platform approvals and the compliance posture that comes with being an established vendor. Switching to save $100 a month and then failing a platform review is a bad trade. Stay if your integration already works, because migration cost is real and almost never counted in these comparisons. Rewriting a working publishing integration to save a subscription is rarely worth the engineering time unless the gap is large and permanent. ### **What About Post Bridge and SocialAPI.ai?** Both come up on this keyword and neither is ranked above, because I have not run either one. [Post Bridge](https://www.post-bridge.com/) is the more interesting of the two. It ships a hosted MCP server, a REST API and a CLI, and it positions itself head-on at agent publishing rather than at dashboards. Its pricing runs $39 a month for 15 connected accounts and $99 for 99, then $1 per extra account, with the REST API, CLI and MCP included on both plans. It briefly ran two different price lists on two different pages earlier in 2026, which is why some comparisons still quote a $9 figure, and it has since dropped its $29 entry tier as well. [SocialAPI.ai](https://socialapi.ai/) shows up in AI answers on this query more than its footprint suggests it should. I have no firsthand read on it. Both are worth your own look. I would rather leave a gap than rank software I have not connected an account to. ### **Three Questions the Buyer Split Does Not Answer** The yourself-or-your-customers question above narrows the field. These three finish the job, and they are the ones I work through on a client build. **How many connections will you have in twelve months?** Price that number rather than today's. The table above reorders completely between one account and fifty, so buying for your current count is how people end up migrating twice. **Is your bill growing from accounts or from posting volume?** This decides the billing unit before it decides the tool. Growing account counts point at Outstand and bundle.social, which do not charge per connection. Heavy volume on a handful of accounts points the other way. **Which platform would end the conversation if it were missing?** One required destination outside a tool's list settles it regardless of price. Check that before you check anything else on this page. ### **Ryan's Final Thoughts** Ayrshare is not overpriced. It is priced for a customer that most people searching this term are not. The $149 entry looks absurd next to a $24 competitor right up until you need to publish for two hundred of your own users, at which point the per-profile math turns and Ayrshare starts looking reasonable. My advice is to figure out which buyer you are before you read another comparison page, including this one. Solo operator with a handful of accounts: Upload-Post or Zernio if you want free, Blotato if you want the writing handled. Product team publishing for customers: shortlist Ayrshare and bundle.social, and ignore the cheap per-account tools entirely. Lots of accounts but modest posting volume: Outstand, because it is the only one that stops charging you for connections. Every price here came from the vendor's own pricing page or its published rate card, with monthly billing selected. I have run Blotato, Zernio, Upload-Post and Postiz directly, and priced Ayrshare, bundle.social and Outstand from their documentation without running them at scale. And treat every vendor comparison page on this keyword, mine included, as an argument rather than a finding. Open the pricing pages yourself. They take two minutes and they are the only source that is not selling you something. ### **Ayrshare Alternatives FAQs** #### **How much does Ayrshare actually cost?** Premium is $149/month and includes one social profile. Launch is $299/month for up to 10 profiles, and Business starts at $599/month for 30 profiles with tiered rates above that. All plans include API access and unlimited team members across 14+ networks. Ayrshare offers a 28-day free trial on the Launch plan only; Premium, Business and Enterprise are billed at signup with no trial. #### **What is the cheapest Ayrshare alternative?** At one or two accounts, nothing beats free: Upload-Post gives you 2 profiles and 10 uploads a month with no card, and Zernio gives you 2 accounts free. Past that it depends on count. Zernio charges $6 per account to 10, Upload-Post's Basic is $24/month for 5 profiles, and Outstand is a flat $19 with connected accounts free, which makes it the cheapest option here from six accounts upward. #### **Is there a free Ayrshare alternative?** Yes. Upload-Post's free plan covers 2 profiles and 10 uploads monthly without TikTok. Zernio gives you 2 accounts free with full API access. Postiz can be self-hosted for free if you are willing to run the infrastructure yourself. #### **Why is Ayrshare so expensive compared to the alternatives?** It prices per customer profile rather than per connected account, because it is built for companies embedding social publishing into their own product for many end users. One profile can hold accounts on every supported network. If you are publishing only for yourself, you are buying a structure designed for a different problem. #### **Which Ayrshare alternative works with AI agents?** All of them. Zernio, bundle.social, Blotato, Upload-Post, Postiz and Outstand each ship an MCP server that Claude Code, Codex and similar agents can call to publish directly. Ayrshare ships MCP too, though note its documentation server is read-only and separate from the one that posts. MCP support has stopped being a differentiator in this category, so compare pricing model and platform coverage instead. Blotato also generates the content, while the others publish material you have already created. #### **Should I switch away from Ayrshare?** Not if you publish on behalf of many customers, need its platform partnerships, or already have a working integration. Migration cost is real and rarely counted. Switch if you are a solo operator or small team paying $149 a month for a single profile you could serve for $24 elsewhere. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine and my account there is comped rather than paid. I have no relationship with Ayrshare, Upload-Post, Zernio, bundle.social, Postiz or Outstand. I only recommend tools I actually use, and I say so plainly where I have priced a tool from its documentation rather than run it. [Full disclosure](/disclosure/).* --- ## 10 Best AI Communities for Marketers & Creators (2026) URL: https://ryandoser.com/best-ai-communities/ Markdown: https://ryandoser.com/best-ai-communities.md Published: 2026-08-31 | Updated: 2026-09-30 Categories: AI Resources > Every price and member count re-verified against the live signup pages. The 10 best AI communities for marketers and creators, free and paid, honestly compared. Joining the right **best AI communities** can compress months of solo learning into weeks of collaborative progress. I have paid for, joined, and quietly left more AI communities than I can count. This list is the shortlist that survived. Every price, member count, and feature below was re-verified against the live signup pages, because half the "best AI communities" roundups you will find are quoting numbers that went stale months ago. ### **Best AI Communities at a Glance** Here is the fast version if you just want to pick one and go. | Community | Best For | Price | Community Size | | **AI Marketing Insiders** | Marketers and creators running AI in a real marketing workflow | Free, $300/yr Premium, $85/mo VIP | 2,100 | | **AI Accelerator** | Established operators wanting production-ready AI systems | $99 to $1,000/mo, billed annually | 1,000+ | | **The Vibe Marketers** | AI marketing workflows and campaign teardowns | $49/mo or $199/yr | 2,500 | | **Grace Leung Growth Community** | Combining AI with digital growth and SEO strategy | Free tier available | Not published | | **AI Automation Society** | n8n workflows and no-code AI agents | Free | 460K+ | | **AI Automation Agency Hub** | Starting an AI services agency from zero | Free | 330K+ | | **AI Automations by Jack** | Turning AI automation into client income | $87/mo | 3,300 | | **Early AI-dopters** | Claude Code, consulting, and one-on-one coaching | From $43/mo | 1,200 | | **Build with Luke** | Shipping real apps with Claude Code | $19/mo | 85 | | **Women Build AI** | Women actively building AI products | Free | 5,300 | ### **Why Most AI Communities Are a Waste of Money** You have probably seen dozens of AI communities pop up over the past year. Most of them follow the same pattern. A creator with a large following launches a paid group, fills it with recycled content from their YouTube channel, and then disappears after the first month. These communities are run by the same "hype grifters" flooding YouTube with INSANE and GAME-CHANGING thumbnails. They collect monthly fees while offering zero real interaction, outdated templates, and no accountability. The members post questions that go unanswered. The "exclusive content" is a repackaged PDF. The community dies within 90 days. This is why so many people view AI communities as an expense rather than an investment. They have been burned before. ### **Why a Good AI Community Is an Investment** A legitimate AI community is one of the highest-ROI moves available to anyone trying to keep pace with AI right now. Here is why. AI moves faster than any single person can track. New models drop weekly. Tools update overnight. What worked last month might be outdated today. A good community gives you a room full of people testing, breaking, and building with these tools in real time. You get answers in hours instead of spending days figuring things out alone. The shift I have watched happen over the last six months is the clearest signal of all. A year ago, nearly every serious AI community was teaching n8n and no-code automation. Today the same communities are shipping Claude Code skills, agent operating systems, and GitHub repos you clone and run. That pivot happened in public, in the feeds of these groups, months before it showed up in any course or article. Being in the room is how you catch that on time instead of a quarter late. The communities on this list are different from the hype-driven groups flooding the market. Every one of them is run by someone who actively teaches, shows up consistently, and builds alongside their members. I have personally vetted each one. ### **How I Vetted These AI Communities** I did not rank these by follower count or by who has the loudest launch. Every community on this list had to clear four tests. #### **The founder still shows up** Not a moderator, not a VA. The person whose name is on the door has to be answering questions in the feed within the last week. This alone eliminates most paid communities. #### **The content reflects current tools** If the newest resource in the classroom is a GPT-4 prompt pack, the community is dead and nobody has announced it yet. I checked what each group shipped most recently. #### **Members post results, not just questions** A healthy community has people sharing what worked. A dying one has a wall of unanswered "has anyone tried this?" posts. #### **The price matches the access** A $200/month group with no live calls and no direct founder access is a course with a chat box attached. Price has to buy you something you cannot get from a YouTube playlist. ### **Best AI Communities in 2026** Whether you are a marketer, content creator, or entrepreneur, one of these groups will match your goals. I included both free and paid options so you can start wherever your budget allows. #### **1. AI Marketing Insiders (Free & Paid)** *AI Marketing Insiders community on Skool for marketers and creators learning AI.* **Best for:** Marketers, creators, and business owners who want AI systems that actually run inside a marketing workflow, not AI theory. *Full disclosure: this one is mine, so weigh it accordingly. I put it first because it is the one I built and the one I can speak for in the most detail. The Vibe Marketers and Grace Leung both serve marketers well and you should read those entries before deciding. Judge my entry against the other nine and pick the fit, not the ranking.* [AI Marketing Insiders](https://www.skool.com/ai-marketing-insiders) now has more than 2,100 members. I built it for business owners, marketers, and creators who want to cut the hype and run AI marketing systems that actually work. The number I would point at: the free tier includes five working Claude Code skills and the full AI Marketing Essentials course. To be fair to the list, AI Automation Society also ships free Claude Code skills and GitHub repos, and it does that at 460,000 members. The difference is scope, not generosity. Those skills are built for automation builders. Mine are built for a marketing workflow, and the free tier is small enough that I am still the one answering questions in it. The reason it exists is simple. I spent a decade in marketing before AI became the whole conversation, and almost every AI community I joined was run by someone who could demo a tool but had never had to hit a client's numbers. The gap between "look what this tool can do" and "here is the workflow that replaced four hours of my week" is where this community lives. **What the free tier includes:** 5 free Claude Code skills, the AI Automations Vault, the AI Marketing Essentials course, community support, and networking with other operators. **Premium ($300/year):** a 1:1 introductory call with me, my AI SEO System, my Claude Skills Stack, the Claude Code Crash Course, and bonus AI masterclasses. **VIP ($85/month or $600/year):** everything in Premium plus weekly live Q&A calls, weekly build-with-me calls, the full archive of recorded calls, priority support, and early access to new skills and drops. The VIP tier is also bundled into [the AI Concierge](/ai-concierge/), my monthly service for owners who want a private working call with me on top of the community. The center of gravity here is [Claude Code for marketing](/claude-code-for-marketing/). Most communities are still teaching AI as a chat window. We treat it as an operating system you build repeatable marketing workflows on top of, which is why the skills library is what members reach for first. **[Join AI Marketing Insiders free here.](https://www.skool.com/ai-marketing-insiders)** Take the five Claude Code skills, run them, and upgrade only if you want the crash course and the live calls. If you would rather start with the reading, I also put together a guide with my full toolkit and workflows. [Grab my free AI Marketing Guide here.](https://guide.ryandoser.com/) #### **2. AI Accelerator (Paid)** *Authority Hacker's AI Accelerator program for established business operators.* **Best for:** Established operators who already have a business and want production-ready AI systems bolted onto it. [AI Accelerator](https://www.authorityhacker.com/ai-accelerator/) is a structured membership from Authority Hacker, founded by Gael Breton and Mark Webster, and it has served over 15,000 customers. It now runs three tiers: Standard at $99/month, Plus at $199/month, and Max at $1,000/month, all billed annually. What you get is roughly 50 live implementation calls a year, courses updated quarterly, deployable tools and automations, weekly AI Nuggets, quarterly briefings, and a private community where Gael personally answers threads. The community itself is smaller than the customer number suggests, at 1,000+ members, so the founder access is real rather than nominal. The thing I respect most about their approach is the filtering. Their own line is that they tested hundreds of AI tools, agents, and workflows, and about 5% survived real-world use. That is the entire value proposition of a paid community stated in one sentence, and it is why this sits at number two. The focus is production systems: content pipelines, prospecting agents, and SEO audits. If you are pre-revenue, this is too much money. If you already have a business generating cash, the Standard tier pays for itself fast. #### **3. The Vibe Marketers (Paid)** *James Dickerson's The Vibe Marketers community for AI-driven marketing.* **Best for:** Marketers who want proven AI workflows and campaign teardowns rather than tool tutorials. [The Vibe Marketers](https://www.skool.com/the-vibe-marketers) is run by James Dickerson and costs $49/month, or $199/year on the annual plan. The community sits at about 2,500 members and holds a 4.9-star rating across more than 2,000 reviews. Members get proven AI workflows, bi-weekly group sessions, campaign breakdowns, customizable templates, and round-the-clock community support. The differentiator is the founder-session access. Members get workshops and beta programs from companies actually building AI marketing tools, including [MindStudio](https://www.mindstudio.ai/), [Lindy](https://www.lindy.ai/), and [Gumloop](https://www.gumloop.com/). You are hearing how the tools work from the people who built them, before that information reaches YouTube. #### **4. Grace Leung Growth Community (Free)** *Grace Leung's website offering digital growth consulting with AI and marketing tech.* **Best for:** Marketers and consultants who want AI applied to search visibility and growth strategy, not just content generation. [Grace Leung's Growth Community](https://community.graceleung.com/) offers a free way in, which is a change worth flagging if you looked at this one before and passed on price. The community sits behind a sign-in, so check the current tiers yourself before assuming what is included. Grace is a digital growth consultant and educator originally from Hong Kong and now based in Canada, with over a decade of digital growth marketing experience across APAC and North American markets. Her core spaces cover AI growth systems for marketing, and the emphasis is on getting found online and building a sustainable channel mix rather than chasing whatever tool launched this week. This is the one on the list I would point a consultant toward. The strategic framing, where AI is a lever inside a growth roadmap rather than the roadmap itself, is uncommon in AI communities and it is exactly what separates people who use AI from people who build businesses with it. It pairs well with the [AI YouTube channels](/ai-youtube-channels/) worth following if you learn better by watching. #### **5. AI Automation Society (Free)** *Nate Herk's AI Automation Society on Skool, now past 460K members.* **Best for:** Anyone learning n8n workflows and building AI agents without writing code. [AI Automation Society](https://www.skool.com/ai-automation-society/about) is run by [Nate Herk](https://www.youtube.com/@nateherk), and it has exploded to over 460,000 members, up from the roughly 312,000 I recorded in the April version of this post. It is free, and it is the largest community on this list. What is more interesting than the size is the direction. This group started as an [n8n](https://n8n.io/) community and has visibly pivoted toward Claude Code. Members now get Claude Code skills they can drop into their own setup, full GitHub repos to clone and build from, over 100 n8n templates, and a 7-day challenge where you build a Claude Code AI executive assistant that handles email, calendar, and admin, ending in a certification. If you have been wondering whether [n8n is dead](/is-n8n-dead/), watching the largest no-code automation community on the internet ship Claude Code curriculum is the most honest answer available. The tradeoff of a 460K-member free group is signal-to-noise. The classroom content is strong, but do not expect the founder to answer your specific question in the feed. #### **6. AI Automation Agency Hub (Free)** *Liam Ottley's AI Automation Agency Hub, now over 330K free members.* **Best for:** Starting an AI services agency from zero with no coding background. [AI Automation Agency Hub](https://www.skool.com/learn-ai/about) is founded by [Liam Ottley](https://www.youtube.com/@LiamOttley) and has grown to more than 330,000 free members. You get the full step-by-step course to start and scale an agency, client contracts and proposal templates, weekly sessions with working agency operators, and a progression system with challenges and rewards. The weekly operator sessions are the real asset. Hearing someone describe how they priced and delivered an actual client project is worth more than another module on prompt structure. Same caveat as above: at this size, it is a library with a forum attached, not a room where people know your name. #### **7. AI Automations by Jack (Paid)** *Jack Roberts' AI Automations community with 110+ blueprints and daily expert calls.* **Best for:** People who want to sell AI automation services and want the delivery systems handed to them. [AI Automations by Jack](https://www.skool.com/aiautomationsbyjack/about) is run by Jack Roberts, the UK entrepreneur behind a seven-figure AI automation business. The price is $87/month, and the community has grown to around 3,300 members. Members get the full Claude Code and Hermes OS setup, the Hermes and Claude masterclass with plug-and-play systems, 110+ battle-tested blueprints spanning lead gen, content, and delivery, a claimed $20K in software discounts, daily expert calls, personalized onboarding, and direct support from Jack. The daily calls are the standout feature. Most paid communities run weekly at best, and the difference between "I will find out Thursday" and "I will find out today" compounds when you are mid-build on client work. This is built for people turning [AI automation into income](/ai-for-small-businesses/), not hobbyists. #### **8. Early AI-dopters (Paid)** *Mark Kashef's Early AI-dopters community with courses, coaching, and templates.* **Best for:** People who want one community instead of five, with real one-on-one coaching attached. [Early AI-dopters](https://www.skool.com/earlyaidopters/about) is led by Mark Kashef, an O'Reilly Media instructor, former AI and analytics professor, and ex-Amazon, with a Master's in AI. Pricing now starts at $43/month, with higher tiers above it, and the community sits around 1,200 members. The curriculum covers Claude Code from beginner to advanced, agentic OS systems for business and enterprise, prompt engineering, machine learning, sales and marketing for AI solutions, and an AI consulting playbook. Members get access to twelve specialized coaches across Claude Code, n8n, cybersecurity, and sales, plus an AI expert network and software discounts. The number Mark reports on the signup page is 92% retention. Treat it as an operator-supplied figure rather than an audited one, but retention is still one of the harder metrics to fake with a good launch. Between the O'Reilly teaching background, the Master's in AI, and twelve coaches on staff, this option leans harder on formal credentials than most. #### **9. Build with Luke (Paid)** *Luke Byrne's Build with Luke community for Claude Code builders.* **Best for:** Builders who want to stop watching AI tutorials and actually ship an app. [Build with Luke](https://www.skool.com/luke) is a small, high-touch community run by Luke Byrne, a former senior technology consultant now building his SaaS business with Claude. It costs $19/month at a founding-members price. It currently has 85 members. You get step-by-step courses and masterclasses, weekly live build calls with a replay library, templates and code, direct access to Luke, and client opportunities. The curriculum runs through LLM fundamentals, RAG systems, AI agents, workflow automation, and shipping SaaS with [Claude Code](/build-a-website-with-claude/). At 85 members, you are getting near-consulting levels of attention for the price of a couple of coffees. That is the entire argument for joining small communities early, and it is also the reason this window closes. #### **10. Women Build AI (Free)** *Sabrina Ramonov's Women Build AI free community for women creating AI products.* **Best for:** Women who are actively building AI products, apps, tools, or automations. [Women Build AI](https://www.sabrina.dev/p/women-building-ai-free-community) is a free private community founded by [Sabrina Ramonov](https://www.sabrina.dev/) for women actively building with AI. It has passed 5,300 members and is free forever, with a monthly events calendar and free masterclasses. The screening is the feature. Sabrina reviews applicants to confirm they are actively creating with AI rather than passively learning, and she recommends completing a build tutorial before you apply. That single gate is why the discussion quality is high and why it stays spam-free at a size where most free groups collapse into self-promotion. ### **Free vs Paid AI Communities: Which Should You Join?** The honest answer is that most people should start free and upgrade only when they hit a specific wall. Free communities are libraries. AI Automation Society and AI Automation Agency Hub have hundreds of thousands of members and enormous classroom sections, and you will not get personal attention in either. That is fine when what you need is structured material and a search bar. Paid communities buy access to a person. That is the only thing you cannot get for free. When you evaluate a paid group, ignore the template count and ask how often the founder is in the feed and how often live calls run. AI Accelerator runs about 50 implementation calls a year. AI Automations by Jack runs daily calls. Build with Luke gives you direct access because there are 85 people in the room. The trap is paying for a large paid community. Big and free works. Small and paid works. Big and paid usually means you are funding a course you could have bought once. ### **Final Thoughts from Ryan** The right AI community can pay for itself within the first month. One workflow you pick up from a fellow member can save you hours every week. One connection can turn into a client or collaboration. If I had to pick the single most valuable thing membership has given me this year, it was not a template. It was seeing the whole category pivot from no-code automation to Claude Code roughly three months before that shift showed up in the content everyone else was reading. That head start is the actual product. A community is one input, not the whole diet. The other two that move the needle are the [best AI newsletters](/best-ai-newsletters/) for weekly signal and the [AI YouTube channels](/ai-youtube-channels/) worth actually watching, and it helps to know [which AI builders are actually shipping](/ai-content-creators-to-follow/) before you pick whose community to join. Between the three, you have covered reading, watching, and asking. Stop viewing community memberships as expenses and start treating them as the fastest shortcut to AI fluency. Pick one or two from this list that match your goals, join today, and actually participate. Lurking does not build skills. If you are on the other side of that decision and thinking about launching your own, I covered [the operator side with my community admin](/how-to-build-an-online-community/). ### **Best AI Communities FAQs** #### **What are the best free AI communities to join?** AI Marketing Insiders, AI Automation Society, AI Automation Agency Hub, Grace Leung's Growth Community, and Women Build AI all offer free membership. AI Automation Society is the largest at over 460,000 members and focuses on n8n and Claude Code automation. AI Marketing Insiders (my own community) offers a free tier with five Claude Code skills and the AI Marketing Essentials course, aimed at marketers specifically. Start with whichever matches your current goals and upgrade later if you want direct access to the founder. #### **Are paid AI communities worth the money?** Paid communities are worth it when the operator shows up consistently, the content stays current, and the members are active. The paid options on this list range from $19/month for Build with Luke to $1,000/month for AI Accelerator's Max tier. The single best signal is live call frequency: AI Automations by Jack runs daily expert calls, AI Accelerator runs roughly 50 implementation calls a year, and Early AI-dopters reports 92% retention. Compare that to the cost of figuring out AI workflows alone or paying for a course that goes stale in three months. #### **What is the best AI community on Skool?** AI Marketing Insiders, AI Automation Society, Early AI-dopters, The Vibe Marketers, and AI Automation Agency Hub are the strongest AI communities on Skool in 2026. AI Automation Society is the largest at 460,000+ free members. The Vibe Marketers publishes the strongest public rating of the group at 4.9 stars across 2,000+ reviews, though most Skool communities do not display a rating at all. AI Marketing Insiders is built for marketers and creators. The right one depends on whether your focus is marketing, automation, agency building, or Claude Code development. #### **How much do AI communities cost in 2026?** Free is common and genuinely useful at the large end. Paid AI communities generally run between $19 and $99 per month, with premium tiers going higher. Current pricing on this list: Build with Luke at $19/month, AI Marketing Insiders Premium at $300/year and VIP at $85/month, The Vibe Marketers at $49/month, Early AI-dopters from $43/month, AI Automations by Jack at $87/month, and AI Accelerator from $99 to $1,000/month. Prices in this category change often, so verify before you join. #### **Which AI community is best for marketers?** AI Marketing Insiders (mine) is built for marketers, creators, and business owners who want to run AI marketing systems rather than experiment with tools. The Vibe Marketers is a strong alternative at $49/month, focused on AI marketing workflows and campaign teardowns. Grace Leung's free Growth Community is the best pick if your priority is search visibility and growth strategy. Most automation-focused communities, including AI Automation Society and AI Automation Agency Hub, teach agency and workflow building rather than marketing itself. #### **How do I know if an AI community is legitimate?** Check four things. First, does the founder still post and respond to questions regularly, or has a moderator taken over? Second, are members sharing real results and not just asking unanswered questions? Third, is the content updated to reflect current AI tools, or is it recycled material from a year ago? A community whose newest resource is a GPT-4 prompt pack is already dead. Fourth, does the price buy you access you cannot get from a free YouTube playlist. The communities on this list pass all four tests. --- ## Blotato vs Buffer in 2026: Which Social Media Tool is Best? URL: https://ryandoser.com/blotato-vs-buffer/ Markdown: https://ryandoser.com/blotato-vs-buffer.md Published: 2026-08-31 | Updated: 2026-09-30 Categories: AI Tool Reviews > Blotato vs Buffer on real per-channel math, AI generation, and the MCP servers both now ship. Buffer is no longer just a scheduler. **Blotato vs Buffer** is usually framed as the AI content engine against the plain old scheduler. That framing is out of date. Buffer shipped a public GraphQL API in May 2026 and a hosted MCP server, so it now talks to Claude just like [Blotato](https://www.blotato.com/?ref=rdoser) does. The real split is pricing shape and whether you need something to write the content in the first place. I run Blotato daily and it publishes most of my content through Claude Code, so my experience with it is long-running and hands-on. I also went back into Buffer for this post, connected accounts, and wired its MCP server into Claude Code to see how close the two have actually gotten. Those are not equivalent amounts of testing, and I will flag where that matters. One thing to flag before the details: almost every comparison ranking for this term right now, including the one Google's AI Overview leans on hardest, still describes Buffer as a scheduler with no API story. If you make your decision on those pages you are deciding on 2025 information. ### **Blotato vs Buffer at a Glance** | | Blotato | Buffer | | Entry price | $29/mo (Starter) | Free, then $6/channel | | Pricing shape | Flat, 20 accounts included | Per channel | | Free plan | No | Yes, 3 channels | | Cost at 10 accounts | $29/mo | $60/mo ($50 annual) | | Cost at 20 accounts | $29/mo | $100/mo, volume discount included | | Platforms | 9 | 11 | | AI content generation | Text, images, video, voice | AI Assistant, text only | | API | Yes, paid plans only | Yes, including free plan | | MCP server | Yes | Yes | | Free trial | 7 days, excludes API | 14 days, plus a free tier | ### **The Pricing Shapes Are Completely Different** This is the whole decision for most people, so I want to be precise about it. [Buffer](https://buffer.com/pricing) charges per channel. Essentials is $6 per channel per month billed monthly, or $5 billed yearly. Team is $12 monthly, or $10 yearly. A channel is one connected account, so an Instagram profile and a LinkedIn page are two channels. There is also a genuine free tier: 3 channels, 10 scheduled posts per channel, and the AI Assistant. ![Buffer pricing page showing the Free, Essentials, and Team plans with per-channel pricing and API request limits](/images/2026/07/blotato-vs-buffer-buffer-pricing.jpg) [Blotato](https://www.blotato.com/?ref=rdoser) charges flat. Starter is $29 a month and includes 20 social accounts and 1,250 AI credits. Creator is $97 for 40 accounts and 5,000 credits. Agency is $499 with 28,000 credits. ![Blotato pricing tiers showing Starter at 20 social accounts, Creator at 40, and Agency credits](/images/2026/07/blotato-vs-buffer-blotato-pricing.jpg) Run the math and the crossover is early. At 3 channels Buffer is free and Blotato is $29, so Buffer wins outright. At 5 channels Buffer is $30 monthly or $25 annual against Blotato's $29, so call it a tie you break on features. At 10 channels Buffer is $60 monthly or $50 annual against Blotato's $29. The tipping point lands at 5 channels on monthly billing and 6 on annual. Past 10 channels there is an important wrinkle most comparisons ignore. Buffer discounts each channel above 10, and it now publishes the bands. On Essentials, channels 1 to 10 are $6 each, 11 to 25 drop to $4, 26 to 50 to $3, and anything past 50 to $1. On Team the first 10 are $12 each and the same $4 and $3 bands apply above that. What that means practically: straight-line math overstates Buffer's bill at higher channel counts. Twenty channels on Essentials is $100 a month, not the $120 you would get by multiplying. If you are pricing a setup that size, put your real channel count into the slider on Buffer's pricing page and read the total, because that is the only figure I would trust. The shape of the thing still holds. Buffer is cheapest when you are small and keeps climbing as you add channels, just more gently than the sticker rate suggests. Blotato costs more on day one and then stops moving until you pass 20 accounts. ![Hand-drawn chart of two pricing shapes with no numbers: one bill that climbs per channel and one that stays flat then takes a single step, with the point where they cross marked](/images/2026/09/blotato-vs-buffer-pricing-shape-diagram-v2.jpg) ### **Buffer Is Not Just a Scheduler Anymore** This is the part that makes most Blotato vs Buffer comparisons stale, and it is the reason I rewrote my own assumptions while researching this. Buffer put its public API and MCP server into public beta in February 2026, then [opened it up properly on May 27, 2026](https://buffer.com/resources/buffer-api-is-here/). It is GraphQL, it has managed OAuth, it shipped with a CLI, and it is available on every plan including the free one. The free tier gives you 1 API key and 3,000 requests a month. Essentials gives 3 keys and 7,500 requests. Team gives 5 keys and 15,000. ![Buffer for Developers page describing its GraphQL API for AI agents and SaaS products](/images/2026/07/blotato-vs-buffer-buffer-developers.jpg) There is also a hosted MCP server at `mcp.buffer.com/mcp`, with native support listed for Claude, ChatGPT, Cursor, Raycast, and Perplexity, and a [first-party setup guide](https://buffer.com/integrations/claude) covering Claude, Claude Cowork, and Claude Code. I connected it and the agent could see my channels, draft posts, review the queue, and schedule. It works. So if you have been avoiding Buffer because you assumed it had no agent story, that assumption is now wrong, and being able to test an API integration on a free plan is a real advantage. Blotato's 7-day trial explicitly excludes the API, and generating an API key ends the trial and starts billing immediately. As a developer evaluating both, you can try Buffer's API for $0 and you cannot do that with Blotato. One limit worth knowing before you build on [Buffer's API](https://buffer.com/made-for/developers): there is no image upload through the GraphQL API. Media has to already be hosted somewhere public and passed in as a URL. Buffer lists it as the top item on its own developer roadmap, so it is a known gap rather than a design choice. Creating, editing, and deleting posts are all documented mutations, so the queue itself is manageable from an agent. ### **The Actual Difference: One Writes, One Schedules** Strip out the pricing and the API parity and you are left with the thing that genuinely separates these two. Buffer assumes you arrive with a finished post. Its AI Assistant will rewrite, repurpose, and adjust tone on text you give it, and it is good at that, but it is an assistant sitting next to a composer. It does not generate images or video. Blotato assumes you arrive with a source and nothing else. Point it at a YouTube video, an article, or an idea, and it produces the copy, the images, the AI video, and the voiceover, then schedules the lot. That is what the AI credits on each plan actually buy. Here is the workflow I run daily, end to end. The detail that sold me was small. I asked it to schedule a LinkedIn post for 1pm the next day, it checked my calendar, saw I already had something in that slot, and asked me to pick another time rather than quietly double-booking. I wrote up that whole setup in my [Blotato review](/blotato-review/), and it is the backbone of my [AI social media system](/ai-social-media-system/). So the question that actually decides this is not which tool is better. It is whether something is already producing your content. If you have a writer, an agency, or your own agent generating posts, you are shopping for a publishing layer and Buffer is an excellent one at a lower price. If nothing is producing the content, a scheduler leaves you with an empty calendar. ### **Platform Coverage and Analytics** Buffer connects to 11: LinkedIn, X, Instagram, Threads, Facebook, TikTok, Pinterest, YouTube, Bluesky, Mastodon, and Google Business Profile. Blotato publishes to 9: X, LinkedIn, Facebook, Instagram, TikTok, Pinterest, Threads, Bluesky, and YouTube. The two Buffer has that Blotato does not are Mastodon and Google Business Profile. If you are a local business posting to Google Business Profile, that single line decides this comparison for you. On analytics Buffer is the stronger product and it is not particularly close, though [Metricool](/blotato-vs-metricool/) beats them both on reporting depth. Advanced analytics come with Essentials, while exportable branded reports, extended date ranges, and custom metric sets sit on the Team plan, so check which tier holds the reporting you actually need before you buy. Blotato's analytics now return metrics for eight of its nine platforms, with LinkedIn the only one that reports nothing. If LinkedIn reporting is the reason you are buying, that single gap decides it, but the coverage is far wider than it was earlier this year. Blotato does have two surfaces Buffer does not: comments and DMs, both currently limited to Instagram and Facebook. Useful if engagement is part of your workflow, though narrower than the marketing implies, and narrower than the [dedicated Instagram DM automation tools](/best-instagram-dm-automation-tools/) built for that job alone. ### **What About Reliability and Support?** Buffer is the older, more established product, and stability is its reputation. It has been running since 2010, which is a long time to have been doing one job. I did not run it long enough to vouch for its uptime myself, so treat that as reputation rather than something I measured. Blotato is a much younger product moving much faster. It holds 4.8 out of 5 from 387 reviews on [Trustpilot](https://www.trustpilot.com/review/blotato.com), which is customer sentiment rather than uptime data, though my own experience matches it. A fast-moving product does ship changes, and I have hit the occasional platform connection that needed reauthorizing. Each time it was a few minutes of clicking rather than a missed posting day, but it is a different profile from a product that has been doing one thing since 2010. Pick accordingly. If you want the tool nobody ever thinks about, that is Buffer. If you want the tool doing the most, that is Blotato, and you accept a little more motion. ### **Before You Buy Either One** A few practical things that decide more purchases than the feature lists do. #### **How to try each without wasting money** Buffer is the easy one. The free plan is permanent, so connect 3 channels, schedule a week of posts, and see whether the workflow fits before you pay anything. If you want the paid features, the 14-day trial sits on top of that. Blotato has no free tier. The 7-day trial requires a card and converts unless you cancel, so treat it as a paid month you can back out of. More importantly, if you are evaluating the API or MCP, do not plan to test it on the trial: generating an API key ends the trial and starts billing immediately. Budget for the first month of Starter and decide inside it. #### **What switching actually costs you** Neither tool locks up your content, but neither migrates it either. Scheduled posts do not transfer between them. If you switch, you reconnect every social account through OAuth and rebuild anything still sitting in the queue, which is an afternoon at 5 accounts and a genuine project at 20. The thing that does not come with you is history. Buffer's analytics live in Buffer, so leaving means leaving the reporting record behind. Export anything you need before you cancel. #### **Contracts, cancellation, and the annual question** Both bill monthly by default and both offer a discounted annual option. Blotato states "cancel anytime" on its pricing page and puts annual savings at around 17%, with bonus credits attached. Buffer's annual billing saves you two months, which is worth taking only once you are sure, since a per-channel annual commitment gets awkward if you drop channels later. My advice on the annual toggle is the same for both: run a month at monthly pricing first. The savings are real but small next to picking the wrong tool for a year. #### **The upgrade cliff to watch** Blotato's jump from Starter to Creator is $29 to $97, and Starter caps at 20 accounts. If you are sitting at 18 or 19, know that your next few connections roughly triple the bill. Credits are the other thing to watch, since Starter's 1,250 a month is what funds the AI images and video, and heavy generation is what burns them. Buffer has no cliff, because it scales one channel at a time. That is the tradeoff between the two pricing shapes in one sentence. ### **Which One Should You Pick?** If you only take one thing from this post, take this. ![Decision diagram asking who writes the content: if you already have it pick Buffer for reporting, more networks and a free API, if you need it made pick Blotato for content plus publishing on one flat bill](/images/2026/09/blotato-vs-buffer-decision-diagram-v2.jpg) **Pick Buffer if** you already have something writing your content, analytics and reporting are central to your job, you need Google Business Profile or Mastodon, you run a handful of channels, or you want to test an API integration for free before paying anything. Note that the first three of those hold at any account count. Price is not the only axis, and if reporting is your job Buffer stays the right answer at 20 channels too. **Pick [Blotato](https://www.blotato.com/?ref=rdoser) if** you need the content generated as well as published, you run enough accounts that per-channel billing starts to sting, and you want one flat bill instead of one that grows every time you add a channel. At 20 accounts it is $29 flat against a Buffer bill of $100, volume discount already applied. The cleanest way to read this: the price crossover sits at 5 or 6 accounts depending on billing, but the product crossover is generation. If nothing is currently writing your posts, that matters more than the money, and it is why I run Blotato. If something already is, Buffer does the publishing job well for less, and I would not talk you out of it. If neither fits, I compared eight of these side by side in my roundup of [social media automation tools](/social-media-automation-tools/), and I put Blotato head to head with an open-source option in [Postiz vs Blotato](/postiz-vs-blotato/). If analytics are what pulled you toward Buffer, [Blotato vs Metricool](/blotato-vs-metricool/) covers the tool that reports better than either. Buffer is the mainstream comparison. On the developer side people cross-shop per-account publishing APIs instead, which I covered in [Zernio alternatives](/zernio-alternatives/). ### **Blotato vs Buffer FAQs** #### **Is Blotato cheaper than Buffer?** At 5 connected accounts on monthly billing, or 6 on annual, yes. Buffer's Essentials plan is $6 per channel monthly or $5 yearly, so 10 channels is $60 monthly or $50 annual against Blotato's flat $29. Above 10 channels Buffer discounts each additional channel, to $4 each for channels 11 to 25, $3 for 26 to 50, and $1 past 50 on Essentials, so 20 channels is $100 a month. Blotato is a flat $29 for up to 20 accounts, then $97 for up to 40. Below 5 accounts Buffer is cheaper, and at 3 accounts Buffer is free. #### **Does Buffer work with Claude and AI agents?** Yes. Buffer launched a public GraphQL API in May 2026 and runs a hosted MCP server at mcp.buffer.com/mcp, with native support listed for Claude, ChatGPT, Cursor, Raycast, and Perplexity. The API is available on every plan including the free one. The main gap is that the GraphQL API does not support image upload, so media has to be hosted elsewhere and passed in as a public URL. #### **Does Blotato have a free plan?** No. Blotato runs a 7-day trial that requires a card and converts to a paid subscription unless you cancel, and the trial excludes API access. Buffer has a genuine free forever plan with 3 channels and 10 scheduled posts per channel. #### **Which one is better for AI content creation?** Blotato, clearly. It generates copy, images, AI video, and voiceovers from a source you give it, which is what the AI credits on each plan pay for. Buffer's AI Assistant rewrites and repurposes text you already have and does not generate images or video. #### **How many platforms does each support?** Buffer connects to 11: LinkedIn, X, Instagram, Threads, Facebook, TikTok, Pinterest, YouTube, Bluesky, Mastodon, and Google Business Profile. Blotato publishes to 9: X, LinkedIn, Facebook, Instagram, TikTok, Pinterest, Threads, Bluesky, and YouTube. Buffer's extras are Mastodon and Google Business Profile. #### **Which has better analytics?** Buffer, and it is not close. Advanced analytics come with Essentials, with branded exportable reports and extended date ranges on Team. Blotato returns analytics for eight of its nine platforms, with LinkedIn the only gap. #### **Can I use both together?** You can, and there is a real case for it: Blotato generating the content, Buffer scheduling it and handling the reporting Blotato does not yet cover. That combination fixes each tool's weak spot. The cost is two subscriptions and a manual handoff between them, so it only makes sense if analytics genuinely drive your decisions. Most people should pick one side of the split and revisit later. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine. Buffer is not an affiliate relationship and I have no commercial interest in it. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## Blotato vs Metricool: Full Comparison for Social Media Management URL: https://ryandoser.com/blotato-vs-metricool/ Markdown: https://ryandoser.com/blotato-vs-metricool.md Published: 2026-08-31 | Updated: 2026-09-06 Categories: AI Tool Reviews > Blotato vs Metricool compared on brand-based pricing, AI generation limits, analytics depth, and which one lets you test an MCP connection for free. **Blotato vs Metricool** looks like a close call on the pricing pages. Metricool starts at $20 a month, [Blotato](https://www.blotato.com/?ref=rdoser) starts at $29, and both now ship an MCP server so an AI agent can post for you. Then you look at what each one is actually counting, and the two stop being comparable at all. Metricool bills per brand. Blotato bills per connected account. Those are different units, and the vendor pages ranking for this term mostly compare the two numbers as though they were the same thing. I run Blotato daily and it publishes most of my content through Claude Code, so my experience there is long-running and hands-on. For this post I set up a Metricool account, connected profiles, and wired its MCP server into Claude to see how the agent side compares. That is weeks against years, and I will flag where the difference matters. ### **Blotato vs Metricool at a Glance** | | Blotato | Metricool | | Entry price | $29/mo (Starter) | Free, then $20/mo | | Pricing unit | Per social account | Per brand | | What the entry plan holds | 20 accounts | 5 brands | | Free plan | No | Yes, 1 brand | | Platforms | 9 | 11 | | AI content generation | Text, images, video, voice | Text only | | AI credits per month | 1,250 | 20 per brand | | Analytics coverage | 8 of 9 platforms | All connected networks, plus ads | | MCP server | Yes, paid plans | Yes, including the free plan | | REST API | Yes, paid plans | Advanced or Custom only | | Free trial | 7 days, excludes API | Free plan, no trial needed | ### **A Brand Is Not an Account** This is the part the comparison pages get wrong, and it decides most of these purchases. In [Metricool](https://metricool.com/pricing/), a brand is a container. Per Metricool's own documentation it holds one profile per network, so a single brand can carry an Instagram account, a Facebook page, a LinkedIn page, a TikTok account, a YouTube channel, a Pinterest account, Threads, Bluesky, a Google Business Profile listing, Twitch, and X, plus ad accounts and a website. That is one brand. ![Metricool pricing page showing Free, Starter, Advanced, and Custom plans priced by number of brands](/images/2026/07/blotato-vs-metricool-metricool-pricing.jpg) So Metricool Starter at $20 a month for 5 brands is not five accounts. Filled out, it is potentially dozens of connected profiles. Blotato Starter at $29 gives you 20 social accounts, and every profile you connect counts as one of those 20. ![Blotato pricing page showing Starter at $29 with 20 social media accounts, Creator at $97, and Agency at $499](/images/2026/07/blotato-vs-metricool-blotato-pricing.jpg) Run that against real setups and the answer flips depending on shape, not size. If you are one business posting to seven networks, that is 1 brand in Metricool and 7 accounts in Blotato. Metricool covers it free. If you are an agency with five clients on six networks each, that is 5 brands at $20 against 30 accounts in Blotato, which needs the $97 Creator plan. On sticker price alone Metricool wins that setup, though the $97 is also buying the content generation that Metricool does not do at any tier. Where Blotato pulls ahead is when you run many profiles under one identity and want them all generating content. Twenty accounts on one flat bill with AI generation included is a different product from twenty profiles you still have to write for. Two caveats before you price it out. Metricool's listed prices are annual billing and exclude VAT, and monthly billing runs higher at $25 for 5 brands. More importantly, X costs extra. Connecting an X account requires a paid add-on at $10 per month per account, a price that took effect on July 13, 2026, and one add-on covers one X account per brand. If X is central to your posting, add that to every brand and re-run the math. ### **The Agent Story Is the Opposite of What You Would Expect** Both tools ship an MCP server, and the access rules run opposite to what the marketing on either side would suggest. Metricool's MCP server runs at `ai.metricool.com/mcp` and works on **any plan, including the free one**. Its documentation covers Claude, ChatGPT, Cursor, n8n, Make, Zapier, and the Gemini CLI. I connected it on Claude and the agent could see my brands, pull metrics, and create and schedule posts. Your plan limits still apply through the agent, so a free account is still capped at 20 scheduled posts a month, but the connection itself costs nothing. The Metricool REST API is a separate product with a different gate. It requires the Advanced plan, which is $53 a month. So if you want to hit endpoints from your own code rather than chat with an agent, Metricool's entry price is not $20, it is $53. ![Metricool documentation table showing MCP available on any plan including Free while the API requires Advanced or Custom](/images/2026/07/blotato-vs-metricool-metricool-mcp-api.jpg) Blotato inverts this. Its REST API and MCP server are both on the $29 Starter plan, so there is no separate tier to reach for programmatic access. But the 7-day trial **excludes the API entirely**, and generating an API key ends the trial and starts billing immediately. So if you want to test an agent connection before paying, Metricool is the only one of the two that lets you. If you want a REST API on the cheapest paid plan, that is Blotato at $29 against Metricool's $53. Here is what the Blotato side looks like once an agent is driving it. Running the same kind of request against both, the split is clear. Metricool's agent answers questions about performance well, because that is what the underlying product is good at. Ask it to produce a week of posts and you are still the one writing them. Blotato's agent will draft the week, generate the images, and put them in the queue. I wrote that setup up in my [Blotato review](/blotato-review/), and it is the backbone of my [AI social media system](/ai-social-media-system/). Both tools also appear in my roundup of [MCP servers for marketers](/mcp-servers-for-marketers/). ### **One Writes the Content, One Measures It** Pricing aside, this is the difference that outlasts any rate card. Metricool's AI assistant is a text tool. By Metricool's own feature list it creates and translates copy, fixes spelling and grammar, changes tone, adds calls to action, suggests hashtags, adds emoji, shortens or lengthens posts, and adapts them per platform. That is a genuinely useful editing companion. It does not generate images, and it does not generate video. The credit allowances match that scope. Free gives you 5 credits per brand per month, Starter 20, and Advanced 35. Those numbers are sized for polishing captions, not producing a content library. Blotato is built the other way around. Point it at a YouTube video, an article, or an idea, and it produces the copy, the images, the AI video, and the voiceover, then schedules the result. Starter includes 1,250 AI credits a month, Creator 5,000, and Agency 28,000. That gap between 20 credits and 1,250 is not a pricing quirk, it is the whole difference in what the two products are for. So the question that decides this is not which tool is better. It is whether something already produces your content. If you have a writer, an agency, or your own agent generating posts, you are shopping for a publishing and reporting layer, and Metricool is an excellent one that starts at free. If nothing is producing the content, a scheduler leaves you staring at an empty calendar. ### **Analytics: Metricool's Home Turf** If reporting is the reason you are buying, this section will decide it. Metricool is an analytics product that grew a scheduler, and it shows. You get analytics across every network you connect, competitor tracking on up to 100 profiles, PDF and PPT reports, and paid ad data from Meta, Google, and TikTok sitting next to your organic numbers. Check the tier before you buy, because the reporting features are split across plans: the Looker Studio connector, customizable report templates, and client and role management all sit on Advanced at $53, not on the $20 Starter. Reporting is where Blotato is still catching up. Per Blotato's own API documentation, metrics come back for eight of its nine platforms, with LinkedIn the only one returning nothing today. If a monthly LinkedIn report is the thing you are paid to deliver, that gap decides it. If you mostly need to know what worked so you can make more of it, the eight covered platforms include the ones most creators actually live on. Here is where my Metricool time runs out, as promised. A few weeks tells you the reports build, export cleanly, and pull the numbers they claim to. It does not tell you whether the data holds up against native platform analytics over a quarter, how the numbers behave when a client disputes them, or what support is like when a connection breaks the day a report is due. Those are the questions that decide whether an analytics tool is any good, and they need longer than I have given it. On its reputation for stability I am relaying what long-time users say rather than something I have proven. Blotato does have two surfaces Metricool matches rather than loses on: comments and direct messages, both limited to Instagram and Facebook. Metricool's Inbox handles comments and messages too, so treat that as a tie rather than a differentiator. ### **Platform Coverage** Metricool connects to 11 networks: Instagram, TikTok, YouTube, Threads, X, Twitch, Google Business Profile, Bluesky, Facebook, Pinterest, and LinkedIn. Blotato publishes to 9: X, LinkedIn, Facebook, Instagram, TikTok, Pinterest, Threads, Bluesky, and YouTube. The two Metricool has that Blotato does not are Twitch and Google Business Profile. If you are a local business that posts to Google Business Profile, Blotato cannot do it at any price, so that alone rules it out. Worth remembering that X on Metricool is the paid add-on, and that LinkedIn and X are both unavailable on its free plan. ### **What the Comparison Pages Get Wrong** Search this matchup and the first page is almost entirely vendors writing about themselves. Blotato's own comparison ranks first, a competitor's comparison page sits in the top five, and Metricool's own versus page is there too. Google's AI Overview for the term leans almost entirely on the vendor pages. Two claims get repeated across those pages that are worth correcting. If you want the wider field rather than this head-to-head, I ran [the pricing math across eight Metricool alternatives](/metricool-alternatives/) at two different account counts. The first is treating brands and accounts as the same unit, which makes Metricool look either far cheaper or far more expensive than it is depending on which side wrote the page. It is neither. It is priced differently, and the answer depends on whether your profiles cluster into brands. The second is the assumption that Metricool is the non-technical option and Blotato is the developer one. On MCP access that is backwards. Metricool ships MCP on its free tier while Blotato requires a paid plan and blocks API access during the trial. Blotato is the stronger agent platform once you are paying, because the API sits on the entry plan rather than a $53 tier, but "try before you buy" belongs to Metricool. On reputation, Blotato holds 4.8 out of 5 from over 350 reviews on [Trustpilot](https://www.trustpilot.com/review/blotato.com). Metricool does not have comparable volume there, which reflects where each company asks for reviews more than product quality, so I would not read much into the gap either way. Metricool is the older and larger product, and stability is the thing people consistently credit it with. ### **Which One Should You Pick?** The whole decision, in one image. ![Decision diagram asking whether you need content made or measured, branching to Blotato for copy, images and video, or Metricool for reports, client brands and ad data](/images/2026/09/blotato-vs-metricool-decision-diagram-v2.jpg) **Pick Metricool if** you manage separate client brands, reporting is your actual deliverable, you need competitor tracking or ad data alongside organic numbers, you post to Google Business Profile or Twitch, or you want to test an agent connection without paying anything. The free plan is permanent rather than a trial, so you can answer the question before spending anything. **Pick [Blotato](https://www.blotato.com/?ref=rdoser) if** nothing is currently writing your content, you want copy, images, and video generated rather than just scheduled, and you want a REST API on the entry plan instead of a $53 one. The two credit systems are not measuring the same unit, so do not read 1,250 against 20 as a 60x ratio, but the direction is not in dispute: one tool is built to produce media and the other is built to polish text. The cleanest way to read it: Metricool is the better deal if you already have content and need to publish and measure it. Blotato is the better deal if the content itself is the bottleneck. That is why I run Blotato, and if reporting were my deliverable instead of creation, I would be on Metricool and I would not feel like I had compromised. There is also a case for running both. Metricool's free plan reports on one brand while Blotato generates and publishes, which covers each tool's weak spot for $29 a month total. Two caveats keep that from being a free win: the free plan excludes LinkedIn and X, and you are maintaining two dashboards with a manual handoff between them. It works if reporting genuinely drives your decisions and one brand is all you need to measure. If neither fits, I compared eight of these side by side in my roundup of [social media automation tools](/social-media-automation-tools/). For other head to head matchups, [Blotato vs Buffer](/blotato-vs-buffer/) covers the mainstream scheduler and [Postiz vs Blotato](/postiz-vs-blotato/) covers the open-source option. For the developer-side equivalent of this comparison, I put two API-first tools head to head in [Postiz vs Zernio](/postiz-vs-zernio/). ### **Blotato vs Metricool FAQs** #### **Is Metricool cheaper than Blotato?** Usually yes on sticker price, but they count differently. Metricool is free for 1 brand and $20 a month for 5 brands on annual billing, while Blotato is $29 a month for 20 social accounts. A Metricool brand holds one profile per network, so 5 brands can carry far more than 5 profiles. If your accounts cluster into client brands, Metricool is cheaper. Add $10 a month per X account, and note that API access needs Metricool's $53 Advanced plan against Blotato's $29. #### **Does Metricool work with Claude and other AI agents?** Yes. Metricool runs an MCP server at ai.metricool.com/mcp and it works on every plan including the free one, with documented setups for Claude, ChatGPT, Cursor, n8n, Make, Zapier, and the Gemini CLI. Your plan limits still apply through the agent. The Metricool REST API is separate and requires the Advanced plan or Custom. #### **Does Blotato have a free plan?** No. Blotato runs a 7-day trial that requires a card and converts to a paid subscription unless you cancel, and the trial excludes API access. Generating an API key ends the trial and starts billing immediately. Metricool has a genuine free forever plan for 1 brand, though it excludes LinkedIn and X and caps you at 20 scheduled posts a month. #### **Which one is better for AI content creation?** Blotato, and it is not close. It generates copy, images, AI video, and voiceovers from a source you give it, with 1,250 AI credits a month on the entry plan. Metricool's AI assistant works on text only. It writes and rewrites captions, adjusts tone, translates, and suggests hashtags, but it does not generate images or video, and the entry plan includes 20 credits per brand per month. #### **Which has better analytics?** Metricool, on breadth. It reports across every connected network except X, which needs a paid add-on, and adds competitor tracking, PDF and PPT reports, a Looker Studio connector on Advanced, and paid ad data from Meta, Google, and TikTok. Blotato returns metrics for eight of its nine platforms, with LinkedIn the only one reporting nothing yet. Pick Metricool if reporting is the deliverable; the gap matters less if analytics mainly tell you what to make next. #### **How many platforms does each support?** Metricool connects to 11: Instagram, TikTok, YouTube, Threads, X, Twitch, Google Business Profile, Bluesky, Facebook, Pinterest, and LinkedIn. Blotato publishes to 9: X, LinkedIn, Facebook, Instagram, TikTok, Pinterest, Threads, Bluesky, and YouTube. Metricool's extras are Twitch and Google Business Profile, though X requires a paid add-on and LinkedIn is unavailable on its free plan. #### **Can I use both together?** Yes, and it is a reasonable setup. Blotato generates and publishes while Metricool's free plan reports on one brand, which covers each tool's weak spot for $29 a month total. Note that Metricool's free plan excludes LinkedIn and X, and you are running two dashboards with a manual handoff, so it only makes sense if reporting genuinely drives your decisions. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine. Metricool is not an affiliate relationship and I have no commercial interest in it. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## How to Setup MCPs in Claude Code (Connect Any Tool) URL: https://ryandoser.com/claude-code-mcps/ Markdown: https://ryandoser.com/claude-code-mcps.md Published: 2026-08-31 | Updated: 2026-09-30 Categories: Claude Code > Learn how to setup MCPs in Claude Code to connect external tools like APIs, databases, and more. Includes a step-by-step MCP setup guide. Setting up **Claude Code MCPs** lets you connect external tools directly inside your coding environment. This guide walks through the exact process I use to add MCP servers, test connections, and start pulling live data without leaving Claude Code. ### **How Claude Code MCPs Actually Work** Most people hear "MCP" and assume it requires heavy configuration or coding knowledge. That is not the case. MCP stands for Model Context Protocol. It is an open standard that connects AI tools to external services like GitHub, Notion, databases, and APIs. Inside Claude Code, MCPs act as a bridge between your AI assistant and the outside world. Instead of copying data between tabs, Claude Code pulls it in directly. If you are still untangling where MCP stops and the other pieces start, I broke down [Claude Skills vs agents vs MCP](/claude-skills-vs-mcp-vs-agents/) without the jargon. The setup process varies between tools. Some MCPs connect via a cloud URL. Others run locally through a command. But the core workflow stays the same: add the connection, authenticate if needed, and test it. *The MCP Setup skill file in VS Code gives Claude Code a step-by-step recipe for configuring any new MCP connection.* ### **Creating an MCP Setup Skill** One resource that saves me hours is a skill markdown file. I have one called MCP Setup that acts as a standard operating procedure for Claude Code. It tells the AI exactly how to research, configure, and verify any new MCP connection. Think of it like a recipe. You hand Claude Code the skill file and a tool name, and it handles the rest. The skill walks through identifying the service type, finding the right MCP URL or command, running the add command, verifying the connection, authenticating, and testing with a simple request. If you have never created a [Claude Code skill](/claude-code-skills-hack/) before, that process takes about five minutes. You can also grab my exact MCP Setup skill from the Free AI Marketing Essentials Guide linked above. ### **Step-by-Step Claude Code MCP Setup** Here is the process I walked through in the video using DataForSEO as an example. If you are deciding whether it deserves an account at all, I covered [what DataForSEO actually costs](/dataforseo-review/) and where its data falls short in a full review. Ahrefs ships an MCP server too, and I compared the two in [DataForSEO vs Ahrefs](/dataforseo-vs-ahrefs/). #### **Recommended Settings** Before starting, I recommend these Claude Code settings: - Leave the model on your plan's default (Opus 5.5 on every paid plan and the API, as of Claude Code v2.1.280) - Keep effort at medium or lower with `/effort` for setup work (thinking can't be turned off on Opus 5.5, so effort is the dial that saves usage) - Keep "ask before edits" enabled for your first setup - Once comfortable, switch to "bypass permissions" for faster workflows #### **Running the Setup** I prompted Claude Code with: "Use my MCP setup skill to set up an MCP connection for DataForSEO." From there, Claude Code read the skill file, researched the [DataForSEO](https://dataforseo.com/?aff=245611) MCP documentation, and configured the connection automatically. The tool asked for my API credentials. After creating a DataForSEO account (which includes a free dollar for testing), I copied over my API email and password. Claude Code stored those credentials and confirmed the connection was active. *The DataForSEO MCP setup guide provides the connection details Claude Code needs to configure the integration.* #### **Tracking Your Connections** I keep a document called mcp-connections inside my [Claude Code workspace](/claude-code-for-marketing/) that tracks every active MCP. This simple file lists each connection name, what it does, and whether it requires authentication. When you start adding multiple MCPs, this kind of organization prevents confusion. The most demanding MCP I have connected is the Robinhood one, because a bad call there costs real money, and I documented that whole build in my [Robinhood trading agent walkthrough](/ai-trading-agent-robinhood/). ### **Testing Your New MCP Connection** After setup, always test the connection in a fresh Claude Code tab. I opened a new chat, switched to bypass permissions, and prompted: "Use the DataForSEO MCP and my keyword research skill to provide high-level keyword research data on the root keyword of Claude Code Marketing." Claude Code read my keyword research skill, accessed the DataForSEO MCP directly, and returned monthly search volume, keyword difficulty, and related keyword suggestions. The entire process ran inside Claude Code with zero tab switching. You can verify the correct APIs were used by checking the [Claude Code MCP](https://code.claude.com/docs/en/mcp) chat logs for references to the connected service. If the logs show successful API calls with no errors, your connection is solid. *Testing the DataForSEO MCP connection by running a keyword research query directly inside Claude Code.* ### **What Makes MCP Integration Worth It** The real value of Claude Code MCP integration is eliminating context switching. Before MCPs, pulling keyword data meant opening a separate tool, running a search, copying results, and pasting them back into your workflow. Now that entire loop happens inside one interface. MCPs also compound with [Claude Code agent teams](/claude-code-agent-teams/). You can build agents that automatically pull data from connected services, process it through your skills, and output finished deliverables. The MCP layer is what makes that possible. The setup process will differ for every tool. But having a reusable MCP setup skill eliminates the guesswork. Follow the steps in the [Model Context Protocol](https://modelcontextprotocol.io/) documentation for any new service, and Claude Code handles the configuration from there. ### **Final Thoughts from Ryan** Claude Code MCPs turn a standalone AI assistant into a connected workflow engine. The setup takes minutes, not hours. Once you have a few MCPs running, you will wonder how you worked without them. Start with one connection that matches your daily workflow and build from there. If you are not sure which one that should be, here are the [7 MCP servers I actually run for marketing work](/mcp-servers-for-marketers/), with what each one really costs. ### **Claude Code MCPs FAQs** #### **How do I add an MCP to Claude Code?** Use the command `claude mcp add` followed by the transport type and connection URL or local command. Cloud services use `--transport http` with a URL. Local tools use `--transport stdio` with a command path. Claude Code stores the configuration automatically after setup. #### **What is an MCP server in Claude Code?** An MCP server is an external service that connects to Claude Code through the Model Context Protocol. It acts as a bridge between the AI and tools like databases, APIs, or SaaS platforms. Once connected, Claude Code can read and write data from that service directly. #### **Do I need coding experience to setup MCP in Claude Code?** No. The setup process involves running a few commands and entering credentials. A skill markdown file can automate most of the configuration. If you can copy and paste, you can connect an MCP server to Claude Code. #### **Can I connect multiple MCPs to Claude Code at once?** Yes. Claude Code supports multiple simultaneous MCP connections. Each connection runs independently. I track all of mine in a simple markdown file inside my workspace to stay organized. #### **What happens if my MCP connection fails?** Check the chat logs for error messages. Common issues include expired API credentials, incorrect URLs, or missing authentication. The `/mcp` command inside Claude Code shows connection status and lets you re-authenticate if needed. --- ## 10 Claude Code Usage Tips to Save Tokens (2026) URL: https://ryandoser.com/claude-code-usage-tips/ Markdown: https://ryandoser.com/claude-code-usage-tips.md Published: 2026-08-31 | Updated: 2026-09-30 Categories: Claude Code > These Claude Code usage tips will help you save tokens, reduce costs, and get more done per session. Plus details from the Claude Code leak. **Claude Code usage tips** are the difference between hitting your session limit by noon and getting a full day of productive work done. ### **Why Token Management Matters in Claude Code** Most people think Claude Code counts messages. It doesn't. It counts tokens. Every time you send a message, Claude rereads the entire conversation from the beginning. Message one might cost 500 tokens. Message 30 costs 15,000 because it's reprocessing everything before it. One developer tracked a 100-plus message chat and found that 98.5% of all tokens were spent rereading old history. Only 1.5% went toward the actual output. That means your cost isn't adding up linearly. It's compounding. On top of your own messages, Claude reloads your CLAUDE.md, MCP tool names and instructions, system prompts, skills, and files on every single turn. This invisible overhead drips into your context constantly. Bloated context doesn't just cost more. It produces worse output thanks to a phenomenon called ["lost in the middle,"](https://arxiv.org/abs/2307.03172) where models pay the most attention to the beginning and end of a session while ignoring what's in between. If you're [new to Claude Code](/why-marketers-should-use-claude-code/), understanding this token math early will save you serious frustration. ### **10 Claude Code Usage Tips That Actually Save Tokens** I pulled these from my own experience, community threads, and hours of testing. Organized from simple habits to advanced strategies. #### **1. Start Fresh Conversations Between Unrelated Tasks** This is the single biggest thing you can do. Use /clear between unrelated tasks. Don't carry context about topic A into a conversation about topic B. Every message in a long chat is exponentially more expensive than the same message in a fresh chat. At roughly 500 tokens per exchange, 5 messages costs about 7,500 cumulative tokens. By message 30, you're at 232,000. That 30th message alone costs 31 times more than the first one. Fresh chats reset this compounding entirely. #### **2. Batch Your Prompts Into a Single Message** Three separate messages cost three times what one combined message costs. Instead of sending "Summarize this article," then "Now list the main points," then "Suggest a headline," combine them all into one prompt. You save tokens twice: fewer context reloads, and you stay further from your session limit. The answers often turn out better too because Claude sees the full picture from the start. #### **3. Be Surgical With File References** Don't say "here's my whole repo, go find the bug." Say "check the verifyUser function inside auth.js." Use @filename to point at specific files instead of letting Claude explore freely. If the bug is in one function, paste just that function. Claude needs precision, but so does your input. Every unnecessary file you feed it is tokens burned for nothing. #### **4. Disconnect Unused MCP Servers** Connected [MCP servers](/claude-code-mcps/) used to load every tool definition into your context on every message, and one server alone could add 18,000 tokens. Claude Code now defers those definitions by default with a feature called tool search. Only tool names and server instructions load when a session starts, and a full definition loads when Claude actually needs that tool. That makes an idle server much cheaper, but not free. The names and instructions still load every session, and tool search switches off in some setups, such as when ANTHROPIC_BASE_URL points to a third-party proxy. There, every definition loads up front again. *The Model Context Protocol documentation explains how MCP servers connect external tools to AI models.* Run /mcp at the start of each session and disconnect the ones you don't need. I keep only two or three connected in any given week, and I covered [which servers earn their place in a marketing setup](/mcp-servers-for-marketers/) in a separate post. Better yet, if a CLI exists for the same tool (like Google Workspace CLI instead of the Google Calendar MCP), use that instead. CLIs are faster and cheaper. The [MCP protocol documentation](https://modelcontextprotocol.io/introduction) has a full list of available servers and their tool definitions. #### **5. Use Plan Mode Before Jumping Into Real Tasks** Plan mode lets Claude map out its approach and ask clarifying questions before writing any code. This prevents the biggest source of token waste: Claude going down the wrong path, writing hundreds of lines, and then scrapping everything. Add something like this to your CLAUDE.md: "Do not make any changes until you have 95% confidence in what you need to build. Ask me follow-up questions until you reach that confidence level." #### **6. Keep Your CLAUDE.md Lean** Claude auto-reads your CLAUDE.md at the start of every single chat as system context. If your file is 1,000 lines, every message you send triggers a full reload of all 1,000 lines. Even if you just say "hi." Keep it under 200 lines. Include your tech stack, coding conventions, build commands, and the most important rules. Treat it like an index that routes to where more data lives, not an encyclopedia. Point to [skills](/claude-code-skills-hack/) and reference docs by file path so Claude grabs them only when needed. If you are still deciding which ones to add, start with a [curated set of skills worth installing](/best-claude-skills/). #### **7. Compact at 60% Capacity, Not at the Limit** Auto-compact waits until the window is nearly full, about 967,000 tokens (roughly 97%) on a model with a 1 million token window. By that point, your context is already degraded and output quality has dropped. Run /context to check your capacity percentage, and at about 60%, run /compact with specific instructions on what to preserve. *The Claude Code CLI reference lists all available slash commands including /clear, /compact, and /context.* After three to four compacts in a row, quality starts to degrade further. At that point, get a session summary, run /clear, paste the summary into a new chat, and keep going. The full list of available commands is in the [Claude Code CLI reference](https://docs.anthropic.com/en/docs/claude-code/cli-usage). #### **8. Long Breaks Cost You (Prompt Cache Timeout)** Claude Code uses prompt caching to avoid reprocessing unchanged context. That cache expires. On a Claude subscription, within your plan's included usage, the main conversation gets a one-hour cache. On an API key or a cloud provider it is five minutes by default, and on a subscription it drops to five minutes once you go past your plan limit and start drawing on usage credits. Step away for longer than your cache lasts and your next message reprocesses the whole conversation without the cache discount, which burns noticeably more of your usage. This is why some people feel their usage randomly spikes after coming back from lunch. If you're stepping away for a while, do a /compact or /clear before you leave, so that first message back is not re-reading a giant context. #### **9. Pick the Right Model for the Task** Choosing the right model is the most impactful decision you make daily. Opus 5.5 is now the Claude Code default on every paid plan, and it is what I run for most of my own work. Sonnet 5.5 costs half as much per token and handles most coding and bulk work well. Haiku 4.5 costs half of Sonnet and handles formatting, brainstorming, simple tasks, and sub-agents perfectly. The second lever is effort. You can't turn thinking off on Opus 5.5 or Sonnet 5.5, so /effort is the control. Drop it to low for mechanical work and save the higher levels for the hard problems. *Anthropic's model comparison page, captured back when Opus 4.6 was the newest model, breaks down the differences between Opus, Sonnet, and Haiku.* You can also bring in external tools like Codex for code reviews. Let Sonnet and Haiku handle the volume work, like batch jobs and sub-agents, and keep Opus for the tasks where judgment matters. If you're running [agent teams](/claude-code-agent-teams/), delegate research and one-off tasks to Haiku sub-agents whenever possible. Check the [Claude pricing page](https://platform.claude.com/docs/en/about-claude/pricing) to compare costs across tiers. #### **10. Stop Scheduling Around Peak Hours** This tip used to tell you to push heavy work into the evening. That advice is now dead, and it is worth knowing why. Anthropic briefly drained your 5-hour session window faster during weekday peak hours. On May 6, 2026 it [removed the peak hours limit reduction](https://www.anthropic.com/news/higher-limits-spacex) on Claude Code for Pro and Max accounts, and doubled the five-hour rate limits for Pro, Max, Team, and seat-based Enterprise plans at the same time. So on Pro and Max there is no longer a clock to work around. Run the big refactor at 9 AM if that is when you are sharp. The nine tips above are what actually move your usage now, and they matter more than the hour on your calendar. ### **What the Claude Code Leak Revealed (and What Shipped)** Anthropic's source code leak earlier this year (512,000 lines of code across nearly 2,000 files) revealed several features that were unreleased at the time. Here is where they stand now. **Kairos** showed up in the leak as an always-on background mode with an "auto-dream" feature, modeled on how humans consolidate memories during sleep. As described, it would review your chat history while you were away, summarize what happened, and store compressed context in memory files. Anthropic has not documented it as a Claude Code feature. **Ultra Plan** sent complex planning to a cloud session that you reviewed in your browser. It did ship, as /ultraplan in April 2026, and Anthropic has since removed it. The Claude Code docs now point you to plan mode instead, which is tip 5 above. **Mythos** was the leak's model tier above Opus, and it has since shipped. Claude Mythos 5 and Mythos 5.1 are now on [Anthropic's pricing page](https://platform.claude.com/docs/en/about-claude/pricing) at $10 per million input tokens and $50 per million output, the same rate as Fable 5.1 and two and a half times what Opus 5.5 costs. Access is by invitation only, through a program called Project Glasswing. So of the three, only Mythos is something you can use today, and only by invitation. The ten tips above are what actually move your usage. ### **Ryan's Final Thoughts** Token management isn't about being cheap. It's about being intentional. The people who master these habits don't just save money. They get better output, longer sessions, and fewer interruptions. Start with fresh chats and batched prompts. Add the advanced strategies as they become second nature. Your future self will thank you. ### **Claude Code Usage Tips FAQs** #### **How many tokens does Claude Code use per session?** It depends on conversation length, MCP servers, and loaded files. A fresh session with no chats already uses tens of thousands of tokens from system prompts, tools, and configuration files, and /context shows you the breakdown. A 30-message conversation can easily hit 232,000 cumulative tokens due to compounding context reloads. #### **Does plan mode actually save tokens in Claude Code?** Yes. Plan mode prevents Claude from writing code down the wrong path, which is the single biggest source of wasted tokens. By clarifying the approach upfront, you avoid costly redo cycles where Claude generates hundreds of lines that get scrapped entirely. #### **What is the prompt cache timeout in Claude Code?** It depends on how you pay. On a Claude subscription, within your plan's included usage, the main conversation gets a one-hour cache. On an API key or a cloud provider it is five minutes by default, and a subscription drops to five minutes once you are drawing on usage credits past your plan limit. Step away for longer than that and your next message reprocesses the entire conversation without the cache discount. Run /compact or /clear before long breaks to shrink that hidden cost spike. #### **Should I use Opus or Sonnet in Claude Code?** Opus 5.5 is the Claude Code default on every paid plan, and at $4 per million input tokens and $20 per million output it costs less than earlier Opus models. Sonnet 5.5 is half that price and handles most coding and bulk work well, so switch to it when a task is high-volume rather than hard. For simple tasks like formatting, brainstorming, and sub-agent work, Haiku 4.5 costs half of Sonnet 5.5 and a quarter of Opus 5.5 per token. --- ## Claude Skills vs Projects: Which One Should You Use? URL: https://ryandoser.com/claude-skills-vs-claude-projects/ Markdown: https://ryandoser.com/claude-skills-vs-claude-projects.md Published: 2026-08-31 | Updated: 2026-08-31 Categories: Claude Code > Claude Skills vs Projects compared. A Project is where Claude works. A skill is the procedure it runs, in a folder you can version and take with you. If you are weighing **Claude Skills vs Projects**, the real question is not which feature is newer. It is which one you actually own. A Claude Project is a workspace inside the Claude app. A Claude Skill is a folder, anchored by a SKILL.md file, that teaches Claude how to do one specific job. They look similar on the surface. Both let you save instructions, add reference files, and stop re-explaining yourself every session. But they behave very differently the moment you try to scale, switch tools, or sell what you built. After using both for real client work and my own products, I moved almost everything I care about out of Projects and into Skills. Here is where each one wins, and why I made that call. ### **What Is a Claude Project?** A Claude Project lives inside Claude.ai. You create a Project, write some custom instructions, and upload a few files for context. From then on, every chat inside that Project remembers those instructions and files. It is a great way to organize work. If you have a client whose brand voice you keep explaining, a Project holds that voice in one place. You open the Project, start a chat, and Claude already knows the rules. Projects are easy. There is no setup, no terminal, no folder structure. For someone who lives in the chat interface, a Project is the fastest way to stop starting from zero. The limits show up later. A Project stays inside Claude. You cannot version it cleanly, and you cannot hand the working setup to someone outside your organization. ### **What Is a Claude Skill?** A Claude Skill is an SOP for AI. Think of it as a standard operating procedure, written in plain markdown, that teaches Claude how to handle one task from start to finish. I keep mine granular. One skill writes SEO blog posts. A separate skill writes email newsletters. Another handles LinkedIn posts. I do not build one giant mega-skill that tries to do everything, because a focused skill gives better output than a bloated one. The file itself is simple. It is a `.md` document with your steps, your examples, your rules, and your past work. Claude Code reads it and follows it like a recipe. You can build and run skills in the Claude app and in Claude Code, and the instructions stay readable in any agent that supports the Agent Skills format. If you want the full walkthrough, I broke down [three ways to create Claude Skills](/claude-skills/) in a separate guide. The short version is that you do not need to write a single line of code to make one. ### **Portability Is Where They Actually Split** This is the split that decides it. **Claude Skills vs Projects** is really a question about ownership. If Claude Code disappeared tomorrow, my skills would not. They are markdown files sitting in a folder on my computer. I could drop them into Codex, Gemini CLI, or whatever AI agent shows up next, and keep working. The instructions transfer because they are just text. Projects do not travel. Neither do Custom GPTs. You can export your data and you can share a Project with your team, but what you cannot do is lift the working setup out and run it somewhere else. If a platform changes the rules, the setup is what you rebuild. I ran into this firsthand when I [switched from ChatGPT to Claude](/switch-from-chatgpt-to-claude/), and it is the same trap I broke down in [Custom GPTs vs ChatGPT Projects](/chatgpt-projects-vs-custom-gpts/). A Project is a room you were given. A skill is a tool you can carry out of it. That sounds like a small distinction until your entire workflow depends on it. When the setup only runs in one place, you are betting your working process on someone else's roadmap. ### **Both Get Better. Only One Gives You Version History.** The second gap is subtler than most comparisons make it, and it is worth getting right. Both improve over time. The difference is whether that improvement has a history you can roll back. When Claude makes a mistake mid-task, you correct it once and tell it to update the skill file. The next time you run that skill, the correction is part of the instructions it reads, and you can open the file and see the exact line that changed. That is the part that matters: the improvement is a diff you can review, revert, or copy into another skill. I take this further with an automation that patches my skills after the same issue shows up a few times, so the fix lands without me opening the file myself. Something still has to write the change, which is the honest version of "self-improving". You can read how I [turned that into a Claude side hustle](/claude-ai-side-hustle/). A Project improves too, and more automatically than most comparisons admit. Each one keeps its own memory space that builds as you chat, on by default for Free, Pro and Max and off by default on Team and Enterprise until an owner turns it on. You can read exactly what it has stored under Settings and Memory, edit a topic, or delete one. What you cannot do is put that under version control. There is no history of what changed and when, no way to roll back to last month's version, and no way to lift the good version into a second Project or hand it to a teammate as a starting point. A skill lets you have all four the moment you put the folder under version control, which is the practical upside of it being a file. That is the whole of the difference, and it is narrower than the usual pitch but it is the part that holds up. ### **Where a Project Is Still the Better Pick** I am not telling you Projects are useless. They are not. If you live entirely in the Claude chat app, never touch Claude Code, and just want a tidy place to keep instructions for a recurring task, a Project is fine. It is the lowest-friction option when you want a place to keep things rather than a procedure to run. Projects also work well for quick, throwaway context. Researching a topic over a few days? Drop your notes in a Project and chat away. You are not building an asset there, and that is okay. Not everything needs to be portable. Projects are built for organizing conversations. Skills are built for systems you keep. ### **When to Build a Claude Skill Instead** Build a skill the moment a task becomes repeatable and valuable. If you do something more than a few times a week, and the quality matters, it deserves a skill. Content production, client deliverables, anything you would hate to lose. That is skill territory. Skills are also the cleanest format if you want to sell a workflow rather than describe one. You cannot hand a customer a Project. You can hand them a skill folder that runs. That is exactly what I did, and I wrote the full playbook on [how to sell Claude Skills as a digital product](/sell-claude-skills/). The deeper reason is the one I keep coming back to. Marketers who treat AI like a chatbot stay stuck at the chatbot ceiling. The ones who build real systems pull ahead, which is the whole argument behind [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) in the first place. ### **Claude Skills vs Projects FAQs** #### **What is the main difference between Projects and Skills?** Scope. A Project is scoped to one body of work and its setup runs only inside Claude. A skill is scoped to one task and travels as a folder you control. That is why the two answer different questions: a Project answers what Claude should know, and a skill answers how Claude should do it. #### **Can I use Claude Skills in Projects?** Yes, and it is the setup I would actually recommend. They are not competing features. Keep the background material for a client or a launch in a Project, then invoke a skill inside that Project to do the repeatable work on it. The Project supplies the context and the skill supplies the method. #### **What are the differences between Claude chat and Projects?** A plain chat has no shared knowledge base behind it, so the reference material you want Claude working from has to come along each time. A Project keeps a knowledge base of files and custom instructions available to every chat you start inside it, and on Team and Enterprise plans it can be shared with your organization. A Project is a workspace scoped to one topic; a chat is a single conversation. #### **Should you use Projects in Claude?** Yes, for anything with a body of reference material behind it: a client, a launch, a codebase. Two things worth knowing before you commit to one. Project memory is on by default on Free, Pro and Max but off by default on Team and Enterprise, so on a work account it may not be doing what you assume. And a Project is per-account unless you are on Team or Enterprise, where it can be shared with your organization. If you have never built either, start with a Project. It takes about a minute and shows you which parts you keep retyping. #### **Are Claude Skills just markdown files?** Not quite. A skill is a folder anchored by a SKILL.md file, and it can carry scripts and reference files alongside those instructions. The instructions themselves are plain markdown, which is the part that matters: you can version a skill in git, edit it in any editor, copy it between machines, and revise it over time. That is what makes a skill an asset and a Project a workspace. ### **Claude Skills vs Claude Projects: The Verdict** Use a Project when you want a clean home for one task inside the Claude app and nothing more. Build a skill when you want something that travels with you across tools and improves in a file you can actually read. For me, that covers almost everything that touches money or clients. The feature you pick today decides how much of your work survives the next platform shift. Projects keep your conversations organized. Skills keep your business portable. If betting your business on someone else's roadmap sounds like a bad idea, the fix is to keep your process in files you control. I packaged 25+ of the skills I run every day, copywriting, SEO, YouTube, email, and social, into my [Claude Code Skills Stack](https://skills.ryandoser.com/). Drop the folders into your own setup and you have a portable, editable workflow from day one. --- ## 7 Best Postiz Alternatives in 2026 (Tested by an Agency Owner) URL: https://ryandoser.com/postiz-alternatives/ Markdown: https://ryandoser.com/postiz-alternatives.md Published: 2026-08-31 | Updated: 2026-09-30 Categories: AI Tool Reviews > Seven Postiz alternatives priced across six different billing units, plus the three cases where leaving Postiz is the wrong move entirely. Most written guides to **Postiz alternatives** on page one come from companies selling one of the alternatives, which is why the same three tools keep winning. I take money from exactly one company on this list and I am telling you which one: [Blotato](https://www.blotato.com/?ref=rdoser) is a client of mine and my #1 pick, so weigh that entry against the math rather than my word. I have no relationship with the other six. Here is the part those vendor lists skip: leaving Postiz is often the wrong move. ### **Who I Am to Rank These** I run an agency and a content business. Publishing is a thing I do every week across my own channels and client accounts, not a category I write about from the outside. Two limits on that, up front, because they change how you should read the rankings. I have run Postiz on their hosted cloud plan and I publish through Blotato most weeks. The rest I have set up and posted through rather than lived in for a year, which is enough to judge setup, pricing and what breaks early, and not enough to tell you how they behave at month eleven. The bigger one: **I have never self-hosted Postiz, or anything else.** Where the self-hosted sections below make a claim, it comes from Postiz's own documentation or from what self-hosters report, and I say which. What I can speak to firsthand is the adjacent version of that work. I spent a long stretch running my publishing through n8n, rebuilding broken nodes and re-authing dead API keys, and that is the same hour of the week under a different name. Pricing here was checked live on each vendor's own page, on the monthly toggle. That last detail matters more than it should. Most of these pages default to annual billing and print the annual rate with a "/month" label next to it. ### **Best Postiz Alternatives at a Glance** Six different billing units sit in this table. That is the actual difficulty of the comparison, and it is why "cheapest" depends entirely on how many accounts you connect. | Tool | Best for | Starts at (monthly billing) | What you pay per | Who runs the server | | Blotato | Creators who want an AI agent writing and publishing without a per-account bill | $29/mo flat | Plan, 20 accounts included | Blotato | | Mixpost | Self-hosters whose objection is subscriptions, not server work | $299 one time (Pro) | License, paid once | You | | Zernio | Anyone running under 10 accounts who wants a free tier that stays free | Free for 2, then $6/account | Connected account | Zernio | | Buffer | Creators on 3 or 4 channels who want the thing to simply never break | Free, then $6/channel | Channel | Buffer | | Upload-Post | Developers who need reach into Discord, Telegram and Reddit | $24/mo (Basic) | Profile, 5 included | Upload-Post | | Post Bridge | A flat-priced agent on a handful of accounts, if 10 platforms are enough | $39/mo (Marketer) | Plan, 15 accounts at $39 | Post Bridge | | Staying self-hosted | Data residency rules, existing infrastructure, or a need to modify the code | $0 license, plus your hours | Hosting, plus maintenance time | You | One column that used to belong here is gone. Every hosted tool on this list ships an MCP server now, so an AI agent can drive any of them, and that stopped being a reason to pick one. One vendor is missing from that table on purpose. Ayrshare bills per customer profile rather than per plan or channel, which puts it in a different category and at a much higher floor, so I gave it [a separate pricing teardown](/ayrshare-alternatives/). ### **The Real Cost of Self-Hosting** Self-hosting is free the way a puppy is free. Per Postiz's documentation and the reports of people running it, here is what you take on. Platform app approvals, which you apply for yourself, per platform, under your own developer account. That is the part most people do not see coming. Then OAuth token refreshes that break quietly, version upgrades that touch the database, server patching, and backups you have to test, because an untested backup is a rumor. Add uptime monitoring, because a scheduler that is down at 9am publishes nothing at 9am and does not tell you. Now price your own hour. Two hours in a bad month, against a $29 cloud plan, means self-hosting pays only if your time is worth under $15 an hour. The failure mode that actually hurts is not downtime. It is silent failure, and that part I have lived on managed tools rather than my own box. Social connections drop on their own, every scheduler I have used does it, and nothing announces it. On a hosted tool you reconnect in the dashboard and move on. On your own box, that same silent failure is yours to detect, diagnose and fix, and you usually find out when someone asks why you went quiet for a week. *Self-hosting moves the cost from your invoice to your calendar. That is the whole decision.* ### **The 7 Best Postiz Alternatives** Ranked by who they actually fit, with the condition attached to each recommendation so you can tell in one line whether it is you. #### **1. Blotato (Best for an AI Agent Doing the Writing Too)** *Blotato bundles content generation with publishing, which is the main thing Postiz does not do.* *Affiliate and client relationship. [Full disclosure here](/disclosure/).* [Blotato](https://www.blotato.com/?ref=rdoser) is the one I publish through most weeks, and its pitch against Postiz is not price, since both start at $29. It is that the $29 buys a different unit and includes the writing. | Cost as you scale | What you pay | | 5 accounts | $29/month | | 20 accounts | $29/month | | 21 accounts | $97/month, the next tier up | | 40 accounts | $97/month | | 100 accounts | $499/month | | Cost per account at 20 | $1.45 | | Cost per account at 5 | $5.80 | **Pros:** - Flat $29/month for 20 connected accounts, so the bill does not move as you add channels - Writes the posts and generates images and video, which Postiz only partly does - API and hosted MCP server included on the entry plan, not gated to a higher tier **Cons:** - No free tier at all, and generating an API key immediately ends the trial and starts billing - Analytics covers 8 of the 9 platforms, with LinkedIn returning no metrics - Comments and DMs reach Instagram and Facebook only - It applies its own posting caps that are stricter than the platforms' own, including 25 Facebook posts per Page per day **Best for:** Creators who want one flat bill covering 20 accounts and want the tool writing the drafts, not just queuing them. **Pricing:** $29/mo Starter (20 accounts, 1,250 AI credits), $97 Creator (40 accounts), $499 Agency (100 accounts). Credits are spent only on AI image and video generation. **Free trial:** 7 days on every plan, card required, and it excludes the API. If you came for the API, plan on starting the subscription rather than trialing it. **Bottom line:** Count your networks first. Blotato earns the $29 when 9 platforms cover your stack and you want the drafts written for you, and it loses outright to Postiz the moment Mastodon or Discord is on your list. #### **2. Mixpost (Best for Owning It Without a Subscription)** *Mixpost sells a license rather than a subscription, and you still run the server.* [Mixpost](https://mixpost.app/) is the honest answer for the reader whose objection to Postiz is not the maintenance at all. Some people self-host because they refuse to rent software, and for them a monthly bill is the problem being solved. | Break-even against a $29/month plan | Result | | Months to recoup $299 | 11 | | Year one total | $299 plus your hosting | | Year two total | $0 plus hosting, if you skip renewing updates | | Year three total | $0 plus hosting | | A $29 plan over 3 years | $1,044 | | Licensed domains | 1 per Pro license | | Update window | 12 months, then optional | **Pros:** - One-time license instead of a recurring bill, so the cost stops after you pay it - A free open-source Lite edition to try the model first - No AGPL copyleft obligation, which matters if you plan to build on it commercially **Cons:** - Solves the subscription problem and does nothing at all about the maintenance problem - Its MCP server runs on your own instance, so an agent can only reach it after you have stood up the server - The Pro license covers one domain or subdomain, and updates are free for one year **Best for:** Self-hosters who want ownership and accept the operational cost, not people trying to escape that cost. **Pricing:** $299 one-time for Pro, $1,199 for Enterprise (white label and subscription management). A free Lite edition exists. **Free trial:** No trial, but the open-source Lite edition is free to run indefinitely. **Bottom line:** Buy Mixpost if renting software is the thing you object to. If your Saturdays are the thing you object to, this fixes nothing, and you should look at any hosted option on this list instead. The licensing contrast matters if you plan to build on either one commercially, and I worked through Postiz's AGPL terms in [Postiz vs Blotato](/postiz-vs-blotato/). #### **3. Zernio (Best If You Want the Free Feeling Without the Server)** *Zernio meters per connected account, with the first two free and no card required.* [Zernio](https://zernio.com/pricing) is the closest thing here to keeping what you liked about self-hosting. You pay for exactly the accounts you connect, and at small scale that number is zero. | Connected accounts | Monthly bill | | 2 | $0 | | 5 | $18 | | 6 | $24 | | 7 | $30, where a $29 flat plan overtakes it | | 10 | $48 | | 20 | $78 | | 100 | $318 | **Pros:** - First 2 connected accounts are free with no credit card, and stay free - Graduated pricing, so each tier's rate applies only to accounts inside that range - Inbox and comments on every platform that has one, which is broader than most tools here manage **Cons:** - Per-account billing gets expensive fast in the middle band, where 20 accounts runs $78/month - It does not write your content, so you bring the posts - X analytics and inbox sync pass X's own per-call API charges straight through to you **Best for:** Anyone running under 10 connected accounts who wants a real free tier rather than a countdown clock. **Pricing:** Accounts 1-2 free, $6/month each for accounts 3-10, $3 for 11-100, $1 past that. Ten accounts works out to $48/month. **Free trial:** Not a trial, an actual free tier. Two accounts, no card. **Bottom line:** Zernio is the cheapest option here up to 6 connected accounts, where it runs $24 a month, and at 7 it hits $30 and a $29 flat plan has already passed it. I would read its comparison pages with some skepticism, and I wrote up [why they need a second look](/zernio-review/). #### **4. Buffer (Best for Wanting a Scheduler That Never Breaks)** *Buffer bills per channel, which makes it cheap at four connections and painful at twenty.* [Buffer](https://buffer.com/pricing) earns a spot because a real share of people who try self-hosting a scheduler just wanted a scheduler. If that describes you, the boring answer is the correct one. | Channels | Essentials, billed monthly | | 1 | $6 | | 3 | $18 | | 4 | $24 | | 10 | $60 | | 11 | $64, where the volume rate kicks in | | 25 | $120 | | 50 | $195 | **Pros:** - The most mature product in this roundup, with the fewest surprises - A genuinely useful free plan: 3 channels, 10 scheduled posts each, plus one API key and 3,000 requests a month - Per-channel rate drops with volume, reaching $4 per channel from 11 to 25 **Cons:** - Per-channel billing punishes wide setups, since 10 channels is $60/month against Blotato's flat $29 for 20 accounts - Reaches far fewer networks than Postiz does - The pricing page defaults to the yearly toggle and prints the annual rate with a "/month" label, which is how nearly every comparison of Buffer gets it wrong **Best for:** Creators on 3 or 4 channels who would rather stop optimizing and start posting. **Pricing:** Free for 3 channels. Essentials is $6/channel/month ($5 on annual billing), Team is $12/channel/month ($10 annual). **Free trial:** A permanent free plan rather than a trial, which is more useful than either. **Bottom line:** At four channels Buffer costs $24/month and will not page you at 2am, and that is a good trade. Past ten channels the per-channel math turns against it and a flat plan wins, which I worked out at both account sizes in [Blotato vs Buffer](/blotato-vs-buffer/). #### **5. Upload-Post (Best for Reaching Networks the Big Tools Skip)** *Upload-Post covers 22 platforms, including Discord, Telegram and Reddit.* If part of why you picked Postiz was its reach into networks the mainstream tools ignore, [Upload-Post](https://www.upload-post.com/pricing) is the hosted option that comes closest to matching it. | Platform | Reachable on Upload-Post | | Discord | Yes | | Telegram | Yes | | Reddit | Yes | | Mastodon | Yes | | WordPress | Yes | | Dev.to and Hashnode | Yes | | The mainstream nine | Yes, all of them | **Pros:** - 22 platforms including Discord, Telegram, Reddit, Mastodon and WordPress - A real free tier with 2 profiles and 10 uploads a month, no card required - Unlimited uploads on every paid plan, plus Python and JavaScript SDKs **Cons:** - Profiles, not accounts, are the unit, and the add-on packs do not stack - Posting links on X is a separate $19/month add-on capped at 50 link-posts - It publishes what you give it and does not write anything **Best for:** Developers and agencies whose distribution list runs past the usual nine networks. **Pricing:** Free for 2 profiles. Basic is $24/month for 5 profiles, Professional $50 for 25, Advanced $147 for 75. Annual billing cuts roughly a third on the lower two tiers. **Free trial:** Yes, and the free tier is permanent rather than timed. **Bottom line:** The 22-platform reach is the entire argument for Upload-Post, so it comes down to whether your distribution list actually uses it. Publishing only to the mainstream nine means paying for coverage that sits idle. #### **6. Post Bridge (Best for a Flat-Priced Agent on a Handful of Accounts)** *Post Bridge's agents page as captured in August 2026, when its entry plan was $29. It now starts at $39.* [Post Bridge](https://www.post-bridge.com/pricing) aims at the same reader Postiz's agent positioning does, and it is the most direct head-to-head on this list. Earlier in 2026 it ran two different prices for the same product depending on which page you landed on. That is fixed. It now sells two plans with the API included on both, and the interesting question is no longer which page you read but whether 15 accounts is enough. | Post Bridge tier | What it costs | | Marketer | $39/month, 15 accounts | | Operator | $99/month, 99 accounts, then $1 per extra account | | REST API, CLI and MCP | Included on both plans | | Yearly billing | Two months free | **Pros:** - MCP access and the REST API are included on both plans, starting at $39 - The $99 Operator plan covers 99 connected accounts and adds $1 per account after that, which undercuts most per-account pricing at scale - Ships an installable agent skill and a CLI, not only an MCP endpoint **Cons:** - Marketer includes 15 connected accounts, and account 16 means jumping to the $99 Operator plan - 10 platforms, so it does not solve the reach problem that sends people to Postiz - Analytics is still labeled beta **Best for:** Someone running a small number of accounts who wants an agent posting through a real API and does not need more than 10 platforms. **Pricing:** Marketer $39 for 15 accounts and Operator $99 for 99 accounts, then $1 per extra account. The REST API, CLI and MCP are included on both, and yearly billing gives two months free. **Free trial:** A 7-day trial with no charge due at signup. **Bottom line:** Post Bridge is a clean flat-priced on-ramp to an agent that posts, as long as you count your accounts first. At 15 accounts it is $39 and at 16 it is $99, so the tier you actually land on matters more than the headline number. #### **7. Staying Self-Hosted (Best When Control Is the Actual Requirement)** Leaving is not automatically the right answer, and a list that never says so is a sales page. Three cases where I would tell you to stay put. Stay if data residency is a requirement rather than a preference, because a client contract or a regulation says so. No managed tool on this list solves that for you. Stay if you already run infrastructure. With a cluster, monitoring, and a backup routine you actually test, Postiz is one more small service on a system you maintain anyway, and the marginal cost really is near zero. Stay if you need to modify the tool. Open source means you can change behavior, and no hosted API will ever match that. Leave if publishing is a means to an end for your business rather than the business itself. Every hour spent on your scheduler is an hour not spent on the content going through it. ### **How to Choose Between These Postiz Alternatives** The same questions I work through on a client build, in the order I ask them. - **How many accounts will you connect twelve months from now?** Under 10 favors per-account pricing. Over 15 favors flat. - **Do you need a network outside the mainstream nine?** Discord, Telegram, Mastodon and Reddit narrow the field to two options fast. - **Are you buying a publisher or a writer?** Most of these queue content you already made. One of them makes it. - **Is your objection the subscription or the maintenance?** They point at opposite answers, and conflating them is the most common mistake I see. - **Does anything legal or contractual dictate where the data sits?** If yes, this decision was already made for you. Two more things worth knowing before you commit. Every hosted tool here ships an MCP server, so agent compatibility is no longer a tiebreaker, and I would not let a vendor sell it to you as one. And check whether API access is included at the tier you are actually buying, because it is gated differently on nearly every one of these. ### **Which One Should You Pick?** Under 10 accounts and cost-sensitive: Zernio, free for the first two. Three or four channels and tired of fiddling: Buffer. Want the tool writing the posts: Blotato at $29 flat. Publishing to Discord or Telegram: Upload-Post. Refuse to rent software: Mixpost, once, and keep the server. A flat-priced agent that posts on 10 platforms without per-account math: Post Bridge at $39. Bound by data residency or already running infrastructure: stay where you are. ### **What About Publer, Metricool and Hootsuite?** They show up on most lists in this category and they are not ranked here, which is deliberate. I have not set them up and posted through them the way I did with the seven above, and ranking software I have not touched is the exact thing that makes vendor roundups worthless. [Publer](https://publer.com/pricing) is the one I would look at first on price, at $5 for the first account and $4 for each additional on Professional. [Metricool](https://metricool.com/pricing/) is the analytics-led pick and I compared it against my own stack in [Blotato vs Metricool](/blotato-vs-metricool/). [Hootsuite](https://www.hootsuite.com/plans) is the enterprise option, and its entry price is multiples of everything above. Any of the three could be right for you. I just have not earned the right to rank them. ### **Ryan's Final Thoughts** The self-hosting decision is not about money, and pretending otherwise is why people end up unhappy with whatever they choose. It is about which failures you want to own. Run it yourself and you own uptime, approvals, upgrades and silent failures, in exchange for control and a $0 line item. Pay someone and you own a subscription, in exchange for someone else waking up when OAuth breaks. My rule is to self-host the things where control is the point and pay for the things where reliability is the point. Publishing is a reliability job for me, so I pay. If you already run servers well, Postiz is excellent and the people running it happily are not wrong. ### **Postiz Alternatives FAQs** #### **What is the best free Postiz alternative?** Zernio, if you connect two accounts or fewer, since its first two are free with no card and no time limit. Buffer's free plan covers 3 channels with 10 scheduled posts each plus API access. Upload-Post gives you 2 profiles and 10 uploads a month. All three are permanent free tiers rather than trials that expire. #### **Is there an open-source alternative to Postiz?** Mixpost is the main one. It is self-hosted and open source, with a free Lite edition limited to a few networks and a $299 one-time Pro license. Unlike Postiz it carries no AGPL copyleft obligation, which matters if you intend to build a commercial product on top of it. #### **Is Postiz really free?** The software is free and open source if you run it on your own infrastructure. You then absorb hosting costs, platform app approvals, upgrades, monitoring and backups. Postiz also sells hosted plans from $29/month for 5 channels if you would rather not run it yourself. #### **Why do people stop self-hosting their social scheduler?** Maintenance, not price. Platform app approvals, OAuth tokens expiring, upgrades that touch the database, and publishing failures that happen silently. The subscription you avoided is usually cheaper than the hours you spend once you price your own time honestly. #### **Does self-hosting Postiz get around platform API approvals?** No, and this surprises people. When you self-host you apply for each platform's API access yourself, per platform, under your own developer account. Managed services have already done that work, and it is a large part of what you are paying them for. #### **Which Postiz alternatives work with AI agents?** All of them. Blotato, Zernio, Upload-Post, Buffer and Post Bridge each run a hosted MCP server that Claude Code, Codex and similar agents can call. Mixpost's runs on your own instance instead, so an agent can only reach it once you have stood up the server. Compare what sits behind the server rather than its presence: account limits, platform coverage, and whether API access is included at your tier. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine and my account there is comped rather than paid. I have no relationship with Postiz, Zernio, Upload-Post, Mixpost, Buffer, Post Bridge, Publer, Metricool or Hootsuite. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## Postiz vs Blotato: Which AI Social Media Tool Wins in 2026? URL: https://ryandoser.com/postiz-vs-blotato/ Markdown: https://ryandoser.com/postiz-vs-blotato.md Published: 2026-08-31 | Updated: 2026-09-30 Categories: AI Tool Reviews > Postiz vs Blotato on pricing, channel limits, AGPL self-hosting, and MCP support. Both start at $29, but not for the same thing. **Postiz vs Blotato** comes down to one question: do you want to own the software or rent the outcome? Postiz is open source, self-hostable, and gives you 5 channels for $29 a month on its cloud plan. [Blotato](https://www.blotato.com/?ref=rdoser) is hosted only and gives you 20 channels for the same $29. Both ship an MCP server, so both work with Claude and other AI agents, and [both show up in my roundup of MCP servers for marketers](/mcp-servers-for-marketers/). I run Blotato daily. It publishes most of my content through Claude Code, and I have been on it since early 2025. I signed up for Postiz cloud and ran my own accounts through it to write this, so the comparison below is based on using both rather than reading two marketing pages. One boundary worth stating up front: I used Postiz on its hosted plan, not self-hosted on my own server. So when I get to the self-hosting section, I am reporting what the docs specify and what the community reports, not what I personally maintained at 2am. Everything about the actual app is firsthand. ### **Postiz vs Blotato at a Glance** | | Postiz | Blotato | | Entry price | $29/mo (Standard) | $29/mo (Starter) | | Channels at entry | 5 | 20 | | Cost for ~20 channels | $49/mo (Pro, 30 channels) | $29/mo | | Cost for ~30 channels | $49/mo (Pro) | $97/mo (Creator, 40) | | Self-hosting | Yes, AGPL-3.0 | No | | Platforms | 28+ (21 with in-app setup) | 9 | | MCP server | Yes, 9 tools | Yes | | CLI for agents | Yes | No, API and MCP | | AI content generation | AI copilot, images, video by tier | Text, images, video | | Free trial | 7 days | 7 days, excludes API | ### **What Each Tool Is Actually Built For** These two get compared constantly because both now market themselves at the AI agent crowd. Underneath that shared pitch they solve slightly different problems, and picking the wrong one is usually a mismatch of intent rather than a mismatch of features. Postiz began as an open-source scheduler and still carries that DNA. Its headline is running social media on autopilot with AI agents, and it backs that with a CLI, an MCP server, webhooks, and a public API on every plan. It is a developer tool that grew a friendly calendar on top. The people who love it tend to be the people who wanted to own their stack. ![Postiz homepage showing agentic social media scheduling for AI agents](/images/2026/07/postiz-vs-blotato-postiz-home.jpg) Blotato started from the opposite end. It was built to generate content first and publish second, which is why the entry plan bundles AI writing, image generation, and video alongside the 20 channels. Its 2026 repositioning toward agent infrastructure added the API and MCP surface, but the creation engine is still the reason people pay for it. You can feel this the moment you open each one. Postiz drops you into a calendar and expects you to bring posts to it. Blotato drops you into a content workspace and expects you to bring a source, a video, an article, an idea. ![Blotato homepage positioning the product as social media automation for AI agents](/images/2026/07/postiz-vs-blotato-blotato-home.jpg) So the real question is not which has more features. It is whether you already have something writing your content. If you do, you are shopping for a publishing layer and Postiz is a strong candidate. If you do not, a publishing layer alone leaves you with a scheduler and nothing to schedule. ### **Pricing: The $29 Is Not the Same $29** This is the part most comparisons get lazy about. Both tools open at $29 a month, which makes them look interchangeable. They are not. Postiz Standard at $29 gives you 5 channels, unlimited posts, the AI copilot, API access, and 3 AI videos a month. Team at $39 moves you to 10 channels and unlimited team members. Pro at $49 gets you 30 channels, and Ultimate at $99 covers 100. [Blotato](https://www.blotato.com/?ref=rdoser) Starter at $29 gives you 20 channels and 1,250 AI credits. Creator at $97 moves to 40 channels and 5,000 credits, and Agency at $499 carries 28,000 credits. ![Postiz pricing page showing Standard $29, Team $39, Pro $49, and Ultimate $99 plans](/images/2026/07/postiz-vs-blotato-postiz-pricing.jpg) Blotato's rate card is shaped differently. Three tiers instead of four, and the jump between them is much steeper, which turns out to be the whole story once you count accounts. ![Blotato pricing page showing Starter $29, Creator $97, and Agency $499 plans](/images/2026/07/postiz-vs-blotato-blotato-pricing.jpg) So the honest read is this. At 5 or fewer accounts the two cost the same and you should pick on features, not price. Between 10 and 20 accounts Blotato is meaningfully cheaper on the cloud version, $29 against $39 to $49. The crossover lands at about 25 channels. Past Blotato's 20-account Starter cap you jump to Creator at $97, while Postiz Pro covers 30 channels for $49 and Ultimate covers 100 for $99, and Blotato publishes nothing between Creator's 40 accounts and Agency at $499. If you genuinely run more than 20 accounts, Postiz is the cheaper cloud product and it is not close. And if you self-host Postiz, the license fee is zero, which is where this comparison gets interesting. ### **Postiz vs Blotato on Self-Hosting and the AGPL Catch** Postiz is genuinely open source. The repository sits at nearly 34,000 stars on [GitHub](https://github.com/gitroomhq/postiz-app) and you can deploy it on your own infrastructure without paying Postiz anything. Blotato has no self-hosted option at all. If that is your requirement, the comparison ends here and Postiz wins. Two things deserve more attention than they usually get. First, the license is **AGPL-3.0**, not MIT. For most readers that is fine. You can self-host it for your own business, run client work through it, and keep your data private with no obligations. The catch only bites if you modify Postiz and offer that modified version to others over a network, which is the classic agency-white-label scenario. Do that and you owe your modifications back under the same license. Read the [license terms](https://www.gnu.org/licenses/agpl-3.0.en.html) before you build a product on top of it. Second, free is not free. Self-hosting means you own the Postgres database, the Redis instance, the upgrade path, and every OAuth token refresh across every connected platform. Social APIs change constantly, tokens expire, and platform approvals are their own bureaucracy. That work does not disappear because the software is free. It moves onto your calendar. If you enjoy running infrastructure, that trade is great. If your goal is to publish content, paying $29 to never think about it is the cheaper deal in real terms. ### **Postiz vs Blotato for AI Agents** Both tools have leaned hard into the agent use case, and this is where they are closest. Postiz exposes an MCP server with 9 tools, so Claude, ChatGPT, Cursor, or any MCP client can list your connected accounts, read a platform schema, and schedule posts through natural language. It also ships a CLI, which is a genuinely nice touch if you want to script posting from a terminal or a CI job rather than a chat window. Blotato exposes an MCP server and a REST API. I use it daily through Claude Code, and the workflow is conversational: point it at a YouTube video, have it write platform-specific posts against a skill file that holds my tone, then publish or schedule without leaving the editor. Here is the full build, start to finish. The detail that sold me on that setup was small. I asked it to schedule a LinkedIn post for 1pm the next day, it checked my calendar, found I already had something in that slot, and asked me to pick another time instead of quietly double-booking. I have written up that whole workflow in my [Blotato review](/blotato-review/), and it is the backbone of my [AI social media system](/ai-social-media-system/). Testing the same kind of thing on Postiz, the MCP connection worked and the agent could list my accounts and schedule posts. What it does not do is write the content for you to the same depth. Postiz has an AI copilot, but Blotato is built around generation and it shows. If your agent is already producing the copy, that gap does not matter and Postiz is the cleaner publishing target. The practical difference is the trial. Postiz gives you 7 days with API access included. Blotato gives you 7 days too, but the API is explicitly excluded, and generating an API key ends the trial and starts billing immediately. If you are evaluating purely as a developer, Postiz lets you test the integration for free and Blotato does not. That is a real advantage and worth knowing before you sign up expecting otherwise. ### **Platform Coverage** Postiz supports 28 or more platforms by its own count, with 21 of them wired up for in-app connection and the rest reachable through the public API. That list includes several Blotato does not touch: Mastodon, Discord, Slack, Telegram, Reddit, Farcaster, Dribbble, Twitch, WordPress, and Dev.to. Blotato covers 9: Instagram, TikTok, LinkedIn, Facebook, X, Threads, Bluesky, Pinterest, and YouTube. On raw count Postiz wins, but count is the wrong metric. Nine platforms covers essentially every network a marketer or creator actually monetizes. The extra Postiz providers matter if you are a developer publishing to Mastodon and Discord communities, and they are irrelevant if you are a business posting to Instagram and LinkedIn. Ask which specific platform you need rather than which number is bigger. If it is Discord, Telegram, or Mastodon, that decides it outright. ### **What Self-Hosting Actually Costs You** Since the free tier is the main reason people choose Postiz, it is worth being concrete about what "free" buys. You need somewhere to run it, which for a small setup means a VPS at roughly $10 to $20 a month once you account for the Postgres and Redis instances Postiz depends on. Call that the easy part. The harder part is maintenance, and here I want to be straight with you: I ran Postiz on its cloud plan, not on my own box. What follows is what the docs specify and what shows up repeatedly in the project GitHub issues, not a war story of my own. Postiz needs Postgres, Redis, and Temporal alongside the app itself, which is more moving parts than a single container. Every connected platform issues OAuth tokens that expire, and when one lapses your posts stop going out until you notice. Several networks require their own developer approval before a self-hosted app can post at all, and that process is between you and the platform. Account connection is the first category listed in the project's own known-issues documentation, and it recurs steadily in the GitHub issues. None of that is a reason to avoid self-hosting. It is a reason to price it honestly. If you already run infrastructure and this is one more service on a box you maintain anyway, the license savings are real and Postiz is a genuinely good piece of software with an active project behind it. If publishing content is the actual goal and servers are not your hobby, $29 a month to make all of it someone else's problem is not the expensive option. ### **Two Things the Comparison Pages Get Wrong** If you search this matchup, the first results you hit are written by the two vendors about themselves. Worth knowing what each leaves out. Postiz's comparison page marks Blotato as having no analytics at all. That is wrong. Blotato tracks views, likes, comments, shares, reach, and watch time on published posts, in the app and through the API. Coverage is nearly complete. Blotato's documentation puts analytics on eight of its nine platforms, with LinkedIn the only one that reports nothing. The same page also lists Blotato as supporting five platforms when it publishes to nine. Blotato's page is more accurate on the numbers, but it leans on Postiz's heaviest self-hosted server requirements without making clear that those apply to running it yourself. If you use Postiz cloud, none of that is your problem, and the hosted version starts at the same $29 Blotato does. Neither page mentions what independent users think. Blotato holds 4.8 out of 5 across 387 reviews on [Trustpilot](https://www.trustpilot.com/review/blotato.com) and 4.7 from 73 on [SourceForge](https://sourceforge.net/software/product/Blotato/). Postiz does not have comparable review volume on those sites, but it has close to 34,000 GitHub stars and ships updates most days, which is its own kind of signal. Different evidence, both worth weighing. ### **Which One Should You Pick?** If you only take one thing from this post, take this diagram. It is the whole decision in one image. ![Two-step decision diagram: if you want to run the server choose self-hosted Postiz, otherwise ask whether you run more than a handful of channels and choose Postiz cloud tiers or Blotato's flat bill with content included](/images/2026/09/postiz-vs-blotato-decision-diagram-v2.jpg) **Pick Postiz if** you want to self-host, you are comfortable owning infrastructure, you need one of the platforms outside Blotato's nine, you want to test an API integration for free before paying, or you run more than 20 channels where Pro at $49 and Ultimate at $99 are clearly the better rate. **Pick [Blotato](https://www.blotato.com/?ref=rdoser) if** you run somewhere between 10 and 20 accounts, you want content generation and publishing behind one flat bill, and you would rather spend your evenings making content than maintaining a scheduler. At 20 channels it is $29 against Postiz's $49, and nothing to host. For most solo creators and small businesses reading this, that second paragraph is the honest answer, and it is the setup I run myself. For developers and self-hosting enthusiasts, the first one is, and I would not try to talk you out of it. If neither fits, I compared eight of these side by side in my roundup of [social media automation tools](/social-media-automation-tools/), and if you are weighing Blotato against a hosted mainstream scheduler rather than an open-source one, [Blotato vs Buffer](/blotato-vs-buffer/) covers that matchup. For the analytics-first alternative, see [Blotato vs Metricool](/blotato-vs-metricool/). If you are weighing Postiz mainly because you would rather not pay a subscription, I also mapped out [the maintenance cost of self-hosting](/postiz-alternatives/) against the managed options. ### **Postiz vs Blotato FAQs** #### **Is Postiz really free?** The software is free to self-host under AGPL-3.0. The cloud version starts at $29 a month for 5 channels. Self-hosting costs you server hosting plus your own maintenance time, so it is free in license terms rather than free in total cost. #### **Does Postiz work with Claude and other AI agents?** Yes. Postiz ships an MCP server exposing 9 tools, so Claude, ChatGPT, Cursor, and other MCP clients can manage posting through natural language. It also has a CLI for scripted workflows. Blotato ships an MCP server and REST API that work the same way. #### **Which is cheaper, Postiz or Blotato?** It depends entirely on channel count. Both start at $29, but Postiz gives 5 channels there and Blotato gives 20. Up to 20 channels Blotato wins at $29 against Postiz Pro's $49. Past 20 the order flips: Postiz Pro covers 30 for $49 while Blotato Creator is $97 for 40, and Blotato publishes no tier between 40 accounts and Agency at $499. Self-hosted Postiz has no license cost at any count. #### **Can I use Postiz commercially if I self-host it?** Yes. AGPL-3.0 permits commercial use, including running it for your own business or client work. The obligation only triggers if you modify Postiz and make that modified version available to others over a network, in which case you must release your changes under the same license. #### **Does Blotato have a free plan?** No. There is a 7-day trial that requires a card and converts to a paid subscription unless you cancel, and the trial excludes API access. Postiz also runs a 7-day trial, but with API access included. #### **How many platforms does each one support?** Postiz supports 28 or more by its own count, with 21 offering in-app setup and the rest available through its public API, including Mastodon, Discord, Slack, Telegram, Reddit, and WordPress. Blotato supports 9: Instagram, TikTok, LinkedIn, Facebook, X, Threads, Bluesky, Pinterest, and YouTube. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine. Postiz is not an affiliate relationship and I have no commercial interest in it. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## 10 Best Social Media APIs in 2026 (Post With AI Agents) URL: https://ryandoser.com/social-media-api/ Markdown: https://ryandoser.com/social-media-api.md Published: 2026-08-31 | Updated: 2026-09-30 Categories: AI Tool Reviews > Ten social media APIs priced on five different billing units. Real allowances, worked cost math at 5 and 50 accounts, and which wins at your volume. Every **social media API** roundup lists sticker prices in a table, and every one of them falls apart the moment you have more than a couple of accounts to post to. The reason is that these vendors do not price on the same unit. Ten of them, five different billing units, and the cheapest one flips identity depending on a number you have not written down yet. So this list fixes a volume first, then does the arithmetic. Two volumes, because the ordering inverts between them. ### **What a Social Media API Actually Sells You** A social media API is the interface that lets your code publish to a platform without a human touching a dashboard. That definition is accurate and it hides what you are really buying. What you are buying is escape from platform review queues. Posting directly to Instagram, TikTok, LinkedIn and YouTube means four separate developer applications, four review processes, and four sets of credentials to rotate and keep compliant. Every vendor below has done most of that work and resells it behind one endpoint. You are paying them to have survived Meta's app review so you do not have to, though a few networks still make you bring your own credentials. That explains why the billing units are so inconsistent. Some vendors believe they are selling API calls, others believe they are selling connected accounts, and the bill lands very differently depending on which belief you buy. ### **Where My Experience Ends, and Why That Shapes This List** I run [Blotato](https://www.blotato.com/?ref=rdoser) daily and publish most of my own content through it from inside Claude Code. It is a client of mine, my account there is comped, and links to it are affiliate links. I also have hands-on time with Zernio and Upload-Post from earlier builds. **The other seven I have never run in production, and I have never self-hosted anything.** Those entries are documentation and pricing analysis, not firsthand accounts, and I have labelled each one so you know which is which. That gap is deliberate rather than lazy. Padding a list with software I have not run is how these roundups become interchangeable, and it is the one thing a vendor page can never honestly offer you. **So the ordering rule here is depth of evidence, not price.** The tool I have actually run in production every day sits first, and it is a client of mine, so discount that placement accordingly. The arithmetic further down is where you should argue with me. Every price was checked against the vendor's own live pricing page, and every scenario cost is calculated rather than asserted. If money is the only variable you care about, skip to the two cost tables. They crown a different tool at each volume, and neither of them is the one I use. ### **The 10 Best Social Media APIs at a Glance** Read the allowance column, not the price column. That is the whole trick, and the table below is built so any single row still makes sense pulled out on its own. | API | Best for | Starts at | What that buys | Billing unit | | Blotato | Creators who need content generated, not just scheduled | $29/mo | 20 social accounts, 1,250 AI credits | Flat, plus credits | | Outstand | Agencies and products with many accounts and moderate volume | $19/mo | 3,000 posts, unlimited accounts, 12 platforms | Per post, then overage | | Post For Me | Solo builders and prototypes on a tight budget | $10/mo | 1,000 posts, unlimited accounts | Per post | | Zernio | Developers who need the widest platform roster | Free, then $6/account | 2 free accounts, then $6 each for 3-10 | Per account, degrading | | Upload-Post | Testing an integration before spending anything | Free, then $24/mo | Free: 10 uploads, 2 profiles. Basic: 5 profiles | Per profile | | Postiz | Teams who want API access without tier games | $29/mo | 5 channels, unlimited posts, API on every tier | Per channel | | bundle.social | SaaS products embedding publishing for their own users | Free, then $100/mo | Free: 20 posts, 3 accounts. Pro: 10,000 posts | Per post | | Post Bridge | Creators who want unlimited posting on a fixed account tier | $39/mo | 15 accounts, unlimited posts, API included | Per account tier | | Ayrshare | Platforms reselling social publishing to their own customers | $149/mo | 1 social profile, one account per network across 14+ networks | Per profile | | Mixpost | Teams who want to own the software and run their own server | $299 one time | Unlimited accounts, API and MCP included | One-time licence | Post For Me at $10 caps you at 1,000 posts but connects unlimited accounts. Ayrshare at $149 gives unlimited posting on exactly one profile. Those are close to inverse products, and a sticker-price table would tell you one is fifteen times cheaper than the other. At the wrong volume it is more expensive. ### **Worked Cost Math at Two Real Volumes** Assertions are cheap, so here is the arithmetic on two scenarios that cover most people searching this term. **Scenario A: a solo builder.** Five connected accounts, roughly 150 posts a month, one person automating their own publishing. | API | Cost at 5 accounts / 150 posts | How it gets there | | Post For Me | $10 | 150 posts sits well inside the 1,000 cap | | Zernio | $18 | 2 free, then 3 paid accounts at $6 | | Outstand | $19 | Flat, nowhere near the 3,000 allowance | | Upload-Post | $24 | Basic covers 5 profiles, uploads unlimited | | Blotato | $29 | Flat, 20 accounts included so 15 go unused | | Postiz | $29 | Standard covers exactly 5 channels | | Post Bridge | $39 | Marketer covers 15 accounts, API included, so 10 go unused | | bundle.social | $100 | Free tier caps at 3 accounts, so Pro | | Ayrshare | $149 | Premium, one profile | | Mixpost | $299 once | Pro licence, plus your own hosting | Post For Me wins Scenario A at $10. Ayrshare costs fifteen times more for the same job, which is the correct read of that vendor at this size rather than a criticism of it. **Scenario B: an agency or a product.** Fifty connected accounts, roughly 2,000 posts a month, which is where the ordering inverts. | API | Cost at 50 accounts / 2,000 posts | How it gets there | | Outstand | $19 | Accounts unlimited, 2,000 posts inside the 3,000 allowance | | Post For Me | Not priced at this volume | 2,000 posts exceeds the 1,000 cap, so Starter no longer applies | | Blotato | $97 and up | Creator covers 40 accounts, so 50 needs the next step | | Postiz | $99 | Ultimate, 100 channels, posts unlimited | | Post Bridge | $99 | Operator covers 99 accounts, API included | | bundle.social | $100 | Pro, 10,000 posts, unlimited accounts | | Upload-Post | $147 | Advanced tier, 75 profiles | | Zernio | $168 | 2 free, 8 at $6 ($48), then 40 at $3 ($120) | | Mixpost | $299 once | Unchanged, because a licence does not scale with you | | Ayrshare | $599 and up | Launch's 10 profiles falls short, so Business at 30 profiles scaling to 300 | Outstand goes from mid-pack to cheapest by roughly five times, purely because it stopped charging for accounts. Zernio goes from second-cheapest to $168. Mixpost is the interesting one at this volume. A $299 one-time licence costs more than Outstand in month one and less than a single month of Ayrshare Business, assuming you can run a server. Post For Me is the honest asterisk. Their page says they will not auto-charge overage and will contact you about upgrading instead, so the Scenario B answer is a quote you have to request rather than a number I can publish. ### **The 10 Best Social Media APIs in 2026** Cheapest almost never means best here, because four of these ten are priced for a customer who is not you. Each entry below carries what it costs, what I have and have not run myself, and the genuine reason to skip it. #### **1. Blotato (Best for creators who need content made, not just scheduled)** *Blotato positions itself around AI agents, with MCP and REST access on the entry plan.* This is the one I actually use, and I publish most of my own content through it from inside Claude Code rather than from its dashboard. Treat this entry as interested rather than neutral, then check the arithmetic against the others yourself. **Pros:** - Generates the content, not just the schedule: copy, images, AI video and voiceover from one source - REST API and MCP server both on the $29 entry plan, with no separate developer tier - Flat bill that does not move when your posting volume does - 20 connected accounts on the entry plan, generous for a flat-rate tool though two cheaper options here do not cap accounts at all **Cons:** - The 7-day trial excludes the API entirely, so you cannot trial the thing most readers of this post came for - At 5 accounts you pay for headroom you will not touch, and Post For Me does that job for $10 - Analytics cover eight of the nine platforms, with LinkedIn the only one still returning nothing **Best for:** Creators and solo marketers where the bottleneck is producing content, not scheduling it. **Pricing:** Starter $29/mo (20 accounts, 1,250 AI credits), Creator $97/mo (40 accounts, 5,000 credits), Agency $499/mo (28,000 credits). Monthly billing. **Free trial:** 7 days, card required, and it excludes API access. Generating an API key ends the trial and starts billing. **Bottom line:** It is first because it is the only one here I have run in production daily rather than read the docs for, and the failure modes I describe further down are all from this tool. If something else already produces your content, you are paying for a generator you will not use, and two cheaper options below beat it on pure arithmetic. #### **2. Outstand (Best value once you pass roughly ten accounts)** *Outstand prices per post and does not charge for connected accounts at all.* On the Scenario B arithmetic Outstand is the strongest value here and it is not close. I have not run it in production, so this entry is a read of their documentation and pricing rather than a field report. **Pros:** - Unlimited connected accounts, which is why it wins at 50 accounts by roughly five times - Overage rates published openly at $0.007 per post to 10,000, then $0.005 beyond - [MCP server exposing 28 tools](https://www.outstand.so/mcp) for agent-driven posting - Managed Keys included free, so 8 of the 12 networks need no developer application from you **Cons:** - 12 platforms is at the small end of this list - Four of those (X, Google Business Profile, Vimeo and Reddit) require your own API credentials - Their homepage states the MCP tool count three different ways (28, 26 and 25) on a single page, which does not inspire confidence in the rest of the copy **Best for:** Agencies and SaaS products with many connected accounts and moderate posting volume. **Pricing:** $19/mo including 3,000 posts, then $0.007/post to 10,000 and $0.005/post above. Monthly, no annual contract. **Free trial:** No free tier. You get an API key and start on the $19 plan. **Bottom line:** If your account count grows while your posting volume stays moderate, nothing here comes close on price. Check your networks are among the 12 before you commit. #### **3. Post For Me (Best cheap entry point for a prototype)** *Post For Me starts at $10 and lets you bring your own platform credentials.* The cheapest credible way onto this list, and the one I would reach for to test an idea. Another documentation read rather than a production account. **Pros:** - $10 a month for 1,000 posts with unlimited connected accounts and unlimited API keys - Lets you [bring your own platform developer credentials](https://www.postforme.dev/pricing) instead of sharing theirs - No automatic overage charging, so a spike does not produce a surprise invoice **Cons:** - One public tier only, so anything above 1,000 posts is a sales conversation rather than a published price - That makes it impossible to budget at agency volume without contacting them **Best for:** Solo builders, prototypes, and anyone testing whether an integration is worth building at all. **Pricing:** Starter $10/mo for up to 1,000 successful posts. Enterprise is custom. **Free trial:** No free tier listed. **Bottom line:** The rational default under 1,000 posts a month. The bring-your-own-credentials option is worth more than its price suggests if you are worried about sharing a rate limit pool. #### **4. Zernio (Best platform coverage, with a real free tier)** *Zernio gives two connected accounts free with full API access.* I have hands-on time with Zernio from an earlier build, and the free tier is genuinely usable rather than a demo. The widest platform roster here by some margin. If you are weighing an exit from its per-account curve, I mapped [who overtakes Zernio at which account count](/zernio-alternatives/). **Pros:** - The widest channel roster here, including Reddit, Telegram and Google Business Profile, plus ad networks - Two connected accounts free with full API access, so you can build before paying - Per-account rate falls as you grow, from $6 to $3 to $1 **Cons:** - Degrading is not the same as flat: 50 accounts still costs $168 against Outstand's $19 - [X API costs are passed through](https://zernio.com/pricing) separately at $0.005 to $0.200 per request - Their marketed "40x faster rate limits" claim did not hold up when I checked it against the published numbers **Best for:** Developers who need channels the others do not carry, especially Reddit or Telegram. **Pricing:** Free for 2 accounts, then $6/account for accounts 3-10, $3 for 11-100, $1 for 101 and up. **Free trial:** Yes, a permanent free tier with 2 accounts and API access included. **Bottom line:** The best free tier here for actually building against, though watch the per-account curve past a dozen accounts. I went deeper in my [full Zernio review](/zernio-review/). #### **5. Upload-Post (Best free tier for testing an integration)** *Upload-Post gives a free plan with no credit card, though TikTok is excluded from it.* I have used Upload-Post before and its free plan is the least friction of any entry here. Paid plans then switch to unlimited uploads, which makes the bill predictable. **Pros:** - Free plan with no credit card at 10 uploads a month across 2 profiles - Unlimited uploads on every paid plan, so volume never moves the price - Whitelabel included from Professional upward, useful if you are reselling - Annual billing cuts 40 percent **Cons:** - TikTok is excluded from the free plan, which is often the whole reason people want this - Per-profile pricing gets expensive at scale: 50 profiles needs the $147 Advanced tier **Best for:** Anyone who wants to prove an integration works before spending a dollar. **Pricing:** Free (10 uploads, 2 profiles), [Basic $24/mo for 5 profiles](https://www.upload-post.com/#pricing), Professional $50 for 25, Advanced $147 for 75. Annual billing saves 40 percent. **Free trial:** Yes, a permanent free plan with no card required. **Bottom line:** The easiest yes for testing. Just confirm TikTok is on your paid tier before you build around it. #### **6. Postiz (Best for API access without tier games)** *Postiz includes API access on every paid tier and is open source if you would rather self-host.* Postiz is the answer when you are tired of finding the API behind a $50 upgrade. I have not run it, self-hosted or otherwise, so this is a documentation read. **Pros:** - API access included on every paid tier, starting at the $29 entry plan - Unlimited posts on all tiers, so only channel count moves the price - [Open source](https://github.com/gitroomhq/postiz-app), so self-hosting is a genuine option rather than a marketing line - Unlimited team members from the $39 tier up **Cons:** - Per-channel pricing loses badly to the flat-rate vendors at high account counts - Self-hosting trades the subscription for your own server maintenance, which is not free in hours **Best for:** Teams who want programmatic access on the cheapest paid plan rather than a developer tier. **Pricing:** Standard $29/mo (5 channels), Team $39 (10), Pro $49 (30), Ultimate $99 (100). API on all four. **Free trial:** Yes, a 7-day trial. Self-hosting the open-source version is free indefinitely. **Bottom line:** Honest tiering and no API upsell. I worked through the real maintenance math in my post on [skipping the self-hosted route](/postiz-alternatives/). #### **7. bundle.social (Best for embedding publishing in your own product)** *bundle.social has a free tier with real API access, then jumps straight to $100.* Built for developers embedding publishing into a SaaS product rather than for end users. Documentation read, not a production account. **Pros:** - Free tier includes real API access at 20 posts and 3 accounts a month - Pro gives 10,000 posts and unlimited connected accounts for a flat $100 - Comment allowances published alongside post allowances, which most vendors omit **Cons:** - The gap between free and $100 is the widest here, with no middle step - [X posts are billed separately](https://bundle.social/pricing) at $0.015 each and $0.20 with a link **Best for:** SaaS teams giving their own customers social publishing inside their product. **Pricing:** Free (20 posts, 3 accounts), Pro $100/mo (10,000 posts, unlimited accounts), Business $400/mo (100,000 posts). Custom above that. **Free trial:** Yes, a permanent free tier with API access. **Bottom line:** Evaluate on the free tier, then decide whether $100 is worth it. Budget the X pass-through separately if X matters to you. #### **8. Post Bridge (Best for unlimited posting on a fixed account tier)** *Post Bridge prices by account tier, with the API included on every plan.* On raw account economics Post Bridge is competitive with anything here, and the API now comes with every plan instead of as a paid add-on. I have not run it myself. **Pros:** - Marketer at $39 covers 15 connected accounts with unlimited posts and no per-post metering - Unlimited posts on every tier - REST API, CLI and MCP server included on every plan **Cons:** - Only two plans, so there is no middle step between 15 accounts at $39 and the $99 Operator plan - Operator's $99 covers up to 99 accounts whether you use that room or not **Best for:** Creators running a lot of accounts who post heavily and do not want a per-post allowance to think about. **Pricing:** Marketer $39/mo (15 accounts), Operator $99/mo (99 accounts, then $1 per extra account). The REST API, CLI and MCP are [included on both plans](https://www.post-bridge.com/pricing), and yearly billing gives two months free. **Free trial:** Yes, 7 days. **Bottom line:** Real value if you fit inside 15 accounts. Between 16 and 99 accounts you pay the full $99 either way. #### **9. Ayrshare (Best for platforms reselling publishing to their own users)** *Ayrshare's $149 entry looks steep until you see who the upper tiers are built for.* The $149 entry price looks indefensible next to a $10 competitor, and for a solo builder it is. It stops looking silly once you read what the upper tiers assume about you. Documentation read, not a production account. **Pros:** - Separately documented [publishing, history, analytics and engagement APIs](https://www.ayrshare.com/docs/apis/post/overview), which is a real depth signal - 14 networks, the widest coverage here after Zernio - Per-profile provisioning built for reselling to your own customers - Unlimited team members with no per-seat charge on every tier **Cons:** - Premium at $149 covers exactly one social profile, so it is poor value for individuals - Scaling to 50 accounts means Business at $599 and up **Best for:** Products and platforms giving social publishing to many end customers under one integration. **Pricing:** Premium $149/mo (1 profile), Launch $299 (10 profiles), Business from $599 (30 profiles, scaling to 300), Enterprise custom. **Free trial:** A 28-day free trial is offered on the Launch tier. **Bottom line:** If you need someone to answer the phone when a platform breaks, the price is the product. One person should look almost anywhere else here, and I covered those routes in my breakdown of [what to use instead of Ayrshare](/ayrshare-alternatives/). #### **10. Mixpost (Best if you want to own the software outright)** *Mixpost is a one-time licence rather than a subscription, and you host it yourself.* The only entry here that is not a subscription. I have never self-hosted anything, so I am reporting the licence terms rather than the experience of running it. **Pros:** - A $299 one-time licence covering unlimited social accounts and unlimited team members - API and MCP both included in that licence - Perpetual fallback licence, so it keeps working after updates lapse - Full data ownership, which matters for some compliance situations **Cons:** - You own uptime, upgrades, OAuth token refreshes and every platform API change, forever - The free Lite licence excludes API and MCP, so there is no free way to evaluate it as an API - Add your own server cost on top of the licence **Best for:** Teams with infrastructure people who would rather own software than rent it. **Pricing:** Lite free (no API), [Pro $299 one time](https://mixpost.app/pricing), Enterprise $1,199 one time. Includes one year of updates. **Free trial:** The Lite licence is free but carries no API or MCP. **Bottom line:** It pays for itself against Ayrshare quickly and against Outstand slowly. The $299 is the sticker price, not the real one, because the maintenance is now your job. ### **How to Choose a Social Media API** These are the questions I work through on every build before looking at a single pricing page. - **Are you paying for accounts or for posts?** Write down both numbers first. That single answer eliminates most of this list before price enters the conversation. - **Is your account count fixed or growing?** A growing count kills per-account and per-profile vendors quickly, even ones with degrading rates. - **Which networks are non-negotiable?** Rosters here run from 11 at the low end to the mid-teens, and some vendors make you supply your own credentials for X or Google Business Profile. - **Do you need the content generated, or only published?** If something already writes your posts, you are shopping for plumbing and should not pay for a generator. - **Can you test before you pay?** Three of these have a free tier with working API access. One has a trial that excludes the API entirely. - **Who owns the platform relationship when it breaks?** This is the question nobody prices, and it is covered below. ### **What a Year of Agent-Driven Posting Actually Taught Me** This is the part no vendor on this SERP can write, because none of them will publish the failure modes of the thing they sell. The single biggest surprise is that the API almost never breaks. The *agent* driving it does. My worst failure was an agent reporting a finished run against an empty folder, because the rendering job was still processing when the conversation ended. The API call was fine. The orchestration around it was not, and nothing in the API response would have told me. A workflow builder would have caught that with a wait node drawn explicitly on a canvas. That is the honest cost of the agent path, and it is the thing an API pricing page cannot warn you about. The second lesson is that credits are the variable that actually surprises you, not posts. Post allowances are easy to estimate because you know your own calendar. Generation credits drain at a rate that depends on whether you asked for text, an image, or a video that day. Third, deleted posts are where the state drifts. Removing something on the platform side does not always reconcile cleanly back through the API, so the tool's record and the live account can disagree. None of that shows up in a comparison table, and all of it decides whether you keep using a tool after month three. It is also why I would not switch to a cheaper option on price alone without running it for a month first. ### **The Thing Nobody Prices: Who Owns the Platform Relationship** Every table above treats these as interchangeable pipes. They are not, and the difference shows up on your worst day rather than your first. When a vendor posts under its own developer credentials, its customers can share a rate limit pool and a compliance surface. If another customer gets that app flagged, your posting can stop for reasons that have nothing to do with your code. In fairness to the vendors, this has not happened to me. Running one of these daily for months, the shared-credential failure I am describing is the risk I have been carrying, not an incident I have lived through. That is worth saying plainly, because most posts raising this point present it as though it were routine. It is a tail risk you are accepting, and the vendors mostly hold up their end. It still explains why Post For Me's bring-your-own-credentials option, and the pass-through X billing at Zernio and bundle.social, are worth more than their line items suggest. Each is a vendor declining to hide a dependency from you. It is also the strongest argument for the expensive end of this list. Part of Ayrshare's $149 is someone whose full-time job is maintaining those platform relationships, and part of Mixpost's $299 is that job becoming yours. ### **Which Social Media API Should You Pick?** Answer one question and most of this resolves. Are you paying for accounts, or for posts? Small fixed account count on a budget, pick Post For Me at $10. Many accounts with moderate volume, pick Outstand at $19. Widest platform roster with a real free tier, Zernio. API access without tier games, Postiz. Needing 14-plus networks with documented analytics and engagement APIs plus a real support relationship is the case where Ayrshare's pricing stops being absurd. Nothing currently writing your content? That is where I land with Blotato, and you should discount that opinion by the disclosure at the bottom of this post. ### **What About Buffer, Hootsuite and Sprout Social?** Those three come up constantly on this query and none of them made the list, which is a deliberate exclusion rather than an oversight. They are social media management platforms that happen to expose an API, not API-first products. [Buffer](https://buffer.com/) prices per channel for a dashboard user, and [Hootsuite](https://www.hootsuite.com/) and [Sprout Social](https://sproutsocial.com/) are built around seats and reporting. If you are searching for a social media API, you want the API to be the product rather than a feature bolted onto a seat licence. That is the line I drew, and I compared the dashboard-first tools separately in my roundup of [social media automation tools](/social-media-automation-tools/). ### **Ryan's Final Thoughts** The reason this keyword is full of weak comparison posts is that the honest answer depends on your volume, and a listicle cannot know your volume. So run the two-line version of what I did above. Write down your account count and your monthly post count, then read those two numbers against the allowance column instead of the price column. Every price here was checked live on each vendor's own pricing page, and every scenario total is calculated rather than quoted from a marketing claim. ### **Social Media API FAQs** #### **What is a social media API?** A social media API is the official interface a platform provides so software can publish, schedule and read content programmatically instead of through a dashboard. The unified APIs in this post sit one layer above that, giving you a single endpoint that fans out to Instagram, TikTok, LinkedIn, X, YouTube and others, so you do not have to apply for and maintain developer access on each platform separately. #### **What is the best social media API?** It depends on whether you are billed for accounts or posts, and the answer inverts between the two. **For a solo builder with a handful of accounts,** Post For Me at $10/mo for 1,000 posts is the cheapest credible option. **For an agency or product with many accounts,** Outstand at $19/mo flat with unlimited accounts wins by a wide margin. **For creators who need posts written as well as published,** Blotato at $29/mo is the only one here that generates the content itself. #### **Is there a free social media API?** Three of the ten give you a free tier with working API access. Upload-Post allows 10 uploads a month across 2 profiles with no credit card, though TikTok is excluded. Zernio's free tier covers 2 connected accounts with full API access. bundle.social allows 20 posts and 3 accounts. Mixpost also has a free Lite licence, but it excludes the API and MCP entirely, so it cannot be used to test an integration. #### **How much does a social media API cost?** Entry prices here run from $0 to $299, but the useful answer depends on volume. At 5 accounts and 150 posts a month, these ten range from $10 to $149. At 50 accounts and 2,000 posts a month, the same ten range from $19 to $599, and both the cheapest and the most expensive change identity. Price the allowance, not the sticker. #### **Can an AI agent post to social media through an API?** Yes, and most of these vendors now ship MCP servers specifically for it. Outstand exposes its whole API as MCP tools, Mixpost includes MCP in its Pro licence, and Blotato, Zernio and Ayrshare all run hosted MCP endpoints, so an agent running in Claude or a similar client can call publishing tools directly instead of going through your backend. MCP support is close to table stakes across this category now, so it is a poor reason to pick one vendor over another. #### **Do I still need developer accounts on each platform?** Usually not, and that is most of what you are paying for. These vendors have already passed Meta, TikTok and LinkedIn app review and let you publish under their approved applications. Post For Me is the notable exception in a good way, since it lets you bring your own platform credentials if you would rather not share a rate limit pool with the vendor's other customers. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine and my account there is comped rather than paid. I have no relationship with Outstand, Post For Me, Upload-Post, Zernio, Postiz, Post Bridge, bundle.social, Ayrshare or Mixpost. All pricing was verified against each vendor's live pricing page. [Full disclosure](/disclosure/).* --- ## 7 DataForSEO Alternatives and What They Actually Cost URL: https://ryandoser.com/dataforseo-alternatives/ Markdown: https://ryandoser.com/dataforseo-alternatives.md Published: 2026-08-29 | Updated: 2026-09-30 Categories: AI Tool Reviews > What seven DataForSEO alternatives really cost, priced from each live rate card, plus the multipliers buried in DataForSEO's own pricing page. Almost every page ranking for **DataForSEO alternatives** is published by a company that sells one. I pulled the results on August 29, 2026 and counted it: SE Ranking's own blog, cloro's own comparison, Bishopi's own decision guide, a LinkedIn post from a vendor, and DataForSEO's own page about its competitors sitting at the top of the organic results. I am not switching. I have run DataForSEO every working day this year, across my own site and a roster of client work, and I have no plans to leave. That is a strange reason to write this, and it is also the reason it is worth reading. A vendor comparing itself to DataForSEO has already decided how the comparison ends. What follows is the version from someone with no switch to sell you. Three terms, once, in plain English, because the rest of this post leans on them. An **API** is the paid pipe that lets software pull search data directly instead of a person exporting it from a dashboard. **MCP**, the Model Context Protocol, is the connector that lets Claude or ChatGPT pull that same data for you in a chat, with nothing to build. A **credit** or **unit** is whatever the vendor decides to count when it bills you, and the whole difficulty of this comparison is that no two of them count the same thing. If you only ever want to ask Claude a question and get search data back, the second one is the only term that matters to you. ### **What Actually Sends People Looking** The reason is almost never the headline price. DataForSEO charges $0.0006 for a Google SERP in its standard queue, which is sixty cents for a thousand of them, and that is genuinely cheap. What sends people to a search box is the shape of the thing. You submit a job, wait in a queue, then come back for the answer. There are three speed tiers priced differently, and a prepaid balance that starts at a $50 minimum payment. If you just want one search result right now, in one go, that is a lot of machinery to stand up. One option keeps DataForSEO underneath and hides the queue and the deposit behind an interface. OpenSEO does exactly that, and I priced [what that wrapper actually adds](/openseo-review/). There is a second reason, and it rarely makes it into a comparison post. ### **The Multipliers On DataForSEO's Own Rate Card** Sixty cents per thousand is the floor, not the bill. DataForSEO publishes a table of cost multipliers that most people never scroll to, and any one of them changes the arithmetic. *DataForSEO, the baseline every tool in this post is measured against.* Its [Google Organic SERP API pricing page](https://dataforseo.com/pricing/serp/google-organic-serp-api) states the following, checked live: - A search operator such as *site:*, *intitle:*, *inurl:* or *filetype:* multiplies the cost **by 5, for each operator used** - Loading the AI Overview adds a full extra base price - Expanding People Also Ask adds $0.00015 per click - Going past 10 results multiplies the price for each additional 10 Run a single *site:* query in Live mode with the AI Overview loaded and you are no longer paying $0.002. You are paying five times that for the operator, plus another base price for the overview. This matters more in 2026 than it did in 2023, because AI Overview data is a large part of why people buy search APIs now. The parameter that answers the current question is the one carrying a surcharge. None of this is hidden. It is published on DataForSEO's own site, in a table, which is more than several vendors here manage. The problem is that a roundup comparing sticker prices has no reason to scroll that far, and a single operator multiplying by 5 does more to your bill than any gap between the vendors below. ### **Which of These I Actually Pay For** One boundary before the list, because it changes how you should read every ranking below. **DataForSEO is the only tool here I run in production.** I have not put the other seven through a real workload as a data source, so what follows is a pricing and architecture read taken from each vendor's live rate card, plus the questions I ask because I have watched this specific kind of bill every month this year. I have used the Ahrefs and Semrush platforms, and written separately about [what the Ahrefs API costs](/ahrefs-api-pricing/) and [how Semrush prices API access](/semrush-api-pricing/). Whether their APIs replace DataForSEO is a different question, and I have not run that test. ### **DataForSEO Alternatives Compared on Price and Billing Model** Read the billing model column before the price column, and read this first: the table holds two different units. DataForSEO, Serper, Bright Data, SearchApi and SerpApi sell you a search. SE Ranking, Ahrefs and Semrush sell you credits or units instead, priced by how much data comes back, with Ahrefs charging at least 50 units for any request at all. You cannot put those on one per-thousand line without lying slightly, so I have not. | Tool | Entry cost | Billing model | Free tier | Best for | | DataForSEO | $0.60 per 1,000 SERPs | Prepaid, $50 minimum, no expiry | Free trial credit | Running high volume at the lowest per-call rate | | Serper.dev | $50 for 50,000 queries ($1.00 per 1,000) | Prepaid top-up, credits expire in 6 months | 2,500 queries, no card | Google-only lookups inside an app | | Bright Data | $1.50 per 1,000 requests | Prepaid wallet, or $499 monthly plan | 5,000 shared credits monthly | Sites that fight back against scrapers | | SearchApi | $40 per month for 10,000 searches | Monthly subscription | 100 requests, no card | Predictable monthly cost at low volume | | SerpApi | $25 per month for 1,000 searches | Monthly subscription | 250 searches monthly | Search engines beyond Google | | SE Ranking | $50 wallet, or $179 per month API-only | Prepaid wallet, or annual API subscription | Free trial, full API access | Wanting a dashboard and an API together | | Ahrefs | $129 per month (Lite) | Subscription, API units metered | Free test queries | Backlink data you cannot rebuild later | | Semrush | $549 per month for API access | Subscription, API units metered | Free trial | Teams already inside Semrush | ### **The Seven Worth Considering** Ordered by how close each one sits to the job DataForSEO actually does, not by preference. #### **1. Serper.dev (Best for Google-Only Lookups)** *Serper leads with speed and price. The credit expiry is further down the page.* [Serper](https://serper.dev/) is the closest thing here to a straight swap for one specific DataForSEO job: give me Google results, fast, in one call. It returns in one to two seconds and there is no queue to manage. **Pros:** - 2,500 free queries with no credit card, and no card means no accidental first bill - No subscription, you top up credits and spend them - You ask once and the answer comes straight back, with no queue to wait on or job to check later **Cons:** - Credits expire after 6 months on every tier, which its own pricing cards state four times - Google only, so a Bing or Baidu requirement rules it out - Its "cheapest" claim holds at volume and not at the door, where $1.00 per 1,000 is more than DataForSEO's standard queue charges **Best for:** Developers who want Google results in one call and will spend the credits inside six months. **Pricing:** Top-up model, no subscription. $50 for 50,000 credits ($1.00 per 1,000), $375 for 500,000 ($0.75 per 1,000), $1,250 for 2.5M ($0.50 per 1,000), $3,750 for 12.5M ($0.30 per 1,000). **Free trial:** Yes, 2,500 queries, no card required. **Bottom line:** Serper markets itself as the cheapest Google search API, and at volume it is. At the entry tier it is not cheaper than DataForSEO's standard queue, and the six-month expiry means unused credits are a real cost if your usage is lumpy. #### **2. Bright Data (Best for Sites That Fight Back)** *Bright Data sells the proxy layer underneath the data, which is what you are really buying.* [Bright Data](https://brightdata.com/products/serp-api) is an infrastructure company that happens to sell a SERP API. You are buying proxy management, unblocking and CAPTCHA handling, with search results as the output. **Pros:** - 5,000 free credits every month, not a one-time trial - Prepaid wallet that stops hard, so there is no surprise invoice - Covers seven engines: Google, Bing, DuckDuckGo, Yahoo, Naver, Baidu and Yandex **Cons:** - Its own navigation advertises "from $1/1k" while the live plan card charges $1.50 - Monthly free credits reset on the 1st and do not roll over - The product surface is enormous, so SERP data is one door into a sprawling platform built for something else **Best for:** Anyone whose real problem is being blocked rather than being billed. **Pricing:** $1.50 per 1,000 requests pay as you go on a prepaid wallet with no commitment, or a $499 per month Scale plan that includes 380,000 requests and charges $1.30 per 1,000 after that. Free tier is 5,000 credits per month shared across several products. **Free trial:** Yes, 5,000 credits monthly, no credit card. **Bottom line:** Check the plan card rather than the navigation. Bright Data's product menu says the SERP API starts from $1 per 1,000, and the live pay-as-you-go card charges $1.50, which is a 50% gap on the number most roundups quote. Its MCP server is free to connect, and the requests you make through it bill at the same rate as any other. #### **3. SearchApi (Best for a Predictable Monthly Number)** *SearchApi bills a flat monthly subscription rather than a prepaid balance.* [SearchApi](https://www.searchapi.io/) answers the complaint that a prepaid balance is hard to budget. You pay a subscription, you get a search allowance, and the number on your card is the same every month. **Pros:** - Failed requests are not billed, only a 200 response costs you - Covers AI surfaces including Google AI Mode, Gemini and ChatGPT - Cancel from the dashboard without contacting anyone **Cons:** - You can only spend 20% of your plan's credits in any single hour, so a big overnight batch has to be paced across five hours - Allowances do not bank, so a quiet month is money you simply do not get back - The $2M Legal Protection Guarantee starts at the $100 Production plan, not the $40 entry plan **Best for:** Agencies that need to forecast a line item rather than watch a balance drain. **Pricing:** Developer $40 per month for 10,000 searches ($4 per 1,000). Production $100 for 35,000 ($2.86 per 1,000). BigData $250 for 100,000 ($2.50 per 1,000). Scale $500 for 250,000 ($2 per 1,000). **Free trial:** Yes, 100 requests, no card required. **Bottom line:** A subscription costs more per call than DataForSEO at almost any volume. What you are buying is the absence of a balance to monitor, and for some teams that is worth the premium. #### **4. SerpApi (Best for Search Engines Beyond Google)** *SerpApi's live playground returns parsed JSON before you sign up for anything.* [SerpApi](https://serpapi.com/) is the name that comes up most often in this category. It is also the only vendor here that publishes a plain-markdown rate card at *serpapi.com/pricing.md*, which meant its numbers were the fastest of the eight to verify, and a company that machine-readable about price is usually machine-readable about the rest. **Pros:** - Over 100 API endpoints, reaching engines Google does not cover, including Baidu, Naver and Yandex - Cached, errored and failed searches do not count against your quota - A result set counts as one search whether it returns 100 rows or zero **Cons:** - The $2M US Legal Shield starts at the $150 Production plan, so the $25 and $75 tiers do not have it - Faster speed modes multiply the base price by 2x or 4x - Unused searches do not roll over, the plan simply renews **Best for:** Products that need a search engine Google is not. **Pricing:** Free $0 for 250 searches. Starter $25 per month for 1,000. Developer $75 for 5,000. Production $150 for 15,000. Big Data $275 for 30,000. All month to month, cancel anytime. **Free trial:** Yes, a permanent free tier of 250 searches per month. **Bottom line:** At $25 for 1,000 searches, the entry plan works out to $25 per 1,000 against DataForSEO's $0.60. You are paying for engine breadth and polish, and if you only need Google that is a lot of money for it. #### **5. SE Ranking (Best If You Want a Dashboard Too)** *SE Ranking sells a platform first, with API and MCP access layered on top.* [SE Ranking](https://seranking.com/) ranks its own comparison post on page one for this query, which is worth keeping in mind when you read where it places itself in that list. **Pros:** - A working interface, so non-technical teammates can use the data too - Platform plans bundle API credits and MCP access rather than charging separately - AI visibility tracking across ChatGPT, Gemini, AI Mode and Perplexity **Cons:** - The $179 standalone API plan is billed annually only, so month-to-month means the wallet or a platform seat - Credits are charged by which data you ask for and how much comes back, so it will not line up against a flat per-search rate - The platform seat is priced for people who open the interface, which a pure data buyer never will **Best for:** Small agencies replacing two tools with one. **Pricing:** Three separate routes. A $50 Wallet buys 250,000 credits with no recurring fee and, unusually for this list, the purchased credits never expire. The standalone Data API plan is $179 per month on annual billing only. Platform seats run Core $129 monthly (or $103.20 annually) with 25,000 API credits and MCP access, and Growth $279 monthly (or $223.20 annually) with 100,000 credits. **Free trial:** Yes, no credit card required. **Bottom line:** The $50 non-expiring wallet is the closest thing on this list to DataForSEO's own prepaid shape, and it is the option most roundups skip in favor of quoting the platform price. Buy the seat only if someone on your team will actually open the interface. #### **6. Ahrefs (Best for Data You Cannot Rebuild Later)** [Ahrefs](https://ahrefs.com/) belongs on this list for one reason that has nothing to do with SERP scraping. Its backlink index and historical data are things you cannot reconstruct after the fact, no matter how many live SERPs you buy. **Pros:** - API access and an MCP server now ship on every plan, including $129 Lite - Backlink depth and historical keyword data that live SERP calls cannot produce - Free test queries on all plans before you spend units **Cons:** - Every request costs at least 50 units, even one asking for a single row, so small frequent queries waste the most - A unit price moves with how many rows and columns come back, which is harder to forecast than a flat per-search rate - Consumed units are non-refundable **Best for:** Link analysis and historical trend work, alongside a cheaper SERP source rather than instead of one. **Pricing:** Lite $129 per month, Standard $249, Advanced $449, Enterprise $1,499 with an annual commitment. Included API units run from 200,000 monthly on Lite to 4M on Enterprise. **Free trial:** No free tier, though free API test queries are available on all plans. **Bottom line:** One correction worth making loudly, because plenty of comparison posts still get it wrong. Ahrefs API access is no longer Enterprise-only. I go deeper on how the two compare for agent work in [DataForSEO vs Ahrefs](/dataforseo-vs-ahrefs/). What Enterprise buys now is the largest unit allotment and unlimited rows per request, and if you read otherwise somewhere, that page is out of date. #### **7. Semrush (Best If Your Team Is Already There)** [Semrush](https://www.semrush.com/) is the most expensive route to API data in this post by a wide margin, and it earns a place only in one situation: your company already pays for it. **Pros:** - Data spanning SEO, PPC and competitive intelligence in one place - MCP access starts at the $199 Starter tier, well below full API access - A per-request display limit lets you reduce unit consumption **Cons:** - Full API access requires the $549 per month Advanced tier - API units are a separate balance from your subscription - Priced for a marketing team, which makes it hard to justify as a pure data source **Best for:** Teams with an existing Semrush contract who want to script against it. **Pricing:** API access requires Advanced SEO plus AI Search at $549 per month billed monthly, or $455.67 per month billed annually. The $199 Starter tier includes MCP access but not full API access. **Free trial:** Yes, on the platform. **Bottom line:** The $549 buys eligibility, not volume, since API units are a separate balance on top. I break down what that subscription actually rents you in [DataForSEO vs Semrush](/dataforseo-vs-semrush/). For scale, that same $549 is roughly 900,000 standard-queue SERPs at DataForSEO's rate. The comparison is unfair because you are also buying a large platform, and it is still the arithmetic anyone evaluating this purely as a data source should run. ### **What About Firecrawl, Exa and Tavily?** *Firecrawl and its neighbors sell retrieval for agents, which is a different job than SEO data.* These three surface constantly on this keyword and I have deliberately left them out of the ranking. [Firecrawl](https://www.firecrawl.dev/), [Exa](https://exa.ai/) and [Tavily](https://tavily.com/) are retrieval tools built to feed context to an AI agent. They fetch pages and return clean text, and Firecrawl is open source if you want to read how. What they do not return is rank position, search volume, keyword difficulty or a backlink profile. Replacing DataForSEO for SEO work with a retrieval API leaves you without the numbers the work depends on. For grounding an LLM they are a better fit than anything above, and the question you are asking is not really this one. ### **Four Questions That Narrow This Fast** These are the same questions I ask on every client build before picking a data source. **Is your volume steady or lumpy?** Steady volume suits a subscription, where the monthly number never surprises you. Lumpy volume suits prepaid, where a quiet month costs nothing. Watch for expiry, since Serper's credits die at six months and Bright Data's free tier resets on the 1st. **Do you need Google, or search engines generally?** If it is Google alone, Serper is the simplest call and DataForSEO the cheapest queued one. For Baidu, Naver or Yandex, check the engine list before the price, because SerpApi, Bright Data and DataForSEO all cover ground beyond Google and they do not cover the same ground. **Is your problem the bill or the blocking?** These get confused constantly. If your calls are failing rather than costing too much, you have a proxy problem. Most of these vendors bill only for successful delivery, so compare their unblocking claims rather than their rates. Bright Data is the one that sells the proxy network itself. **Does anyone besides you need to see this data?** If a client or a teammate needs to open something and look at it, a wall of raw data in a text file is not that thing. That is the case for a platform seat over a raw data provider, and it is worth what it costs only if someone actually logs in. ### **Why I Am Still Paying DataForSEO** Two reasons, and the first one is not the price. It is the only provider I found here that sells SEO data, live search results and AI search visibility from a single balance. I can pull a SERP, then keyword volume, then what ChatGPT and Perplexity say about a brand, without a second vendor or a second invoice. Splitting that across a SERP API plus a keyword tool plus an AI visibility tool costs more and breaks more. The second is that it connects to Claude over MCP, which is how I actually use it. I ask a question in a sentence and the data arrives, which is also true of several tools above and worth checking before you assume it is a differentiator. I wrote up that setup in my [full DataForSEO review](/dataforseo-review/) and in a broader piece on the [SEO MCP servers worth connecting](/best-seo-mcp-servers/). The honest limitation is the one I opened with. The prepaid balance takes a $50 minimum, the queue takes patience, and the multipliers mean the advertised sixty cents is not what a real month costs. I have watched a careless *site:* query in a loop cost more than a week of normal pulls. If you want one call with no queue, Serper hands you 2,500 queries without a card, which is enough to find out whether the simpler shape is worth the higher rate. That is not the workload I have, and it may well be yours. ### **DataForSEO Alternatives FAQs** #### **What is the cheapest DataForSEO alternative?** At small volume, none of them beat DataForSEO's own standard queue at $0.60 per 1,000 SERPs. Serper's entry tier is $1.00 per 1,000 and Bright Data's pay-as-you-go card charges $1.50. Serper becomes cheaper at scale, reaching $0.30 per 1,000 once you buy 12.5 million credits up front. Compare the rate at the volume you actually run, not at the top tier. #### **Are there free alternatives to DataForSEO?** There are free tiers, not free providers. Serper gives 2,500 queries with no card, Bright Data gives 5,000 credits every month that reset on the 1st, SerpApi has a permanent 250-search monthly tier, and SearchApi gives 100 requests. Those are enough to test a workflow. None of them carry real client work past the first week. #### **What is the difference between SerpAPI and DataForSEO?** Billing shape and breadth. SerpApi sells a monthly subscription starting at $25 for 1,000 searches and publishes over 100 API endpoints, counting Google Search, Images and Maps separately rather than 100 distinct engines. DataForSEO sells prepaid credit at $0.0006 per SERP with a $50 minimum and no subscription. SerpApi costs far more per call and is simpler to budget. DataForSEO is cheaper at volume and sells keyword, backlink and AI search data the SERP-only providers do not. #### **Is DataForSEO cheaper than Semrush or Ahrefs?** For buying search data, yes, by a wide margin. Ahrefs API access requires the $129 Lite plan or higher, and Semrush needs the $549 Advanced tier for full API access, while DataForSEO bills per request with no subscription. They are not really substitutes though. Ahrefs and Semrush sell backlink indexes and historical data that you cannot reconstruct later, which no volume of live SERP calls replaces. #### **Does DataForSEO have an MCP server for Claude?** Yes, and so do most of the alternatives here. DataForSEO, SerpApi, Bright Data, SearchApi, SE Ranking, Ahrefs and Semrush all ship one, which means MCP support is no longer a reason to pick any of them. Serper is the exception and does not advertise a hosted MCP server. Treat it as table stakes and compare on billing model instead. #### **Why is my DataForSEO bill higher than $0.60 per 1,000?** Almost certainly a cost multiplier. A search operator such as *site:* or *intitle:* multiplies the price by 5 for each operator used, loading the AI Overview adds a full extra base price, requesting more than 10 results multiplies again for each additional 10, and expanding People Also Ask adds $0.00015 per click. Live mode also costs $0.002 per SERP against the standard queue's $0.0006. *Disclosure: this post contains no affiliate links. I pay for DataForSEO myself and it is not a client. Links to SerpApi, Serper, Bright Data, SearchApi, SE Ranking, Ahrefs, Semrush, Firecrawl, Exa and Tavily are plain links. The seven alternatives are priced and assessed from their live rate cards and documentation, with monthly billing selected where a toggle exists. [Full disclosure](/disclosure/).* --- ## AI Content Repurposing: One Idea, a Week of Content (In Your Voice) URL: https://ryandoser.com/ai-content-engine/ Markdown: https://ryandoser.com/ai-content-engine.md Published: 2026-08-28 | Updated: 2026-09-04 Categories: AI Automations, Claude Code > Most AI repurposing sounds like everyone else because a prompt starts from zero. Here is the system, built on a voice file, that turns one idea into a week. I publish a blog post, a newsletter, and a week of social content off one idea, and I do it as a one-person business. The reason is not discipline. It is that **AI content repurposing** is the one part of that I stopped doing by hand. Most creators lose the same way. You have the idea. You record the video or write the long post. Then the multiplication, the part that turns one piece into ten, is four more hours you never find. So the idea gets published once and dies there. Here is the whole workflow running end to end, if you would rather watch it than read about it. ### **Why Repurposing Is the Step That Never Gets Done** Repurposing is unglamorous. Nobody feels creative reformatting the same thought for the fifth platform, and it is the first task that falls off the list in a busy week. So people reach for ChatGPT, paste in a transcript, and ask for ten LinkedIn posts. What comes back is technically ten posts and unmistakably not yours. It has the cadence, the throat-clearing openers, and the tidy summary endings that readers now scroll past on sight. I wrote a whole guide on [how to avoid AI slop](/avoid-ai-slop/), and repurposed content is where it shows up worst, because the model is furthest from your actual thinking. That leaves two bad options: hours you do not have, or output that sounds like everyone else's feed. The interesting question is what has to be true for a system to give you the speed without the second problem. ### **The Four Things an AI Repurposing System Needs** Building this for my own brand, the parts that actually matter narrowed down to four. Miss any one and you are back to slop. #### **1. A Voice File the Writers Have to Obey** This is the whole game and almost nobody does it. A prompt starts from zero every time, which is exactly why the output is generic: the model has no information about you, so it produces the statistical average of everyone. The fix is a written voice file built from your real writing, not a longer prompt. Your vocabulary, your sentence rhythm, the opinions you actually hold, and the words you would never use. Every draft then gets checked against that file rather than against nothing. It is the difference between asking a stranger to imitate you and handing a writer your last twenty pieces first. The practical detail people miss: it has to be a file you own and can edit. When something reads wrong, you fix the guide once instead of re-explaining yourself every week. A prompt has no memory of that correction. #### **2. Per-Platform Rules, Not One Draft Reformatted** A LinkedIn post and an X post are different pieces of writing, not the same paragraph at two lengths. Line breaks, opener structure, how much context a reader needs before the first idea lands, what a link does to reach on each network. Guessing at this is how repurposed content underperforms the original. Each platform needs its own rules written down once. Then the multiplication step is applying known rules instead of improvising each week. If you want the manual version of this before automating any of it, my breakdown of how to [post consistently with AI](/post-consistently-with-ai/) covers the cadence side. #### **3. A Quality Gate That Runs Before You See the Draft** Reviewing AI output is the hidden cost nobody prices in. If every draft arrives needing a heavy edit, you have moved the work rather than removed it. So the check belongs upstream of you. Score each draft against a slop checklist and the voice file, and rewrite anything that fails before it reaches your review. You should only ever read drafts that already passed. That single change is what turns this from a toy into something you use on a Tuesday. #### **4. A Way In When You Have Nothing to Repurpose** Every repurposing tool assumes you already have a content library. Most small business owners do not. They have twenty years of answers to customer questions and zero published content, which is a supply problem no repurposing tool solves. The way around it is an interview. Answer six to eight sharp questions about something you already know, and the transcript of that becomes the seed. Ten minutes of talking is enough raw material for a week, and it is a better seed than most blog posts because it is genuinely what you think. This is the assumption I got most wrong, and it nearly sank the whole premise. I have a YouTube channel, so I always have a seed, and I built the first version around that without noticing I had assumed it. The person who most needs this has twenty years of expertise and nothing published, and handing them a repurposing tool is handing them a machine with no input. Watching that happen is what put the interview in, and it turned out to be the piece that makes the whole thing make sense for the people I built it for. ### **What One Run Should Actually Produce** Concretely, here is the output I expect from one seed, whether that seed is a video, a webinar, a long post, or an interview transcript. - **A blog post** of 1,200+ words, with title options rather than one take-it-or-leave-it headline - **Social posts per platform**, several each for the platforms you actually use, formatted to each one's rules - **A newsletter email**, with subject line options - **10 to 20 short-form hooks**, mined from the strongest moments in the seed - **Graphics**, an infographic from the seed's best idea plus quote and hook cards, in your brand colors One note on the graphics, because it is the part that surprises people. AI image generators still mangle text, so a card with a quote on it comes back with warped or invented letters often enough that you cannot ship it unchecked. Rendering the graphic as a small designed page and snapshotting it sidesteps that entirely. The text is text, so it is always crisp, and it is the same reasoning behind how I [automate infographics](/automate-infographics/) rather than generating them as images. The card below is a real one, rendered from this very post using the template that ships in the download. It was built as a page and snapshotted rather than generated as an image, which is why every letter in it is sharp. ### **Where the Human Still Has to Stay** Two things this does not do, and being straight about them is the difference between a system you keep using and one you abandon in three weeks. It does not publish for you. Every run produces drafts. Nothing posts, schedules, or sends itself, and I would not want it to. The review pass is short when the quality gate has done its job, but it is not optional, and auto-publishing unreviewed content at volume is the exact pattern [Google's spam policies call scaled content abuse](https://developers.google.com/search/docs/essentials/spam-policies#scaled-content-abuse). That is the same line I hold in my [AI SEO system](/ai-seo-system/). It also does not manufacture ideas. The multiplication is free now. Having something worth multiplying is not. If a video had no real thesis, the blog post inherits that, and no amount of processing invents one. Tighter seeds make tighter output, every time. ### **The Version I Packaged** I built this for myself first, because I run a YouTube channel, a blog, a weekly newsletter, LinkedIn, and X with no team. Packaging it into something another person could run is what forced the four parts above to be written down instead of living in my head. That is the **[AI Content Engine, $47 one time](https://engine.ryandoser.com/)**. It is a folder of files you hand to an AI assistant, and it turns that assistant into your content team: the Brand Guide Builder, the writers for each format, per-platform rules, the graphic designer, and the anti-slop quality gate. No subscription, and updates are included. It is plain files, so it is not locked to one app. It runs in Claude, [ChatGPT's Codex](https://learn.chatgpt.com/docs), [Cursor](https://cursor.com/), [Google Antigravity](https://antigravity.google/), and any other assistant that reads files. On [Claude Code](https://claude.com/product/claude-code) it installs as a plugin with its own slash commands, and everywhere else you drag in a folder. The honest cost note: it needs a paid plan on one of those assistants, which is separate from the $47, and a $20 Claude Pro plan is plenty. I priced it as the thing you buy without a meeting about it. It is less than most freelancers charge for a single blog post, and one run produces considerably more than one blog post. My other products sit further up: the [AI SEO System](/ai-seo-system/) at $199 does a completely different job, which is getting you cited in AI search rather than writing your content. Neither requires the other, and I would rather say that plainly than sell you the wrong one. If you would rather build your own version, everything above is the blueprint and I mean that. The four parts are the four parts whether you buy them or write them. My walkthrough of how I [repurpose YouTube videos with Claude Code](/claude-code-repurpose-youtube-videos/) is the hands-on version of the same pipeline. #### **Who Should Not Buy This** The limitations above are how the system works. These are the situations where it is the wrong purchase for you specifically, and they matter more than usual here because digital sales are final, so the time to decide is before you buy rather than after. You do not want a paid AI assistant. The Engine is a system your AI tool runs, not a standalone app, so the $20-a-month plan is a real prerequisite rather than an upsell. If you were not going to have one anyway, the $47 buys you nothing. You are looking for done-for-you. This produces drafts you edit and publish. If what you actually want is someone else running your content, hire that, and I would rather tell you so than sell you a system you will not open twice. You publish to one place, occasionally. The whole economic case here is multiplication across formats. If you post to LinkedIn once a month and that is the plan, the setup cost is not worth it. Your work is not something you can talk about for ten minutes. Interview mode helps you get an idea out of your head, but it cannot put one there. ### **Where the Real Leverage Is** Generic content has no moat. Competent-sounding prose is the thing that got commoditized, and what is left that a model cannot produce from nothing is what you specifically know. Extracting your subject matter expertise is the advantage. The mistake is treating AI repurposing as a volume play, because volume without a voice file is just a faster way to publish things nobody remembers. Build the voice layer first, then the speed. One idea a week, multiplied properly, beats five ideas published once each and forgotten. For the strategy layer underneath all of this, my comparison of [nine content creation agents and what each one can publish](/ai-agent-for-content-creation/) covers how I think about the workflow itself, and [the AI tools I actually use as a content creator](/best-ai-tools-for-content-creators/) covers what runs alongside it. ### **AI Content Repurposing FAQs** #### **What is AI content repurposing?** AI content repurposing is turning one piece of content, like a video, podcast, webinar, or long post, into every other format you publish: a blog post, platform-specific social posts, a newsletter, short-form hooks, and graphics. The useful versions check every draft against a written record of your voice, so the output does not read as generic AI content. #### **How do you make AI content sound like you?** Give it a voice file built from your actual writing rather than a prompt. It should capture your vocabulary, sentence rhythm, opinions, and the words you avoid, and every draft should be scored against it before you read it. A prompt starts from zero each time, which is why prompt-only repurposing produces the same generic voice for everyone. #### **Can you repurpose content if you do not have a YouTube channel or podcast?** Yes. The seed does not have to be published content. A voice memo transcript, a webinar recording, a post you already wrote, or a ten-minute interview where an AI asks you questions about your work all give you enough raw material for a week of content. #### **How long does AI content repurposing take?** With the voice file and the format rules already written down, one seed to a full week of drafts is a single focused work session, plus your review. The setup is the slow part and you only do it once. Doing the same multiplication by hand is most of a workday every week. #### **Is repurposed AI content bad for SEO?** Not inherently. Google penalizes unhelpful, scaled, low-quality content regardless of how it was made, not repurposing itself. What gets sites in trouble is publishing unreviewed near-duplicate pages at volume. Repurposing one genuine idea across formats, with an editor approving each piece, is normal content marketing. #### **Do you need to know how to code to use an AI repurposing system?** No. The system is a folder of plain text files you hand to an AI assistant, and you drive it by typing sentences like "turn this into my week of content." If you can describe your business and copy-paste a link, that is the skill bar. The one requirement is a paid plan on an assistant that can read files. --- ## 4 AI Search Myths That Cost You Money (These Don't Matter) URL: https://ryandoser.com/ai-search-myths/ Markdown: https://ryandoser.com/ai-search-myths.md Published: 2026-08-28 Categories: AI Rabbit Holes > llms.txt, prompt volume, AI rankings and training-data spam, checked against Google and OpenAI docs. Plus the advice Google itself still gets wrong. The most repeated piece of AI search advice on the internet stopped being true back in 2024, and Google's own AI Overview was still handing it to me last week. It told me to go optimize for Bing. That one is the bonus at the end. First, **four AI search tactics** that fall apart the moment you check them, all of which someone is actively selling you right now. One quick note on where this came from. Dan Petrovic of DEJAN AI went on the [Ahrefs Podcast](https://www.youtube.com/watch?v=roTPZBj4JSc) in August and took apart several of these live. He is one of the [people worth following on AI search](/best-ai-seo-experts/), and I verified his claims independently rather than repeating them. Most held up. The one that did not is the same line Google is repeating. Fair warning on my bias. All four already sit on the do-not-chase list inside my [AI SEO System](https://seo.ryandoser.com/), so I am not arriving at this neutrally. Where a primary source settles a question I quote it directly, and where the evidence is one practitioner's own testing I label it as that. Every source is linked so you can check the reasoning instead of taking mine. ### **Myth 1: llms.txt Gets You Into AI Answers** There are generators, plugins, agency line items, and consultants selling you a plain text file. Start with Google, since it is the only player here that states a position in writing. Its documentation on AI features says this, word for word: *"You don't need to create new machine readable files, AI text files, or markup to appear in these features. There's also no special schema.org structured data that you need to add."* That is [Google Search Central](https://developers.google.com/search/docs/appearance/ai-features), not a blogger. Same page also states there are no additional requirements to appear in AI Overviews or AI Mode. Then there is the question of whether anything reads the file at all. Ahrefs studied 137,000 domains and found 28 percent publish an llms.txt. Of the roughly 38,000 that had a valid one, [97 percent received zero requests for it](https://ahrefs.com/blog/what-is-llms-txt/) in May 2026. Their words: no bots, no humans, nothing. A separate study from [SE Ranking](https://seranking.com/blog/llms-txt/) ran 300,000 domains through correlation and machine learning and found the file did not make a domain more likely to be cited. Google's John Mueller compared it to the old keywords meta tag, and noted you can tell from your server logs that the AI services do not even check for it. #### **Now Here Is My Own Contradiction** Go type ryandoser.com/llms.txt into your browser. There is a file sitting right there. Petrovic has one too, and his reasoning on the podcast was blunt. He said he put it on his site because it is so easy to do and it does not harm anything, then added that some fringe models use it and nothing important does. That is the honest position rather than a clean one. The file costs fifteen minutes and zero dollars, so calling it a scam overstates things. Calling it a strategy overstates them a lot more. It does carry one cost people skip past. It is a document you wrote about yourself that something might read, so a stale price or a dropped capability in there shows outdated information to anything that opens it. Keep the facts current, then stop thinking about it, and do not pay anyone a monthly fee to maintain one. ### **Myth 2: You Can Look Up Prompt Volume** Several tools now sell you something labeled prompt volume, presented the way keyword volume is presented, as though a number of people per month typed a given prompt. Petrovic's response to this on the podcast is the most quotable thing in the whole hour. His words: "for everyone who's been hypnotized by the prompt search volumes, look at me in the eyes. There is no prompt volume." His argument is mechanical rather than cynical. Outside a few short common phrasings, the odds of two people typing the same prompt the same way are small. People also do not send one prompt and stop, they have multi-turn conversations, and personalization layers on top so location, history and logged-in state all bend the answer. Tim Soulo, Ahrefs' CMO, backed this up from their own sampling of clickstream providers. Real prompts run long, multi-topic, and often follow on from something else. There is a defensible version of the measurement, and it is genuinely useful. Take one prompt, pull the fan-out queries the search backend actually fired, and look at real search volume for each. Petrovic's condition is the whole point. What you are looking at there is the volume of the queries the backend triggered, so call it that, and since those queries overlap, treat any sum of them as a rough ceiling rather than a headcount. That distinction matters because the fan-out is real and documented. Google's own AI features page confirms both AI Overviews and AI Mode may use a query fan-out technique, issuing multiple related searches across subtopics. So the sub-queries exist and have measurable volume. The prompt on top of them does not. ### **Myth 3: You Can Rank in ChatGPT** Search how to rank in ChatGPT and you will find guides promising a number one position, some in 48 hours. There is no fixed position to hold. Answers are generated per request, so while a brand can certainly be named first, that order is not a standing placement anyone assigns. Ask the same question twice and you can get different companies in a different sequence, from the same model, on the same day. What does exist is a rate. Across many asks, phrasings and engines, you get named some percentage of the time. That number is real, it moves with your work, and it behaves nothing like a ranking you can hold. The distinction changes what you should buy. If a vendor uses the word ranking as shorthand for a metric they will show you, fine. If they cannot say what position means or how they measure it, that is the moment to slow down, because everything else they tell you sits on top of it. Same logic on the dashboards. If a tool scores your brand out of 100, ask what it measures, how many prompts it samples, which engines, and whether it can tell being recommended apart from being cited in an answer that sells somebody else. Those two are not the same, and I dug into [why grounding, citation and mention are three different outcomes](/how-to-manipulate-ai-search/) separately. Any of these numbers will move on their own between runs, which is exactly why you want to see the underlying answers rather than the score. It is also worth asking whether the vendor keeps its own numbers straight, which is where my [AIclicks review](/aiclicks-review/) ended up. ### **Myth 4: You Can Spam Your Way Into the Training Data** The theory goes that if you publish enough content saying your brand is the best, the next model learns it. The labs have moved toward curated and filtered datasets, and the filtering step is cheap enough that volume alone is a bad bet. Petrovic showed how cheap one kind of detection gets. He built a text classifier on gzip compression alone, no machine learning involved, and reports 90 to 99 percent accuracy separating quality writing from filler on his own test set. I covered [how that classifier works in my roundup of AI search experts](/best-ai-seo-experts/). Be precise about what that shows. A quality filter is a different tool from a brand-manipulation detector, and this was his own unpublished test without a stated sample size or false-positive rate. He tells you to go replicate it, which is the right way to offer a claim like that. What it does establish is the economics. If sorting real writing from generated filler costs almost nothing, then the cheapest thing you can do at scale is also the easiest thing to screen out. Soulo drew that conclusion on the episode, and it is the part of the argument that holds regardless of the exact accuracy figure. ### **The Bonus Myth: Rank in Bing and ChatGPT Will Find You** The other four all have somebody selling them. This one is different, and it is the reason I wanted to write this post at all. When I searched "how to rank in chatgpt" on August 28, Google's own AI Overview listed optimizing for Bing indexing as step two, on the reasoning that ChatGPT leans on Bing's index. Petrovic gave a version of the same answer on the podcast, with the caveat that he was simplifying. Run that search yourself, since AI Overviews are personalized and change constantly. It has gone stale. Your eligibility to appear in ChatGPT now runs through OpenAI's own crawler rather than through Bing, and [OpenAI's crawler documentation](https://developers.openai.com/api/docs/bots.md) says so plainly. I laid out the full evidence, including what the retrieval stack looks like by tier, in [my breakdown of which search index each AI assistant reads](/what-search-engine-does-claude-use/). What matters here is who was repeating it. Petrovic is a credible practitioner with fifteen years in and first-party research behind his claims, and he hedged the line as he said it. Google's own AI feature repeated it too. Nobody was selling anything. That is the actual lesson. In a field moving this fast, most bad advice starts out as a true statement that quietly goes stale while everyone keeps repeating it, including the people who got it right the first time, and including Google. ### **Final Thoughts from Ryan** Here is the test to run on anything you get pitched from here on. Ask what it measures in one plain sentence. Ask to see the actual AI answers behind the number. Ask what happens to the score if you change nothing for a month. What survives that test is usually boring. Can AI crawlers reach your pages. Are those pages indexed. Does the page answer the question in the first 40 words instead of the fifth paragraph. Is there a comparison table a model can lift cleanly. Does the web mention you anywhere you do not own. None of that photographs well in a dashboard, which is roughly why nobody is selling it to you. AI search is new enough that nobody has to lie to sell you something useless. As the bonus item shows, a description that was accurate two years ago does the job on its own, even coming from Google. Almost everything above traces to a document you can open in ten minutes, and where it traces to one guy's unpublished test instead, I said so. Go check my llms.txt while you are at it. ### **AI Search Myths FAQs** #### **Does llms.txt actually do anything for AI search?** There is no demonstrated citation benefit. Google's documentation states you do not need machine readable files or AI text files to appear in its AI features, and of roughly 38,000 domains Ahrefs found with a valid llms.txt, 97 percent received zero requests for it in May 2026. Some tools and smaller models do read the file, so this is not the same as saying nothing touches it. Keeping an accurate one costs little. Building a strategy on it is the mistake. #### **Is prompt volume a real metric?** Not as it is usually sold. Outside a few short common phrasings, identical prompts are improbable, most real usage is multi-turn, and personalization changes the result per person. The defensible version is to pull the fan-out queries a prompt actually triggers and look at search volume for those, treating any total as a ceiling rather than a headcount, since the sub-queries overlap. #### **Should I pay for an AI visibility tracking tool?** Only if it shows you the underlying answers, and only after you have checked [which trackers ration AI engines at the entry tier](/best-ai-visibility-tools/). A tool that surfaces the actual prompts and responses is doing work you could not do by hand at volume. A score with no visible evidence behind it cannot be audited, and it drifts between runs regardless of what you changed, so you cannot tell a real move from noise. I worked through what that costs in practice in my [Searchable review](/searchable-review/), where the vendor publishes enough numbers to check the sampling against the research. *How I sourced this: Google's position is quoted from Search Central's AI features documentation and OpenAI's from its published crawler docs, both read directly on August 28, 2026. The llms.txt figures come from Ahrefs' 137,000-domain analysis and SE Ranking's 300,000-domain analysis, both linked above and run on different samples, so their adoption rates are not directly comparable. Dan Petrovic's claims are quoted from the Ahrefs Podcast episode published August 18, 2026, and are his own first-party testing rather than published studies, which is how I have labeled them throughout. The AI Overview I describe was what I saw on August 28 and is personalized, so yours may differ. I sell an AI SEO product, which is linked in this post. [Full disclosure](/disclosure/).* --- ## Alertmouse Review: The Best Way to Track Brand Mentions Online URL: https://ryandoser.com/alertmouse-review/ Markdown: https://ryandoser.com/alertmouse-review.md Published: 2026-08-28 | Updated: 2026-08-28 Categories: AI Tool Reviews > Alertmouse is the best brand mention tracker I have found, and a real Google Alerts upgrade. Verified pricing, the annual-billing catch, and the one thing it misses. **Alertmouse** is a brand mention tracker built by Rand Fishkin, cofounder of Moz and SparkToro, along with Adam Doppelt and Nathan Kriege. It starts free, and it is a genuine upgrade on Google Alerts. It is the best tool I have found for tracking brand mentions across the open web, and I want to be precise about that boundary. Alertmouse does not track mentions inside ChatGPT, Gemini, or Perplexity answers, and I checked that against every page the company publishes about the product. That distinction is the whole reason this **Alertmouse review** is worth your time. The tool watches the open web, which is the material AI answers get built from, and that turns out to be a more useful job than the one people assume it is doing. My position, so you can weigh the rest: I have read the pricing page, the API docs, the terms, and the FAQ, and I have not run this on a client campaign for six months. I can tell you what it commits to in writing and where the marketing outruns the product, not what it produced for me over a long haul. I earn nothing if you sign up. There is no affiliate link in this post. ### **What Alertmouse Actually Does** You give it a phrase. It searches the web for that phrase and emails you when it finds something. That is genuinely the whole product, and the team says so plainly on the about page: "We make alerts. Really. That's our whole thing." ![Alertmouse homepage showing the tagline Simple, free email alerts, prioritized, filtered and graphed](/images/2026/08/alertmouse-review-homepage.jpg) What separates it from Google Alerts is what happens between finding a mention and sending you the email. Alertmouse scores, sorts, and suppresses. Every mention gets a score from 1 to 100, which the API documentation confirms. Mentions from prestigious outlets and accounts get flagged as "big cheese." Mentions the system judges unimportant or spammy get "hushed," meaning they never reach your inbox but stay visible in gray on your dashboard. That last detail matters more than it sounds. Suppression you cannot inspect is just data loss. Suppression you can audit is a filter you can actually trust, because you can go check what it decided to hide from you. ### **Why Brand Mention Tracking Became an AI Search Problem** This is the part that moved Alertmouse from mildly interesting to something I think marketers should genuinely care about. When someone asks ChatGPT or Claude to recommend a tool in your category, the model draws on what the open web says about you, plus whatever it can retrieve at answer time. Your own homepage copy carries far less weight in that process than most marketers assume. Your brand's reputation across blogs, forums, news, and Reddit is the raw material those answers get built from. Which means the mentions you never saw are still shaping how you get described to buyers. The same goes for the people behind your brand. Chris Panteli of Linkifi says ChatGPT often recommends a named specialist over the firm on local questions, which I cover in [why ChatGPT recommends the person behind the business](/how-to-get-chatgpt-to-recommend-your-business/). Alertmouse names this audience directly on its homepage. It lists "AI marketers and SEOs monitoring how their brand mentions co-occur with words that influence search engine and LLM answers" as a target user. Co-occurrence is the useful idea buried in that sentence. What matters is not simply whether you get mentioned, but which words sit next to your name when you do. If your brand keeps appearing beside "expensive" or "hard to cancel," that pairing is exactly the kind of material these systems can retrieve and repeat. Catching it early is a content and PR problem you can act on, and one you cannot act on if nobody tells you it happened. I wrote more about how this fits a wider plan in my breakdown of [AI SEO strategy](/ai-seo-strategy/), and the tooling side in [the best AI SEO tools](/best-ai-seo-tools/). ### **The Thing Alertmouse Does Not Do** Several published roundups imply otherwise, so here is what the vendor actually says. Alertmouse will not tell you whether ChatGPT recommended you last Tuesday. Nothing on the homepage, pricing page, API docs, FAQ, about page, or terms of service claims to read model output. Notice how carefully the company words its own AI pitch, though. Marketing itself for mentions that "co-occur with words that influence" LLM answers is a claim about the input side, and it stops there rather than promising to read model output. I give them credit for that restraint. This is a team whose about page cheerfully calls Google Alerts "so bad it might as well not exist," so they are clearly not shy about marketing claims, and they still did not overreach on the AI question. The vendor silence is the actual evidence here. For what it is worth, ChatGPT with live web search reached the same conclusion when I asked, but the reason to believe it is that a company this happy to market itself has never once claimed the capability. So if your goal is a dashboard showing your share of AI answers, this is the wrong purchase and no amount of clever alert setup will get you there. A dedicated AI visibility tracker is the tool built for that job, and I worked through what one actually measures in my [Searchable review](/searchable-review/). If you want the cheap end of that market, [Otterly starts at $29 a month](/otterly-ai-review/), with the caveat that three of the seven AI engines it advertises are billed separately. What it does instead is monitor the layer underneath. Public web content is a major part of what those answers get assembled from, and Alertmouse watches that layer closely. Both jobs are real. They are not the same job, and I would rather you buy the right one. ### **Alertmouse Pricing, Verified** I pulled these from the live pricing page on August 28, 2026. ![Alertmouse pricing page showing Nibble free, Slice at 120, Wedge at 600, and Wheel at 1200 per year](/images/2026/08/alertmouse-review-pricing.jpg) | Plan | Annual price | Alerts | Users | Mentions/day | History | API | | Nibble (Free) | Free | 1 | 1 | Up to 10 | 60 days | No | | Slice (Basic) | $120 | 5 | 3 | Unlimited | 1 year | No | | Wedge (Pro) | $600 | 50 | 10 | Unlimited | 2 years | No | | Wheel (Enterprise) | $1,200 | 200 | 100 | Unlimited | 2 years | Yes | Now the detail the cards bury. Every paid tier is billed annually. The page shows "$10/month billed annually" under Slice, and there is no monthly toggle anywhere on it. The arithmetic is honest, since $120 divided by 12 is exactly $10, but the commitment is a year of cash up front rather than ten dollars. For Slice that is a $120 decision, which is small enough that most people will not care. For Wedge it is $600 committed before you have seen how it handles a busy month for your brand. The free tier is what makes this defensible. One alert, forever, no card, is a real evaluation path and not a countdown trial, so you can point it at your own brand name and see what it surfaces before you commit anything. Watch the free plan's ceiling of 10 mentions a day, though. If your brand is mentioned more than that, you are sampling rather than monitoring, and the tool will feel quieter than reality. ### **The API Is Enterprise Only** This is the limitation most likely to bite the people reading my site, so it gets its own section. ![Alertmouse API documentation page showing the enterprise-only notice and endpoint reference](/images/2026/08/alertmouse-review-docs.jpg) API access is gated to the $1,200 Wheel plan. The docs say it outright: "Heads up! The API is only available to enterprise customers." If you were planning to pipe mentions into a Claude workflow or an automation on the cheap plan, that door is closed. Everyone below Wheel gets email and the dashboard, full stop. One thing worth knowing if that gate stings: the precise filtering is in the web interface too, so you do not need API access for it. You can require a keyword or exclude one, which is how you rescue a brand name that collides with a common word. If you have ever tried to monitor a brand named after an ordinary noun, you already know why that matters more than API access does. ### **What Other Alertmouse Users Actually Say** My read is one data point, so here is the public pool. The pattern in it is unusually consistent. Arielle Johncox, Head of Marketing at Balsamiq, calls it "1000x better than Google Alerts" and credits it for catching conversations across Google, Reddit, job postings, and social media. Talia Wolf, CEO of GetUplift, says she keeps "uncovering new blogs, sites, forums, and profiles that mention me, that I had no idea about." Jono Alderson, a digital marketer the site describes as an exceptionally picky software user, calls it "far better at detection and noise reduction than anything else I've ever used." Coywolf reviewed it in October 2025 and updated the piece in June 2026, highlighting the inclusion and exclusion keywords and the auto-ignore rules among the upgrades over Google Alerts. Two honest caveats about that pool. These are marketers in Rand Fishkin's professional orbit, which is exactly the crowd most likely to try a tool he built and least likely to be neutral about it. And there is no large independent review base yet. I could not find a G2 or Trustpilot listing with meaningful volume, so what exists is testimonials and a handful of blog posts rather than hundreds of scored reviews from strangers. The praise clusters tightly around one specific thing, though, and it is the thing that matters: detection. Different people, independently, saying it found things they did not know existed. ### **Where Rand Fishkin Fits In** Rand Fishkin's [SparkToro bio](https://sparktoro.com/team/rand) lists Alertmouse as one of the companies he cofounded, alongside SparkToro itself. His history is the relevant credential here. He cofounded Moz and grew it past 200 employees and $50 million in revenue across 17 years, stepping down as CEO in 2014 and leaving the company in 2018. I want to be precise about why that matters, because founder pedigree is usually a lazy argument. Founder pedigree alone does not prove the software works. What it does explain is the product's shape. SparkToro is an audience research tool, and Alertmouse is a monitoring tool, and both are bets that knowing what the web says about you is worth paying for. Fishkin has also published research arguing that AI systems are strikingly inconsistent when they recommend brands. A person who believes that is going to build for the durable layer, which is the mentions themselves, rather than for a dashboard of model outputs that shift week to week. Worth noting for anyone tempted to read this as an endorsement of him as a service provider. He left the SEO consulting world in 2018, as I noted in my roundup of [AI SEO experts worth following](/best-ai-seo-experts/). He builds software now. ### **Alertmouse vs Google Alerts** The comparison is unavoidable, since the company frames its entire existence around it. | | Alertmouse | Google Alerts | | Price | Free tier, then $120/year | Free | | Mention scoring | Yes, 1 to 100 | No | | Spam suppression | Yes, auditable on dashboard | No | | Include/exclude filters | Yes | Limited to search operators | | Dashboard and graphs | Yes | No | | Mention history | 60 days to 2 years by plan | None retained | | API | Enterprise plan only | No | The honest version of this comparison: Google Alerts was never really finished. It sends you links with no scoring, no history you can go back through, no way to see what it decided to skip, and no view of whether mentions are trending up or down. It notifies you and stops there, which leaves the actual monitoring work on your desk. Alertmouse is the same job with the missing half built. Whether that half is worth $120 a year depends entirely on whether anyone at your company would act on a mention. It is worth knowing the wider field, because Alertmouse is not the only answer here. Talkwalker Alerts is the usual free recommendation, F5Bot covers Reddit and Hacker News for nothing, and Mention, Awario, and Brand24 sit at the heavier social-listening end with pricing to match. Alertmouse sits in a gap those leave open. It is better filtered and better organized than the free tools, and far cheaper and simpler than the listening platforms, which is the whole reason I rate it for a solo operator or a small team. If nobody would, stay on Google Alerts and save the money. This is not a tool that creates value on its own. ### **Where Alertmouse Falls Short** The annual billing is my biggest complaint. No monthly option means the cheapest way to actually test a paid tier is to commit to a full year. The free plan softens this a lot, but 10 mentions a day is a low ceiling for exactly the brands most likely to buy. The API gate is the second issue. Locking programmatic access to the $1,200 tier puts it out of reach for the solo operators and small teams who would get the most creative use out of it. Third, no tool catches everything, and Alertmouse admits it. Under a FAQ entry for a mention that looks wrong, the company says pages with "messy or strangely formatted text can confuse our parsers" and that "documents and PDFs can be particularly difficult." I would rather read that than a promise of total coverage. It is still a limitation, and if you need legally defensible completeness, no email alert product is your answer. Fourth, mentions surface with two different dates. The system records when it discovered something and separately notes any date found in the content, because old pages turn up at any time. That is the correct design, but it means a fresh alert is not always fresh news, and you will occasionally get excited about a mention from 2021. Finally, this is a small operation. Three cofounders, an all-remote team in Seattle, and a deliberately narrow product, which keeps it focused and also means support and roadmap move at the pace of a very small crew. ### **Who Should Actually Buy Alertmouse** Buy it if your name or your brand is the product. Founders, consultants, authors, podcasters, and anyone whose reputation drives their pipeline get the clearest return, because a single caught mention can be worth the annual price. Buy it if you do digital PR or run comms and you currently find out about coverage when someone forwards it to you. The history and the graphs turn scattered mentions into something you can put in front of a client or a boss. Buy it if you are working on AI search visibility and you want to see what the web is actually saying about you, since that is the material models draw on when they describe you to a buyer. Skip it if you are hoping to track your presence inside ChatGPT answers. That is a different category of tool and this one does not claim the job. Skip it if nobody on your team has the time or authority to act on a mention. An alert nobody responds to is just email. Skip the paid tiers if the free alert covers you. One well-built alert on your brand name genuinely is enough for a lot of solo operators, and the company seems fine with that. ### **Final Notes from Ryan** Alertmouse is a narrow tool that does one job properly, and I have a lot of time for that in a market where everything wants to become a platform. The strategic case is stronger now than it would have been three years ago. Brand mentions used to be a PR metric, and now they are an input into how AI systems describe you to people evaluating a purchase. My honest reservation is the annual commitment on a product with such a thin independent review base behind it. Use the free alert first, for a few weeks, on your own name, and see whether it surfaces things you genuinely did not know. If it does, the paid tier is easy math. If it goes quiet, you learned that cheaply and you are out nothing. The part I keep coming back to is that "hushed" mentions stay visible in gray. A tool confident enough to show you what it filtered is a tool built by people who expect to be checked, and that is rarer than it should be. ### **Alertmouse Review FAQs** #### **How much does Alertmouse cost?** Alertmouse is free to start. The Nibble tier gives you one alert, one user, up to 10 mentions a day, and 60 days of history, with no credit card required, and the company describes that first alert as free forever. Paid plans are Slice at $120 a year, Wedge at $600, and Wheel at $1,200. All paid tiers are billed annually, with no monthly-only option on the pricing page. The per-month figures on the cards, $10, $50, and $100, are the annual price spread across twelve months rather than a separate monthly rate. #### **Who created Alertmouse?** Rand Fishkin, Adam Doppelt, and Nathan Kriege. Fishkin cofounded Moz and is CEO and cofounder of SparkToro, and his SparkToro bio lists Alertmouse as one of three companies he cofounded. Doppelt previously founded Urbanspoon and Dwellable. The company is Alertmouse LLC, based in Seattle, and the about page describes an all-remote team. #### **Does Alertmouse track brand mentions in ChatGPT or other AI answers?** No. Alertmouse monitors the open web, including news, blogs, forums, and social media, and it does not read or report on what AI chatbots say about you. If you want a share-of-answers dashboard across ChatGPT, Gemini, or Perplexity, this is the wrong tool. What it does track is the kind of public web content those systems commonly draw on, which is why it still matters for AI search visibility. #### **Is Alertmouse better than Google Alerts?** For most people who care about the answer, yes, and the gap is in what happens after a mention is found. Google Alerts sends links with no scoring, no retained history, and no record of what it chose not to send you, while Alertmouse does all three. The tradeoff is cost. Google Alerts stays free forever, while the first paid Alertmouse plan costs $120 a year if you outgrow the free tier, whether from needing more alerts or from passing its 10-mentions-a-day ceiling. #### **What are the best Alertmouse alternatives?** Talkwalker Alerts is the most common free alternative, and F5Bot covers Reddit and Hacker News at no cost. At the paid end, Mention, Awario, and Brand24 offer heavier social listening with sentiment analysis and reporting, at prices well above Alertmouse. Alertmouse occupies the middle: better filtered and better organized than the free options, much cheaper and simpler than the listening platforms. #### **Does Alertmouse have an API?** Only on the $1,200 Wheel plan. The documentation states plainly that the API is available to enterprise customers only, so Nibble, Slice, and Wedge users get email alerts and the dashboard and nothing programmatic. Worth noting the include and exclude keyword filters work in the web interface, so you do not need the API for precise alerts. *Disclosure: this post contains no affiliate links and I earn nothing if you sign up for Alertmouse. I have no relationship with Alertmouse or its founders. Method: I reviewed the live Alertmouse homepage, pricing page, about page, FAQ, API documentation, and terms of service on August 28, 2026, alongside published coverage and public testimonials, and I verified the AI-answer tracking question against a live web-search-enabled model query. I have not run Alertmouse on a long-term client campaign, and this review reflects documented capabilities rather than firsthand long-term use. I sell my own AI SEO training, which competes for the attention of the same readers. [Full disclosure](/disclosure/).* --- ## How to Manipulate AI Search (With Data from SEO Expert) URL: https://ryandoser.com/how-to-manipulate-ai-search/ Markdown: https://ryandoser.com/how-to-manipulate-ai-search.md Published: 2026-08-28 | Updated: 2026-08-28 Categories: AI Rabbit Holes > Experiment data from Kasra Dash plus Dan Petrovic on what AI search actually rewards. Grounding, citation, and mention are three different things. This guide shows you **how to manipulate AI search** using real experiment data from SEO expert [Kasra Dash](https://www.youtube.com/@kasradash), one of the [people worth following on AI search](/best-ai-seo-experts/). No theory, just what moved the needle across ChatGPT, Claude, Perplexity, Grok, and Google AI. ### **How to Manipulate AI Search in 2026** Most AI SEO advice on X is pure theory. Kasra ran a real test. He published 50 self-referencing listicles on a mid-age domain and tracked the citations. The results were wild. Grok and Perplexity picked up the brand 8 out of 10 times. ChatGPT and Claude hit 6 out of 10. Google AI was the toughest, landing only 3 out of 10. **[Kasra's full AI search manipulation data](https://x.com/Kasra_Dash/status/2043655484821922039)** is public on X. The takeaway is simple. LLMs are easy to game right now, but each engine has a different weak spot. *Kasra's live test dashboard shows Grok and Perplexity cited the test site 8 out of 10 times, while Google AI trailed at 3 out of 10.* ### **Why Grok and Perplexity Are the Easiest to Manipulate** Both tools get gamed because they lean on live web search for almost every query. They crawl the SERP and summarize the top results. Rank on page one, and your citation is almost guaranteed. ChatGPT works differently. It runs three bots in parallel. A cache bot checks its own pre-trained library. A SERP bot scans meta titles and descriptions. A page-fetch bot visits specific URLs when the first two are not clear. Claude sits in the middle, with web fetch spinning up sub-agents in real time. A brand new entity can show up inside the live-search tools within days. Getting into the ChatGPT cache takes three to six months, since the refresh cycle only runs a few times a year. *Kasra published 50 articles in three batches across six weeks to measure how each LLM picks up new citations over time.* #### **What Happened When Pages Were Deleted** Kasra also 410'd the pages to see what would happen. The live-search tools dropped citations almost instantly. Claude, ChatGPT, and Google AI kept referencing the deleted URLs for weeks. That gap matters. The bigger players hold onto stale data far longer than expected. ### **Self-Referencing Listicles, Comparisons, and Alternative Pages** Kasra tested three page formats in the experiment. Each one targets a different buyer intent. - **Self-referencing listicles** like "Best SEO Tools in 2026" with his brand listed at the top - **Comparison pages** like "Ahrefs vs Semrush" with his brand included as an option - **Alternative pages** like "Semrush alternatives" for users who churned from a competitor All three formats pulled citations, but the listicles hit hardest. Comparisons worked best when the content stayed balanced. A 50/50 tone gets picked up. A biased page does not. For an alternatives page that ranked first when we recorded and still drew a public rebuttal from the competitor it targets, see my [SaaS SEO episode with Sam Dunning](/saas-seo/). One catch. If a competitor already owns the entity in the SERPs, listicles alone will not topple them. User signals inside the LLM tools push the rankings too. When people search your brand inside ChatGPT or Claude, your position jumps in general queries. YouTube, Reddit, and newsletters compound the effect. See [my guide on Claude Code for SEO](/claude-code-seo/) for the workflow I run on my own site. ### **Why Your Vibe Coded Website Is Tanking Your SEO** Kasra pulled 6,500 sites built on Lovable. The results were brutal. Most do not rank, and plenty never even get indexed. The problem is how the browser renders the page. Everything loads through JavaScript. Right-click, view page source, and there is almost no content in the HTML. Google and the LLMs crawl the code first, not the rendered view. No content in the source means no content to cite. *A Lovable-built site on screen has almost no crawlable content in the source, which is why most vibe coded websites fail SEO.* I pulled up Foreignerds, an AI consulting firm running on Lovable, and the source was a wall of JavaScript. A fencing company in Seattle had the same issue. Both were chasing money keywords, and both were invisible to the crawler. **[Kasra's Lovable website SEO data](https://x.com/Kasra_Dash/status/2038885686938370541)** confirms the pattern across the board. Not every vibe-coded site fails. [Claude Code for landing pages](/claude-code-landing-pages/) outputs clean server-side HTML with real on-page SEO baked in. Lovable works for one-page brochures and paid media landers. It does not work for anything that needs to rank. ### **Grounding, Citation, and Mention Are Three Different Things** Most people chasing AI visibility are measuring the wrong thing, and this distinction is the fix. It also explains why the trackers disagree with each other, which I get into in my [Searchable review](/searchable-review/). Some of that gap is simpler than it looks, since two tools quoting similar prices can be watching different sets of engines, a split I picked apart in [this Otterly AI review](/otterly-ai-review/). Dan Petrovic of DEJAN AI laid this out on the [Ahrefs Podcast](https://www.youtube.com/watch?v=roTPZBj4JSc), and it reframed how I read my own tracking data. He splits AI visibility into three separate outcomes that people constantly blur together. **Grounding** means your page got handed to the model as candidate context. The model saw it. That is all. **Citation** means the model used your page to support a specific claim. **Mention** means your brand name actually appears in the answer the reader sees. Those are not steps on one ladder. You can be grounded and never cited. You can be cited as a source while the sentence built from you recommends a competitor. Petrovic's ranking of what matters is blunt. The linked mention is the prize, and he says stop obsessing over citations. Getting quoted is not the same as getting recommended, and only one of those sends you a customer. For a local business the gap shows up plainly in [which pages an AI answer is built from](/how-to-rank-in-chatgpt/). #### **The Reddit Shortcut Is Weaker Than It Looks** Here is the finding that surprised me most. In Petrovic's API testing, Reddit was rejected as a grounding source over 90 percent of the time. His explanation for why it still shows up: Reddit ranks, so it gets pulled into the grounding set, and then the model declines to use it. That is his data from his own testing rather than a published study, so weigh it accordingly. But it cuts against the "just get mentioned on Reddit" advice that has been sold hard for two years. The practical read is not that Reddit is worthless. It is that a Reddit mention is a lottery ticket, not a placement, and pricing it like a placement is how people waste budget. ### **Write So Every Sentence Survives Being Lifted Out Alone** One more mechanic worth knowing, because it changes how much of your page survives. Petrovic describes Google as grounding one-to-many. A single sentence in an AI Overview can carry three or four sources behind it. Google grounds nearly everything, because running its own search costs it nothing. OpenAI he describes as one-to-one. One URL grounds one sentence. The consequence is about compression. Google does extractive summarization, meaning it lifts verbatim fragments from your page and stitches them together. Your full page never reaches the model, and you do not control where it cuts. So the unit that travels is the chunk, not the article. If your qualifying condition sits in a different sentence from your claim, the two can get separated, and the version that survives is the one that speaks for you. That is the single most actionable idea in this whole post. Write so that any individual sentence still tells the truth when it is lifted out alone. If you want the layer underneath this, which index each assistant is actually reading when it grounds an answer, I dug into [what search engine each AI uses](/what-search-engine-does-claude-use/) separately. ### **GEO vs SEO: You Cannot Skip the Fundamentals** The biggest mistake people make in AI SEO right now is thinking GEO or AEO is a separate game. It is not, and a lot of what gets sold under those labels is [four tactics that do nothing at all](/ai-search-myths/). I walk through why those acronyms describe the same work, and where the real differences show up, in my [guide to getting cited in AI answers](/ai-seo-strategy/). Every site I have seen win in AI citations also won in traditional search first. Google Search Console. Bing Webmaster. Yandex. Proper H1, H2, H3 hierarchy. Internal linking. Schema. These foundations drive the entire citation stack. Short version. You cannot rank in ChatGPT, Claude, or Perplexity without HTML content, indexing, and backlinks. The AI era did not kill SEO. It raised the floor. See [my post on Claude Code for keyword research](/claude-code-keyword-research/) for how I handle the fundamentals now. Kasra is speaking at **[The Masterminders SEO Conference](https://themasterminders.com)** in June. Follow his work at [kasradash.com](https://kasradash.com/). ### **Final Thoughts from Ryan** AI search manipulation is in its 2011 SEO phase. Easy, wide open, and closing fast. The winners are stacking mentions across owned and offsite content and keeping the core SEO fundamentals tight, using the [best AI SEO tools](/best-ai-seo-tools/) to track visibility and earn the trust signals that get them cited. If you want to win over the next year, start testing now. ### **How to Manipulate AI Search FAQs** #### **What is AI search manipulation?** The practice of shaping your content, entity mentions, and site signals so that ChatGPT, Claude, Perplexity, Grok, and Google AI cite your brand inside their answers. It covers self-referencing listicles, comparison pages, alternative pages, and user signal nudges inside the LLM tools themselves. #### **Which AI search engine is easiest to rank in?** Grok and Perplexity. Both engines rely on live web search for nearly every query, which means strong SERP rankings translate directly into citations. Kasra's test pulled 8 out of 10 references on both tools from a brand new site with 50 articles. #### **Do self-referencing listicles still work in 2026?** Yes, but only when the content is written well. Balanced tone, correct entities, and factual comparisons all matter. Biased or thin content gets filtered. Stack 30 to 50 pages across listicles, comparisons, and alternatives rather than publishing a single piece. #### **Why are Lovable and vibe coded websites bad for SEO?** Most vibe coding tools render content through JavaScript inside the browser. When Google or an LLM crawls the page source, there is almost no HTML to index. The site does not rank in traditional search and does not get cited in AI search. Claude Code and WordPress output clean HTML and avoid this problem. #### **Can you rank in AI search without ranking in Google?** Rarely. Every case study so far shows sites winning in AI citations also have strong traditional SEO foundations. Search Console, Bing Webmaster, Yandex, on-page structure, and backlinks still drive the citations. Skipping SEO basics to chase GEO or AEO is the most overrated tactic in the industry right now. --- ## 7 Repurpose.io Alternatives Priced by How Many Brands You Run URL: https://ryandoser.com/repurpose-io-alternatives/ Markdown: https://ryandoser.com/repurpose-io-alternatives.md Published: 2026-08-28 | Updated: 2026-08-31 Categories: AI Tool Reviews > Repurpose.io bills per account per network, so your brand count sets the price. What 7 alternatives cost at real setups, checked live. Nearly every page ranking for **Repurpose.io alternatives** is published by a company selling you the alternative. When I searched it on August 28, 2026, six of the ten organic results were vendor pages. Planable, OpusClip, Quso, Taja, ShortSync and Exemplary each explain why you should switch to them, Repurpose.io holds a slot itself, and the closest thing to a disinterested source is a Reddit thread titled "Stop using Repurpose.io." Worth knowing before you read my list: [Blotato](https://www.blotato.com/?ref=rdoser) is a client of mine, it appears below, and it runs its own roundup on this keyword that Google cites in the AI answer. That makes me the seventh interested party here rather than a neutral observer. All of those pages agree on one thing, and the arithmetic says they are wrong about it. They call Repurpose.io expensive. Run the numbers and whether Repurpose.io is expensive depends on something none of those pages mention. It bills per account *per network*, so the price is set by how many brands you run rather than how many accounts you have connected. Twenty-four accounts spread as 3 on each of eight networks costs $35. The same 24 accounts sitting on a single network costs $179. That single detail decides the comparison, and it cuts both ways. ### **Where My Knowledge Stops on This One** **I have never been a Repurpose.io customer.** I have not run a workflow on my own channels, so I cannot tell you how their support answers or what breaks in month four. What I have done is read the documentation properly and price every tool here from its own live rate card, monthly billing selected. Where a claim is the vendor's rather than mine, I say so. Of the tools below I use Blotato daily through its MCP server, I have run Opus Clip on my own videos, and I have used Zernio's dashboard without ever running it in production. The rest I priced and read rather than tested, and I have marked their entries accordingly. I wrote a full [Repurpose.io review](/repurpose-io-review/) separately, including the reach claim that Reddit thread is built on. ### **The One Distinction That Sorts This Whole List** Most tools sold as Repurpose.io alternatives are doing a different job, and sorting them by that job is the fastest way to cut the list down. Repurpose.io watches a source you already publish to. You post a video to YouTube or TikTok, and it detects that and pushes the file onward to your other platforms, resized, watermark stripped. Its own [platform matrix](https://support.repurpose.io/en/article/supported-platforms-roles-and-media-types-j22278/) sets out which platforms can act as a source, which can only receive, and which do both. Three different products get sold against that job. **Watchers** monitor a source and republish automatically. That is Repurpose.io's actual category, and very few tools genuinely sit in it. **Clippers** cut long video into shorts. OpusClip, Klap and Vizard do this. They solve the step before distribution, not distribution itself. **Publishers** post what you hand them, on a schedule you set. Buffer, Publer and Blotato live here, and most of page one is quietly this. Buying a publisher when you wanted a watcher is the easiest mistake to make here, because the marketing language for the two is nearly identical. ### **Repurpose.io Alternatives at a Glance** Every figure below is the monthly-billing rate from each vendor's own pricing page. Where a page opened on annual billing I switched it to monthly first, which changes the number on Buffer, Publer, Quso, Taja and Metricool. People search this as both Repurpose.io and repurpose io, and the tools below are the same either way. | Tool | Which job it does | Starts at (monthly) | What you pay per | Free tier | | Repurpose.io | Watches a source, republishes | $35 | Accounts per network | No, 14 days or 10 videos | | Blotato | Writes the post, then publishes | $29 | 20 accounts flat | No, 7-day trial | | Publer | Publishes, plus RSS auto-post | $5 first account | Each account, then $4 | Yes, 3 accounts | | Buffer | Publishes on a schedule | $6 per channel | Each channel, rate drops | Yes, 3 channels | | Zernio | Publishes, API first | Free, then $6 per account | Each account, graduated | Yes, 2 accounts | | ShortSync | Uploads once to 12 platforms | EUR 14.99 | Flat, one workspace | Yes, 5 uploads a month | | Quso.ai | Clips, then publishes | $29 | Credits per month | Yes, 75 credits | | Taja AI | Writes YouTube metadata, then posts | $19.99 | Videos and social sets | No, 7-day trial | ### **What It Costs by How Many Brands You Run** Not one of the ranking pages I read worked this out, which is odd, because the bill for your own setup is the thing people are trying to find. Repurpose.io's unit is the reason it gets misreported. Starter connects up to 3 accounts for *each* social network, so 3 Instagram plus 3 TikTok plus 3 YouTube all sit inside one $35 plan. Per-account tools charge for every one of those connections separately. *Repurpose.io prices per account per network, and leads with a daily figure rather than the monthly one.* So the number that moves your Repurpose.io bill is brands, not accounts. Here is what a few common setups cost, monthly billing, worked from each vendor's published rates. | Your setup | Accounts | Repurpose.io | Blotato | Zernio | Buffer | | 1 brand, 5 networks | 5 | $35 | $29 | $18 | $30 | | 1 brand, 9 networks | 9 | $35 | $29 | $42 | $54 | | 3 brands, 5 networks | 15 | $35 | $29 | $63 | $80 | | 3 brands, 9 networks | 27 | $35 | $97 | $99 | $126 | | 10 brands, 5 networks | 50 | $79 | $499 | $168 | $195 | | 10 brands, 9 networks | 90 | $79 | $499 | $288 | $235 | Read the top row and the bottom row together. One brand on five networks is the cheapest scenario for everyone except Repurpose.io, which charges $35 where Zernio charges $18. Ten brands on nine networks flips it completely. Repurpose.io is $79 and every per-account tool has passed it, with Buffer at $235 and Blotato at $499. The crossover sits around three brands. Below that, the cheap per-account tools genuinely are cheaper and the pages saying so are right. Above it, Repurpose.io is the cheapest thing on this page and those same pages are quietly wrong. One caveat on the comparison, because it matters. These tools are not doing identical work, so read the table as what each vendor charges to connect your accounts, not as a like-for-like quote for the same job. ### **The 7 Repurpose.io Alternatives Worth Your Time** Ordered by the job they do rather than by preference, with the two genuine watchers marked as such. #### **1. Blotato (Best for the part Repurpose.io never does)** *Blotato is flat per plan, so the bill does not move as you add accounts inside a tier.* [Blotato](https://www.blotato.com/?ref=rdoser) is the tool I actually publish through, every day, driven by an agent rather than a dashboard. It goes first because it fixes the thing Repurpose.io leaves to you. Repurpose.io moves a file you already made. Blotato writes the post around it, generating captions per platform and images or video, then publishes to nine platforms. That is a different product category bolted onto the same delivery job, and it is the reason I run it rather than a pure distribution tool. One thing to be straight about, because I have not seen it stated on a page selling you either tool. **Blotato has no source watcher of its own.** Its API exposes publishing, scheduling and DM automations, which I put up against [purpose-built DM tools](/best-instagram-dm-automation-tools/) separately, and its [Make integration](https://www.make.com/en/integrations/blotato) ships nine action modules and zero triggers. To copy Repurpose.io exactly you pair it with Make or [n8n](https://n8n.io/integrations/blotato/), whose own RSS or YouTube trigger does the watching and hands off to Blotato. That is a real extra step, and it buys content generation Repurpose.io has never offered. **Pros:** - Writes platform-native captions and generates images or video, so the post arrives finished - Flat $29 for 20 connected accounts, and the bill does not move until you cross the tier - Official n8n and Make nodes plus a hosted MCP server, so an agent can drive it end to end - Nine platforms including Pinterest, Bluesky and Threads **Cons:** - No native source-watching trigger, so trigger-and-republish needs Make or n8n alongside it - The 7-day trial excludes the API, and generating a key ends the trial and starts billing immediately - Jumps from $29 to $97 at 21 accounts, which is a steep step if you land just over - Caps posting below what the platforms allow, for example 50 Instagram posts per 24 hours **Best for:** Anyone who wants the caption and the creative written, not just the file moved. **Pricing:** $29 Starter (20 accounts), $97 Creator (40), $499 Agency (100), monthly billing. Annual saves about 17%. **Free trial:** 7 days, card required, and it does not include API access. **Bottom line:** If your bottleneck is writing the posts, this is the upgrade. If your bottleneck is purely moving a finished video and you want zero extra parts, a watcher below is the more honest fit. #### **2. Publer (The closest thing to a real watcher, and it is cheap)** *Publer bills per social account, and the first account costs more than the ones after it.* [Publer](https://publer.com/pricing) is the only tool here that does trigger-based publishing natively, with no second product bolted on. Its [RSS feature](https://publer.com/features/rss-feed) auto-posts new items, in its own words, "as soon as they arrive." That matters because a YouTube channel has an RSS feed. Point Publer at it and you have rebuilt the common Repurpose.io workflow for a few dollars a month, with the caveat that it distributes the link and text rather than re-uploading the video file natively. **Pros:** - Genuine auto-post from RSS, with auto-schedule and manual review as alternatives - Cheapest paid entry on this list at $5 for one account, and $4 for each one after that - Free plan covers 3 social accounts and 10 scheduled posts each - Wide platform list including Mastodon, Telegram and WordPress **Cons:** - RSS distributes links and text, so it is not a substitute for native video re-upload - Priced per social account, so the bill still climbs as you add accounts, reaching $37 at ten - The pricing page opens on the yearly toggle, so check it is set to monthly before you read a number - I priced and read this one rather than running it **Best for:** Anyone whose source publishes an RSS feed and who wants automation without a monthly platform fee. **Pricing:** Free, then Professional at $5 a month for the first social account and $4 for each additional one. Business is $10 then $7. Publer's help centre adds that every tenth account is free. **Free trial:** Yes, a permanent free plan plus a 7-day trial on Professional. **Bottom line:** The best value on this page if RSS covers your source. Check that first, because it decides whether Publer replaces Repurpose.io or merely resembles it. #### **3. ShortSync (Best free tier for actually publishing video)** *ShortSync inverts the model, taking a direct upload rather than watching a source.* [ShortSync](https://www.shortsync.app/) answers the question people actually type, which is whether there is a free Repurpose.io alternative. Its free plan gives you 5 uploads a month to all 12 platforms, permanently, with API and MCP access included. It also sidesteps Repurpose.io's most annoying constraint. Its [scheduling documentation](https://support.repurpose.io/en/article/how-scheduling-works-in-repurpose-setup-and-limits-iyhn5d/) puts it plainly, saying Repurpose does not currently support directly uploading video or media files into the platform, so everything has to arrive from a connected source. ShortSync is built the opposite way round, taking your upload and fanning it out. **Pros:** - Permanent free tier with 5 uploads a month and no card required - Accepts direct uploads, so nothing has to be published somewhere else first - Flat EUR 14.99 for unlimited uploads rather than per-account pricing - API and MCP access on every plan, including free **Cons:** - No source watching at all, so it does not replicate the automated workflow - Per-platform daily upload caps apply, inherited from each platform's API - Extra workspaces are EUR 10 each, which adds up for multi-brand work - Priced in euros, and its /pricing URL returned a 404 when I checked, so I read the rates off the homepage **Best for:** Creators who make the video themselves and want it everywhere without a subscription. **Pricing:** Free (5 uploads a month), Creator EUR 14.99, Team EUR 49.99, monthly billing. **Free trial:** Yes, a permanent free plan. **Bottom line:** The genuine free answer, as long as you accept that you are trading automation for a manual upload step. #### **4. Buffer (Best when you want boring and reliable)** *Buffer's page opens on Yearly, so the $5 shown is the annual rate and monthly is $6.* [Buffer](https://buffer.com/pricing) is the safe answer and the one most often named as the free option. Its free plan covers 3 channels with 10 scheduled posts each, which is enough to test whether scheduling alone solves your problem. The detail worth knowing is that its per-channel rate falls as you add channels, from $6 each down to $1 above 50, which makes it far less punishing at scale than a flat per-account rate implies. **Pros:** - Free plan on 3 channels with no time limit - Per-channel rate drops in bands, reaching $1 per channel past 50 - Publishes a machine-readable rate card, so the numbers are checkable - The longest track record here, running since 2010 by its own account **Cons:** - No source watching and no repurposing, it publishes what you give it - The pricing page defaults to Yearly and prints the annual rate with a "/month" suffix - Costs more than Repurpose.io beyond about 9 channels - I priced this from the rate card rather than running it **Best for:** Someone who wants a plain calendar and never wanted automation in the first place. **Pricing:** Free for 3 channels. Essentials $6 per channel monthly, Team $12, with volume bands above 10 channels. **Free trial:** Yes, free forever on 3 channels plus a 14-day trial on paid plans. **Bottom line:** Buy it knowing it is a scheduler. It is the wrong tool if the automation was the point, and the right one if you had quietly outgrown needing it. #### **5. Zernio (Best at the very small end)** *Zernio starts free for two accounts and meters everything after that per account.* [Zernio](https://zernio.com/pricing) is usage-based with no plans at all. The first 2 accounts are free, accounts 3 to 10 are $6 each, then $3, then $1 past 100. At three or four accounts nothing here comes close on price. Its own published example bills confirm the curve, and my arithmetic reconciles against them exactly. **Pros:** - Two accounts free permanently, no card - Every feature included on every account, nothing gated behind a tier - Graduated rates, so the marginal account gets cheaper as you grow - Publishes a rate card built for agents to read **Cons:** - No source watching, so it does not do the trigger job - Per-account metering climbs hard at scale, reaching $288 at 90 accounts against Repurpose.io's $79 - X usage is passed through at the platform's own per-call rates on top of your bill - I have used the dashboard but never run it as a production publisher **Best for:** Testing something real at two accounts without paying, and staying cheap under about eight. **Pricing:** Free for 2 accounts, then $6 each to 10, $3 to 100, $1 above. **Free trial:** Yes, two accounts free with no card and no expiry. **Bottom line:** The cheapest honest starting point on this page, and the one that punishes you most if you scale past a hundred accounts. #### **6. Quso.ai (Best if the clip is the missing step)** *Quso bundles clipping and publishing on one bill, metered in credits.* [Quso.ai](https://quso.ai/pricing) ranks on page one for this keyword and belongs in a different category, which is worth saying plainly. It cuts long video into shorts and then publishes them, so it covers a step Repurpose.io never claimed. If your real problem is that you have a two-hour podcast and no shorts, no watcher solves that. I covered this category properly in my roundup of [Opus Clip alternatives](/opus-clip-alternatives/), so I will keep this short. **Pros:** - Free plan with 75 credits a month and TikTok publishing - Clipping and scheduling on a single bill rather than two subscriptions - Credits double on annual billing, so the tiers are not simply the same product cheaper **Cons:** - Not a watcher, and not a like-for-like Repurpose.io replacement - Credit metering makes the bill harder to predict than a flat plan - Free tier renders at 720p with 7 days of data retention - Priced and read, not tested **Best for:** Long-form creators who need the shorts made before anything can be distributed. **Pricing:** Free (75 credits), Lite $29, Essential $39, Growth $49, monthly billing. **Free trial:** Yes, a permanent free plan. **Bottom line:** A good buy for the wrong problem. Only pick it if clipping, not distribution, is what is actually stuck. #### **7. Taja AI (Best if everything starts on YouTube)** *Taja prices by videos and social sets rather than by connected account.* [Taja AI](https://www.taja.ai/alternatives/repurpose-io) is built around YouTube first, writing titles, descriptions and tags, then scheduling outward from there. Its unit is unusual enough to flag. You are buying a number of videos per month and a number of "social sets" rather than connected accounts, so comparing it to a per-account tool on price alone is misleading. **Pros:** - Cheapest paid entry among the platform tools at $19.99 - Handles YouTube metadata, which nothing else on this list touches - Unlimited videos on the top tier rather than a credit meter **Cons:** - Starter covers only 4 videos a month, so the entry price is narrow - No free plan, only a 7-day trial - Useless if YouTube is not your primary platform - Priced and read, not tested **Best for:** YouTube-first creators who want the metadata handled as part of distribution. **Pricing:** $19.99 Starter, $49.99 Professional, $99.99 Teams, monthly. Annual drops those to $15.99, $39.99 and $79.99. **Free trial:** 7 days, no permanent free plan. **Bottom line:** A narrow tool that is excellent inside its lane. Check the video allowance before the price, because 4 a month binds long before the dollars do. ### **Four Questions That Pick the Tool For You** These are the questions I would ask on any client build, in this order. **Does your content already exist somewhere?** If it is already on YouTube or TikTok, a watcher works. If it is a file on your desktop, Repurpose.io cannot take it and ShortSync or Blotato can. **How many accounts, and on how many networks?** Many accounts on few networks favours Repurpose.io's unit. Few accounts spread wide favours per-account pricing. **Is the post written when it arrives?** If you still have to write every caption by hand, a pure distribution tool is solving your second problem. **Does your source publish an RSS feed?** If yes, Publer does trigger-based automation for a few dollars, and that question alone can save you thirty a month. ### **What About OpusClip, Metricool and Later?** Three names come up constantly on this keyword and are deliberately not ranked above. [OpusClip](https://www.opus.pro/alternatives/repurpose-io) holds the top vendor slot on this SERP and is a clipper, not a distributor. It is genuinely good, I pay for it, and it does not do Repurpose.io's job. [Metricool](https://metricool.com/pricing/) is a scheduler with strong analytics, free for one brand and 20 posts a month, with Starter at EUR 20 monthly or EUR 16 on annual billing. I ranked its rivals separately in my [Metricool alternatives](/metricool-alternatives/) post, so it would be double counting to rank it here too. [Later](https://later.com/pricing/) is a capable scheduler, and I could not confirm its live monthly rates to my own standard on the day I wrote this, so I have left it unpriced rather than publish a number I had not verified. ### **What I Would Do With Thirty Dollars a Month** If the video already lives on YouTube and you want it everywhere with no thought, Repurpose.io at $35 is a fair price and the pages calling it expensive have not done the arithmetic. If the writing is the bottleneck, Blotato at $29 is the one I use, paired with Make when a trigger is genuinely needed. If you want to spend nothing, ShortSync's five free uploads a month are the closest thing to a real answer, and Publer's free three accounts are the closest thing to real automation. The tool that fails you is the one bought for the wrong job. Work out whether you need a watcher, a clipper or a publisher first, and the price comparison mostly answers itself. ### **Repurpose.io Alternatives FAQs** #### **What is the best Repurpose.io alternative?** There is no single best one, because Repurpose.io does three separable jobs and most alternatives only do one. If you want the caption and creative written as well as published, Blotato at $29 a month is the pick. If you want the watch-and-republish automation itself and your source has an RSS feed, Publer does it natively from $5. If you want to pay nothing, ShortSync gives you 5 uploads a month to 12 platforms. Most pages ranking for repurpose io alternatives are selling one tool, so match the pick to whichever of those three jobs is actually stuck. #### **What is the best free Repurpose.io alternative?** ShortSync's free plan is the closest fit, giving 5 uploads a month to 12 platforms permanently, with API and MCP access. Publer's free plan covers 3 social accounts and includes RSS auto-posting, which is the only free route to genuine trigger-based automation. Buffer is free for 3 channels but does no repurposing. Repurpose.io itself has no permanent free plan, only 14 days or 10 published videos. #### **Is Repurpose.io actually expensive?** It depends on how many brands you run, not how many accounts you have. Repurpose.io bills per account per network, so one brand on five networks costs $35 where Zernio costs $18, and it looks expensive. Run ten brands and it is $79 where Buffer is $235 and Blotato is $499, which makes it the cheapest option compared here. The crossover sits at about three brands. #### **Can Blotato replace Repurpose.io?** Partly, and the difference is worth understanding. Blotato writes captions and generates images or video, which Repurpose.io does not, and publishes to 9 platforms for a flat $29. It has no source-watching trigger of its own, so to copy Repurpose.io's watch-and-republish workflow you pair it with Make or n8n, using their RSS or YouTube trigger. #### **Why does Repurpose.io only publish 5 videos a day?** That cap applies to schedule-based automatic publishing, where its documentation allows a maximum of 5 publishing slots per day with one video per slot. Snapchat destinations are the exception, allowed more slots and more videos per slot, up to 50 a day. Manual scheduling has no such limit, which is where the advertised 5,000 videos a month comes from. #### **Which alternatives can watch a source and republish automatically?** Very few. Publer does it from RSS feeds, publishing new items as they arrive. Blotato and Zernio can do it when paired with Make or n8n, which supply the trigger. Buffer, ShortSync, Quso and Taja publish only what you hand them, so they are alternatives to the destination half of Repurpose.io rather than the automation half. Disclosure: Blotato is a client of mine and my account there is comped, and links to it in this post are affiliate links, so I earn a commission if you subscribe. I have no financial relationship with Repurpose.io, Publer, ShortSync, Buffer, Zernio, Quso, Taja, OpusClip, Metricool or Later. Of the tools here I use Blotato daily, pay for Opus Clip, and have used Zernio's dashboard but never run it in production. The rest I assessed from their live pricing pages and documentation, with monthly billing selected, and I have marked those entries as priced rather than tested. Where a vendor's own surfaces disagreed, or where I could not verify a figure, I said so rather than filling the gap. Full [disclosure policy](/disclosure/). --- ## Repurpose.io Review: Is This Tool Worth It in 2026? URL: https://ryandoser.com/repurpose-io-review/ Markdown: https://ryandoser.com/repurpose-io-review.md Published: 2026-08-28 | Updated: 2026-09-30 Categories: AI Tool Reviews > Repurpose.io costs $35 a month to cross-post your videos automatically. What the pricing page does not tell you, what users actually complain about, and who should skip it. **Repurpose.io** costs $35 a month, and its Starter plan advertises 5,000 published videos a month. Its own help centre caps automatic publishing at 5 videos a day, which works out to about 150. Both numbers are true. They describe different things. Nobody selling you this tool explains which one applies to you, and that is the single most useful thing in this **Repurpose.io review**. The other thing worth knowing before you buy: the warning you keep reading, that posting through a third-party tool quietly buries your reach, traces back to one Reddit post, five upvotes at the time of writing, whose author never mentions APIs or algorithms and reports no numbers at all. **The short answer:** worth it if you already publish video regularly on one platform and want it mirrored to the rest, and a poor buy if you expected volume automation on the entry plan or need anything written for you. The rest of this post is why, and what I could not verify. I earn nothing whether you buy Repurpose.io or skip it. It is not an affiliate link here, which is the position I would want a reviewer in. ### **What I Can and Cannot Tell You Here** One boundary, stated plainly, because it changes how you should read everything below. **I have not run Repurpose.io on my own accounts.** I did not test it for ninety days and I am not going to pretend otherwise. What follows is a documentation, pricing and evidence review from someone who publishes through a competing tool daily and reads a lot of rate cards. Where I make a claim about how something behaves, I will tell you whose evidence it is. What I do bring is the part most reviews skip. I opened the sources. Every one of them. ### **What Repurpose.io Actually Does** Repurpose.io is a distribution tool. You post a video somewhere, and it pushes that video to your other platforms automatically, resized, with the watermark stripped. Its [supported-platforms matrix](https://support.repurpose.io/en/article/supported-platforms-roles-and-media-types-j22278/) sets out which platforms do what. TikTok, Instagram, Facebook, Snapchat, YouTube, Google Drive and Dropbox work as both source and destination. Twitch, Zoom and podcast feeds are sources only. Pinterest, LinkedIn, Threads, X and Bluesky take content but cannot supply it. Worth opening that page yourself if one specific platform is the reason you are buying, because the media types differ per platform and the list changes. Two constraints matter more than the platform list. **It writes almost nothing.** There is a caption generator for LinkedIn, Instagram and Facebook, and it only runs on manual publishing, not on the automated workflows that are the entire point of the product. It does not write your posts. It moves your video. ![Repurpose.io documentation stating it does not support directly uploading video or media files into the platform](/images/2026/08/repurpose-io-review-upload.jpg) **You cannot hand it a file.** Its documentation is blunt about this: Repurpose does not currently support directly uploading video or media files into the platform. Everything has to arrive from a connected account. So the workflow starts with you publishing somewhere else first, and Repurpose copies it onward from there. One Trustpilot reviewer describes that friction directly, saying he still had to edit and post to TikTok by hand before anything could be repurposed. ### **Repurpose.io Pricing, and the Cap Nobody Mentions** Note what the pricing page leads with before you read the plans. Starter shows "$1.17/day" in large type, with "$35 billed monthly" underneath in small grey text. That is a presentation choice rather than an error, and it is worth registering on a page where the headline figure and the number you actually pay keep describing different things. Live monthly rates on the [pricing page](https://repurpose.io/pricing/) are $35 for Starter, $79 for Pro and $179 for Agency. Annual billing runs $349, $790 and $1,790 on the pricing page, though the help centre lists Starter annual at $350. A dollar is nothing in itself, but it is worth noticing when you are checking whether a company keeps its own numbers straight. ![Repurpose.io pricing page showing Starter at $35, Pro at $79 and Agency at $179 billed monthly, with account limits per social network](/images/2026/08/repurpose-io-review-pricing.jpg) Starter connects 3 accounts per network and advertises 5,000 published videos a month. Pro moves to 10 accounts per network with unlimited publishing. Agency goes to 25. The free trial is 14 days or 10 successful posts, whichever comes first. There is a separate 90-day YouTube trial with Instagram and TikTok as sources. Now the part I have not seen in a single review on page one. **Automatic scheduling tops out at 5 videos a day.** Repurpose.io's own [scheduling documentation](https://support.repurpose.io/en/article/how-scheduling-works-in-repurpose-setup-and-limits-iyhn5d/) puts it plainly: a maximum of 5 publishing slots per day, one piece of content per slot. Snapchat destinations are the one exception, allowed up to 50. Manual scheduling has no publishing limit at all, which is where the 5,000-a-month figure comes from. ![Repurpose.io help centre stating automatic scheduling supports a maximum of 5 publishing slots per day](/images/2026/08/repurpose-io-review-cap.jpg) Five a day is 150 a month. The Starter tier advertises 5,000. Those two numbers describe different things, manual versus scheduled, and both are technically true, but if you bought the $35 plan imagining automated volume, the number that governs you is 5. While you are checking numbers: a [comparison page](https://www.shortsync.app/resources/repurpose-io-pricing-vs-alternatives) that ranked on page one when I searched this keyword headlines Repurpose.io at $25 a month. That price is not on the pricing page. ### **The Reach Claim, Checked Properly** This is the reason most people search for a Repurpose.io review, so it deserves more than a shrug. The claim is that Instagram detects content published through a third-party API and suppresses it, so a scheduler quietly costs you the reach you would have had posting by hand. Here is everything that claim actually rests on. #### **The Reddit post at the top of Google** When I ran this search on August 28, 2026, the first organic result was a thread titled ["Stop using Repurpose.io"](https://www.reddit.com/r/ContentCreators/comments/1obxvo2/stop_using_repurposeio/) from October 2025, and Google's AI Overview cited it in the cons half of its answer. Search results move, so check where it sits today rather than taking my word for it. I read the whole thread. Four things about it are worth knowing. **It had five upvotes when I checked on August 28, 2026.** Fourteen comments. One person's post that happened to rank, rather than a verdict the community weighed in on. **The author never mentions APIs or algorithms.** Not once. The words API, algorithm, throttle, suppress and shadowban do not appear anywhere in his post. That framing comes entirely from people replying to him. **He reports no numbers.** No views, no followers, no percentages, no before and after. The single quantified line in the whole post is "year-long results of previous Reels, now happening in a day." **He changed four things at once.** By his own description he stopped using Repurpose, started uploading through Instagram's Edits app and redoing captions natively, began posting every Reel as a Trial Reel first, and started re-uploading old Reels daily. Those last three are all Instagram-native features that Instagram was actively pushing at the time. Any of them could explain what he saw. His result is real. His explanation for it is a guess, and he does not claim otherwise. #### **The comment everyone quotes is a competitor's ad** The most technical, most quotable line in that thread says the algorithms can detect third-party API uploads versus native uploads, and that Instagram flags automated cross-posting. It is worth reading who wrote it. The same comment closes by introducing a tool the commenter built, getrepurposer.com, which does content generation while you post by hand. Another commenter replies, "intriguing self promo haha." So the sharpest statement of the reach thesis, the one that reads like inside knowledge, is marketing copy from someone selling the alternative. That does not make the claim false. It does mean the sentence carries a seller's interest, so weigh it accordingly. #### **What the platforms have actually said** Almost nothing, and this cuts both ways. Instagram's own [ranking explainer](https://about.instagram.com/blog/announcements/instagram-ranking-explained) lists the signals it uses for Feed and Reels. Your activity, your history with the poster, information about the post, information about the person posting. Publishing method is not among them. That is silence, not a denial. TikTok publishes [how its recommendation system works](https://www.tiktok.com/transparency/en-us/recommendation-system/) and lists user interactions, video information and device settings. Upload method is not among them. [YouTube's explainer](https://www.youtube.com/howyoutubeworks/product-features/recommendations/) does not mention it either. You will find a widely repeated quote from Adam Mosseri saying scheduled posts do not affect reach one way or the other. I am not going to use it, because I could not find the original. Every trail ends at a marketing blog, the source was an Instagram Story that expired, and the wording drifts between versions in a way that suggests people are quoting each other from memory. So the honest line is narrower than what most of these posts tell you: **I could not find a statement from any of the three platforms saying that API-published content is ranked differently from content posted by hand.** Not that Meta debunked it. The platforms do publish rules about API posting, and TikTok's is further down this page, but those govern permission and quota rather than ranking. #### **The tests, and who paid for them** The study cited everywhere as proof this is a myth is [Buffer's](https://buffer.com/resources/3rd-party-social-media-tools/), from January 2018. Over 200 posts across 35 profiles, and it found no significant difference. It tested Facebook, Twitter and LinkedIn. It did not test Instagram. The entire complaint is about Instagram Reels, and the headline rebuttal never touched Instagram. It is also eight years old. The one Instagram-specific test I could find is [Hootsuite's](https://blog.hootsuite.com/experiment-third-party-scheduling-instagram/), from April 2025. Scheduled posts beat native ones, 8.19% engagement against 6.44%. The sample was five posts per method on one wrestling account, and the author says in the piece that with five posts per method the difference may not be statistically significant. Both tests were run by companies that sell scheduling software. That is the whole record I could find. One vendor study that skipped the platform in question, one vendor study with ten posts, and a pile of anecdote on the other side. Nobody has actually measured this. ### **Four Reasons Your Reach Really Can Drop** Here is where I think the truth sits. The mechanism creators blame looks like the wrong one. The reach loss some of them see is probably real. These four are documented, and every one produces the same symptom without any algorithm penalty. **Watermarks.** Meta's [unoriginal content guidance](https://creators.facebook.com/blog/combating-unoriginal-content) from July 2025 tells creators to avoid visible third-party watermarks and content visibly recycled from other apps. Be precise about what that page does and does not say, because I nearly got this wrong myself. The watermark line sits in a best-practices section and carries no stated penalty. The account-level consequence on the same page, reduced distribution on everything an account shares, is aimed at accounts that repeatedly reuse other people's videos and photos. Welding those two together would be the exact move this post is complaining about. What is fair to say is narrower and still useful. Meta tells you not to ship other apps' watermarks, Instagram's creator guidance says visibly recycled reels are less discoverable, and a daily repurposing workflow is an efficient way to put a TikTok watermark on your Reels. That is a signal about the content itself, and it has nothing to do with which pipe published the file. Repurpose.io strips watermarks by pulling the clean original, so its users may be avoiding this rather than causing it. But plenty of people cross-post by hand with the watermark intact and blame the wrong thing. Worth separating from a related question: Mosseri [clarified in October 2024](https://www.socialmediatoday.com/news/instagram-clarifies-including-your-own-logo-on-a-reel-is-ok/730852/) that your own logo on a Reel is fine. It is other apps' watermarks that cost you. **Trending audio.** The API cannot attach Instagram's licensed audio library, which is a licensing limitation rather than a penalty. On short-form, the audio you pick moves reach. Repurpose.io concedes this itself, in the same help article where it argues repurposing does not hurt views: each platform has different music and trending sounds, and this can be a major factor in whether a video gets an extra boost. **Compression.** Two separate [Trustpilot reviewers](https://www.trustpilot.com/review/repurpose.io) report video arriving downgraded from 1080p to 720p, one of them writing that manual posting leads to noticeably better quality. Instagram's creator guidance says low-resolution reels are less discoverable. No algorithm needs to know how the file got there. **Nobody is home when it posts.** A scheduled video goes out while you are asleep. Early engagement shapes distribution, and the creator who posts by hand tends to be there replying in the first hour. That is a real difference in outcome that has nothing to do with the pipe. One more that is specific and worth knowing: on TikTok, content posted by an [unaudited API client](https://developers.tiktok.com/doc/content-posting-api-get-started) is restricted to private viewing mode. It looks published. Nobody can see it. That is a permission gate, not a ranking penalty, and it would absolutely convince a creator they had been suppressed. ### **What Users Actually Complain About** Here is the thing that surprised me. Once you set the reach argument aside, Repurpose.io's real problems are well documented and almost nobody writes about them. On [Trustpilot](https://www.trustpilot.com/review/repurpose.io) it sits at 4.0 out of 5 across 92 reviews, and the distribution is strange. Sixty-one percent are five-star. Thirty-four percent are one-star. Almost nothing in between. That shape tells you what kind of product this is. It either runs quietly for months or it breaks and you find out late. The one-star reviews repeat the same complaint. A workflow gets disabled with no notice and content stops publishing, and the user finds out afterward. One reviewer describes connections dropping two or three times a month. Another says posts simply stop reposting with no notification. Consider what that failure mode looks like from the inside. Your content is not going out. Your numbers fall. Nothing tells you anything is wrong. If you already suspect the tool is throttling your reach, a silent publishing failure is going to feel like proof. The second theme is billing. Charges after cancellation, cancellation by email, refused refunds, one reviewer locked into an annual plan after their business closed. The five-star reviews are just as consistent, and they praise one thing: it runs without being touched. Support staff get named personally. Both experiences are real, which is what a 61/34 split means. One caveat on the sample. Trustpilot reviews are self-selected, so people tend to arrive there delighted or furious and rarely in between, which may be doing some of the work in that split. ### **Who Should Buy It** **Buy it if you already publish video consistently on one platform and want it mirrored everywhere else.** That is the job it is built for, and I should be consistent about whose evidence that is: I have not run it, so the support comes from the 61% of Trustpilot reviewers who describe it running untouched for months. Podcasters and daily short-form creators are the fit, at $35. **Do not buy it expecting automated volume on the cheap plan.** Five scheduled videos a day is the real ceiling, whatever the 5,000 figure suggests. **Do not buy it if you need something written.** It moves video that already exists. If your bottleneck is producing the posts rather than distributing them, this is the wrong category of tool and no plan tier fixes that. **Check your watermarks before you blame anything.** It is the one documented content signal in this whole argument, and it costs nothing to rule out. ### **What I Use Instead, and Why It Is Not a Fair Comparison** *Affiliate links below. [Full disclosure](/disclosure/).* I publish through [Blotato](https://www.blotato.com/?ref=rdoser), which is $29 a month for 20 connected accounts, and I should say plainly that it is not a like-for-like swap. Repurpose.io takes one video and mirrors it. Blotato takes an idea and writes the posts, then publishes them, which is a different job. If all you want is a TikTok landing on Reels and Shorts automatically, Repurpose.io does that directly and Blotato is a detour. Where they diverge is what happens before publishing. I write per-platform copy from one recording and Blotato distributes it, which I do because a caption written for LinkedIn reads badly on TikTok, a formatting argument rather than a reach one. I went through that setup in [posting to all social media at once](/post-to-all-social-media-at-once/). Both tools do assume you have already made something. Repurpose.io needs a published video, Blotato needs the copy written. If you are weighing the switch rather than the tool itself, I priced seven [Repurpose.io alternatives](/repurpose-io-alternatives/) against it and found its per-network billing beats most of them once you run more than about three brands. That is the step I ended up building for myself, as [the AI Content Engine](/ai-content-engine/), which takes one recording and drafts the posts, the blog and the newsletter from it. I am flagging it because it solves a different bottleneck than the one this post is about, and buying the wrong category is how people end up disappointed by a tool that was working correctly. ### **Ryan's Final Thoughts** Repurpose.io is a competent distribution tool with a scheduling cap buried in its docs while the marketing quotes a number forty times larger, and a reliability record that is genuinely mixed. The product is not what bothers me here. The loudest criticism of it turns out to have the least behind it, while the complaints users have repeated for years go largely unmentioned. The reach claim rests on a five-upvote post whose author never made that claim, amplified by a comment from someone selling a competing tool. The billing complaints and the silent workflow failures sit in public on Trustpilot across several years, and they barely register. That is backwards, and it is worth noticing how it happened. A claim that sounds technical travels further than one that is merely well documented. If you want the thing it does, buy it and watch your first month closely. If you want to know whether a scheduler is costing you reach, check your watermarks first, then check whether your posts are going out at all. Those two answers are where I would look first, and they are checkable in an afternoon. ### **Repurpose.io Review FAQs** #### **Does Repurpose.io hurt your Instagram reach?** I could not find a statement from Instagram, TikTok or YouTube saying that API-published content is ranked differently, and Instagram's published ranking signals do not include publishing method. The claim traces to anecdote rather than measurement. What is documented is separate: Meta tells creators not to post other apps' watermarks, the API cannot attach trending audio, and some tools re-compress video. Each of those can cost you reach with no penalty on the API involved, so rule them out first. #### **How much does Repurpose.io cost?** $35 a month for Starter, $79 for Pro and $179 for Agency, or $349, $790 and $1,790 annually. The free trial runs 14 days or 10 successful posts, whichever comes first. A separate 90-day YouTube trial is available. #### **How many videos can Repurpose.io publish per day?** Five, if you are scheduling them to go out automatically, and that ceiling is the same on the $35 plan and the $179 one. Snapchat is the exception at 50. The 5,000 per month figure on the Starter tier describes manual scheduling, which carries no cap. #### **Does Repurpose.io write captions or posts for you?** Barely. It has an AI caption generator for LinkedIn, Instagram and Facebook that works only on manual publishing, not on automated workflows. It moves video around rather than producing anything, and it cannot accept direct file uploads at all. #### **What is the most common complaint about Repurpose.io?** Silent failures. The recurring theme across one-star reviews is workflows being disabled or connections dropping without notification, so content stops publishing and the user finds out later. Billing and cancellation friction is the second theme. Its Trustpilot rating is 4.0 across 92 reviews, split 61% five-star and 34% one-star. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine and my account there is comped rather than paid. Links to Repurpose.io are not affiliate links and I earn nothing if you buy it. I have not run Repurpose.io on my own accounts, which I have said plainly at the top of the post rather than burying here. [Full disclosure](/disclosure/).* --- ## What Search Engine Does Claude Use? (I Checked the Receipts) URL: https://ryandoser.com/what-search-engine-does-claude-use/ Markdown: https://ryandoser.com/what-search-engine-does-claude-use.md Published: 2026-08-28 | Updated: 2026-09-06 Categories: AI Rabbit Holes > Claude uses Brave Search, and Anthropic publishes the proof. What each AI searches, and why the ChatGPT answer everyone repeats went stale. **Claude uses Brave Search.** Anthropic names Brave as a Web Search vendor on its own subprocessor page, which makes it a documented business relationship rather than a rumor. Almost every article covering this still calls it unconfirmed, and I want to show you where that confirmation actually lives. Here is the thing. When you ask an AI a question and it searches the web, it is querying somebody's search index. Knowing whose index changes what you optimize for. ### **What Search Engine Does Claude Use?** Claude's web search runs on Brave Search. That is the named vendor behind the feature, and it is neither Google nor Bing. You do not have to take my word for it, or anyone else's. Anthropic maintains a public subprocessor list, which is the legal disclosure a company publishes naming the vendors that handle data on its behalf. Brave is on it. Go look for yourself on [Anthropic's subprocessor page](https://trust.anthropic.com/subprocessors), and note one thing before you do. The list is paginated, ten entries at a time, and Brave sits on the second page. Load it, click through to page two, and read the row yourself. The entry reads exactly like this: *Brave Search. Products: All products. Web Search. United States. search.brave.com* *The Brave Search row on Anthropic's own subprocessor page, listed under Web Search for all products. It sits on page two of the list, which is why so many write-ups still call it unconfirmed.* That is Anthropic naming its own search vendor, on a compliance page it is obligated to keep accurate. It documents the relationship, though it stops short of describing how the retrieval actually works. So why does half the internet hedge on this? Search the question and you will find pages ranking well that say Claude uses Brave "though Anthropic has not confirmed it publicly." That exact framing is sitting on page one right now. That framing is out of date. Anthropic named the vendor in writing, on a page anyone can load. The confusion is understandable, because the help docs most people would check genuinely do not name a provider, and the subprocessor list is paginated so Brave sits on the second page. Most people never get there. One detail almost nobody mentions, and it is a useful check on getting too confident. That same list carries a second Web Search subprocessor, turbopuffer, which sells vector search and storage. Brave is the named web search vendor, but a subprocessor list tells you who is involved, not how the pieces divide the work. ### **Which Search Engine Each AI Actually Uses** This is the part worth internalizing. The models do not all read the same web, and the people [doing real testing in AI search](/best-ai-seo-experts/) keep finding the same thing. Dan Petrovic of DEJAN, whose research prompted a lot of this digging, is one of them. | AI | Search index | Evidence quality | | Claude | Brave Search | Confirmed. Named on Anthropic's subprocessor list. | | Gemini | Google Search | Confirmed. Documented in Google's own API. | | ChatGPT | Its own index plus scraped Google | Contested. Reported, not vendor-confirmed. Bing is not the driver. | *Three assistants, three different indexes. ChatGPT is the contested one: its own index dominates on the free tier, while paid Thinking leans on scraped Google results instead. Neither is Bing.* Gemini is the easy one. Google's [Gemini API documentation](https://ai.google.dev/gemini-api/docs/google-search) describes the feature as "Grounding with Google Search," and you invoke it in code by passing a tool literally named `google_search`. Google grounding Gemini in Google is not a surprise. ChatGPT is where the popular answer has quietly gone stale. ### **The ChatGPT Answer Everyone Repeats Is Out of Date** Ask any SEO how to show up in ChatGPT and a lot of them will tell you to rank in Bing. That advice was correct once. It has aged badly, and the part it now misses is the part you can actually control. It was true in 2023. Microsoft and OpenAI announced Bing integration into ChatGPT in May of that year, and the feature was literally called Browse with Bing. Then OpenAI launched its own ChatGPT Search product in October 2024, and OpenAI began running search infrastructure of its own. The advice never got updated. Two things tell you Bing is no longer the whole story. The first is [OpenAI's own crawler documentation](https://developers.openai.com/api/docs/bots). OpenAI runs a crawler called OAI-SearchBot, and the docs say this about it: *"OAI-SearchBot is for search. OAI-SearchBot is used to surface websites in search results in ChatGPT's search features. Sites that are opted out of OAI-SearchBot will not be shown in ChatGPT search answers, though can still appear as navigational links."* Sit with that for a second. If ChatGPT were only reading Bing's index, blocking OpenAI's crawler could not remove you from ChatGPT's answers, because Bing would still have you. So OpenAI controls its own inclusion, on its own infrastructure. That does not prove Bing contributes nothing, and it does prove Bing is not the lever that decides whether you show up. The second is measurement. Olivier de Segonzac published [research at Search Engine Land](https://searchengineland.com/chatgpt-retrieval-stack-index-cache-pages-485036) in August 2026 analyzing 1,200 ChatGPT answers, 88,000 search results, and 26,900 distinct pages. His conclusion, in his words: "OpenAI has its own web index, and Bing doesn't supply it." The split he found is stranger than a single number, and it depends on what you are paying. On the free Think mode, about 75 percent of results came from OpenAI's own index. On paid Thinking, that flips almost exactly: roughly 75 percent came from scraped Google results and only about 25 percent from OpenAI's index. Read that twice, because it is the part nobody is repeating. Free and paid users are being served from meaningfully different sources, and neither of those sources is Bing. On the Bing question specifically, his numbers are stark. Only 1.5 percent of the URLs from OpenAI's own index also showed up in Bing's top 20 for the same underlying queries. If Bing were supplying that index, you would expect those two sets to overlap far more than that. I want to be careful here, because this is the one claim on this page that is not vendor-confirmed. That is independent research, not an OpenAI statement, and OpenAI has neither confirmed nor denied it. Treat it as strong evidence rather than settled fact. But notice you do not need that research to reach the practical conclusion. OpenAI's own documentation already tells you that blocking its crawler removes you from ChatGPT. That is enough on its own to retire "just rank in Bing" as complete advice. Worth noting the asymmetry in what you can verify. Anthropic publishes a subprocessor list naming its search vendor outright. I could not find an equivalent public OpenAI list naming one, which is why the Claude answer on this page is documented and the ChatGPT answer is inferred. ### **One Prompt Is Not One Search** Here is the mechanic that reframes all of this, and it is easy to verify yourself. When you ask an AI a question, it does not run your question as a search. It breaks your prompt into multiple sub-queries, runs those, and assembles an answer from what comes back. The industry calls this query fan-out. I ran a live grounded query against Gemini to see the real number. On that one prompt, on that one model, the API handed back **21 separate fan-out queries**. Twenty-one sub-queries from a single broad question, which is one run and not a benchmark. Things like "what is cloaking in SEO" and "adversarial SEO examples" and "how search engines detect and penalize content manipulation," none of which I typed. That was one query on one model, so I am not offering 21 as a typical number. Published estimates vary a lot depending on who is measuring and which assistant they measured. The point is that the multiplier is real and often larger than people assume, and the API will show you your own number in about thirty seconds. So the useful reframe is this. You are not trying to rank for the prompt. You are trying to rank for the spread of sub-queries the prompt silently spawned, in whichever index that model happens to read. ### **What This Actually Means for Your Site** Four things change once you know which index you are actually being read from, and the first one has a documented consequence attached. **Check whether you are in Brave at all.** Search your brand on [Brave](https://search.brave.com) the way you would on Google. Brave runs [its own independent index](https://brave.com/blog/search-independence/) rather than reselling someone else's results, so it is possible to be findable on Google and thin on Brave. It is a five minute check that most people have never run once. **Do not block OAI-SearchBot by accident.** This is the one item here with a documented consequence attached, straight from OpenAI. Plenty of sites added blanket AI crawler blocks in the last two years, and OpenAI says that setting keeps you out of ChatGPT's search answers, though you can still appear as a navigational link. Open your robots.txt and look for two separate user-agents: GPTBot governs training, OAI-SearchBot governs whether you show up in search answers. **Stop treating "AI search" as one destination.** Three assistants, three different indexes, three different sets of results. Winning on one is not evidence you are winning on another, so check them separately rather than assuming they move together. Most of the [AI SEO tools worth using](/best-ai-seo-tools/) now track citations per platform for exactly this reason. If you want a fuller picture of how those citations get won, I broke that down in my guide on [how to manipulate AI search](/how-to-manipulate-ai-search/). **Fundamentals still carry most of the weight.** These systems lean on retrieval, whether that is an index, a live fetch, or a licensed feed. Being findable is still the prerequisite, which is why this looks less like a new discipline than people selling courses would prefer. My full approach lives in my [AI SEO strategy](/ai-seo-strategy/) breakdown. ### **Final Thoughts from Ryan** The lesson here is not really about Brave. It is that a fact everyone repeats about AI search was checkable in about ten minutes, and the checking is what nobody did. Claude's provider was sitting on a public compliance page while article after article called it unconfirmed. The Bing answer was accurate in 2023 and still gets handed out as current advice. This field moves fast enough that received wisdom goes stale in months. When someone tells you how AI search works, ask where they checked. Then go check. I will say the obvious caveat too. These are private systems that can change without telling anyone, so the specific mappings on this page could shift. The habit of verifying is the part that keeps working. ### **What Search Engine Does Claude Use FAQs** #### **Does Claude use Google or Bing?** Neither is the named provider. Claude's web search runs on Brave Search, which Anthropic lists directly on its public subprocessor page as a Web Search vendor. Brave operates its own independent index rather than reselling Google or Bing results, so Claude sees a genuinely different set of pages than Gemini or ChatGPT would for the same question. #### **Does ChatGPT still use Bing?** Not the way it did. Bing powered the original Browse with Bing feature launched in 2023, but OpenAI now runs its own crawler, OAI-SearchBot, and its documentation states that sites opting out of that crawler will not appear in ChatGPT search answers. Independent research published at Search Engine Land in August 2026 found the mix depends on your tier: on free Think mode about 75 percent of results came from OpenAI's own index, while on paid Thinking roughly 75 percent came from scraped Google results instead. Either way, only 1.5 percent of URLs from OpenAI's index overlapped with Bing's top 20. OpenAI has not publicly confirmed that research. #### **What search engine does Gemini use?** Google Search. Google's Gemini API documentation calls the feature Grounding with Google Search, and developers enable it by passing a tool named google_search. The API also returns the exact sub-queries the model ran, which makes Gemini the easiest assistant to study if you want to see fan-out behavior directly. #### **How do I show up in Claude's search results?** Start by confirming Brave has indexed your site, since Brave runs an independent crawler and index. Standard technical SEO applies from there: crawlable pages, clear topical relevance, and content structured so a specific passage answers a specific question. I have not seen a Brave-only trick worth chasing, and the ones being sold tend to be guesses dressed up as method. #### **Should I block AI crawlers on my site?** Understand the tradeoff before you do. With OpenAI the crawlers are split: GPTBot relates to training data, while OAI-SearchBot governs whether you appear in ChatGPT's search answers. Blocking both removes you from an answer surface people actively use. Blocking training while allowing search is a defensible middle position, and it is worth checking which one your robots.txt currently blocks. --- ## Why I Quit ChatGPT in 2026 (Best ChatGPT Alternatives) URL: https://ryandoser.com/chatgpt-alternatives/ Markdown: https://ryandoser.com/chatgpt-alternatives.md Published: 2026-08-27 | Updated: 2026-09-30 Categories: AI Tool Reviews, ChatGPT > This article explains why I quit ChatGPT in 2026 and also provides the best ChatGPT alternatives you should be using instead. The following article explains why I quit ChatGPT in 2026 including the best**ChatGPT Alternatives**. I don't see myself coming back. ### **Best ChatGPT Alternatives in 2026** You might be wondering if quitting ChatGPT Plus is even worth the hassle of switching. Here's the short answer: for me, yes. The platforms I moved to are doing things OpenAI simply can't match right now. #### **Claude: My Daily Driver for Business Work** The main reason I moved was Claude Opus 4.5, the best model available at the time. Anthropic has since shipped [Claude Fable 5](/claude-fable-5/) and then Fable 5.1 for the hardest work, but my daily driver in Claude Code today is Opus 5.5, for the reasons in [why I switched to Opus 5.5 for writing](/best-claude-model-for-writing/). I was using Claude Sonnet 4.5 for a while, but every flagship upgrade since has made the outputs noticeably better. I'm now on the [Claude Max plan at $100/month](https://www.anthropic.com/pricing). That sounds like a lot, but Claude Code is a huge part of why. I'm generating YouTube thumbnails inside Claude Code by connecting to Google's Nano Banana 2 API, writing automation scripts, and building marketing workflows I couldn't run before. The more I use it, the more the light bulb clicks. If you try to get serious work done on Claude Pro or the free version, you'll hit limits fast. Max gives you five or twenty times Pro's usage, which is the headroom that heavy work needs. If you're weighing ChatGPT's own top tier instead, here is [why ChatGPT Pro stopped being worth it as a solo plan after DevDay](/is-chatgpt-pro-worth-it/). Perplexity's Comet agentic web browser now runs on Claude by default (Opus 4.6 for Max subscribers). Even third-party platforms are betting on Anthropic's models. That tells you something. *Ryan Explaining his Claude Code Setup* #### **Google Gemini: The Ecosystem Nobody's Talking About** This is the bigger story. Google went from the laughingstock of AI (remember Google Bard?) to a powerhouse in under two years. Since Gemini 3 dropped, they've been shipping constantly. Gemini 3.1 Pro is still the newest Pro model, in preview, while the Flash line has kept moving and is now up to Gemini 3.8 Flash. I'm on [Google AI Pro at $20/month](https://one.google.com/explore-plan/gemini-advanced). For that, I get expanded Gemini access across the entire Google suite: Docs, Sheets, Gmail, and NotebookLM. Plus five terabytes of storage. As a content creator with large video files, that storage alone is worth it. Here's why I think Google wins long-term on media generation: they have YouTube to train their Veo 3.1 video model and billions of indexed images to train the Nano Banana image models. No competitor can replicate that data advantage. If you're doing anything with AI images or video, being in Google's ecosystem is the obvious call. The SimilarWeb data backs this up. In early 2025, ChatGPT held 86.7% of generative AI traffic share and Gemini sat at 5.7%. By January 2026, ChatGPT had dropped to 64.5% while Gemini climbed to 21.5%. That's a massive shift. Google's distribution machine (Android, Chrome, Apple's Siri partnership, Google Play) means that gap will keep closing. *Open Router dashboard showing Gemini 3 Pro running at 3 cents per output, a fraction of what comparable ChatGPT API calls cost.* ### **Why Memory Was the Last Thing Keeping Me on ChatGPT** ChatGPT has always had better memory than Claude or Gemini. That's the honest truth. It was the main reason I stuck around as long as I did. But two things changed. First, I found a way to [export all my ChatGPT history](/transfer-chatgpt-memory/) and upload it to NotebookLM, Gemini, and Claude. So I didn't lose anything. Second, Google launched Personal Intelligence, which pulls from your history across Search, YouTube, Gmail, Drive, Maps, and more. That kind of cross-app memory context blows ChatGPT's memory out of the water. Once I cracked both of those problems, there was nothing left holding me to OpenAI's ecosystem. ### **The Google Tools Worth Knowing About** Beyond the Gemini chat app, Google has built out a suite of free tools most people overlook. [NotebookLM](https://notebooklm.google.com) is the most useful. You upload sources (PDFs, YouTube videos, markdown files, website links) and use a Gemini-powered chatbot to extract exactly what you need. No irrelevant training data bleeding through like you get with a custom GPT. The Studio tab keeps adding features: infographics via Nano Banana, slide decks, mind maps, and video overviews powered by Veo. Google AI Studio is another one. You can build apps, generate images with the latest Nano Banana models, and screen share directly with Gemini to get real-time help debugging an automation. I've used that screen share feature to troubleshoot workflows in real time. It works. Google Labs is where new experiments live before they graduate into full products. NotebookLM came out of Labs. Google Flow and Pali are recent ones worth watching. None of this is available inside OpenAI's ecosystem at this quality level or price point. *NotebookLM with multiple sources loaded: PDFs, YouTube videos, and markdown files for instant AI-powered research and extraction.* ### **Should You Cancel ChatGPT Plus?** Let me be straight about this. If ChatGPT Plus is working for you, I'm not telling you to drop everything and switch today. But if you're paying $20/month and you're not sure you're getting the value, here's what I'd do instead. Spend that same $20 on Google AI Pro. You get the Gemini 3 model family (which [SimilarWeb data](https://www.similarweb.com) shows closing the gap on ChatGPT fast), five terabytes of storage, NotebookLM access, and Nano Banana for image generation. That's a better return on $20 for most people. If your work involves serious coding, long-form content, or complex reasoning, Claude is worth the investment. Even Claude Pro at $20/month is a meaningful upgrade over ChatGPT Plus for writing quality. Claude Pro already includes Claude Code. Claude Max is for people who run it hard and need five or twenty times Pro's usage. The reality is OpenAI had a three-year head start, and that advantage is shrinking fast. I'd rather build my workflows inside ecosystems that are growing stronger, not ones that are playing defense. ### **Ryan's Final Thoughts** I cancelled ChatGPT Plus because the tools I use every day are simply doing more for my work. Claude handles business writing and Claude Code. Google handles research and media. The memory advantage that kept me on ChatGPT is gone. Google's Personal Intelligence and the ability to export ChatGPT history solved that problem. This isn't about hating on OpenAI. ChatGPT built this entire category. But for what I'm doing in 2026, Anthropic and Google are where I'm putting my time and money. If you're on the fence, try the free versions of Claude and Gemini for a week before you decide anything. When you do commit, the [official import tool makes the move take about five minutes](/switch-from-chatgpt-to-claude/). ### **ChatGPT Alternatives FAQs** #### **Why did Ryan quit ChatGPT Plus?** After three-plus years as a power user, the memory advantage that kept him on ChatGPT was solved by exporting his history and using Google's Personal Intelligence feature. Claude's current models (Opus 5.5 day to day, Fable 5.1 for the hardest work) and Google's Gemini 3 family outperform ChatGPT for his actual daily work in content creation, copywriting, and automation. #### **Is ChatGPT Plus worth it in 2026?** For most users, probably not at the same value-to-cost ratio it once had. Google AI Pro at $20/month now includes the Gemini 3 models, NotebookLM, Nano Banana image generation, and five terabytes of storage. Claude Pro at $20/month produces better long-form writing and reasoning for many tasks. ChatGPT Plus still makes sense if you rely heavily on its ecosystem or specific integrations. #### **What are the best ChatGPT alternatives in 2026?** The two strongest are Claude (Anthropic) and Google Gemini. Claude leads on reasoning, copywriting, and code, with Opus 5.5 as the everyday model and Fable 5.1 for the hardest problems. The Gemini 3 family leads on research, media generation, and cross-app context through Google's ecosystem. Perplexity is worth adding for research and real-time web queries. #### **Is Claude better than ChatGPT for marketing?** Based on real production use, Claude produces tighter, less verbose copy and follows brand guidelines more consistently than ChatGPT. It's less prone to the generic, over-hedged outputs ChatGPT often defaults to. For long-form content, email, and landing page copy specifically, Claude is the stronger choice. #### **How do I switch from ChatGPT to Claude or Gemini?** Export your ChatGPT data from your account settings, then upload the conversation history to NotebookLM or Claude as a source file. This preserves the context and preferences you've built up. From there, spend a week running your normal prompts in Claude and Gemini to find where each one fits your workflow best. --- ## Semrush API Pricing 2026: Is It Worth the Cost? URL: https://ryandoser.com/semrush-api-pricing/ Markdown: https://ryandoser.com/semrush-api-pricing.md Published: 2026-08-23 | Updated: 2026-09-30 Categories: AI Tool Reviews > Semrush names two plans for API access, at two prices. Either one starts you at zero API units, and it will not say what units cost. Semrush's developer documentation tells you to buy the **SEO Business plan** to get API access. Open the Semrush pricing page and there is no Business plan on it. Both pages were live when I checked. They belong to the same company and they name different products. The plan carrying API access there is called **Advanced**, at **$549 a month**. Nothing on the developer page says so. Business is still documented, on a knowledge base page Semrush labels legacy, at **$499.95 a month**. So the same buyer sees two different prices for API access depending on which page they land on. Both numbers are the smaller half of the bill anyway. Whichever plan you buy, Semrush starts you at **zero API units**, and units are a second purchase whose price it does not publish anywhere public. So the sticker price is the one number everybody quotes and the one number that decides least. Here is what sits underneath it. One term, once, in plain English. An API is the paid pipe that lets software pull Semrush data directly, rather than a person clicking through the dashboard and exporting a file. I do not pay for a Semrush seat and I have never bought its API, so nothing here is a firsthand report of running it. What I can do is read what Semrush publishes and check it against what its other pages publish, on the day this went up. ### **Two Semrush Pages, Two Different Products** Here is the developer page that starts the confusion. It is the first organic result for this search, directly under Google's AI Overview. *From [developer.semrush.com, "API access"](https://developer.semrush.com/api/v4/get-started/api-access/). Note the illustration showing Pro, Guru and Business. Verified August 23, 2026.* Step one reads: *"Upgrade to the SEO Business plan to buy API units and generate an API key."* Look at the screenshot Semrush embedded underneath its own instruction. It shows a pricing page offering Pro, Guru and Business, with a red arrow pointing at Business. Those three plans are not on the pricing page a new buyer sees. They are not quite gone either, which is where this gets genuinely messy. Now the page a buyer actually lands on. *The live lineup on [semrush.com/pricing/seo-ai-search](https://www.semrush.com/pricing/seo-ai-search/). The page loads on the annual toggle, so the large figure is the annual per-month rate and the monthly rate sits struck through beside it. Verified August 23, 2026.* Four plans: SEO, Starter, Pro+ and Advanced. "API data integration" appears in exactly one column, under Advanced at $549 a month, or $455.67 a month paid annually. Semrush still documents Pro, Guru and Business on a [knowledge base page](https://www.semrush.com/kb/1547-seo-toolkit-pricing-limits) that opens by calling them *"legacy plans, no longer listed on our current pricing page."* It lists Business at $499.95 a month, with API Access as the feature separating it from Guru and Pro. So the docs are followable after all, just not from the page Semrush sends you to. Step one says go to the Pricing page, and the plan named in step two is not on it. It gets stranger, because a single page cannot keep its own story straight. The [API overview page](https://developer.semrush.com/api/v4/introduction/semrush-api-overview) says the Standard API *"is available as an add-on to a Business subscription"* and, a few paragraphs above that, says *"API access is available on paid Semrush plans."* One of those gates you to a single top tier. The other says any paid plan will do. The [Semrush MCP page](https://www.semrush.com/mcp/) then adds two more names again, citing "Semrush One" and "SEO Classic" plans that appear on none of the pricing pages you can buy from. None of this reads as bad faith to me. It reads like a company running new plans and legacy plans side by side, with the documentation still pointing at the old ones. That is ordinary and very common. The cost lands on the buyer anyway. You are told to buy a $499.95 plan, shown a $549 one, and left to work out on your own whether those are the same purchase. ### **Paying $549 Buys You Zero API Units** This is the part that actually decides your bill, and it is stated plainly in a place most people never reach. Directly beneath the upgrade instruction, Semrush writes: *"Note that after upgrading to the SEO Business plan the number of units will still be zero."* Read that again with the price attached. You pay $549 a month for the plan that unlocks API access, and you still cannot make a single call until you buy something else. API units are the metering currency. Every question you ask spends some, and they are sold in separate packages on top of the subscription. Semrush's [knowledge base article on the API](https://www.semrush.com/kb/5-api) lists the package sizes: 2,000,000, 5,000,000, 10,000,000 or 20,000,000 units. The smallest one on the menu is two million. The same page adds a detail worth more than it looks. *"Unused units will expire instead of being added to the renewed amount."* So units do not roll over. Buy a package sized for a busy month, have a quiet one, and the remainder is gone at renewal rather than banked against the next project. #### **How far a package actually goes** Semrush prices units by the line of data returned, and charges more for history than for the current picture. Its documented example: one line of the Domain Organic Search Keywords report costs **10 units live** and **50 units historical**. Semrush then works the arithmetic out itself. Listing 1,000 organic keywords for 100 domains costs **1,000,000 units** live, or **5,000,000 units** historical. Sit with that against the package menu. That single sweep eats half the smallest package, and asking the same question about the past consumes an entire five million unit package on its own. Scale it down if that example feels large. A hundred keywords across ten domains is a tenth of a tenth of it, which still spends 10,000 units live before you have asked anything else. The practical translation for a marketer is simple. Think of units as how many questions you get before you have to buy more, and remember that asking about the past costs five times what asking about today costs. ### **The Number Semrush Will Not Print** Here is where the research stops, and the stopping point is the finding. Semrush publishes how many units every report consumes, in detail, for free, without a login. It does not publish what a unit costs in dollars anywhere I could find. I checked the developer docs, the API access page, the knowledge base article, the main pricing page and the SEO and AI Search pricing page. The package menu shows sizes and a Buy button. The prices sit behind an account. Third parties fill that vacuum with a figure of roughly **$50 per million units**. That number appears on [thatmarketingbuddy.com](https://thatmarketingbuddy.com/blog/semrush-api-pricing), which ranks on page one for this query and is cited by Google's AI Overview. I could not verify it against any Semrush page, so I am not going to repeat it as fact. Treat it as an estimate circulating among people who have seen the logged-in screen. The [Reddit thread ranking third for this search](https://www.reddit.com/r/SEMrush/comments/1hvvwkr/how_much_does_2_million_api_unit_package_cost/) puts the two-million package at "$100 per month added to the business plan," back when the plan itself cost $499. Google's snippet shows that claim, and Reddit blocks automated reading, so I am reporting what the snippet says rather than what I confirmed on the page. Both figures point the same direction and neither is a published price. If you need a real number before committing, you have to be far enough into an account or a sales conversation to see it, which is itself the answer to how Semrush prices this. ### **Why Every Source You Read Says Something Different** Google's AI Overview sits above all of this, and it hedges in a way that gives the whole thing away. *Google's AI Overview for "semrush api pricing", captured August 23, 2026. It cites the Semrush developer page alongside two third-party pages.* It writes the tier as **"Advanced (Business)"**, carrying both names at once because its sources disagree and it cannot tell which is current. Then it states that "lower tiers like Pro or Guru do not include API capabilities." That sentence is true, and useless to anyone shopping on the page Google sent them to, where no plan by either name appears. It also passes along the unverified $50 per million figure with no hedge at all. I asked ChatGPT with live web search the same question, and it answered from the other lineup entirely. It named the **SEO Business plan at $499.95 a month**, which is a real Semrush price on a real Semrush page. So one engine sends you to Advanced at $549 and the other to Business at $499.95, and neither mentions that the other exists. Both are defensible readings of Semrush's own pages, which is the problem. ChatGPT did catch the expensive part the AI Overview missed: that the plan includes no units, that packages start at two million, and that unused units expire. ### **What To Budget, By What You Are Actually Doing** List prices before the extra user seats most teams add. **You want to ask Semrush questions inside Claude or ChatGPT.** This is most people reading this, and it is the cheapest door in. Semrush's MCP connection runs on the same unit meter, but [four mid-tier plans include 50,000 units](https://www.semrush.com/kb/1618-mcp) that refresh each renewal, so you can start without buying a package at all. I ranked the wider field in my roundup of the [best SEO MCP servers](/best-seo-mcp-servers/). **You want scheduled pulls into a spreadsheet or a client dashboard.** Advanced at $549 a month, plus a unit package you have to ask about. Budget the subscription as the floor rather than the cost. **You want historical data.** On the report Semrush documents, history costs five times what the current picture costs. Assume that gap is large on whatever you pull, and get a real unit quote before agreeing to anything. **You are pulling one report a month.** Do not buy this. Exporting from the dashboard costs you a few minutes and no extra money, and the smallest unit package is priced for something far heavier. ### **Cheaper Ways To Get Search Data Into Software** None of these replace a Semrush subscription, and none of them match it feature for feature. They cover the narrower job of getting search data into software without paying $549 a month plus units. [**Google Search Console**](https://developers.google.com/webmaster-tools/v1/getting-started) is free, has an official API, and reports your own site's real clicks and impressions rather than an estimate of them. For your own properties, start here before spending anything. [**Ahrefs**](https://ahrefs.com/pricing) bills the opposite way, and the contrast is the useful part. Its Lite plan at $129 a month [includes 200,000 API units](https://help.ahrefs.com/en/articles/6559232-about-api-v3) in the subscription. Semrush includes none at $549 and sells them separately, which is a genuine structural difference in how the two companies charge. I worked through that side in [Ahrefs API pricing](/ahrefs-api-pricing/). *Affiliate link below. [Full disclosure](/disclosure/).* [**DataForSEO**](https://dataforseo.com/?aff=245611) is one I use and earn a commission on, so weigh it accordingly. It publishes a per-request price for every endpoint on public pages, billed from a prepaid balance with a $50 minimum. It sells raw data rather than a dashboard, and I covered where that hurts in my [DataForSEO review](/dataforseo-review/). One open source project, OpenSEO, bills itself as an alternative to Semrush and Ahrefs while buying its data from DataForSEO. I looked at [what OpenSEO adds over DataForSEO direct](/openseo-review/). If you are weighing the whole subscription rather than the API specifically, I compared the two head to head in [DataForSEO vs Semrush](/dataforseo-vs-semrush/), and the answer there is usually a plan audit rather than a switch. ### **So Is It Worth The Cost?** For most people who searched this, no, and the reason is the zero-units rule rather than the sticker price. The API is worth it when software has to touch the data on a schedule, when nobody is around to click export, and when you have enough volume that a quote from sales beats a person doing it manually. That is a real buyer, and Semrush serves them well. It is not worth it if you are pulling reports yourself. You would be paying $549 a month for permission to spend more money, when the dashboard on a cheaper plan already answers the same questions at no extra cost. The honest middle path is the one Semrush buries. If your goal is asking questions of Semrush data inside Claude or ChatGPT, four mid-tier plans already include 50,000 MCP units per renewal, and that is the cheapest door into everything above. What I would not do is commit to Advanced before getting a written unit quote. The plan price is the one number you can check, and it is the one that decides least. ### **Semrush API Pricing FAQs** #### **How much does the Semrush API cost?** On the current pricing page, API access is listed on the Advanced plan at $549 a month, or $455.67 a month billed annually, verified August 23, 2026. Semrush also still documents a legacy Business plan at $499.95 a month carrying API Access. Either way the plan is only part of the cost. API units are bought separately in packages starting at two million, and Semrush does not publish their price publicly. #### **Does the $549 plan include any API units?** No. Semrush's developer documentation states that after upgrading, "the number of units will still be zero." The subscription unlocks the ability to buy units and generate a key. Making actual calls requires a separate unit purchase on top, and unused units expire at renewal rather than rolling over. #### **Is the Semrush API free?** Not for the Standard API. Semrush documents that a new subscription starts at zero units, so calls require buying a unit package on top. The one free allowance I found documented is on the MCP side, where four mid-tier plans include 50,000 MCP units per renewal, enough to ask questions in an AI assistant without a separate purchase. #### **Does Semrush have an API?** Yes. The one most people mean is the Standard API, covering SEO and Projects data, and it is the one that needs a top-tier plan plus purchased units. Semrush runs other APIs for traffic trends and local listings that are sold and metered separately, so confirm which one a quote refers to. #### **Why do sources disagree about Semrush API pricing?** Because Semrush documents new and legacy plans at once, and its developer pages still name the legacy ones. The docs say buy "SEO Business," a knowledge base page prices that plan at $499.95, the pricing page sells Advanced at $549, and the MCP pages cite "Semrush One" and "SEO Classic" plans appearing on neither. Third parties repeat whichever name they found. Disclosure: I am not a Semrush affiliate, earn nothing if you buy it, and do not pay for a seat, so this is a read of published sources rather than a report of using the product. I am a DataForSEO affiliate and earn a commission through my link. I also sell an AI SEO product, a competing interest you should weigh. Method: every price, unit cost and eligibility claim was read from semrush.com/pricing/seo-ai-search rendered with the billing toggle confirmed, developer.semrush.com, semrush.com/mcp and the Semrush knowledge base. The $50 per million unit figure is third-party and unverified, and Semrush labels the $499.95 Business plan legacy. Prices change; verify before you buy. [Full disclosure](/disclosure/). --- ## Ahrefs API Pricing 2026: The Real Cost at Scale URL: https://ryandoser.com/ahrefs-api-pricing/ Markdown: https://ryandoser.com/ahrefs-api-pricing.md Published: 2026-08-22 | Updated: 2026-09-30 Categories: AI Tool Reviews > Ahrefs API access starts at $129/mo, not the $1,499 Google's AI Overview claims. Here is the unit math that decides what you actually pay. **Ahrefs API pricing** starts at **$129 a month** on the Lite plan. Google's AI Overview says it requires an Enterprise plan at **$1,499 a month**. Both numbers are in circulation, and the cheaper one is correct. Ahrefs says so on its own help page, which the AI Overview cites as a source while contradicting it. But the plan price is the smaller half of this question. Ahrefs meters every request in API units, so what you actually pay at scale depends on math the pricing page never shows you. That is what this post works out. Two terms, once, in plain English. The API is the paid pipe that lets software pull Ahrefs data directly rather than a person exporting it from the dashboard. MCP, the Model Context Protocol, is the connector that lets Claude or ChatGPT pull that same data for you in a chat, with nothing to build. They matter together here, because they run off the same meter, and most people reading this only need the second one. I pay for Ahrefs. I have not bought API access, so nothing here is a firsthand report of running it. What I can do is read what every source publishes and check the numbers against each other. ### **The Entry Price, Settled** Ahrefs' help center article "About API v3", updated June 18, 2026, says it plainly: *"Using API v3 from any of the above methods is possible for Lite and higher subscription plans."* The three methods are direct API access, the MCP server, and Ahrefs Connect. *From [help.ahrefs.com, "About API v3"](https://help.ahrefs.com/en/articles/6559232-about-api-v3), updated June 18, 2026. As captured August 22, 2026, before Ahrefs doubled the unit allowances.* Here is what each plan includes, rechecked against the current help center table, the [pricing page](https://ahrefs.com/pricing) and the [MCP page](https://ahrefs.com/mcp/) on September 30, 2026. All three agree on Lite, Standard and Advanced, which now carry twice the units they did in August. For Enterprise, the pricing and MCP pages say 4M or custom, while the help center says only custom. | Plan | Price per month | API units per month | Max rows per request | | Starter | $29 | No API access | Not applicable | | Lite | $129 | 200,000 | 100 | | Standard | $249 | 800,000 | 250 | | Advanced | $449 | 2,000,000 | 500 | | Enterprise | $1,499, annual commitment | 4,000,000, or custom | Unlimited | Ahrefs lists annual billing as "save up to 17%" rather than printing a per-month figure, so treat that as the discount and check the exact charge at checkout. The $29 Starter tier is the one trap worth knowing: it is a real plan, and it has no API access at all. ### **The Unit Math That Decides Your Real Cost** This is the part that separates the sticker price from the bill, and it is why two people on the same plan get very different mileage. What $129 buys is a monthly allowance of API units, and every question you ask spends some of it. Per the docs, each request costs at least 50 units, and more as it returns more rows and more fields. On Lite, a request pulling 100 backlinks with six fields costs 600 units. Against a 200,000-unit allowance, that is roughly 333 of those a month. Price that same pull across the tiers and the plans separate less than the prices suggest. Filling the row cap each time, Lite gives you about 333 requests a month, Standard about 533, and Advanced about 666. Advanced costs three and a half times what Lite does and buys roughly twice the requests, because a bigger response spends proportionally more units. What the higher tiers really buy is a bigger answer per question, not many more questions. On Lite that works out to about ten a day, and fewer if your questions are heavier than the example. #### **The three things that quietly cost you money** **Lots of small questions.** Because every request costs at least 50 units whether it returns 10 rows or 50, a habit of asking many narrow questions burns the allowance far faster than asking fewer, broader ones. If you point an automation at it that checks something every hour, expect that to hurt. **The row cap on cheaper plans.** Lite returns at most 100 rows per request. Ask for your top 300 referring domains and it takes three requests, at three base fees, to answer one question. Advanced does it in one. If you routinely work with big lists, that cap costs you more than the unit count suggests. **Running out.** Ahrefs' MCP help article says that ["to increase your monthly limit, upgrade your plan or purchase additional units on the Enterprise plan"](https://help.ahrefs.com/en/articles/13913559-getting-started-with-ahrefs-mcp). On Lite or Standard that means the documented fix is moving up a tier, not buying a top-up. Budget for the plan you will need in month six. Two things work in your favor. Repeated questions served from cache cost nothing, and the docs say plans without API access still get a limited set of free test queries, so you can try before paying. ### **Do You Even Need The API?** For most marketers reading this, the answer is no, and it saves the entire developer budget. Per Ahrefs' help center, the MCP server and direct API access draw from the same unit pool and the same row cap. Same data, same budget, no code. Everything above applies to asking Claude a question exactly as it applies to a script. Choose the REST API only when you need scheduled jobs, a data warehouse, or output feeding something other than a chat window. I compared the options in my [DataForSEO vs Ahrefs breakdown](/dataforseo-vs-ahrefs/) and my roundup of the [best SEO MCP servers](/best-seo-mcp-servers/). ### **Why The $500 And $1,499 Figures Persist** Here is the AI Overview that sent me down this road. *Google's AI Overview for "ahrefs api pricing", captured August 22, 2026. It cites five sources, including two Ahrefs pages.* It matched the Enterprise unit count Ahrefs published at the time, 2,000,000. The requirement to be on Enterprise at all is where it fails, and one of its own cited sources says so. Its arithmetic does not hold either. It says $1,499 a month "billed annually at $14,990/year", but twelve months at $1,499 is $17,988. The $14,990 figure is exactly ten months, so two months appear to have gone missing somewhere in the summarizing. The two third-party sources it leans on explain where the numbers came from. [seobotai.com](https://seobotai.com/blog/ahrefs-api-alternatives/), dated September 30, 2025 and nearly eleven months old, is almost certainly the origin of the Enterprise claim. [checkthat.ai](https://checkthat.ai/brands/ahrefs/pricing), dated March 30, 2026, lists a different structure again: API Standard $500 a month, API Plus $2,000, API Premium $10,000, priced by rows rather than units. *From [checkthat.ai](https://checkthat.ai/brands/ahrefs/pricing), last updated March 30, 2026. Verified August 22, 2026.* That page contradicts itself on one screen. It says Advanced includes 500,000 API units, then calls Enterprise "the only tier with unlimited projects, unlimited users, and bundled API access." Its unit figures miss too, listing 150,000 for Standard where Ahrefs published 400,000 at the time and now publishes 800,000. Those row-based tiers look like standalone API plans Ahrefs no longer sells, though that is my inference rather than something Ahrefs announced. What is certain is that `ahrefs.com/api` and `ahrefs.com/api/pricing` both now redirect to the developer docs, so there is no such rate card to buy from. Ahrefs is not blameless. Its developer docs say the API is available on ["eligible paid plans"](https://docs.ahrefs.com/en/api/docs/introduction) without ever naming which ones. When the vendor will not state the tier, third parties fill the gap with whatever they have, current or not, and answer engines repeat it as fact. ### **What To Budget, By Use Case** List prices as of September 30, 2026, excluding the extra user seats most teams add, and assuming you stay inside the included allowance. **Asking questions of Ahrefs data in Claude or ChatGPT:** Lite at $129. MCP is included and 200,000 units goes a long way when a human is typing the prompts. **Regular automated pulls across a handful of sites:** Standard at $249. Four times the units and 250 rows per request, which cuts your base-fee multiplier meaningfully. **Anything where a truncated response breaks the job:** Advanced at $449, for the 500-row cap rather than the unit count. **Uncapped rows, SSO and audit logs:** Enterprise at $1,499. A legitimate tier for large teams, just not the entry point for API access. ### **Cheaper Routes If Ahrefs Is Out Of Reach** None of these give you Ahrefs' backlink index, and that index is usually the whole reason someone wanted the Ahrefs API. If link data is the job, a cheaper SERP API will not cover for it. [**Google Search Console**](https://developers.google.com/webmaster-tools/v1/getting-started) is free, has an official API, and covers your own site's query and click data better than any paid tool. If you are reporting on sites you own, start here before spending anything. [**Semrush**](https://www.semrush.com/pricing/) puts API data integration on its Advanced plan, $549 a month or $455.67 billed annually. It is the closest like-for-like if you want a full suite with its own index, though it meters and gates the API very differently, which I worked through in [Semrush API pricing](/semrush-api-pricing/). *Affiliate link below. [Full disclosure](/disclosure/).* [**DataForSEO**](https://dataforseo.com/?aff=245611) is the one I use and the one I earn a commission on, so weigh that accordingly. No subscription, billed per request from a prepaid balance at a published $0.0006 per standard-queue SERP, $0.0012 priority and $0.002 live, with a $50 minimum payment. It is raw data rather than a dashboard, and I covered where it falls short in my [DataForSEO review](/dataforseo-review/). If you want a dashboard on that same data, OpenSEO resells DataForSEO at a [28% markup inside a $10 monthly plan](/openseo-review/), which is still a fraction of Ahrefs Lite. ### **Ahrefs API Pricing FAQs** #### **How much does the Ahrefs API cost?** Access starts at $129 a month on Lite, and there is no separate API subscription to buy on top. Which tier you need depends less on price than on how you work: Lite suits occasional questions, Standard at $249 suits regular automated pulls, and Advanced at $449 is worth it mainly if you routinely request more than 250 rows at a time. #### **Is the Ahrefs API free?** No, but every plan including free accounts gets a limited set of free test queries so you can develop against the API without spending units. Ahrefs notes that consumed units are non-refundable, which is why those test queries exist. #### **How are Ahrefs API units calculated?** Every request costs at least 50 units no matter how little it returns, then scales with the rows and fields you ask for. The practical consequence is that many small questions cost far more than a few broad ones, so an automation polling Ahrefs every hour will drain an allowance that comfortable manual use would not. #### **Do I need the Ahrefs API, or is MCP enough?** For most marketers, MCP is enough. It draws from the same unit allowance and row cap as the REST API, so it is the same data and the same budget without writing code. Choose the REST API for scheduled jobs, a data warehouse, or output feeding something other than a chat window. #### **Why do sources disagree about Ahrefs API pricing?** Because Ahrefs' developer documentation says the API is available on "eligible paid plans" without naming them, so third parties guess and answer engines repeat the guess. The circulating $500 and $1,499 figures appear to come from standalone API plans Ahrefs no longer sells. Read the plan table in the help center, which does name the tiers. Disclosure: I am not an Ahrefs affiliate and earn nothing if you buy Ahrefs, which I pay for myself. I am a DataForSEO affiliate and earn a commission through my link. I also sell an AI SEO product, a competing interest you should weigh. Method: all Ahrefs prices, unit allowances, row caps and the cost formula were read from ahrefs.com/pricing, ahrefs.com/mcp, docs.ahrefs.com and the Ahrefs help center; third-party figures are dated and linked to their sources. I have not purchased Ahrefs API access, and the note about retired standalone API plans is my inference, not an Ahrefs statement. Prices change; verify before you buy. [Full disclosure](/disclosure/). --- ## DataForSEO Review: The Best SEO MCP for AI Agents URL: https://ryandoser.com/dataforseo-review/ Markdown: https://ryandoser.com/dataforseo-review.md Published: 2026-08-22 Categories: AI Tool Reviews > DataForSEO is the SEO data layer I run in Claude Code daily. Real pay-as-you-go costs, where the data loses to Ahrefs, and the v3 MCP server that changed the setup. Every SEO review you have read compares tools by their monthly price. That framing does not work here, because **DataForSEO has no monthly price**. A Google SERP costs $0.0006 in the standard queue. One thousand of them cost sixty cents. I pull that data every working day through Claude Code and Codex, for SEO and AI search work across my own site and a roster of clients. It is the paid SEO MCP server I would hand an AI agent before any other. MCP is the Model Context Protocol, the standard that lets an assistant like Claude pull from an outside tool on its own. You ask a question in plain language instead of writing code. Pair it with the free [Google Search Console server](/best-seo-mcp-servers/), which reports your own traffic rather than the market. DataForSEO covers everything Search Console cannot see, which is every competitor, keyword and SERP outside your own property. The price is the least interesting thing I have to tell you. DataForSEO quietly shipped a new version of its Claude connector that deprecates the old one, and the change is significant enough that most tutorials published before this month now describe a setup that no longer ships. ### **What DataForSEO Actually Is** DataForSEO sells the data layer that sits underneath an SEO tool, and stops there. *Affiliate links below. [Full disclosure](/disclosure/).* #### **[Try DataForSEO with $1 in free credit](https://dataforseo.com/?aff=245611)** There is no dashboard to log into, no rank tracker, no site audit report waiting for you on a Monday morning. What you get is an API: you send a request describing the data you want, and you get structured JSON back. Keyword volumes, live SERP results, backlink profiles, competitor rankings, on-page crawls, and increasingly, what AI models say when asked about a topic. This is the single most important thing to understand before you buy, and it is where most reviews mislead people. If you want to open a tab, type a domain, and look at a chart, DataForSEO is the wrong purchase and no price advantage will fix that. There is a middle option. OpenSEO puts a $10-a-month dashboard on top of DataForSEO's data, and I weighed whether that layer is worth paying for in my [OpenSEO review](/openseo-review/). Ahrefs and Semrush sell you an interface, an opinion about what matters, and a set of decisions already made on your behalf. DataForSEO sells you the raw material those interfaces are built from. The trade is real in both directions. You give up the interface. You get data that is roughly two orders of magnitude cheaper and that you can point at anything you want. If you are weighing the two against each other rather than reading up on DataForSEO alone, I compared them directly in [DataForSEO vs Ahrefs](/dataforseo-vs-ahrefs/). If the subscription you are questioning is a Semrush one, that is a different calculation, and I worked through it in [DataForSEO vs Semrush](/dataforseo-vs-semrush/). ### **The Pricing Model, With Real Numbers** DataForSEO runs pay-as-you-go with a $50 minimum deposit. There is no subscription, no seat count, and no monthly renewal. You put money in the account and it draws down as you make requests. Unused balance does not expire. New accounts get [$1 in free credit](https://dataforseo.com/?aff=245611) without a credit card, which sounds trivial and is not. DataForSEO puts that at 833 SERPs on high-priority tasks, or 20,000 backlinks, or 20,000 keywords with Google Ads metrics. That is more than enough to decide whether the data is any good before you spend anything. Test it that way before depositing the $50. *DataForSEO has no plans or seats. You fund a balance, with a $50 minimum, and draw it down per request.* Here are the live rates, pulled from DataForSEO's own pricing pages on August 22, 2026. #### **Google Organic SERP API** *The three speed tiers, straight off the rate card. One SERP means 10 search results.* | Mode | Turnaround | Per SERP | Per 1,000 SERPs | | Standard Queue | ~5 minutes | $0.0006 | $0.60 | | Priority Queue | Up to 1 minute | $0.0012 | $1.20 | | Live Mode | Up to 6 seconds | $0.002 | $2.00 | The three-tier structure is where people overspend without noticing. Live mode costs more than three times the standard queue, and it buys you seconds. Running a scheduled overnight job across a thousand keywords? You have no reason to be in live mode. Asking Claude a question and waiting on the answer? You do. I use live mode constantly, because my volume is low and my patience during a working session is lower. But it costs 3.3 times the standard rate and I know I am paying it. Run 50,000 pulls a month and the choice is $100 in live mode against $30 in the standard queue. Defaulting to live costs an extra $70 a month to save time nobody is awake to notice. #### **Keyword and Ranking Data** | Endpoint | Price per task | Price per item | | Google Ads search volume (Live) | $0.09 | Up to 1,000 keywords per task | | DataForSEO Labs (most endpoints) | $0.012 | $0.00012 per item | | Backlinks (Live) | $0.024 | $0.000036 per row | That backlinks row is the one that tends to stop people. A thousand rows of backlink data costs six cents, calculated as the $0.024 task price plus $0.000036 per row. #### **The AI Search Data** This is the newest part of the platform and the reason I would still be here even if the price advantage disappeared. DataForSEO sells structured access to AI search surfaces: - **Google AI Mode SERP API:** $0.0012 per page in the standard queue, $0.0024 priority, $0.004 in live mode - **LLM Responses API:** $0.0006 per task in live mode, or $0.0002 in the standard queue, plus whatever the underlying model charges - **AI Keyword Search Volume** and **LLM Mentions** for tracking how often a brand surfaces in AI answers Being able to ask, programmatically, "what does ChatGPT say when someone asks about this category, and are we in the answer" is a genuinely different capability from rank tracking. Note the pricing shape on LLM Responses. DataForSEO's own fee is tiny, and you also pay whatever the model's API charges. On the standard queue that arrives as a $0.01 automatic prepayment, refunded in part if the model bills less. Your real spend depends on which model you query. ### **One Real Workflow, Start to Finish** Here is an actual sequence rather than a description of one, because "ask Claude for the data" is easy to write and vague to act on. I was deciding whether this post was worth writing. In Claude Code I asked for search volume and the twelve-month trend on "dataforseo" and a set of related terms. One request came back showing 3,600 a month against 1,300 the previous August, with the curve stepping up rather than decaying. That is the check that decided the post, and at Labs rates it cost a fraction of a cent. Then I asked for the live SERP for "dataforseo review" to see what I would be competing against. That returned the top ten plus the AI Overview and the People Also Ask questions. That is where most of the FAQ section at the end of this post came from. Those questions are not invented, they are what Google already shows people searching this term. The pull ran in live mode at $0.002. The whole research pass, volume plus trend plus SERP plus the AI Overview citation list, cost me under a nickel and took about four minutes of wall-clock time. The equivalent on a subscription tool is $129 a month whether I run it once or two hundred times, and the AI Overview citation list is not something most of them will hand me at all. That is the case for this thing, and it only works because the model sits between me and the JSON. I never opened a documentation page or wrote a request body. ### **The Cost Comparison Everyone Wants** Ahrefs Lite, the entry tier most solo SEOs land on, is $129 per month billed monthly. That tier is also where Ahrefs API and MCP access begins, which I broke down in [Ahrefs API pricing](/ahrefs-api-pricing/). Set against $0.60 per thousand SERPs, the arithmetic looks absurd, and this is where most reviews stop and declare a winner. It is not that simple, and I want to be straight about why. At $129 a month, Ahrefs gives you a crawler with its own index, a rank tracker that remembers yesterday, a site audit that interprets what it finds, and a UI a junior team member can use on day one. To match that with DataForSEO you would build the storage, the scheduling, the deduplication, the charts and the interpretation layer. That build is not free even when the data is nearly free. The honest comparison puts $129 against $0.60 plus however many hours you spend building the parts Ahrefs already shipped. Which is exactly why the AI angle changes the calculation, and why I think this tool got dramatically more interesting in the last eighteen months rather than gradually cheaper. The interpretation layer used to be the expensive part. Now I can ask Claude for it in a sentence. ### **What Changed: The v3 MCP Server** DataForSEO has now shipped a **v3 MCP server, and the previous version is formally deprecated**. The old repository has been renamed with a "deprecated" suffix. This is not a minor version bump, and if you set this up from a tutorial written before this month, you are looking at instructions for software that is no longer the current release. *The repo states it plainly: this is the new v3 server, and the previous one is deprecated.* The architectural change is the interesting part. The old server exposed a separate named tool for every endpoint across ten modules, so Claude saw `serp_organic_live_advanced` and `dataforseo_labs_google_keyword_ideas` as distinct capabilities. The v3 server replaces all of that with four general-purpose tools. The model reads DataForSEO's documentation and builds the request itself, so new endpoints get picked up automatically instead of going stale. It is a trade rather than a pure upgrade, because the model now looks something up before it can act, which is an extra step and an extra chance to get an unusual request wrong. I found this because the DataForSEO connection I use in Claude Code every day still points at the older multi-tool build. It is the kind of change you only notice when you already have a working setup. Being straight about the limit of that: I have read the v3 repository closely and I am still on v2. I can tell you what v3 ships and how it is designed, not how it feels after a month of daily use. If you are on v2 like me, nothing has broken and there is no fire drill here. New setups should start on v3, and the hosted endpoint below makes that the easier path anyway. #### **Connecting It to Claude** There is now a hosted remote endpoint at `https://mcp.dataforseo.com/v3/mcp` that uses OAuth, so you authorize in a browser instead of pasting credentials into a config file. That is a meaningful quality-of-life change and the path I would point most people at. If you have never connected a tool this way, I walk through the general process in my guide to [setting up MCPs in Claude Code](/claude-code-mcps/), and I cover how this fits a research workflow in [keyword research in Claude Code](/claude-code-keyword-research/). ### **What I Actually Use It For** Concrete, from real working sessions: **Validating a keyword before committing to a post.** I ask for volume, the trend curve, and the live SERP in one request. The trend curve is the part that earns its keep, because a keyword averaging 300 a month can be 80% off its peak and still falling, and the annual average hides that completely. I have killed planned posts on this signal alone. **Reading the actual SERP instead of guessing.** Volume tells you people search. The SERP tells you whether you can win. When page one is the vendor's own documentation answering a question only that vendor can answer, a third-party post is not the result Google wants there, and knowing that before writing saves a day. **Checking AI visibility separately from rankings.** These diverge more than people expect. A page can rank third and go completely uncited in AI Overviews. I pull the AI Overview and read which domains sit in its citation list, and which sentence each one is credited for. Being cited as research while a competitor gets named as the recommendation is a different problem from ranking badly, and it needs a different fix. It is also why I ignore [the AI ranking numbers some tools report](/ai-search-myths/), since there is no standing position to report on. **Client audits.** Ranked keywords, competitor overlap and backlink profiles across five domains lands in single-digit dollars at the rates in the tables above, against a subscription I would keep paying between engagements whether or not I had an audit to run. ### **Where It Falls Short** Five real limitations, and the first one is the big one. **The data quality is a step behind Ahrefs and Semrush, and I am not going to dance around it.** This is the one genuine downside that matters, and it is worth understanding before you deposit anything. DataForSEO's default keyword volumes come from Google Ads data, so they arrive in the same rounded buckets Keyword Planner gives you. Ahrefs and Semrush lead with clickstream-blended estimates that carry more texture. There is a clickstream-refined volume option, but the Ads-based figures are what the standard endpoints and the MCP hand you unless you ask for it. In my own pulls, the backlink data also does not match the depth I am used to from Ahrefs' index. For the way I work the trade is worth it, because the keyword data is decent and the SERP pulls are live and exact. But if your work lives or dies on volume precision or backlink completeness, that gap is real and you should know it walking in. This is the one place where paying Ahrefs genuinely buys you something DataForSEO does not have. **There is no interface.** I keep returning to this because it disqualifies more buyers than every other factor combined. If nobody on your team is comfortable in a terminal or an AI assistant, this will sit unused. The $50 you deposited will still be there in a year. **Nothing remembers anything.** Every request is a snapshot. Rank tracking, in the sense of a chart showing movement over eight weeks, requires you to store results yourself on a schedule. Subscription tools do this by default and it is a larger part of their value than their marketing suggests. **Costs are hard to forecast.** Per-request pricing is only predictable once you know your request count, and you do not know that on day one. A runaway loop can spend real money before you notice, which is an argument for starting with the free credit and watching the balance rather than depositing $200 and assuming. **Index gaps are real.** DataForSEO returns no measurable volume for genuinely new terms, and that reads as "no demand" when it often means "too new to be indexed." I have watched a keyword go from unmeasurable to thousands of searches in four months. Treat a zero as one input, never as a verdict, and check the live SERP alongside it. ### **Who Should Buy This** **Buy it if** you already work through Claude Code, Codex or a similar assistant, you are comfortable when something needs debugging, you run data across many domains, or you want AI search visibility data most subscription tools do not sell at all. Testing costs nothing, since the first dollar is free. Committing costs $50 plus the afternoon you spend wiring it into your workflow, and that afternoon is the real price of entry. **Skip it if** you want to look at charts, you manage one or two sites where a subscription's flat fee is simpler than metering, you need historical tracking without building it, or you would be the only person on the team who could operate it. Ahrefs at $129 is priced for someone who wants the interpretation included, and that is a legitimate thing to want. Workflow fit decides this, not budget. The real question is whether you want data or answers. ### **The Verdict** For an AI agent doing SEO work, this is the MCP server I would install first among the paid options. It also sits in [the wider marketing stack I run](/mcp-servers-for-marketers/), next to the publishing and video servers it does not overlap with. Three things keep me on it every day despite that gap. It is very affordable at scale, and the bill tracks what I actually use across client work instead of renewing whether I worked or not. If the per-request model is the part you want, I compared it against [the seven closest alternatives on price and billing shape](/dataforseo-alternatives/). The keyword and SERP data is decent, and the SERP side in particular is live and exact rather than a cached index. DataForSEO was also one of the first SEO data vendors I saw ship an MCP server, which means they were building for AI agents doing SEO work before most of the category had noticed the protocol existed. That head start shows in how well the connector actually works. What earns the recommendation from me is that the interpretation layer, which used to be the entire reason to pay for a subscription tool, is now something I can ask an AI assistant for. That flips the calculation. Raw data plus a capable model beats a fixed interface for the work I do, and it did not beat it two years ago. The v3 MCP change is a genuine improvement and it is also a warning about the category: this moves fast enough that a six-month-old tutorial can describe deprecated software. Go to the source repository rather than trusting a blog post, including this one, six months from now. If that sounds like your kind of workflow, [DataForSEO](https://dataforseo.com/?aff=245611) gives you $1 of real API credit with no card required. Spend that before you spend the $50. ### **DataForSEO FAQs** #### **How much does DataForSEO cost?** There is no monthly fee. You deposit a minimum of $50 and draw it down per request. Google SERP results cost $0.0006 each in the standard queue ($0.60 per thousand), $0.0012 in the priority queue and $0.002 in live mode. Most DataForSEO Labs endpoints cost $0.012 per task plus $0.00012 per item, and backlink data runs $0.06 per 1,000 rows. New accounts get $1 in free credit without a credit card. #### **What is the catch with DataForSEO's pricing?** Two things the rate card does not spell out. Live mode costs 3.3 times the standard queue for the same data, so defaulting to it on scheduled jobs quietly multiplies your bill. The $50 minimum is also a deposit rather than a subscription, so the money is not wasted, but you cannot start with $5. The genuine risk is a runaway loop spending faster than you notice, so start small and watch the balance for the first week. #### **Does DataForSEO work with Claude?** Yes. DataForSEO ships an MCP server that connects it to Claude Code, Claude Desktop, and other MCP-capable assistants. As of the v3 release there is a hosted remote endpoint at `https://mcp.dataforseo.com/v3/mcp` using OAuth, or you can run it locally with `npx dataforseo-mcp-server@latest` and API credentials in your environment. #### **What is the difference between the v2 and v3 MCP servers?** The v2 server exposed a separate named tool for each API endpoint, spread across ten modules. The v3 server exposes four generic tools that let the model read DataForSEO's documentation and then construct requests itself. The v3 approach uses far less context and picks up new endpoints automatically. The v2 server is deprecated and now lives in a separate repository marked as such. #### **Is DataForSEO the best SEO MCP server?** For market data, yes, and it is the one I run daily. The honest ordering is to install the free Google Search Console MCP first, because it reports your own impressions and positions rather than an estimate. DataForSEO is the best paid SEO MCP and the one to add second. Live SERPs, keyword volume, backlinks and AI Overview citation data are all things Search Console cannot show you. Ahrefs and Semrush both ship MCP servers with better data depth, but each is gated behind a paid subscription. Ahrefs MCP requires a paid plan starting at $129 a month, and Semrush includes MCP access on its Semrush One and SEO Classic plans. DataForSEO asks for a $50 balance you draw down at your own pace. *How I sourced this: all pricing was read off full JavaScript renders of DataForSEO's own rate-card pages on August 22, 2026, because those pages load their prices with JavaScript and a plain fetch returns empty fields. MCP server details, including the v3 tool list, the deprecation of the v2 server, the npm package name and the remote endpoint URL, were read from the official DataForSEO MCP repository rather than from marketing pages. Ahrefs Lite pricing was taken from its public pricing page the same day. Free-trial credit terms come from DataForSEO's own help center. This post contains affiliate links to DataForSEO, so I earn a commission if you sign up through them, at no additional cost to you. I also sell a competing AI SEO product. [Full disclosure](/disclosure/).* --- ## DataForSEO vs Ahrefs: Which One Should Your AI Agent Use? URL: https://ryandoser.com/dataforseo-vs-ahrefs/ Markdown: https://ryandoser.com/dataforseo-vs-ahrefs.md Published: 2026-08-22 | Updated: 2026-08-31 Categories: AI Tool Reviews > DataForSEO vs Ahrefs, compared on cost, data and AI agents. Both now ship MCP servers, so the old developer-versus-marketer split no longer decides it. Search this comparison today and Google's AI Overview tells you the same thing every article on page one tells you: **DataForSEO is a developer API and Ahrefs is a marketer's dashboard**. It is out of date. Both companies now ship MCP servers, so a marketer who has never written a line of code can connect either one to Claude and ask questions in plain English. The objection the whole comparison rests on has quietly collapsed. MCP is the Model Context Protocol, the standard that lets an assistant like Claude pull live data from an outside tool on its own. You ask for what you want in a sentence instead of building anything. So the useful question is no longer which one you are technical enough to use. It is which one you should point your agent at, and that comes down to a distinction nobody on page one is making. The short version of DataForSEO vs Ahrefs: DataForSEO bills per request and is cheaper for live SERP and AI search data at volume, while Ahrefs charges from $129 a month and is worth it for backlink depth and historical data you cannot rebuild after the fact. People are already asking it. A Reddit discussion titled "Ahrefs vs Dataforseo for SEO automations in Claude," posted in r/seogaps in May 2026, ranks on page one of this query while every article above it answers the dashboard question instead. *Affiliate links below. [Full disclosure](/disclosure/).* I pay for Ahrefs and I run [DataForSEO](https://dataforseo.com/?aff=245611) through Claude Code most working days. I am not going to declare a winner, because having used both I do not think they are the same kind of purchase. If you want the full rate card and my verdict on DataForSEO alone, that is in my [DataForSEO review](/dataforseo-review/). ### **One Sells Data. The Other Sells Memory.** **DataForSEO sells you data by the request.** You ask for a live Google SERP, a search volume, a keyword list, and you are billed for that specific pull. Nothing is stored on your behalf and nothing accumulates. **Ahrefs sells you access to an index it maintains.** Its own crawler runs continuously, and what you are paying for is the accumulated record across links, keywords and rankings: which sites linked to whom, when the link appeared, when it disappeared, what the rankings looked like last quarter. That difference does not care whether you access it by dashboard or by agent. It is a difference in what the product fundamentally is, and it decides almost every real question you will have. Data answers "what is true right now." An index answers "what changed, and when." You cannot ask the second question of a tool that does not remember. There is a partial middle ground. OpenSEO stores your rank tracking history and saved research on top of DataForSEO's data, though it keeps no backlink index of its own. I covered where that memory helps in my [review of OpenSEO](/openseo-review/). ### **What Connecting Each One to Claude Looks Like** Both connections are a URL and a login. Neither requires code. Ahrefs publishes setup guides for Claude, ChatGPT, Cursor and Copilot Studio, and its own screenshot shows Ahrefs sitting in Claude's connector directory alongside ActiveCampaign and Asana. *Ahrefs in Claude's connector list. This is the screenshot that ends the developer-versus-marketer framing.* DataForSEO runs a hosted server too, and it authenticates by sign-in rather than by pasting a key anywhere. Its current version reads its own documentation to build requests, which I covered in the review. Where they genuinely diverge inside an agent loop is billing shape, and this is worth understanding before you turn a research agent loose. #### **API Units Versus Per Request** Ahrefs meters MCP access in API units with a monthly allowance, and it also caps how many rows one request can return. *Ahrefs publishes rows per request and monthly API units by plan. Verified on ahrefs.com/mcp, August 22, 2026.* MCP is included on every paid Ahrefs plan, starting with Lite at $129 per month, confirmed on both [ahrefs.com/mcp](https://ahrefs.com/mcp) and [ahrefs.com/pricing](https://ahrefs.com/pricing). The $29 Starter tier does not include it. Plenty of sources still claim this costs $500 or $1,499 a month, and I traced where those numbers came from in [Ahrefs API pricing](/ahrefs-api-pricing/). The row cap is the part that bites in an agent loop. When you ask Claude for the top 300 referring domains on Lite, it cannot get them in one call, so it either paginates and burns more units or quietly hands you a truncated answer. DataForSEO has no allowance to exhaust and no row ceiling of that kind. You are billed per request from a prepaid balance, so an agent that fires forty calls costs roughly forty times one call and simply keeps working. The flip side is real. An allowance that runs out stops you, which is an annoyance that doubles as a spending cap. A prepaid balance imposes no such ceiling until it hits zero, so a badly scoped agent loop can spend its way through your funds while you are not watching. ### **What Ahrefs Does That DataForSEO Cannot** I pay for Ahrefs and I intend to keep paying for it. Cheap data does not replace what it does. **Backlink depth and freshness.** Ahrefs runs its own crawler and is the industry benchmark here. Even DataForSEO's own comparison blog post concedes differences in what each index captures. On links, Ahrefs is the reference and I treat it that way. **History you cannot reconstruct.** Its plans include six months of historical data at the entry tier and up to five years higher up. If you did not start pulling and storing SERPs two years ago, no amount of pay-as-you-go spending gets you that record today. This is the single most underrated thing you are buying. **DR as shared currency.** Domain Rating is a proprietary Ahrefs score, and its value is that everyone in the industry already speaks it. When a client asks what DR a prospect site is, the useful answer is the Ahrefs number, because that is the number the other side is looking at too. **Tools that remember yesterday.** Rank tracking and site audit are only meaningful across time. Ahrefs stores that for you, and rebuilding equivalent storage and scheduling yourself is work, even when the underlying data is nearly free. If your job involves link building, competitor link analysis, or reporting on progress over months, that is what you are paying $129 and up for, and it is a fair trade. ### **What DataForSEO Does That Ahrefs Does Not Sell** **Cost across many domains.** A standard-queue Google SERP is $0.0006, which is $0.60 per thousand, verified on the SERP API page today. When you are checking live positions across a roster of client sites, that shape is very different from a seat-priced subscription. Note that DataForSEO's minimum payment is $50, so it is prepaid rather than free to start. **Live SERPs, pulled fresh.** When I need to know what renders for a query right now in a given location, including which AI Overview sources got cited, I pull it live rather than read an estimate. That is the pull I make most often and it is why the tool earns its place in my [Claude Code keyword research](/claude-code-keyword-research/) workflow. **AI search surfaces.** DataForSEO sells an AI Optimization API covering LLM responses and AI search data. Ahrefs is not absent here either, tracking AI visibility through Brand Radar and tracked prompts. For my AI citation work I want the raw pull, which is why it shows up in my roundup of the [best SEO MCP servers](/best-seo-mcp-servers/). **No seat, no renewal.** If you go three weeks without pulling anything, you spend nothing. Balance carries; a subscription month does not. What I will not tell you is that the data is better. On depth of insight Ahrefs is ahead, and I said so in my review of the tool I actually get paid to recommend. ### **Pick By the Job, Not By the Tool** | The job | What I would use, and why | | Link building and prospecting | Ahrefs, because prospecting depends on a maintained link index and per-request data cannot substitute for one. | | Competitor backlink audit | Ahrefs, because you need to see which links appeared and disappeared over time, which requires a tool that stored yesterday. | | Rank tracking over months | Ahrefs if you want it handled for you today; DataForSEO only if you are willing to store and chart the pulls yourself. | | Live SERP checks and exact positions | DataForSEO if you need what renders right now and will accept raw output; Ahrefs if a periodic estimate in a readable interface covers the question. | | AI citation and LLM visibility tracking | DataForSEO if you want raw per-request access for an agent; Ahrefs Brand Radar if you would rather have a monitored product with tracked prompts. | | Agency work across many client domains | DataForSEO for the volume pulls, because per-request cost scales with domains better than seats do, plus Ahrefs if link or historical work is part of what you bill for. | | Solopreneur with one site | Ahrefs alone if you want links, tracking and audits under one login; DataForSEO alone if your work is mostly live SERP and AI search research and you already work in Claude. | ### **Do You Actually Need Both?** For most people reading this, no, and I would rather say that than sell you a second subscription. If you run one site and your questions are about links and progress over time, Ahrefs alone is the honest answer. Adding DataForSEO gets you a live SERP tool you will use occasionally and a $50 minimum you did not need to spend. If you run one site and your work is mostly live SERP checks and AI search visibility, DataForSEO alone is defensible. You give up the link index, which is a real loss, and you should know you are giving it up rather than discover it during a client conversation. Both makes sense when you are billing for SEO across several domains. That is my situation, and the split is not fifty-fifty: Ahrefs is the reference I open for links and history, and DataForSEO is what my agent calls all day for live data. Buy the second one when a specific job you are actually being paid for keeps hitting the first one's limit, not because a comparison post implied you need a complete stack. ### **My Honest Read** Access is no longer the axis. Any marketer who can install a Claude connector can now run either one, and the "you would need a developer" line is a leftover from a version of the market that no longer exists. What decides it is the question you spend your week answering. If that question is who is linking to whom and what changed since last quarter, pay for the index. If it is what sits on the SERP right now and who the AI engines are citing, pay for the data. If you are genuinely billing for both across a roster of sites, that is the case for carrying both. ### **DataForSEO vs Ahrefs FAQs** #### **Can I use Ahrefs with Claude?** Yes. Ahrefs ships an MCP server that connects to Claude, and it publishes setup guides for ChatGPT, Cursor and Copilot Studio as well. It is included on every paid Ahrefs plan, starting with Lite at $129 per month, and no coding is involved. #### **Is DataForSEO good?** It is very good at what it sells, which is live SERP, keyword and AI search data billed per request. It is not a replacement for an SEO dashboard and does not pretend to be one. If you want depth of insight on backlinks, Ahrefs is ahead. My full assessment is in my [DataForSEO review](/dataforseo-review/). #### **What is the most accurate SEO tool?** It depends on what you are measuring, and any answer that skips that is selling something. For live SERP positions, a fresh pull from DataForSEO reflects what actually renders. For backlink data, Ahrefs is the industry benchmark on depth and freshness. For your own traffic and impressions, neither one beats Google Search Console, which is free. #### **What are some good alternatives to Ahrefs?** Semrush is the closest like-for-like if you want a full dashboard, and I put it head to head with the pay-as-you-go option in [DataForSEO vs Semrush](/dataforseo-vs-semrush/). Its API is billed very differently from the Ahrefs model above, which I covered in [Semrush API pricing](/semrush-api-pricing/). DataForSEO is the alternative if what you actually need is data rather than an interface, and it is cheaper for that job by a wide margin. Neither replaces Ahrefs for backlink depth or stored history. I cover the wider field in my roundup of the [best AI SEO tools](/best-ai-seo-tools/). #### **What are the cons of Ahrefs?** Price is the main one, since $129 a month is a real commitment for a single site and there is no free tier beyond limited webmaster tools. Beyond cost, the row cap on the entry plan limits how much one agent request can return, and it does not sell the raw AI search response data DataForSEO does. #### **What are some alternatives to DataForSEO?** Serper and SerpApi are the closest on live SERP data, and Semrush or Ahrefs if what you actually want is a full dashboard rather than raw data. I priced [seven of them against each vendor's live rate card](/dataforseo-alternatives/) if you want the arithmetic. If cost is the reason you are asking, Google Search Console is free and covers your own site's performance, which is the one thing no paid tool does better. Its [free MCP server](/best-seo-mcp-servers/) connects to Claude the same way these two do. #### **How much does each one cost?** Ahrefs is a subscription, listed today at $129 per month for Lite, $249 for Standard and $449 for Advanced, with up to 17 percent off for paying annually. A $29 Starter tier exists but excludes MCP. DataForSEO has no monthly fee and bills per request from a prepaid balance with a $50 minimum payment, with a standard-queue Google SERP at $0.0006. Methodology and disclosure: every figure in this post was verified against primary sources, specifically ahrefs.com/pricing, ahrefs.com/mcp, the DataForSEO SERP API pricing page and dataforseo.com/pricing. I am a DataForSEO affiliate and earn a commission if you sign up through my link. I am not an Ahrefs affiliate and earn nothing if you buy Ahrefs, which I pay for myself. I also sell an AI SEO product, which is a competing interest you should weigh. Prices and plan limits change; check both vendors before buying. [Full disclosure](/disclosure/). --- ## DataForSEO vs Semrush: Which AI SEO Tool is Better? URL: https://ryandoser.com/dataforseo-vs-semrush/ Markdown: https://ryandoser.com/dataforseo-vs-semrush.md Published: 2026-08-22 | Updated: 2026-09-23 Categories: AI Tool Reviews > DataForSEO vs Semrush, compared on what you actually use. Semrush sells a bundle, DataForSEO replaces one slice of it at $0.0006 per request. A Semrush subscription is not one product. It is roughly a dozen products sold under one login and one monthly charge, and **most people paying for it use two or three of them**. So the honest answer to which one is better is that they are not competing for the same job. Semrush is better at almost everything it sells, and DataForSEO is better at the one thing they overlap on, which is buying search data cheaply. That is the part every comparison of these two tools skips. It sets up a duel, picks a winner, and never asks the question that actually decides your bill. Before you compare DataForSEO to Semrush, open your last invoice and work out which parts of that bundle you opened this month. The answer changes what this comparison even means for you. *Affiliate links below. [Full disclosure](/disclosure/).* I run [DataForSEO](https://dataforseo.com/?aff=245611) through Claude Code most working days, across my own site and client work. I have used Semrush in the past and do not pay for a seat today, so what follows on the Semrush side is read off its live pricing page, its documentation and its feature set rather than off a dashboard I log into. If you are weighing the other big suite instead, I ran that comparison separately in [DataForSEO vs Ahrefs](/dataforseo-vs-ahrefs/), and it lands somewhere different, because Ahrefs sells a narrower product than Semrush does. ### **Semrush Is an Adobe Company Now** The logo on semrush.com reads "An Adobe Company," and that is the newest fact on this comparison by a wide margin. [Adobe completed its acquisition of Semrush](https://news.adobe.com/news/2026/04/adobe-completes-semrush-acquisition) on April 28, 2026, and Semrush told customers nothing changes for now on contracts, features, billing or support. I take that at face value and would still prefer monthly billing over an annual commitment while a new owner settles in. Neither company has said anything specific about the API or the MCP server, which is the part an agent workflow depends on. ### **The Plans Changed, and the PAA Box Still Has the Old Ones** When I pulled the search results for this comparison on August 22, 2026, Google's People Also Ask box answered "How much does Semrush cost per month?" with a table listing **Pro at $139.95 and Guru at $249.95**. Those are not the plans a new buyer sees. The pricing page now sells SEO, Starter, Pro+ and Advanced, and the numbers moved with the names. The old names still exist inside Semrush's modular toolkit model, where the help centre maps SEO Pro to Starter and SEO Guru to Pro+. What changed is what you are quoted when you go to buy. *Semrush's current lineup. Note the page loads on the annual toggle, so the large number is the annual per-month rate and the monthly rate sits greyed out beside it. Verified on semrush.com/pricing, August 22, 2026.* Verified on [semrush.com/pricing](https://www.semrush.com/pricing/) today, the monthly rates are $139 for SEO, $199 for Starter, $299 for Pro+ and $549 for Advanced. Paying annually takes those to $117.33, $165.17, $248.17 and $455.67 per month. One detail matters more than the rest for anyone reading a comparison post. **MCP access starts at Starter, which is $199 a month**, and the $139 SEO plan does not list it. MCP stands for Model Context Protocol. In plain terms it is the plug that lets Claude or ChatGPT reach into a tool and fetch real data on its own, so you ask in a sentence instead of writing code. There is still a one-time setup, and it is a connection to authorise rather than a thing to build. So if your reason for looking at either tool is connecting SEO data to an AI assistant, the entry price on the Semrush side is not the number on the front of the pricing page. ### **What You Are Actually Renting for $199 a Month** Here is the case for the bundle, made properly, because a comparison that undersells the incumbent is not worth reading. A Semrush seat covers work that spans far past keyword research. Competitor and keyword gap analysis, traffic and market data on domains you do not own, position tracking that runs on a schedule, and site audits. Then the AI visibility layer, which tracks prompts and brand sentiment across AI engines and is now bundled into the same plans rather than sold separately. Check the tier before you assume a given feature is yours. Content optimization and historical data start at Pro+, share of voice and API access at Advanced, and extra users and white-labeled reporting are paid add-ons on top. Ahrefs gates its API differently, starting much lower than most sources claim, which I covered in [Ahrefs API pricing](/ahrefs-api-pricing/). Underneath all of it sits the thing that is easiest to overlook and hardest to replicate. **It is an interface a non-technical person can be productive in on their first afternoon.** Hand a junior marketer a Semrush login and they will produce something useful today. Hand them raw API access and you have given them a project, not a tool. I said as much in my roundup of the [best AI SEO tools](/best-ai-seo-tools/), where Semrush earns its spot as the all-in-one default rather than as the cheapest option on the page. ### **The One Slice DataForSEO Actually Buys Back** Now the narrow part. DataForSEO sells search data by the request from a prepaid balance, with no seat and no renewal. The overlap with Semrush is real but thin. Keyword volume, live SERP results, backlink data as raw rows, and AI search surfaces. What that costs, verified today on DataForSEO's own [published rate card](https://dataforseo.com/pricing-list), is the reason people keep bringing this comparison up. Every figure below is on a public page you can open without an account. A Google Organic [SERP in the standard queue](https://dataforseo.com/pricing/google-serp/google-organic-serp-api) is **$0.0006**, which is sixty cents per thousand. High priority in that same queue is $0.0012, and live mode, which returns in seconds, is $0.002. Google Ads search volume runs $0.06 per task in the standard queue, and one task covers up to 1,000 keywords. A full thousand-row backlink pull lands at about six cents. The minimum payment is $50, so this is prepaid rather than free to begin. That balance does not expire and no month renews it. Put a number on the slice. Say you pulled 1,000 SERPs in a month, 20 keyword volume tasks covering up to 20,000 keywords, and 20 full thousand-row backlink pulls. In the standard queue that is $3.00. Pull all 1,000 SERPs in live mode instead and it is $4.40, because the speed tier is the only line that moves. That is the arithmetic doing the work in every "replace your SEO suite" post you have seen. It is also, on its own, misleading, which is the next section. ### **What Leaves With the Subscription** Cancel Semrush and buy data per request instead, and here is the honest inventory of what stops existing. Position tracking that runs on a schedule and charts itself. Site audits that crawl on a cadence and flag what changed. Keyword gap analysis. Paid search and ad copy research. Traffic analytics on competitor domains. Content optimization tooling, local listings management, scheduled and white-labeled client reporting, and the AI brand sentiment layer. Then the two that people underestimate most. **The interface, and anyone on your team who is not you.** Raw JSON is not a deliverable. If a teammate or a client needs to look at something themselves, someone has to turn that raw output into a view first, and that someone is you. **Anything that depends on remembering last month.** DataForSEO returns what is true at the moment you ask. Storing it, scheduling it and charting it is work you now own. On raw data depth, I have been consistent about this and will stay consistent. Semrush and Ahrefs are ahead of DataForSEO, which I said plainly in my [DataForSEO review](/dataforseo-review/). DataForSEO's keyword volumes arrive in Google Ads buckets, while the suites blend clickstream data on top. So the trade is not "same thing, cheaper." It is a much narrower thing, much cheaper, with real work handed back to you. ### **One Publishes Every Price. The Other Will Not Tell You.** There is a difference between these two companies that has nothing to do with features, and it surprised me while checking figures for this post. DataForSEO publishes a per-request price for every endpoint it sells, on public pages, with no login. Every figure I quoted above is one you can check in a browser right now. Semrush does not publish what an API unit costs. That gap, and the plan confusion underneath it, is the whole subject of my breakdown of [Semrush API pricing](/semrush-api-pricing/). *The word is Price, and the unit is API units. Semrush tells you exactly how many a report costs, and nowhere public what one is worth. Verified on developer.semrush.com, August 22, 2026.* Its [developer documentation](https://developer.semrush.com/api/basics/get-started/) explains units thoroughly. How they are consumed, how to check your balance, what happens when you run out, even a parameter for limiting rows to spend fewer of them. What it never states is a price. The docs go as far as telling you how many units each report consumes, ten per line for live data and fifty for historical, then route you to sales for a quote. The balance page sits behind a login. What I can verify is the access rule. [Semrush's MCP page](https://www.semrush.com/mcp/) states that MCP access is included in Semrush One and SEO Classic plans and is also available for API users. For a marketer trying to budget an agent workflow before committing, that gap is the finding. On one side you can model your monthly spend to the cent before you deposit anything. On the other you cannot model it at all until you are already a customer. ### **The Third Option Nobody Puts on the Comparison Table** There is a path that is neither tool, and it showed up in Google's AI Overview for this query, which is how I found it. People are building Semrush-shaped interfaces on top of DataForSEO data. The most serious is [OpenSEO](https://github.com/every-app/open-seo), an MIT-licensed project covering keyword research, rank tracking, backlinks, site audits and AI visibility, hosted at $10 a month. It is worth watching and not worth betting a client on yet, because it is **pre-1.0 at version 0.1.9** with roughly 95 percent of its commits from one maintainer. The hosted plan resells DataForSEO data at a 28% markup, and self-hosting means supplying your own DataForSEO key and clearing that $50 minimum underneath it. I priced what the hosted layer adds in my [OpenSEO review](/openseo-review/). It ranked fourth in my roundup of the [best SEO MCP servers](/best-seo-mcp-servers/), and that placement still reads right to me. ### **Four Ways This Actually Goes** Do the audit first, then pick. List the parts of the bundle you opened in the last thirty days, and next to each one write what it would cost you in time or money to replace it. Frequency alone is the wrong test. One position-tracking report that goes to a client every month can justify the whole subscription, and three tools you clicked once can justify nothing. **Keep the full suite, unchanged, if anything on that list would be genuinely painful to rebuild, or if anyone besides you logs in.** The bundle is doing its job, and per-request pricing does not pay you back for work you now have to do yourself. **Downgrade a tier if the list is short and everything on it sits in a cheaper plan.** Semrush now runs four tiers, so the gap between $549 and $199 is a real lever, and this is the outcome most people in this position actually need. **Keep the suite and add DataForSEO if you are running volume work that your plan meters, such as SERP checks across a roster of client sites.** A $50 balance is cheap next to upgrading a tier to buy headroom, and the two do not conflict. **Leave, and accept the losses, only if your month is almost entirely keyword volume and live SERP research, you work in Claude or a similar assistant already, and nobody else needs a login.** That reader exists and I am one of them for my own site, but they are rarer than the switching posts imply. What should not decide it is a monthly price sitting next to a per-request price, because those two numbers are not measuring the same purchase. ### **What I Would Tell a Friend Over Coffee** The reason this comparison keeps getting written badly is that it flatters the reader. Cancel the expensive thing, buy the cheap thing, feel clever. The real answer is duller and more useful. Plenty of people paying $199 a month would be just as well served at $139, and the fix is a plan audit rather than a migration. DataForSEO is genuinely excellent at the slice it sells, and I use it daily because live SERP and AI search data at those prices beats paying a subscription for the same pulls. That is a narrow endorsement, deliberately. If you cannot name what you used your Semrush plan for this month, you have a bundle problem. Buying an API is one way to solve it. Dropping a tier is the way almost nobody writes a post about, and it is usually the right one. ### **DataForSEO vs Semrush FAQs** #### **Can I use DataForSEO instead of Semrush?** For one part of Semrush, yes. DataForSEO covers keyword volume, live SERP data, backlinks as raw rows and AI search surfaces, billed per request. It does not replace position tracking, site audits, keyword gap analysis, paid search research, local listings, client reporting or the interface itself. If those are why you subscribe, this is not a swap. #### **Does Semrush have an MCP server?** Yes. Semrush's MCP page states that access is included in Semrush One and SEO Classic plans and is also available for API users, with documented setup for ChatGPT, Claude, Claude Code, Gemini, Perplexity, Cursor and VS Code. On the current pricing page, MCP access is listed starting at the Starter plan at $199 a month, not on the $139 SEO plan. #### **How much does Semrush cost per month?** Verified on semrush.com/pricing, the monthly rates are $139 for SEO, $199 for Starter, $299 for Pro+ and $549 for Advanced. Annual billing brings those to $117.33, $165.17, $248.17 and $455.67 per month. Posts still quoting Pro at $139.95 and Guru at $249.95 are using legacy SEO Toolkit names, which Semrush maps to Starter and Pro+. #### **What is the best alternative to Semrush?** It depends which part of Semrush you are replacing. For raw search data at volume, DataForSEO is far cheaper per request. For an all-in-one dashboard, Ahrefs is the closest like-for-like. For your own site's traffic and impressions, Google Search Console is free and reports your actual numbers rather than an estimate of them. For a cheap open source interface, OpenSEO is worth watching while it is pre-1.0. #### **Is Semrush owned by Adobe?** Yes. Adobe announced the deal in November 2025 and completed it on April 28, 2026, all-cash and valued at roughly $1.9 billion. Semrush was delisted from the New York Stock Exchange and now runs as an Adobe subsidiary, with site branding reading "An Adobe Company." Semrush says contracts, features and billing are unchanged for now, and nothing specific has been announced about the API or MCP server. #### **Who are the competitors of Semrush?** Ahrefs and Moz are the direct suite competitors, with SE Ranking and Mangools sitting below them on price. DataForSEO competes on only one dimension of the product, selling the underlying search data per request rather than an interface. Serper and SerpApi compete on live SERP data specifically, and I broke down [what each of those actually charges per thousand](/dataforseo-alternatives/). Google Search Console overlaps for free on your own properties. Methodology and disclosure: every figure in this post was verified against primary sources, specifically semrush.com/pricing rendered in a browser with the toggle state confirmed, semrush.com/mcp, developer.semrush.com, DataForSEO's per-endpoint rate card pages and dataforseo.com/pricing, plus the GitHub API for the OpenSEO repository figures and Adobe's newsroom and Semrush's SEC filing for the acquisition. The $1.9 billion figure comes from the November 2025 announcement rather than the April 2026 completion release. Semrush API unit pricing is not published on any public page I could find, and I have not stated a figure for it. I am a DataForSEO affiliate and earn a commission if you sign up through my link. I am not a Semrush affiliate, earn nothing if you buy Semrush, and do not currently pay for a Semrush seat, so the Semrush assessment here is based on its published pricing, documentation and feature set rather than on current daily use. I also sell an AI SEO product, which is a competing interest you should weigh. Prices and plan structures change often, as this post documents. [Full disclosure](/disclosure/). --- ## BabyLoveGrowth Review: Does the $99 AI SEO Agent Work? URL: https://ryandoser.com/babylovegrowth-review/ Markdown: https://ryandoser.com/babylovegrowth-review.md Published: 2026-08-18 | Updated: 2026-09-30 Categories: AI Tool Reviews > BabyLoveGrowth costs $99/month to auto-publish 30 articles and trade backlinks. Its refund terms, review data and real rankings, checked before you subscribe. BabyLoveGrowth sells a feature its own homepage describes like this: *"Our agent identifies the Reddit and Quora posts that LLMs learn from, then suggests comments that naturally mention your brand."* That is a real feature, sold on the pricing page as a "Reddit AI agent for brand mentions in key communities," and the reasoning behind it is sound. Reddit carries unusual weight in both Google results and AI answers, so being named there genuinely does influence whether an assistant recommends you. Whether you want that done automatically, on your behalf, in communities that mostly prohibit undisclosed promotion, is a separate question and one you should answer deliberately rather than by accident. If the appeal is knowing where you are being talked about rather than planting the mentions yourself, a monitoring tool does that job honestly. I covered the one I rate in my [Alertmouse review](/alertmouse-review/). This **BabyLoveGrowth review** covers that feature, but it is not the thing I would most want you to know before paying. That turns out to be a mismatch between the refund the site advertises and the refund its contract actually gives you, and I get to it below. Before anything else, you should know where I am standing. I sell [an AI SEO System](https://seo.ryandoser.com/) that competes with this for the same budget, at $199 once instead of $99 a month. Discount me accordingly. I take no affiliate money here, which is the only reason a post like this is worth writing when the entire first page of results for this product is monetized. And the limit of what I can tell you: I have read every page of the pricing, the terms, the docs and the public review pool, but I have not run this on a client campaign. So this is a review of what the company commits to in writing and what its customers report happened. It is not a report of what it produced for me. ### **What BabyLoveGrowth Actually Does** BabyLoveGrowth is an AI SEO and GEO platform that runs your blog on auto-pilot. It analyzes your site and competitors, builds a keyword cluster and content calendar, writes articles, and publishes them straight into your CMS. WordPress, Shopify and Webflow are named on the pricing page. Around that core it stacks four things most competitors at this price do not bundle together: a **backlink exchange** across what it calls 4,000+ partner sites, **AI citation tracking** for ChatGPT, Perplexity and Gemini, a **site audit**, and the **Reddit agent** above. The company is BLG INC., listed at 835 Fifth Avenue, San Rafael CA 94901 on its own pricing page. The founder is Tilen Savnik, who signs the company's Trustpilot replies personally. *The BabyLoveGrowth homepage, captured August 18, 2026. The 90-day money-back promise appears here too.* Credit where it is due on the product surface: AI citation tracking on a $99 plan is genuinely useful, and it is the feature I would actually want. Knowing whether ChatGPT names you is the measurement most businesses are missing entirely. That part is a real answer to a real question. ### **What It Costs, Once You Strike the Anchors** These prices load with JavaScript and the page defaults to the discounted view, so a plain fetch or a cached copy will mislead you. Rendered in full on August 18, 2026, with the monthly toggle active: | Plan | Anchor price | Actual price | What you get | | Grow | $247/month | **$99/month** | 30 articles, auto-publishing, backlink exchange, AI citation tracking, site audit, Reddit agent, keyword research | | Scale | $599/month | **$299/month** | Everything in Grow, plus a dedicated SEO/GEO specialist (2 hours monthly), 3 extra languages, beta access, priority support | Yearly billing is advertised at 25% off. There is a **3-day free trial**, card required, and an advertised **90-day money-back guarantee** that its Terms of Use did not contain when I first checked. It is in there now, with conditions that get their own section below. *Captured August 18, 2026 with the Monthly toggle active. Note the "90-day money-back guarantee" badge on the Grow plan, and compare it to what the Terms of Use say below.* Two observations on that table. The $247 and $599 anchor prices are struck through next to the real ones, permanently, under a "Special offer" label. A discount that never expires is not a discount, it is the price. I would price this at $99 and $299 in your head and ignore the anchors entirely. ### **The 90-Day Guarantee Was Missing From the Binding Terms** **Update:** BabyLoveGrowth has since added the guarantee to its [Terms](https://www.babylovegrowth.ai/en/terms-and-conditions). As of September 30, 2026, Section 7 says no refunds after the 3-day trial "except under the 90-Day Money-Back Guarantee in Section 8," and Section 8 sets the conditions: it only pays out if none of organic clicks, organic impressions or Domain Rating rises over the 90 days, after at least three consecutive paid months with every article it produced published and publicly visible, not behind a login, paywall or noindex tag. That uses the looser "organic metrics" trigger I flagged below, and impressions tend to rise when you publish 30 pages a month. The rest of this section is the August 18 reading. This was the finding I most wanted you to have before you entered a card, and it took reading the actual contract to see it. The homepage advertises a **90-day money-back guarantee**, worded: *"If your organic metrics don't improve within 90 days, you get your money back."* The pricing page carries the same promise with a narrower trigger: *"If your organic traffic doesn't increase within 90 days, you get your money back."* The Terms of Use, the document you legally agree to, said this instead on August 18, verbatim: *"Due to the operational costs associated with external APIs and AI services, **we do not offer refunds after the 3-day trial period has ended.** By continuing to use the service after the trial period, you acknowledge and agree to this no-refund policy."* On August 18, the number 90 did not appear anywhere in the Terms. I searched the full document. The Terms also carved out a discretionary path, which is still there: in "exceptional cases" such as a bug or "if the service is not as advertised," you may *request a review* for a refund, which requires scheduling a call with support. That is meaningfully different from a guarantee. A guarantee is something you claim. A discretionary review is something you apply for, to the company holding your money, under terms it wrote. Two more things from that page worth knowing. The Terms are **governed by the laws of the United Kingdom**, despite the California address and "BLG INC." branding. I am not a lawyer and consumer-protection rules can override a chosen forum, so I will not tell you what that means for your rights. I will say it is worth knowing before a dispute rather than during one. And note that the two pages do not promise the same thing. The pricing page conditions the refund on "organic traffic," which is the number that matters to you. The homepage conditions it on "organic metrics," which is looser: impressions are an organic metric, and impressions tend to move when you publish 90 pages whether or not a single person visits. If you ever needed to claim this, which sentence the company pointed at would matter. I am not calling this fraud, and there is a plausible innocent explanation: marketing pages and legal pages drift apart at fast-moving startups, and the Terms are dated December 2024. But the mismatch was live on the site that day, it ran in the company's favor, and the version that bound you was the one promising three days rather than ninety. Compare it to [Outrank](/outrank-review/), whose seven-day refund window is at least stated identically in its marketing and its contract. ### **The 4.6, the Missing Reviews, and Trustpilot's Flag** **Update:** Trustpilot has since suspended BabyLoveGrowth's rating. As of September 30, 2026, its profile reads "This company's rating is unavailable due to a breach of our guidelines," with a banner stating "This company has been offering incentives for reviews." Everything below is the August 18 snapshot, taken before that flag appeared, and should be read with it in mind. On August 18, BabyLoveGrowth held a **4.6 TrustScore across 203 reviews**, 191 of them in the last twelve months. That was a strong number and I am not going to explain it away. It also looked, on Trustpilot's own data at the time, **unsolicited**. I checked the transparency tab rather than assuming: all 191 recent reviews were recorded as organic, with zero collected through invitations, automatic prompts, or redirects. On that data it looked like a 4.6 the company had earned. Trustpilot's later incentive flag is exactly the kind of thing that transparency tab cannot show. Then I looked at the reporting statistics on the same page, and this is the part nobody else has reported. BabyLoveGrowth has **filed 21 reports against reviews on its own profile**. Broken down by star rating, those reports were: **17 one-star, 1 two-star, 1 three-star, and zero four- or five-star**. Every review it challenged was a critical one. The outcome: **10 reviews were taken offline**, and **9 of the company's reports were ruled invalid by Trustpilot** and the reviews reinstated. Let me be careful about what that does and does not mean. Reporting reviews is a legitimate tool, companies do get fake and abusive reviews, and 10 of those removals happened because the reviewer never responded to Trustpilot's verification request, which can happen to genuine customers and fraudsters alike. This is not proof of anything improper. But the shape is worth seeing clearly. A 4.6 that looked unsolicited reads very differently once you know that 19 negative reviews were formally challenged, that nearly half those challenges were judged invalid, and that ten critical reviews are no longer on the page you are reading. Outrank, for comparison, filed 3 reports total. **Read how a review pool was maintained, not just how it was assembled.** One number genuinely in BabyLoveGrowth's favor. In August it had **13 negative reviews** live, and it had replied to **76.9%** of them, averaging 5.7 days. Outrank had replied to 17.4% of its negative reviews and had stopped replying entirely for seven months. Somebody at BabyLoveGrowth was answering unhappy customers, and that counts. ### **What the Negative Reviews Say, and How the Company Answers** Thirteen negative reviews is a small pool, so treat this as signal rather than verdict. The complaints cluster on two things: content quality and backlinks that do not arrive. On content: *"Their daily blogs are garbage. It would take me every day to edit them into something meaningful and relevant. No sign of back links, not even one."* A three-star reviewer, the most useful review in the pool because he is neither angry nor delighted, described a specific mechanical failure: he added about 30 researched keywords, they vanished from the tool, support could not explain where they went across two weeks, and *"it just writes random stuff with no important keywords."* He also noted the internal linking chose *"old urls that are not even showing on the web site and have no content to them."* On backlinks: *"you get literally 1 backlink a month haha, like that's going to help you rank anything... with 10 backlinks a year at this rate."* The company's public reply states that *"on average, each website gets quality 6+ backlinks a month,"* which is a useful number to have on record and one you can hold them to. Now, the pattern in the replies. To four separate negative reviewers, the founder responded that he could not find their account: *"I wasnt able to locate your account in our database."* *"I am not able to locate any account under this name."* *"there is no account linked to Garry Walker."* There is a mundane explanation worth putting first. Trustpilot display names frequently do not match billing names, so a founder searching by display name would genuinely fail to find real customers. That is the likeliest reading, and I am not going to imply otherwise. But notice the effect regardless of intent. A public reply saying "this person is not in our database" reads to every future shopper as a suggestion the complaint is not from a real customer, while asking the reviewer to email privately moves the resolution somewhere nobody else can see. Used four times on four different critics, that becomes a pattern worth naming even when each individual instance is innocent. ### **The Incentivized-Review Allegation** **Update:** Trustpilot has since flagged this profile for incentivized reviews. As of September 30, 2026, the profile carries the banner "This company has been offering incentives for reviews" and its rating is withheld for a breach of guidelines. Trustpilot does not say what the incentive was, so the reviewer's specific claim that it was backlink credits is still unverified. One reviewer made a specific and serious claim: *"most of these reviews on this site are not honest as they give you credits which is against trust pilots policy (which you cant even spend or use) for backlinks to give a good rating."* He is alleging customers were given backlink credits in exchange for positive reviews. I want to handle this precisely, because it is exactly the kind of claim that gets repeated carelessly. On August 18 I wrote this: **I could not verify it, and there was evidence against it.** Trustpilot's own data field for this profile recorded `hasCollectedIncentivisedReviews: false` at the time, and Trustpilot flags profiles where it detects incentivization. One anonymous reviewer's assertion was not proof, so I reported it as an allegation rather than a finding. I include it for one reason: it is in the public pool that shapes this product's reputation, it is the sort of thing a buyer should be able to weigh, and the responsible thing was to show you both the claim and the evidence as it stood, rather than either amplifying it or hiding it. Trustpilot's later flag is why the update above matters. ### **The Reddit Strategy Is the Real Story** BabyLoveGrowth's Reddit agent is sold as a feature. The homepage says it identifies Reddit and Quora posts "that LLMs learn from," then suggests comments that "naturally mention your brand." The pricing page lists it as "Reddit AI agent for brand mentions in key communities." The underlying theory is correct, and I want to give it that. Reddit is weighted heavily in both AI answers and Google results, and third-party mentions genuinely do influence whether a model names you. I have run [my own tests on how much those mentions actually move AI citations](/how-to-manipulate-ai-search/), so this is not a mechanic I dismiss. The company was open about using it. In February 2025 the founder posted a thread titled *"I grew BLG in 3 weeks to $850 MRR using only Reddit,"* which still surfaces in Google's results today. A founder promoting his own product on Reddit is ordinary startup behavior, and I am not accusing this company of running fake accounts. I found no evidence that it does. What changes the calculation is selling it as a service. A founder talking about his product in public is participating. An agent generating brand mentions across communities on behalf of paying customers is manufacturing the third-party signal that AI models mistake for consensus, in communities that mostly ban undisclosed promotion. **There are only two ways to be present in the sources AI assistants read, and they age in opposite directions.** You can earn the mentions, by publishing things people cite and by being genuinely useful somewhere public. Or you can generate them. Both work today. Only one of them gets safer over time. Generated mentions are a bet that detection stays where it is. Every incentive at Reddit, Google and the model labs points the other way, because a platform whose recommendations are gameable at $99 a month is a platform with a corroded product. When that detection improves, earned mentions keep compounding and generated ones become a cleanup project on a domain you cannot swap out. That asymmetry is the whole argument, and it applies to every tool in this category rather than just this one. The practical version for a business owner: if a tactic would embarrass you when the community it targets finds out, it is a rental, not an asset. Price it accordingly. ### **The Link Exchange Problem** The exchange is where I would spend your attention, because unlike a wasted subscription it can cost you an asset you cannot re-buy. The backlink exchange trades links across a partner network. Google's spam policies name the mechanic directly, listing as link spam: *"Excessive link exchanges ('Link to me and I'll link to you') or partner pages exclusively for the sake of cross-linking."* That is Google's own wording, not my characterization, and a network where members' sites link to each other is that pattern by construction. The company's framing is that these are real contextual links inside relevant articles on relevant sites, which is a meaningful distinction in quality but not one that changes the reciprocal structure underneath. The content half meets a second policy. Google defines *"scaled content abuse"* as *"when many pages are generated for the primary purpose of manipulating search rankings and not helping users,"* naming *"using generative AI tools or other similar tools to generate many pages without adding value for users."* The word doing the work in that definition is *value*, not *AI*. Nothing in the policy prohibits machine-written pages, and I publish AI-assisted content on the site you are reading. What it targets is publishing at a scale nobody is curating, which means the article count is not the variable that decides your exposure. Whether a person is deciding each page deserves to exist is. ### **Does It Work on Its Own Site?** This is the test I apply to every tool in this category, and BabyLoveGrowth passes it better than most. Its own pages rank. Its pricing page shows up on page one for its brand-review query, its LinkedIn presence is active, and its case studies name real founders at real companies with specific figures: DR 12 to DR 32, 620 to 14K organic reach, 1.4M impressions. Named customers with checkable companies are a materially stronger form of evidence than anonymous testimonials, and several of these are more specific than what most competitors publish. The honest caveat is what those case studies measure. The headline metrics are overwhelmingly Domain Rating, impressions and traffic. Domain Rating is an Ahrefs score Google does not use, and it responds directly to acquiring links, which is what a link exchange does. Impressions are the metric that inflates most easily and convert least reliably. Almost none of the case studies lead with revenue or qualified leads. Then I ran the tool's own domain through a rank check rather than taking the case studies on faith, and this is where it gets awkward. BabyLoveGrowth's site publishes roughly 4,800 URLs across six language versions, the same pages mass-translated into French, Dutch, German, Spanish and Portuguese. That is the product's own strategy applied to itself at full volume. The return on those 4,800 pages, per a DataForSEO rank pull I ran on August 18, 2026, is **694 ranking keywords** in the US. For comparison, that is a smaller keyword footprint than plenty of single-author blogs with 100 posts. What it ranks for is the more interesting part. Setting aside its own brand name, its best-performing pages are: *"4p in marketing example"* at position 4, *"student blog template"* at position 6, *"how long is an article"* at position 5, and *"seo for electricians"* at position 13. Its single biggest listing is a page for *"search google or type a url"*, sitting at position 28. In the top 25 keywords by traffic value, **exactly one** is a commercial term for the category it sells into: "auto seo platform," at position 8, with 390 monthly searches. So the machine produces pages that rank for student blog templates and the four Ps of marketing, not for the buyers of AI SEO software. That is the actual output profile, measured on the one site where the tool has unlimited budget, full control, and every incentive to prove itself. No case study can tell you as much, because no case study is selected by anyone other than the vendor. ### **The Three Questions That Decide It** Rather than a list of buyer types, here are the three questions whose answers actually determine whether this is a good purchase for you. Answer them honestly and the decision makes itself. **Question one: who is reading the articles before they publish?** If the answer is nobody, stop here. Auto-publishing unreviewed pages to your domain while pointing exchange links at it is the configuration that collides with both of the Google policies quoted above at the same time. If the answer is "me, every one of them," the picture changes completely, and at $99 for 30 drafts with real CMS publishing this is fairly priced as a pipeline. **Question two: can you afford to be wrong about the links?** This is the question about your domain rather than your budget. A throwaway project, a niche site you could abandon, a brand you have not built anything on yet: the downside is small and the upside is real. The business whose domain carries ten years of equity and whose leads come through search: that is a different bet entirely, and the exchange is the part I would leave switched off. **Question three: is your real bottleneck volume, or is it knowing what to publish?** Volume is a solvable problem and this tool solves it. Judgment is not, and a machine producing 30 articles a month multiplies whatever judgment you bring to it, including none. One genuine recommendation that cuts across all three. If you do buy in, **the $299 Scale tier is the more interesting purchase than the $99 one**, because it includes two hours a month with an actual SEO specialist. That is the only part of this product that cannot be commoditized, and two hours of a competent human looking at your specific site is worth more than 30 additional articles nobody reads. The one thing I would not buy at any tier is the Reddit agent. Automated brand mentions in communities that explicitly ban undisclosed promotion is a moderation risk stacked on a reputational one, and a tactic that only works until the platforms notice is not a strategy you can build on. ### **The Part Where I Am Selling Something** Everything below is my pitch. Read it that way. BabyLoveGrowth's underlying premise is one I agree with completely: if you want AI assistants to recommend you, you have to exist in the sources those assistants read. That is not marketing spin, it is how retrieval works, and most businesses still have no plan for it. My disagreement is the durability point I made above: the generated version of that presence is a rental with an expiry date, and the earned version compounds. The data backs the earned side. In Linkifi's three-week study of ChatGPT's sources, 7 in 10 of the sources cited on day one were still being cited three weeks later once day-to-day noise was removed, which I cover in [what Linkifi's study says about ChatGPT's steady sources](/how-to-get-chatgpt-to-recommend-your-business/). I have run the earned version on my own property rather than a client's, which is the only reason I will put numbers next to it. Starting from nothing in February 2026, no backlinks and no history, six months produced 5.77K clicks and 890K impressions in Search Console, 12.1K AI citations logged in Bing Webmaster Tools, and north of $100K in revenue. Not one link came from an exchange and not one comment was automated. The charts are on the [consulting page](/ai-seo-consulting/) if you want to audit them. What I sell is that process rather than a subscription that performs it for you. The [AI SEO System](https://seo.ryandoser.com/) is $199 paid once, it drives the AI tools already on your bill, and the reason I think it beats renting this category is unglamorous: you still have it next year whether or not you are still paying me. When someone would rather I just look at their site and rank the fixes, [that is the consulting session](/ai-seo-consulting/). Wider context lives in my [best AI SEO tools](/best-ai-seo-tools/) roundup and my [AI SEO strategy](/ai-seo-strategy/) breakdown. ### **My Verdict on BabyLoveGrowth** BabyLoveGrowth is the better-run of the two $99 auto-publishing tools I have looked at this month. The support answers, the case studies name real people, and the AI citation tracking is a genuinely good inclusion at this price. It is also built on two mechanics Google's documentation describes as spam, and it sells automated brand-mention seeding as a feature. Both of those are true at the same time, and neither cancels the other. So the question is not whether the company is competent. It is whether you want your domain's long-term equity riding on link exchanges and manufactured mentions to save time you could spend learning what to publish. For a throwaway project, the math might work. For the business you intend to still own in three years, I would not take that trade, and I would not advise a client to. And if you do subscribe, make your decision inside the first three days. The contract now includes the 90-day guarantee, but it only pays out if none of organic clicks, organic impressions or Domain Rating rises over the 90 days, after at least three consecutive paid months with every article it produced published and publicly visible, not behind a login, paywall or noindex tag, so treat the three-day trial as your real exit. ### **BabyLoveGrowth Review FAQs** #### **How much does BabyLoveGrowth cost?** BabyLoveGrowth costs **$99 per month** for Grow and **$299 per month** for Scale, shown against permanent struck-through anchors of $247 and $599. Grow covers 30 auto-published articles, a backlink exchange, AI citation tracking and the Reddit agent; Scale adds two hours a month with a human SEO specialist. There is a 3-day trial with a card required. The Terms now include the advertised 90-day money-back guarantee, but it only pays out if none of organic clicks, organic impressions or Domain Rating rises over the 90 days, after at least three consecutive paid months with every article it produced published and publicly visible, not behind a login, paywall or noindex tag. Prices verified on a full render of babylovegrowth.ai/en/pricing, August 18, 2026; Terms rechecked September 30, 2026. #### **Is BabyLoveGrowth legit?** Yes, in the sense that matters most narrowly: it is a real company (BLG INC., San Rafael, California) with a working product, 209 Trustpilot reviews (though Trustpilot has suspended its rating for offering incentives for reviews), named case-study customers, and a founder who answers complaints publicly under his own name. It replied to roughly 77% of its negative reviews when I checked in August, which is high for this category. Legitimate as a business is a separate question from safe for your site, though, and its backlink exchange and auto-published content both map onto practices Google's spam policies name directly. #### **Is BabyLoveGrowth's backlink exchange safe?** It carries real risk. Google's spam policies explicitly list "excessive link exchanges ('Link to me and I'll link to you') or partner pages exclusively for the sake of cross-linking" as link spam, and a partner network that trades links between member sites is that structure by design. The company frames its placements as real contextual links inside relevant articles, which is a genuine quality distinction but does not change the reciprocal mechanic. Separately, several reviewers report receiving far fewer links than expected, with the company publicly stating an average of "6+ backlinks a month" per site. #### **What is the BabyLoveGrowth Reddit agent?** It is a feature that, in the company's own words on its homepage, "identifies the Reddit and Quora posts that LLMs learn from, then suggests comments that naturally mention your brand." The pricing page lists it as "Reddit AI agent for brand mentions in key communities." The underlying theory is sound, since Reddit is weighted heavily in both AI answers and Google results, but automating brand mentions into communities whose rules prohibit undisclosed promotion carries moderation and reputational risk that sits on you rather than on the vendor. #### **BabyLoveGrowth vs Outrank: which is better?** They are near-identical products at $99 a month for 30 auto-published articles plus a link exchange, and the differences are operational rather than functional. On reviews the picture has changed: Trustpilot has suspended BabyLoveGrowth's rating for offering incentives for reviews, while Outrank holds 3.7 across 87. BabyLoveGrowth still replied to 77% of negative reviews against Outrank's 17% when I checked in August, and it names its case-study customers. On refunds, BabyLoveGrowth's 90-day guarantee is now in its Terms but pays out only if none of organic clicks, impressions or Domain Rating grows, and only after three paid months with every article published and publicly visible, while Outrank's 7-day window is stated the same way in its marketing and its contract. Outrank offers a REST API and CLI for coding agents, broader CMS integrations, and cheaper multi-site volume discounts. Read my full [Outrank review](/outrank-review/) for the billing complaints that shape that comparison, or the [wider field of tools doing this job](/outrank-alternatives/) if neither convinces you. Both rest on the same two mechanics Google names as spam, so the honest answer is that the choice between them matters less than the choice of whether to run this playbook at all. #### **What is the best BabyLoveGrowth alternative?** It depends what you are missing. If you want drafting and publishing, the category is crowded and largely interchangeable, and I compare the options in my [best AI SEO tools](/best-ai-seo-tools/) roundup alongside [Rankability](/rankability-review/) and [Adaptify](/adaptify-seo-review/). If what you actually lack is knowing which pages to write and how to earn AI citations without buying links, no subscription supplies that, which is why my [AI SEO System](https://seo.ryandoser.com/) teaches the process instead of running it for you, at $199 paid once. Swapping one link exchange for another is not an alternative, it is the same bet with a different logo. *How I sourced this: pricing, guarantee, feature and company details were read off full JavaScript renders of babylovegrowth.ai on August 18, 2026, since those pages load their prices with JavaScript. Trustpilot ratings, review counts, review text, verification sources and reply statistics were pulled from the live Trustpilot profile the same day. The suspended rating, incentive banner and 209-review count were read from the same profile on September 30, 2026, when the Terms were also rechecked. Google policy language is quoted verbatim from Google Search Central's spam policies documentation. Ranking-keyword and URL counts come from a DataForSEO pull run on August 18, 2026. Reddit blocks automated access, so the Reddit section relies only on the founder's own public thread and on the company's own published description of its Reddit feature. I am not a BabyLoveGrowth affiliate and earn nothing if you buy it. I sell a competing AI SEO product, which is disclosed at the top of this post. [Full disclosure](/disclosure/).* --- ## 7 Opus Clip Alternatives and What They Cost Monthly URL: https://ryandoser.com/opus-clip-alternatives/ Markdown: https://ryandoser.com/opus-clip-alternatives.md Published: 2026-08-18 | Updated: 2026-09-04 Categories: AI Tool Reviews > Seven Opus Clip alternatives priced on monthly billing, not the annual rate most vendors show first, plus the add-on that doubles one tool's price. Search **Opus Clip alternatives** and almost everything on page one is published by a company selling you one. When I ran it on August 18, 2026, I counted six vendor pages telling you to switch to them, two roundups that rank themselves first, and one Reddit thread. Results move around, but that shape is the reason this keyword is hard to research. Here is what none of them will tell you: I quit Opus Clip for about a year and hired a human editor instead. I said so on a live call with my community back in June, before I had any reason to be diplomatic about it. "I've just found that a human editor is still better in most cases than what Opus Clip can provide. There's just better human touches in short form with the editing, the b-roll, the clips, the transitions, that Opus Clip still hasn't mastered yet." I came back in late July, and only because it shipped an MCP server that lets Claude Code drive the whole thing. That round trip, out for a year and back for one specific reason, is the useful part of this post. My conflicts before anything else. [Blotato](https://www.blotato.com/?ref=rdoser) handles publishing in my setup, it is a client of mine, my account there is comped, and its links here are affiliate links. Nothing else in this post is affiliated, and I pay for Opus Clip myself. ### **Where My Knowledge Stops** One boundary, stated plainly, because it changes how you should read the rankings. **Opus Clip is the only tool in this post I have run on my own videos.** I have not put Klap, Vizard, Descript, Riverside, CapCut, Submagic or Quso through a real workload. So what follows is pricing and positioning analysis, plus the questions I would ask having been burned by metering once. Where I say a tool suits someone, that is a read of its design rather than a report from using it. What I do bring is a year of watching this bill from both sides. I publish through an agent rather than a dashboard, and I have seen what a clipping subscription does over months instead of during a trial. That means the questions I ask are not the ones a review site asks. Not "does it have nice captions," but: what does this tool count against me, does the number on the pricing page assume I paid for a year up front, and what does the bill do the month I actually use it hard. ### **The Annual-Price Trick That Breaks Every Comparison** One thing has to come before the tools, because it is what makes most roundups on this keyword wrong. Of the eight pricing pages I opened for this post, **four default to annual billing and print the annual rate with a "/month" label next to it.** Opus Clip, Klap, Riverside and Submagic all load that way. Vizard, Descript and Quso show both, and CapCut's would not load at all. Klap is the clearest case. Land on its pricing page and you see $14 a month for 100 clips. Click Monthly and the same plan is **$29**. The advertised number is barely half the real month-to-month cost. *Klap with the Monthly toggle selected. The $14 you see on arrival is the annual rate.* So every figure below is the **monthly-billing rate**, taken from each vendor's live pricing page with the toggle switched. Where annual is meaningfully cheaper I say so in that tool's entry. The sanity check that survives everything: an annual per-month price must be lower than the monthly one. If a comparison you are reading has them the other way round, it has them backwards. Watch for entitlements moving too, because Quso doubles your credits on annual, so its two columns are not the same product at two prices. ### **Opus Clip Alternatives at a Glance** Read the metering column before the price column. It is the one that decides your bill. | Tool | Monthly entry | Annual per month | What it counts | Free tier | Best for | | Opus Clip | $15 Starter, $29 Pro | $14.50 Pro | Credits, 1 per source minute | Yes, 60 credits, watermarked | Agent-driven clipping over MCP | | Klap | $29 | $14 | Finished clips | No | Predicting cost from clip count | | Vizard | $29 | $14.50 | Credits, 1 per minute | Yes, 60 credits, full editor | Testing AI clipping for free | | Descript | $24 Hobbyist | $16 | Media hours, 10 per month | Yes, 1 hour | Editing, not clip selection | | Riverside | $35 Pro | $24 | Flat, clips uncapped | 14-day trial | Recording remote interviews | | Submagic | $19, plus $19 clips add-on | $12, plus $12 | Videos per month, add-on covers 10 long | No, 3 free videos | Caption-led short-form | | Quso | $29 Lite | $19 | Credits, 1 per minute | Yes, 75 credits | Clipping plus publishing | Three different units sit in that table, which is the actual difficulty here. A tool counting finished clips and a tool counting source minutes cannot be compared on price alone, because feeding in a two-hour episode moves one bill and not the other. CapCut is missing from the table on purpose. Its pricing page would not resolve for me on the day I checked, so rather than quote a figure I could not read myself, I have kept its entry below to what its free tier does. ### **What Changed on Opus Clip This Month** Two things moved since the first version of this post in early August, and one of them is a correction to my own earlier reporting. When I first published it, [Opus Clip's pricing page](https://www.opus.pro/pricing) marked the MCP connector as Business-only while its API docs said Pro. I called the pricing page wrong, because one authenticated call on my $29 Pro account returned API access and loaded the full tool catalog. **They have since fixed the page.** The live comparison table now shows the MCP connector, Video Editing API and Scheduler API as included on Pro, which matches what my account actually does. *The API and integration rows on Opus Clip's own comparison table. MCP connector now carries a checkmark under Pro.* *Opus Clip on the Monthly toggle. Pro is $29 with 300 credits, not the $14.50 the page shows on arrival.* The second change is the one that costs money. **Pro now includes 300 credits a month.** Credits and API calls are metered separately, and the distinction matters if you drive this with an agent. Your plan credits pay for clipping. The API has its own monthly cap on top: 900 credits per workspace per calendar month on the Pro Beta and Max tiers, and Opus Clip returns a 403 rather than a 429 when you hit it, specifically so agent frameworks do not sit there retrying. I checked my own account while writing this. It reported 40 of 900 API credits used, 860 remaining, resetting September 1, with a concurrency limit of 10 in-flight projects. One note on plan names, because the two surfaces still disagree. Opus Clip's API docs reference "Pro Beta" and "Max" plans that do not appear anywhere on the public pricing page. My Pro account has working API access, so I read Pro and Pro Beta as the same thing, and that is an inference from behavior rather than something either page states. Read calls like identity and usage checks burn no credits. If you are ever stuck on a vendor's contradictory entitlement docs, one read call settles in seconds what an hour of documentation archaeology will not. ### **Why I Went Looking in the First Place** Clipping quality was part of it, as the quote above says. The thing that actually pushed me out was the review tax. Every batch meant opening the dashboard, watching each short, judging whether it was any good, and rewriting headlines one at a time. That is not a small chore when you publish weekly. My editor handed back finished clips instead, so the trip was hard to justify. Then there is clip selection. These tools find moments that look like highlights: a raised voice, a pause before a punchline, a sentence that scans as quotable. The moment that actually matters to my audience is often quiet and sits in the middle of an explanation. I watched this happen on a real job. I fed in a 27-minute podcast episode, and the clip Opus Clip ranked highest, a 99 virality score, was one I rejected outright because it framed the guest badly. The ones I kept scored 88, 86, 94, 93 and 98. The scoring is directionally useful and it is not judgment. *The five clips I kept from a 27-minute episode, pulled into Claude Code with their scores and captions. The tool generated 29.* Third is b-roll and transitions, and nothing I have seen in this category has convincingly closed that gap. A human editor cutting to the exact screen recording I was describing is worth more than any virality score. Clipping is only one job anyway. I run a separate pipeline to [turn the same long video into a blog post](/claude-code-repurpose-youtube-videos/), and that one an agent handles end to end. Fourth is credit math, and it is worth understanding precisely, because most roundups get it backwards. On that same podcast job I asked for 5 clips and got 29. That did not cost me extra credits. Opus Clip charges one credit per minute of the source video you import, so a 27-minute episode costs about 27 credits whether it hands back five clips or twenty-nine. I documented the whole run in my [OpusClip MCP walkthrough](/opusclip-mcp/). What the extra 24 clips cost was my attention, which is the more expensive resource. That is the review tax arriving in a different form. The practical consequence is that your bill tracks how much video you feed in, not how much you get out. Trim the source before you upload rather than asking for fewer clips. ### **The 7 Opus Clip Alternatives Worth Testing** Ordered by the situation each one fits, with the qualifying condition attached so you can tell in one line whether it is you. #### **1. Klap (Best for Knowing Your Bill Before You Upload)** [Klap](https://klap.app/pricing) is the closest direct substitute and the one I would test first if Opus Clip's output annoyed you. It counts finished clips rather than source minutes, which is the easiest metering model in this post to reason about. **Pros:** - Counts finished clips, so source length does not drive the bill as long as you keep the clip count the same - Unlimited connected social accounts on every plan, including the cheapest - Clip allowances are generous at the top end, 1,000 a month on Pro+ **Cons:** - No free tier at all, which makes it the only tool here you cannot try before paying - The API is billed separately per operation, so agent use is not covered by your plan **Best for:** Anyone who uploads long source video and wants the bill to track output rather than runtime. **Pricing:** Monthly $29 Basic (100 clips), $79 Pro (300), $189 Pro+ (1,000). Annual drops those to $14, $39 and $94. **Free trial:** No. There is no free plan and no trial, so testing it costs $29. **Bottom line:** If you upload long podcasts, clip-based counting usually beats minute-based, and Klap is the cleanest version of it. It does publish a [REST API](https://docs.klap.app/), billed per operation at $0.32 to generate a short and $0.48 to export, so an agent can drive it, just on a separate meter from your subscription. #### **2. Vizard (Best Free Tier in the Category)** *Vizard's free plan gives you the full editor, which is unusual at zero dollars.* [Vizard](https://vizard.ai/pricing) has the most usable free plan in this group, and the reason is that it does not cripple the editor to get you to upgrade. **Pros:** - Free plan includes full editor access, not a preview mode - 60 free credits a month covers an hour of uploaded video - Credit model is legible, one credit equals one minute of video **Cons:** - Free exports carry a watermark and cap at 720p - Free storage expires after 3 days, so download what you keep - Free tier connects only one social account **Best for:** Finding out whether AI clipping suits your content before spending anything. **Pricing:** Free (60 credits), then $29/month Creator and $39 Business on monthly billing. Annual is $14.50 and $19.50, and Creator starts at 600 credits a month. **Free trial:** Not needed. The free plan is permanent rather than a countdown. **Bottom line:** Start here if you have never run an AI clipper, because an hour of free upload answers the question for you. Move on if you need 4K or want to keep files longer than three days, both of which are paid. #### **3. Descript (Best If Your Problem Is Editing, Not Selection)** *Descript meters media hours rather than clips, which suits editing work rather than batch clipping.* [Descript](https://www.descript.com/pricing) is a different category of tool and it is the honest answer for a lot of people who think they want a clipper. You edit video by editing a transcript. **Pros:** - Transcript-based editing is built to beat a timeline for talking-head content - Real editor features, including filler-word removal and Studio Sound - Free plan gives you an hour of media a month to try the workflow **Cons:** - Media hours are tight, 10 a month on the entry paid plan - It will not batch-select clips as aggressively as a dedicated clipper - Priced per person, so a small team multiplies the cost **Best for:** The person whose bottleneck is "I need to edit this and I am slow at it." **Pricing:** Monthly $24 Hobbyist (10 media hours), $35 Creator (30 hours), $65 Business (40 hours). Annual is $16, $24 and $50. **Free trial:** A free plan with 1 media hour a month, watermark-free export not included. **Bottom line:** Buy Descript when the job is editing and buy a clipper when the job is finding moments. Those are different products, and picking the wrong category is the most common mistake I see on this keyword. #### **4. Riverside (Best If You Record Remote Interviews)** *Riverside on monthly billing. Magic Clips is included on every tier and consumes no AI credits.* [Riverside](https://riverside.com/pricing) earns a spot for one structural reason: it records and clips in the same place, so there is no export-and-reupload round trip. **Pros:** - Records and clips in one tool, removing an entire handoff - Magic Clips is included on every paid tier and burns no AI credits - Records up to 4K locally, so clip quality does not depend on the call **Cons:** - The highest plan entry price here at $35, beaten only by Submagic once you add its clipping add-on - The pricing page leads with paid plans and a 14-day trial rather than a free tier - Pointless if you do not record remotely, since clipping alone will not justify it **Best for:** Podcasters running remote guests who want recording and clipping under one login. **Pricing:** Monthly $35 Pro, $45 Grow, $99 Webinar, Business by quote. Annual is $24, $34 and $79. **Free trial:** 14 days on every plan. The pricing page presents Pro as the entry point rather than a free tier, so budget for the subscription. **Bottom line:** Worth it when the recording and the clipping are the same job, because you are buying a workflow rather than a feature. If you upload files recorded elsewhere, you are paying for a recording studio you are not using. #### **5. Submagic (Best for Captions, Once You Read the Add-On)** *The clipping feature is an add-on. Submagic's real cost is the plan plus $19, not the plan alone.* [Submagic](https://www.submagic.co/pricing) is on four of the eight pages ranking for this keyword and in both AI Overviews I pulled, so it belongs here even though I have not run it. It is caption-led rather than selection-led. One detail I found only by reading the plan cards properly, and no roundup I checked mentions it. **Magic Clips, the feature that turns a long video into shorts, is a paid add-on at $19 a month on every single tier.** The add-on carries its own allowance of 10 long videos a month, separate from the plan's short-video count. So Submagic as an Opus Clip alternative is not $19. The cheapest configuration that actually does long-to-short clipping is $38 a member, which puts it above Opus Clip Pro rather than below it. **Pros:** - Captions are the thing it is actually built for, and no watermark on any paid plan - API access is included from the entry tier, at 10 minutes a month - Storyblocks b-roll and audio bundled from the Pro tier up **Cons:** - The clipping feature costs an extra $19 per member per month on every plan - Base video length caps are strict, 2 minutes on Starter and 5 on Pro - Priced per member, and the add-on is per member too **Best for:** Creators whose real need is polished animated captions, with clipping as a secondary job. **Pricing:** Monthly $19 Starter (15 videos), $39 Pro (40 videos), $69 Business (100 videos). Annual is $12, $23 and $41. Magic Clips adds $19 monthly or $12 annual per member and covers 10 long videos a month. **Free trial:** 3 free videos, no card required. That is a trial rather than a standing free tier. **Bottom line:** Price it as plan plus add-on or you will underestimate the entry tier by half. Judged that way it competes on caption quality rather than on price, which is a fairer fight for it than the sticker suggests. #### **6. Quso (Best for Clipping and Publishing in One Bill)** *Quso doubles your credits on annual billing rather than only cutting the price.* [Quso](https://quso.ai/pricing), formerly vidyo.ai, bundles AI clipping with a scheduler and social publisher, so clips go out without a second tool. If you would rather keep those jobs separate, the distribution half is its own category, and I priced one of the better-known options in my [Repurpose.io review](/repurpose-io-review/) and its [seven closest competitors](/repurpose-io-alternatives/). Its annual structure is unusual enough to flag. Paying yearly cuts the price by about a third **and doubles the monthly credits**, where every other tool here only discounts the price. **Pros:** - Free plan includes 75 credits a month, the largest free allowance in this post - Publishing is built in, so there is no download-and-reupload step - Annual billing doubles credits rather than only discounting **Cons:** - Free tier publishes to TikTok only and holds data for 7 days - Free renders cap at 720p - If you already run a scheduler, adding this one points two tools at the same accounts **Best for:** Solo creators who want one login and one bill covering clip and post. **Pricing:** Free (75 credits), then monthly $29 Lite, $39 Essential, $49 Growth. Annual is $19, $26 and $33, with credits doubled. **Free trial:** Not needed. The free plan is permanent, though limited to one platform. **Bottom line:** The consolidation is real if publishing is currently a manual step for you. I split these jobs myself for a reason I explain below, though that is my setup rather than a fault in the tool. #### **7. CapCut (Best When the Honest Answer Is "Do It Yourself")** [CapCut](https://www.capcut.com/) has a genuinely free editing tier with no AI credit meter on it, and it is what a large share of short-form creators actually use. You pick the moments yourself. A caveat on this entry specifically. CapCut's pricing page would not load for me on the day I checked, so I am not quoting its paid tiers, and you should confirm them yourself before buying. What I can say is that the free editor exists and does not meter clipping. **Pros:** - Free editing with no per-clip credit meter - You choose the moments, so there is no pass spent judging what an AI picked - Enormous template and effect library **Cons:** - Manual selection costs you time that the paid tools spend for you - Some Pro-marked templates and effects apply a watermark on free exports - Nothing to automate, so an agent cannot touch it **Best for:** Anyone publishing two or three clips a week who would rather spend an hour than $29. It is also the natural fit if you shoot raw and unpolished, which is how I [keep a posting habit alive by recording on walks](/post-consistently-with-ai/). **Pricing:** Free tier confirmed. Paid tiers not verified here, see the caveat above. **Free trial:** The free tier is the trial, and it is permanent. **Bottom line:** For low volume the math genuinely favors this. Automation is worth paying for at volume, and below that volume it is a tax. One outside data point on hit rate: an affiliate marketer I share a mastermind with runs Opus Clip at roughly 50 clips generated for about 10 usable, with a human yes or no pass on every one. That is one person's experience next to mine rather than a category benchmark, but both point the same way. Budget for a review pass whichever tool you pick. ### **What I Actually Run, and Why It Is Split** *This section mentions a tool I have an affiliate relationship with and that is also a client.* Here is my real setup, stated plainly because it is the part every vendor roundup leaves out. In my setup Opus Clip renders and nothing else. It never touches publishing. That split is deliberate rather than forced. Opus Clip ships perfectly good scheduling and posting tools, and I leave them switched off, because two schedulers pointed at the same accounts is how you end up double-posting. It is the same tradeoff I flagged on Quso above. Blotato holds my account connections, so it owns distribution. The full pipeline, from long video to a month of scheduled posts, is written up in my [AI social media system](/ai-social-media-system/). The MCP fixed the exact thing that made me quit. An agent now does the review pass I used to do by hand, which is why a tool I had written off is back in my rotation. Two things it still gets wrong. On my podcast episode the captions sat at the bottom and covered my guest's mouth, so for two-person footage you want them centered. It also missed a shade of blue I thought was in my brand guide. Build your brand template first, by hand, in the web editor. There is no tool to create one over MCP, only to list what exists. Skip that step and everything renders on the stock preset, which is the green and yellow caption style you have seen on thousands of shorts. One more thing I only learned by running this on a schedule rather than testing it once. Rendering is asynchronous, and the gap between submitting a video and having clips back is long enough that an agent will happily declare victory before anything exists. My first working version did exactly that. It reported a successful run, and the folder was empty, because the job was still processing when the conversation ended. If you wire this up yourself, make the agent poll for completion and confirm the clips came back before it moves on. That is the difference between a demo that works once and a pipeline you can leave alone on a Monday. I still pay a human editor for long-form and for any short that has to land. That is a decision against automation, made by someone who automates most of his workflow. Update, October 2026: long-form flipped. Claude Code skills now cut my podcast episodes and build the intro, and my editor keeps the shorts, so here is [what happened when AI edited a full episode](/ai-video-editing/). ### **Three Questions That Narrow This to One Tool** These are the questions I work through rather than a pick-for-me list, because the right answer genuinely changes by person. **How many clips a month?** These are my rough thresholds rather than a formula, and they assume you value an hour of your own time at more than a few dollars. Under about ten clips, manual selection in CapCut is usually the cheaper trade. Above thirty, a subscription pays for itself even at a mediocre hit rate. **What does the tool count, and does that match how you upload?** Long source video favors clip counting, which is Klap. Short source video favors minute-based credits, which is Vizard, Quso or Opus Clip. Getting this backwards is the expensive mistake. **Does an agent need to drive it?** Opus Clip is the only tool here with an MCP server, and it works on the $29 Pro plan with no separate API bill. Klap and Submagic both expose APIs, but Klap meters its per operation and Submagic allots API minutes by tier, so check what agent use adds before you assume it is included. It is worth reading which [MCP servers actually earn a place in a marketing stack](/mcp-servers-for-marketers/) before you commit. One more worth asking before you pay: are you buying selection or editing? Selection problems point to Opus Clip, Klap or Vizard. Editing problems point to Descript. ### **What About Munch and Ssemble?** Both come up on this keyword and neither is ranked above, because I have not run either one. [Munch](https://www.munchstudio.com/) shows up in AI answers for this query more than its footprint suggests it should, and it is worth knowing it has moved on since those answers were trained. It now sells itself as Munch Studio, an AI that runs your whole social presence from your website rather than a clipper you feed a long video to. [Ssemble](https://www.ssemble.com/) ranks page one with its own roundup and is a browser-based editor with a clipping layer on top. Each is worth your own look. To be straight about the criterion, since I have not run any of the seven above either: the ranked list is the set that both shows up repeatedly on this query and publishes a rate card clear enough to price honestly. Munch no longer sells the job this post is about, and Ssemble I simply have not looked at closely enough to place. ### **The Honest Read After a Year Away** The automated end of this category has converged. The dedicated clippers here all find faces, add captions and reframe to vertical, and most attach some flavor of virality score. What still separates them is the billing unit, the free tier, and whether an agent can reach the thing at your price. That last one is why clipping ended up inside my wider [set of content creation tools](/best-ai-tools-for-content-creators/) rather than sitting off on its own. My read: AI clipping is a genuine time-saver on the first pass and is still not a replacement for an editor on anything that represents you. I quit the category for a year over exactly that, and I came back only when an agent could absorb the review work I did not want to do. Start with Vizard's free tier, because an hour of upload costs nothing and answers the question. If clipping earns a place in your week, compare Klap and Opus Clip on the metering model that matches how you upload. And if you publish a few clips a week, seriously consider that CapCut and an hour of your attention beats all of it. Every price here came from the vendor's own pricing page with monthly billing selected. I have run Opus Clip on my own videos and priced the other six from their live rate cards without putting them through a real workload. CapCut is the one entry with no verified price, and I have flagged that where it appears. Treat every comparison page on this keyword, mine included, as an argument rather than a finding. Open the pricing pages yourself, switch them to monthly, and you will already know more than most of page one. ### **Opus Clip Alternatives FAQs** #### **What is the best free Opus Clip alternative?** Vizard has the most usable free plan: 60 credits a month covering an hour of upload, with full editor access, capped at 720p and 3-day storage. Quso's free plan gives more credits at 75 a month but publishes only to TikTok. CapCut is free with no AI meter at all if you are willing to pick the clips yourself. #### **Is Klap cheaper than Opus Clip?** Not on equal terms. Klap's advertised $14 for 100 clips is the annual rate, and its real monthly price is $29, the same as Opus Clip Pro. They also meter differently: Klap counts finished clips while Opus Clip counts source minutes as credits. Price both on the same billing period, then pick by which unit matches how you upload. #### **Does Opus Clip have an API or MCP server?** Yes, and it works on the $29 Pro plan. Opus Clip's pricing page now lists the MCP connector, Video Editing API and Scheduler API as included on Pro, which matches what my own Pro account does. The hosted server sits at mcp.opus.pro/mcp, uses OAuth rather than an API key, and exposes 29 tools. API usage is capped separately from plan credits at 900 credits per workspace per month. #### **How much does Opus Clip cost per month?** On monthly billing, Starter is $15 and Pro is $29 with 300 credits a month, plus a free plan with 60 credits and a watermark. Annual billing drops Pro to $14.50 a month, billed $174 up front. The pricing page loads on the annual toggle, so the first number you see is not the month-to-month rate. #### **Can AI clipping replace a video editor?** Not yet, in my experience. These tools handle selection, captions, and vertical reframing well. They still do not deliver relevant b-roll, considered transitions, or reliable judgment about which section carries the idea. I use AI clipping for speed and still pay an editor for anything that has to land. #### **Which Opus Clip alternative is best for podcasts?** Riverside if you record remote interviews, because recording and clipping happen in one place and you skip the upload step entirely. Klap if you upload long episodes recorded elsewhere, since counting finished clips means a two-hour episode costs no more than a short one. Descript if your episodes need real editing rather than clip extraction. Opus Clip is the only one of those I have run on my own podcast, so read the other two as a reading of their pricing and design rather than a field report. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine and my account there is comped rather than paid. Links to Opus Clip, Klap, Vizard, Descript, Riverside, Submagic, Quso, CapCut, Munch and Ssemble are not affiliate links, and I pay for Opus Clip myself. Opus Clip is the only tool here I have run on my own videos. The other six are priced and assessed from their live rate cards and documentation, which I have said plainly at the top of the post and in the closing section rather than burying here. [Full disclosure](/disclosure/).* --- ## Outrank.so Review: Is the $99 Backlink Exchange Worth the Risk? URL: https://ryandoser.com/outrank-review/ Markdown: https://ryandoser.com/outrank-review.md Published: 2026-08-18 | Updated: 2026-09-30 Categories: AI Tool Reviews > Outrank.so costs $99/month for 30 auto-published articles and a backlink exchange. What its own terms, Trustpilot data and llms.txt reveal before you buy. Outrank tells AI assistants that it is **"Rated 4.8/5 by users."** That sentence lives in a file called llms.txt, which is a plain-text summary a company publishes at its own web address for AI models rather than for people. It is the cheat sheet ChatGPT or Claude may read when someone asks them about the product. Its actual Trustpilot score, pulled from the live profile the same day in August, was **3.4 out of 5**. It has since risen to 3.7. That was a 1.4-point gap. At today's 3.7 it is still 1.1 points, not a rounding error, and where it sits is what makes it worth your attention. An llms.txt file is a brief a company writes for AI assistants rather than for people. Adoption of the format is still uneven and there is [no evidence it earns anyone AI citations](/ai-search-myths/), but the intent behind the file is not ambiguous: it exists to shape how answer engines describe the product. On a tool whose entire pitch is getting *you* cited by those engines, the number it feeds them about itself is a fair thing to check first. Two things about my position, up front. I sell a competing product, [my AI SEO System](https://seo.ryandoser.com/), which is $199 once rather than $99 a month, so weigh what follows accordingly. I earn nothing if you buy Outrank and I am not an affiliate, which is also why I can be blunt about it. And I have read Outrank's pricing page, terms, docs and its full public review pool closely, but I have not run it on a client site for a full campaign. I can tell you what it commits to in writing and what its customers report. I cannot tell you what it produced for me, and I will not pretend otherwise. ### **What Outrank Actually Is** Outrank is an AI SEO platform that publishes for you. You connect a site, it researches keywords, writes articles, generates images, and pushes finished posts into your CMS on a schedule without you touching them. The integration list is genuinely broad: WordPress, WordPress.com, Webflow, Shopify, Wix, Framer, Notion, Ghost, Next.js, and a custom webhook. It publishes real posts into your site rather than rendering changes through a JavaScript layer, which is the architecturally correct call and a real point in its favor. There is also a REST API and an official CLI (`npm install -g outrank-cli`) so coding agents can drive it programmatically. For the kind of reader who already runs SEO through Claude Code, that is the most interesting thing on the feature list. The other half of the product is the **Backlink Exchange**. It is a credit-based network: you earn credits by hosting links to other members' sites, and you spend credits to get links pointed at yours. Hold that thought, because it is the part of this product that carries the real risk, and I will come back to it. The company is Outrank SAS, registered in Paris, France (SIREN 988 048 575), per the footer on its own pricing page. *The Outrank homepage. The pitch is auto-pilot: you connect a site and it publishes without you.* ### **Outrank Pricing, Verified** Outrank's pricing page renders with JavaScript, so I pulled a full render rather than trusting a cached copy. As of August 18, 2026, there is exactly one plan. | Item | Price | What it covers | | All-in-One Plan | $99/month or $999/year | 30 articles/month, unlimited keyword research, backlink exchange access, AI images, unlimited users, all integrations | | 60 articles/month | +$85/month | Add-on, doubles output for one site | | 90 articles/month | +$160/month | Add-on, triples output for one site | | Human Curated Service | $1,399/month | Human editors review and fact-check every article | | Backlink Premium | $199/month | Extra backlink credits | | Backlink Enterprise | $899/month | High-volume backlink credits | | Free Tools Builder | $199/month | One interactive SEO tool per week | | Premium Images | $49/month | Better image model | | Directory Submission | $500 one-time | Submission to 100+ directories | Annual billing at $999 saves $189 against monthly. Volume discounts apply automatically: 10% off for 2 to 4 sites, 15% for 5 to 19, and 20% for 20 to 25. *Outrank's pricing page, captured August 18, 2026. Note the permanent struck-through $200 anchor beside the $99 price.* Two things on that table deserve a flag. The first is the **$1,399 Human Curated Service**. That is the add-on where "professional human editors review, fact-check, and polish every article before publication." Read that next to the base product and the implication is hard to miss: fact-checking is not what the $99 plan does. It is a fourteen-hundred-dollar upgrade. For a tool publishing 30 articles a month to your domain under your name, that is the single most important line on the pricing page. The second is that the base plan is genuinely cheap for what it does mechanically, and I am not going to pretend $99 for 30 published articles is a bad deal on volume alone. It is not. The question is whether volume is the thing you actually need, and I will get to that. ### **The Trustpilot Distribution Is the Story** **Update:** As of September 30, 2026, the profile reads 3.7 across 87 reviews, 81 of them from the past twelve months, and Trustpilot still notes that Outrank has no recent history of inviting reviews. The breakdown below is the August 18 snapshot. On August 18, Outrank held a **3.4 TrustScore across 71 reviews**, 70 of them in the last twelve months. That number alone undersold what was happening underneath it. I pulled the profile's underlying data rather than eyeballing the page. Of the 20 most recent reviews at the time, **13 were one star and 7 were five star**. There was nothing in the middle. Trustpilot's own count put 23 negative reviews in the pool overall. Then I checked how those reviews arrived, and this is the part that gives the number its weight. Trustpilot publishes a transparency breakdown for every profile. For Outrank, all 70 reviews in the past twelve months came in **organically**: zero invited, zero automatic, zero redirected. Trustpilot states outright that it has no recent record of Outrank asking customers for reviews. That matters more than it sounds. Most vendor ratings you read are inflated by solicitation, because a company sending review requests to its happiest customers reliably lifts its average. Outrank is not doing that. **The 3.4 is what people said when nobody prompted them**, which makes it a more honest signal than most scores in this category, and a worse one for Outrank. One more number from the same profile data, as it stood on August 18, 2026. Outrank had replied to **17.4% of its negative reviews**, with an average reply time of 10.5 days, and its most recent reply to a negative review was logged in January 2026. That leaves seven months of one-star reviews after it with no public response. ### **What the One-Star Reviews Are Actually About** I read the negative pool rather than only counting it, because the count tells you nothing about the failure mode. The complaints are strikingly uniform, and almost none of them are about SEO quality. They are about billing and cancellation. Here is the pattern, in customers' own words: *"I tried to cancel my subscription months ago, but there is no way to cancel from within the website. I emailed support multiple times requesting cancellation and received no response."* *"Charged me $99 after I tried to cancel before the trial ended. There is no cancel button in the app. The Stripe billing portal doesn't show one either."* *"They lure you into a trial, then there is no support, no help, no nothing. They charge you $99 every month without you knowing, only the bank notification."* *"I have been charged by this company for approximately six months, despite never knowingly using their services."* Now put that beside what Outrank's own pricing page says, in bold type, directly under the price: **"Cancel anytime. No questions asked!"** Those two things cannot both be true, and I want to be careful about what I am claiming. I have not tried to cancel an Outrank subscription myself, so I cannot tell you from firsthand experience that the button is missing. What I can tell you is that multiple unrelated customers, across several months, independently describe the same specific mechanic: no self-service cancellation, and support that does not answer. That is a consistent enough signal to take seriously before you hand over a card. ### **The Refund Policy Is Real, and It Is Documented** This is worth knowing precisely, because one reviewer quoted it correctly and said it was not honored. Outrank's Terms of Use, section 8.3, states verbatim: *"First-time subscribers may request a full refund within seven (7) calendar days of the initial subscription payment by emailing support@outrank.so. Refunds are limited to one per customer and will be issued to the original payment method. After the 7-day period, all sales are final and non-refundable."* So the policy exists and it is clear. A customer wrote that he was charged $99 on July 3rd, emailed support the same day citing exactly that clause, emailed again on July 7, and had received nothing over a week later "from a company that advertises 24/7 support on every page." I cannot verify any individual customer's account of what support did or did not do. What I can verify is the policy text, the date it was quoted, and that the complaint matches the written terms rather than misreading them. If you buy this, that seven-day window is the entire safety net, and you should treat it as a hard deadline rather than a courtesy. ### **The DR Challenge and Its Missing Refund Process** Outrank runs a public promotion at outrank.so/dr-challenge headlined **"+10 DR in 60 days or your money back."** The page states one hard qualifier, that your site must start under DR 30, alongside the steps it expects: run Outrank for 60 days, let it auto-post, and keep backlink generation on. A customer reported following the program for the full 60 days, not getting the 10-point Domain Rating increase, requesting the refund under the stated terms, and receiving neither the refund nor an explanation. *The DR Challenge page. The guarantee and its conditions are here; a process for actually claiming the refund is not.* Here is what I can verify independently, and it is the part that matters. I rendered that challenge page in full. It states the guarantee and the qualifying terms, and it contains **no refund claim process whatsoever**. There is no form, no deadline, no named contact, no description of what evidence you submit or who adjudicates whether your DR moved. A guarantee with qualifying conditions but no documented mechanism for claiming it puts the entire burden on the customer to chase a company whose review pool is dominated by people saying support does not reply. That is not an accusation of bad faith. It is a structural observation about a promise, and it is checkable by anyone who opens the page. ### **The Backlink Exchange Is the Real Risk** This is where I stop talking about billing and start talking about your site, because this is the part that can cost you something you cannot refund. The Backlink Exchange works exactly as it sounds. You host links to other members' sites to earn credits, then spend those credits to receive links back. Outrank claims 25,000+ backlinks added across the network. Google's spam policies name this directly. Under "Link spam," the documentation lists as a violation: *"Excessive link exchanges ('Link to me and I'll link to you') or partner pages exclusively for the sake of cross-linking."* That is not my interpretation, and it is not a gray area someone is reading uncharitably. It is the mechanic the product is built on, described almost word for word in Google's own published policy. The r/SaaS thread about this tool, which held the number one organic result for this query when I pulled the SERP on August 18, 2026, lands in the same place. Google's own snippet of it reads: *"The articles are okay, but the backlink exchange is pretty bad. You are getting backlinks from low-authority websites, which look like spam."* Notice what the Outrank success stories lead with. Of the six featured on its success-stories page, the headline results are framed around Domain Rating rather than revenue, qualified leads, or even organic traffic. "DR 15 to DR 25 in 4 weeks." "Domain authority from 13 to 36 in four months." Domain Rating is an Ahrefs metric. Google does not use it. You can move it reliably by acquiring links, which is precisely what an exchange network does, and you can move it without moving a single thing that pays you. So the headline result this product advertises is a third-party score that responds directly to the mechanic Google names as link spam. That is the sentence I would want someone to read to me before I connected this to a domain I cared about. ### **Read Section 7 of the Terms Before You Turn Links On** Everything above is inference from Google's policy. This next part is Outrank's own contract, and it is the most important thing in this review. In plain English, before I quote any of it: **Outrank publishes links to your website without showing them to you first, and you agree in advance that if Google punishes your site for those links, the loss is yours and Outrank owes you nothing.** Both halves of that are written down. Section 7.2 says that when you activate a backlink package, Outrank's system *"automatically creates and publishes the agreed-upon links,"* and that *"no manual preview or approval step is provided."* No sample, no queue, no approval screen. It also means the reviewer who reported finding a competitor's link inside an article on his own site was describing something the contract expressly allows. Section 7.3 handles the consequences: *"Search engines set and update their own rules. They may reduce visibility or penalize sites they believe use links in ways that violate those rules. By choosing to use the Backlink Exchange you accept that risk and agree to indemnify and hold us harmless from any related penalties, losses, or liabilities."* Read that twice. Outrank has written into its terms that its link product may get you penalized, and that if it does, **you** carry the loss and agree to hold Outrank harmless. To be fair, section 7.4 says the company monitors industry guidelines and refines its placement systems to align with best practices, and indemnity clauses of this shape are standard legal hygiene rather than an admission of guilt. But note who is holding which end. The vendor takes $99 a month, publishes links to your domain without showing them to you first, and has you sign away recourse if Google reacts. That is a clean transfer of the entire downside onto the customer, and it is in writing on their own site. ### **The Second Google Policy Problem** There is a second exposure, and it applies to the content half of the product. Google's spam policies define *"scaled content abuse"* as *"when many pages are generated for the primary purpose of manipulating search rankings and not helping users,"* and specifically name *"using generative AI tools or other similar tools to generate many pages without adding value for users."* I broke down [where that line actually falls in practice](/google-ai-search-guidelines-exposed/) separately. Read that carefully, because the distinction is the whole game and most people get it backwards. **Google's policy does not say AI content is banned.** It says pages generated at scale without adding value are. Volume is not the violation. Valuelessness is. I want to be fair here: 30 articles a month is not automatically scaled content abuse, and I publish AI-assisted content myself on the site you are reading. The trigger is publishing pages that add nothing, which is a function of what goes into them and who checks them, not of how they were drafted. Which brings you back to that $1,399 line item. The version of Outrank where a human fact-checks every article costs $1,498 a month all in. The $99 version publishes 30 unchecked articles to your domain. Those are two genuinely different products with two genuinely different risk profiles, and the pricing page is honest about which is which if you read it closely. ### **Does It Work on Outrank's Own Site?** This is the test I apply to every tool in this category, because a company selling automated SEO has unlimited budget, full control and every incentive to prove the method on itself. It is the most honest demo available. Outrank passes the first half. Its domain ranks for **2,477 keywords** in the US, per a DataForSEO rank pull I ran on August 18, 2026, which is a real footprint and more than most tools in this price band manage. The method demonstrably produces pages that rank. What those pages rank *for* is the part worth your attention. Sorted by traffic value, the top results are: - *"search google or type a url"* at position 5, which alone accounts for the overwhelming bulk of the site's organic traffic - *"search engines other than google"* and *"google alternatives"* at positions 8 to 10 - *"blog entry examples for students"* at position 1 - *"googlebot login"* at position 42 These are informational browser-and-homework queries. A person searching "search google or type a url" is trying to fix their address bar. A person searching "blog entry examples for students" is doing an assignment. Neither is buying SEO software, and the traffic is concentrated in essentially one page. I want to be fair about what this proves. It proves the content ranks, which is a genuine result and more than many competitors can show. It does not prove the content reaches anyone who buys anything, and on the site where the tool is best resourced, the commercial keywords are largely absent from the top of the list. There is a tell worth noting on top of that. [BabyLoveGrowth](/babylovegrowth-review/), a completely separate $99 competitor I looked at the same week, ranks for an overlapping set of the same filler terms, including student blog examples and article-length queries. When two rival tools independently converge on the same low-commercial-intent topics, that is the shape of the underlying keyword strategy showing through, not a coincidence. ### **What Outrank Genuinely Does Well** The critique only means something if the credit is honest first, so here is the credit. The integration coverage is real and broad, and direct CMS publishing is the right architecture. The API and CLI are a legitimately good idea that most competitors in this price band do not offer. Unlimited users on a $99 plan is generous when rivals charge per seat. Article generation in 150+ languages is a real capability. And the seven-day refund policy, whatever the disputes about honoring it, is written down clearly rather than buried. The five-star reviews are not empty either. One reads: *"I have been really happy with my first few weeks of using outrank. The quality of the blogs it produces are really good. I go through and check everything."* Read that last sentence again, because it is the most useful line in the entire positive pool. **"I go through and check everything."** The happiest reviewer in the set is describing a workflow where a human reviews every article before it goes live. That is the correct way to use this category of tool, and it is the opposite of the auto-pilot the marketing sells. ### **Who Should Actually Buy Outrank** **Buy it if you will treat it as a drafting engine and edit everything.** At $99 for 30 drafts with CMS publishing and an API, it is priced fairly as a content pipeline. Turn the backlink exchange off, review every article, and you have a reasonable tool. That is not how it is marketed, but it is how the satisfied customers describe using it. **Do not buy it if you are turning on auto-pilot and walking away.** The default configuration publishes unreviewed AI articles to your domain and points exchange links at it, which lines up with two separately named Google spam policies at once. If nobody is reading the output, you are not saving time. You are accumulating a liability on an asset you own. **Do not buy it if you cannot afford a billing fight.** I am not going to soften this. The most common complaint in the public record is that cancellation is hard and support does not answer, and Outrank has replied to under a fifth of its negative reviews with a seven-month gap in responses. If that would be a genuine problem for you, use a virtual card with a hard limit or skip it. **Do not buy it if what you actually lack is judgment.** This is the honest one. If you cannot tell whether an article is worth publishing, a tool that publishes 30 of them a month is not solving your problem, it is scaling it. ### **The $99 Question Nobody Frames Correctly** My bias is loudest here, so discount it accordingly. The debate about tools like this usually gets framed as cheap software versus expensive agency. That framing is wrong, and it is why people buy the wrong thing. Outrank sells two products bundled at one price. The first is a content pipeline: research, drafting, images, CMS publishing on a schedule. That is real engineering and $99 is fair for it. The second is a link scheme, and it is not priced at all, because its cost is contingent. It is zero if Google never reacts and it is your domain if Google does. You cannot evaluate a bundle where one component has an unpriced tail risk by comparing its monthly fee to anything. The pipeline half is also the half that has changed most in the last year. Drafting and publishing on a schedule is now something an AI assistant does directly when you give it a defined process. What no tool sells you, at $99 or $499, is the judgment about which pages are worth publishing, and that is the part that actually determines whether any of this works. I can be concrete about that because I tested it on my own domain rather than a client's. This site started at zero in February 2026 with no backlinks and no domain history. Six months later it had 5.77K clicks and 890K impressions in Google Search Console, 12.1K AI citations tracked in Bing Webmaster Tools, and over $100K in attributable revenue. No exchange network and no partner links, which matters here specifically because it means the growth is not resting on the mechanic this post spends 2,000 words warning you about. The charts are on my [AI SEO consulting page](/ai-seo-consulting/) if you want to check them. I turned that process into [an AI SEO System](https://seo.ryandoser.com/), at $199 once, and the structural argument for it over a subscription is simple: it runs on AI tools you already pay for, and you keep it when you stop paying me. If you would rather someone just look at your site and tell you what to fix first, [a consulting session](/ai-seo-consulting/) does that instead. ### **The Ten-Minute Audit You Can Run on Any AI SEO Tool** Everything in this review came from six checks that took less time than a demo call, and none of them required a subscription. Tools in this category launch constantly, so the method is worth more to you than the verdict on this particular one. Run these before you enter a card anywhere. - **Read their llms.txt against reality.** Try `vendor.com/llms.txt`. It is the file they write for AI models, so it is where the most flattering version of their numbers lives. Compare any rating it claims to the live review profile. - **Read the Terms, not the sales page.** Search the terms for "refund," "cancel," and "indemnify." Where the marketing page and the contract disagree, the contract is the one you signed. - **Check Trustpilot's transparency tab, not just the score.** It is at `trustpilot.com/review//transparency` and it shows whether reviews arrived organically or by invitation, how many reviews the company has reported, and how many of those reports were ruled invalid. - **Ask whether a guarantee has a claim process.** A promise with qualifying conditions but no stated deadline, form, or contact is a marketing asset, not a warranty. - **Rank-check the vendor's own domain.** They have unlimited budget and full control, so their own site is the most honest demo of their product. Look at what it actually ranks for, not how much. - **Match the link mechanic against Google's spam policy wording.** If the product description and the policy describe the same thing in nearly the same words, that is your answer regardless of how the vendor frames it. Applied to [BabyLoveGrowth](/babylovegrowth-review/), the same six checks surfaced a different and arguably worse problem, which is a decent sign the method travels. ### **My Verdict on Outrank** Outrank is a competent publishing pipeline attached to a link scheme that Google's documentation describes as spam, sold alongside a self-published rating, in the file it hands to AI models, that is 1.1 points above its actual one. Each of those three things is verifiable in about ten minutes, and I would rather hand you the method than the verdict. Open outrank.so/llms.txt and read the rating it claims. Open the Trustpilot profile and read the real one. Open Google's spam policy page and read the link exchange line. Then decide. If you buy it, use it as a draft generator, edit every article, leave the exchange off, put a calendar reminder on day six of the refund window, and pay with a card you can cap. That is the version of this product I would not argue with. ### **Outrank.so Review FAQs** #### **How much does Outrank.so cost?** Outrank costs **$99 per month or $999 per year** on a single All-in-One Plan covering 30 auto-published articles, unlimited keyword research, backlink exchange access, unlimited users and all CMS integrations. The add-on worth knowing about is the Human Curated Service at **$1,399 per month**, which is where human fact-checking of your articles lives. Volume discounts run 10% to 20% for multiple sites. Verified on a full render of outrank.so/pricing, August 18, 2026. #### **Is Outrank.so legit?** Outrank is a real company, Outrank SAS, registered in Paris, France under SIREN 988 048 575, with a working product and paying customers. Legitimate as a business is not the same as safe for your site. Its Trustpilot score is 3.7 across 87 reviews, its backlink exchange matches the practice Google's spam policies name as "excessive link exchanges," and the most common complaint in its public review pool is that self-service cancellation does not exist. Treat it as a real product with real risks rather than as a scam or as a safe default. #### **What is Outrank.so's actual Trustpilot rating?** 3.7 out of 5 across 87 reviews as of September 30, 2026, up from 3.4 across 71 on August 18. Both are materially lower than the "Rated 4.8/5 by users" claim Outrank publishes in its own llms.txt file, which is the file AI assistants read when asked about the product. On August 18, the 20 most recent reviews were 13 one-star and 7 five-star with nothing in between, and Trustpilot recorded all 70 recent reviews as organic, with zero collected by invitation. Trustpilot still states it has no recent record of Outrank asking customers for reviews. #### **Is Outrank's backlink exchange safe for SEO?** It carries real risk. Google's spam policies explicitly list "excessive link exchanges ('Link to me and I'll link to you') or partner pages exclusively for the sake of cross-linking" as link spam, and a credit-based network where you host links to earn links is that mechanic by design. Customers on Reddit and Trustpilot independently describe the resulting links as coming from low-authority sites that "look like spam." Note also that of the six customer stories featured on its success-stories page, the headline results are framed around Domain Rating, an Ahrefs metric Google does not use, which responds to link acquisition without necessarily reflecting traffic or revenue. #### **Can I cancel Outrank.so anytime?** Outrank's pricing page states "Cancel anytime. No questions asked!" Multiple recent Trustpilot reviewers dispute this in specific terms, independently reporting no cancellation option inside the app or the Stripe billing portal and unanswered support emails, with several describing continued charges afterward. Separately, the written Terms of Use section 8.3 gives first-time subscribers a full refund within seven calendar days of the initial payment by emailing support, limited to one per customer, after which all sales are final. If you subscribe, treat that seven-day window as a hard deadline. #### **What is the best alternative to Outrank.so?** It depends which half you need. If you want a drafting and publishing pipeline, most tools in this band do the same job, and I compare them in my [best AI SEO tools](/best-ai-seo-tools/) roundup alongside [Rankability](/rankability-review/) and [Adaptify](/adaptify-seo-review/), and I priced [seven auto-publishers against Outrank](/outrank-alternatives/) from their live rate cards. If what you are missing is knowing which pages to write and how to get cited by AI assistants, that is a skill rather than a subscription, and it is what I packaged into my [AI SEO System](https://seo.ryandoser.com/) for a one-time $199. What I would not do is replace a link exchange with a different link exchange. *How I sourced this: pricing, terms, llms.txt, success-story and DR Challenge figures were read off full JavaScript renders of outrank.so on August 18, 2026. Trustpilot ratings, review counts, review text, verification sources and reply statistics were pulled from the live Trustpilot profile the same day. Google policy language is quoted verbatim from Google Search Central's spam policies documentation. G2 blocks automated access, so third-party claims of a G2 rating for this product are not verified here. I am not an Outrank affiliate and earn nothing if you buy it. I sell a competing AI SEO product, which is disclosed at the top of this post. [Full disclosure](/disclosure/).* --- ## Adaptify SEO Review: What $499/Month Actually Buys You URL: https://ryandoser.com/adaptify-seo-review/ Markdown: https://ryandoser.com/adaptify-seo-review.md Published: 2026-08-14 | Updated: 2026-09-30 Categories: AI Tool Reviews > Adaptify SEO costs $499 a month. Here is what that buys, what its own pricing page and 89 Trustpilot reviews reveal, and the measurement nobody has published. Every **Adaptify SEO review** on page one of Google is either the vendor, a review aggregator, or a company Adaptify is partnered with. That is not a slight against the product. It is the most useful fact about it. Adaptify is a real platform with real customers. It holds a 4.7 out of 5 on Trustpilot across 89 reviews, and the people writing them name features, name the competitors they left, and name their customer success manager by first name. Whatever else follows, that part is genuine and I am not going to talk you out of it. But it costs $499 per month for a single site, and I could not find a single conflict-free practitioner who has publicly measured whether the content it publishes actually ranks. For a platform that says it has published 525,000 articles for more than 1,000 agencies, that gap is worth sitting with before you put a card down. Two things about my position here, up front. I sell a competing AI SEO product, so weigh what follows accordingly. And I have spent time inside Adaptify and read its documentation and public reviews closely, but I have not run it on a client site across a full campaign, which means I can tell you what it does and what it reports and not what it produced for me. Where that limit matters, I say so. ### **What Adaptify Actually Is** Adaptify sells itself as an AI visibility platform for agencies. Strip the category language off and it is a managed SEO service with a dashboard on top: you give it a keyword, and it researches, outlines, writes, adds images, runs quality checks, and publishes the finished article into your CMS without you touching it. The CMS list is genuinely broad. WordPress with Yoast, RankMath or AIOSEO, plus Squarespace, Webflow, Shopify, HubSpot CMS and Duda, with custom integrations available. It submits each new URL to the Google Indexing API on publish and runs a 30-day rolling content calendar up to 50 articles a month. One thing worth being precise about, because it separates Adaptify from other tools in this category: it publishes directly into your CMS. The article lands in your site as a real post you own. There is no JavaScript layer rendering changes on top of your pages, which is a meaningfully different architecture from how some competitors deploy, and it is a point in Adaptify's favor. The [$99 tier of this market](/outrank-alternatives/) publishes the same way for a fraction of the price, with different tradeoffs. I covered that distinction in my [roundup of the best AI SEO tools](/best-ai-seo-tools/) and will not relitigate it here. Backlinks are the other half of the product. Adaptify pitches journalists on your behalf and places guest posts, using your approved sender domain so the outreach comes from you rather than from them. *Adaptify's own description of how the links are acquired. The phrase "and guest posts" is doing more work than it appears to, as the FAQ later makes clear.* ### **The Pricing, Verified** Adaptify's pricing page is JavaScript-rendered, so it does not show up in a plain fetch. Rendered on August 14, 2026, here is what it says. | Plan | Price | Scope | | Single Site | $499 per month | 1 website, billed monthly | | Multi-Site | $333 per site | $999 per month for 3 sites, billed monthly | *Adaptify's two plans, captured from its pricing page on August 14, 2026. The prices load with JavaScript, so they do not appear in a plain page fetch.* There is no annual toggle and no discount for paying up front. Both tiers include a 7 day free trial and unlimited seats. The $333 figure is the entry rate for the multi-site tier, not a flat rate. A slider on the pricing page runs to 100 or more sites and the FAQ mentions discounts for larger agencies, so the real per-site cost drops as you scale. Those rates are not published, which means the number an agency actually pays at 50 sites is between them and a sales conversation. This pricing has held steady for roughly two years. The same $499 and $999 figures appear in a review written in September 2024. ### **What the Reviews Genuinely Praise** I want to give this its due, because the critique later only means something if the praise is honest first. Support and onboarding are the overwhelming theme. One customer success manager gets named by name in at least five separate reviews across two platforms, which is not a thing that happens to companies with bad service. Reviewers describe onboarding that actually got them running rather than a login and a documentation link. The time savings are specific and repeated. "Saves me 30+ hours per month." "What used to take me days can be done in an afternoon." For an agency owner whose real constraint is production capacity, that is the entire pitch and reviewers say it lands. Content quality comes up more positively than I expected for an automated tool. Several reviewers went in braced for generic AI output and said it exceeded that. A few praised Adaptify for a deliberately narrow scope, that it "doesn't try to be all things to all people," which is a real compliment in a category full of bloated suites. The recurring criticisms are mild and mostly about price ("It is not cheap, folks"), a learning curve, WordPress plugin setup friction, and AI-generated infographic quality. ### **Read the Review Pool Before You Read the Rating** The 4.7 is real, and it needs context that the number alone does not give you. Every review on the first page of Adaptify's Trustpilot profile carries an "invitation" verification source. That means Adaptify asked for them. Solicited reviews are a completely normal business practice and they are not fake, but a rating built from invitations tells you about the customers a company chose to ask, which is not the same population as everyone who has paid. The shape of that first page is 22 five-star reviews and one one-star, with nothing in between. Trustpilot itself adds a note to the profile that Adaptify "hasn't invited customers recently," so the solicitation appears to have happened in waves rather than continuously. Capterra and Software Advice both show 5.0 from 66 reviews, and that is not two independent sources agreeing. Both are Gartner properties drawing on one shared review pool, so it is a single dataset counted twice. Adaptify also has a G2 profile, which ranks on page one for this very query, and advertises a 5.0 G2 rating on its own about page. G2 blocks automated access, so I am reporting that rating as Adaptify states it rather than as something I read off the profile. None of that makes the product worse. It makes the rating less informative than it looks, which matters when the rating is most of what page one offers you. ### **The Reporting Gap One Customer Named Precisely** Buried in the five-star reviews is the sharpest observation anyone has made about this product, and it comes from a managing partner who had been paying for eight months and still rated it 5 out of 5: *"My only gripe about Adaptify is that the reporting and client dashboard seem to be more focused on tactics and fulfillment than results. For me, SEO results = traffic and rankings. Traffic is reported, but there isn't a section that watches and displays how your rankings are being affected over time."* That is one reviewer, not a chorus, and I am not going to inflate it into consensus. A handful of others gesture at the same area with vaguer language about wanting deeper analytics and more reporting customization, and one noted the SEO audit "lacks specific recommendations" and sometimes flags issues already fixed. What gives the observation weight is not the review count. It is that Adaptify's own product structure agrees with him. Look at what the feature matrix lists on the reporting side: white-label reporting, live monitoring, a branded client portal, custom domain. Now look at what is not on it: any line item for tracking rankings over time. The backlinks page reports its own performance the same way, in activity counts. Average 44 pitches per site per month. Average 9% placement rate. Those are all real numbers and they all measure delivery. They tell an agency how much work went out the door, which is genuinely useful information and exactly what a client wants to see itemized at the end of the month. It does report traffic, so this is not a black box. The specific gap the reviewer named is longitudinal: no view tracking how rankings move over time, which is the measurement that tells you whether the content is doing its job. So you will want a rank tracker and an analytics setup outside the platform to answer the question the platform does not. ### **What the Backlink Guarantee Actually Guarantees** Adaptify advertises DR45+ backlinks, and its pricing page lists "1-20 Avg. DR45 PR Backlinks per month per site." The FAQ is where the commitment gets specific: *"At least one high-quality backlink per client every month. If journalist outreach falls short in a given month, the system automatically writes and places a guest post on a vetted publication so the quota is always met."* Read that carefully. The guaranteed floor is one link per month. The 1-to-20 range is a range, not a promise. And when the earned-media pitching does not land, the quota gets filled by a guest post Adaptify writes and places itself, which is a different asset than an earned journalist citation even though both count as one link in the report. At a fifth of the price, [the $99 version of that promise](/outrank-review/) drops the outreach entirely and trades links between its own customers, which is a materially riskier mechanic. Their own stated placement rate supports the math: 9% on roughly 44 pitches per site per month. That is a normal digital PR hit rate and I am not criticizing it. I am pointing out that a 9% rate against a quota that must always be met is precisely why the guest-post backstop exists. *Adaptify publishes its own outreach numbers: 44 pitches per site per month at a 9% placement rate. Note this page says DA, while the pricing page says DR.* The quality promise is looser than it first reads, in two ways. The plan card states a floor, "DR45+," while the feature matrix directly beneath it states an average, "1-20 Avg. DR45." And the metric changes name between pages: pricing says DR, which is Ahrefs Domain Rating, while the backlinks page above reports "Avg. Domain Reputation DA 45+," which is Moz Domain Authority. Different scales, not interchangeable. ### **I Could Not Find an Independent Measurement of Whether It Ranks** This is the finding I would want if I were the one considering the purchase. The only hands-on written review I could find that is neither the vendor nor a review aggregator ran on Penji's blog in September 2024. The author did real testing: built a keyword cluster, generated an article, reverse-image-searched the infographics. Her verdict was broadly positive. Adaptify and Penji are publicly partnered, and the post carries no partnership disclosure. Beyond that, the field is thinner than I expected. Ranktracker has a review, but Ranktracker is a competing SEO tool vendor. Everything else on page one is Trustpilot, Capterra, Software Advice, Adaptify's own site, a Glassdoor page about working there, and a Reddit thread from March 2024 in which someone calls an SEO engagement a scam. That thread predates most of the current product and appears to describe an agency relationship rather than the platform, so I would not weigh it heavily, but it is sitting at number three on this query and you will see it. Be precise about what that does and does not prove. Plenty of Adaptify customers have surely checked their own rankings, and some of them are the reviewers reporting lifts. What is missing is a public measurement by someone with no commercial stake, which is the thing you would normally use to sanity-check a vendor's claims before spending $6,000 a year. That absence is a real risk in buying this, and it has nothing to do with whether Adaptify is honest. It just means the burden of measurement lands on you, and the platform's own reporting is not built to carry it. ### **Is Adaptify Worth $499 a Month?** Here is where I will tell you what I actually think, as someone who does this work for seven and eight figure clients. What Adaptify automates is real work: keyword research, outlining, drafting, images, publishing, indexing, outreach. A chunk of that is now work an AI assistant does directly if you hand it the judgment about what to do, and that capability is recent enough that a lot of the pricing in this category was set before it existed. Where most comparisons like this one cheat is in stopping there. A DIY setup is not equivalent to Adaptify: you do not get the CMS publishing integrations, the journalist outreach and link placement, the onboarding, the same-day support, the client approval flows, or the white-label portal. Anyone telling you a $20 subscription replaces a managed service is selling you something. So the honest question about a $499 monthly bill is which layer you are buying. If it is delivery infrastructure for client work you resell at a markup, the platform is doing genuine work and the math can be good. If what you are missing is knowing which fixes matter for your site, that layer is cheaper to own than to rent, and it keeps working after you stop paying. That is the gap I built [my AI SEO System](https://seo.ryandoser.com/) to close, for $199 once instead of $499 a month. ### **Who Should Actually Buy Adaptify** **If you run one site and you are comfortable directing an AI, this is not your buy.** The research, drafting, audit and on-page work is what a capable assistant already does when you give it a defined process, and $499 a month is steep for putting a schedule and a dashboard around it. What you would genuinely be missing is the outreach and link placement, so buy that as a service on its own rather than buying a whole platform to reach it. Adaptify appears to agree: replying to a critical review, they wrote that the product is "designed for agencies managing multiple client sites, making it perhaps not the ideal solution for single-site users." **Buy it if you are an agency reselling SEO.** This is what the product is built for and Adaptify says so plainly. White-label portal on your domain, branded reports, client approval flows, alerts from your own email domain, unlimited seats. If your constraint is fulfillment capacity and your client wants a monthly deliverable, Adaptify produces both. At $333 a site against what you bill, the margin is the business case and it is a legitimate one. **Buy it if the alternative is genuinely nothing.** Plenty of businesses publish zero content because nobody has time and nobody will make time. Automated adequate content that actually ships beats excellent content that never gets written, and it is not close. If what you want is a second opinion on which fixes matter rather than a subscription that executes a plan for you, [an hour of consulting](/ai-seo-consulting/) costs less than a month of this and answers a different question. ### **My Verdict on Adaptify** Adaptify is a competent product whose public evidence is much better at showing what it delivers than what it achieves. Both halves of that are worth saying plainly, and neither is an accusation. The support is real, the CMS integration is genuinely good, the direct publishing is architecturally the right call, and the reviewers describing large time savings are specific enough to be credible. If you resell SEO and your constraint is output, it does what it says on the box. What I would not do is buy it as a substitute for knowing what should happen to your site. So whatever you decide, put a rank tracker and an analytics view outside the platform before you spend anything. That holds whether you buy Adaptify, build the workflow yourself, or hire someone. ### **Adaptify SEO FAQs** #### **How much does Adaptify cost per month?** Adaptify costs $499 per month for a single website, or $333 per site on the multi-site plan, which works out to $999 per month for three sites. Both are billed monthly and there is no annual option or prepay discount. A slider on the pricing page goes up to 100 or more sites with unpublished volume discounts for larger agencies. Both tiers include a 7 day free trial and unlimited seats. Figures read off a full render of adaptify.ai/pricing on August 14, 2026, since the page loads its prices with JavaScript and does not show them to a plain fetch. #### **Is Adaptify SEO legitimate?** Yes. Adaptify is a real company based in Miami with a functioning product, a 4.7 rating across 89 Trustpilot reviews, and reviewers who name specific features and staff members. Read that rating with two things in mind: the Trustpilot reviews are solicited by invitation, and the Capterra and Software Advice scores come from one shared Gartner review pool rather than two independent sources. Legitimate, with a rating that carries less independent signal than the number suggests. #### **Does Adaptify actually get you backlinks?** It guarantees at least one per month. Adaptify pitches journalists using your approved sender domain at a stated 9% placement rate across roughly 44 pitches per site per month, and when that outreach falls short its own documentation says the system writes and places a guest post so the quota is always met. The pricing page advertises "1-20 Avg. DR45 PR Backlinks per month per site," so 20 is a ceiling rather than an expectation, and DR45 is stated there as an average even though the plan card above it promises "DR45+." The metric also changes name between pages: pricing says DR, which is Ahrefs Domain Rating, while the backlinks page reports "Avg. Domain Reputation DA 45+" and shows a sample placement at DA 91, which is Moz Domain Authority. Different vendors, different scales, not interchangeable. #### **Are Adaptify's reviews trustworthy?** They are real reviews, but three things shape how much independent signal they carry. Every review on the first page of Adaptify's Trustpilot profile is invitation-verified, meaning Adaptify asked for it. The Capterra and Software Advice scores are identical at 5.0 from 66 reviews because both are Gartner properties drawing on one shared review pool, so that is a single dataset counted twice rather than two sources agreeing. And the only independent hands-on review I could find, on Penji's blog, was written by a company Adaptify is publicly partnered with, with no partnership disclosure on the post. None of that means the praise is false. It means the page-one evidence is thinner than the ratings make it look. #### **Is paying someone to do SEO worth it?** It is worth it when your constraint is genuinely time or a skill you do not have, such as journalist outreach and link placement. It is a poor trade when what you actually lack is knowing which fixes matter for your site, because a service that executes a plan cannot tell you whether it was the right plan. The practical test: if you can describe what you want done and why, you are buying labor. If you cannot, you are buying judgment, and that is worth owning rather than renting. I have ranked [the people actually publishing work on AI search](/best-ai-seo-experts/) and what each one charges. #### **What is the best alternative to Adaptify?** It depends which half of Adaptify you actually need. For an agency buying white-label fulfillment at volume, the real alternatives are other managed platforms, because the client portal and approval flows are most of what you are paying for. For a single-site owner, the alternative is running the work yourself through Claude Code or Codex against a defined process, which is what my [AI SEO System](https://seo.ryandoser.com/) packages. I compare the wider category in my [best AI SEO tools](/best-ai-seo-tools/) roundup. *How I sourced this: pricing and feature figures were read off a full render of adaptify.ai/pricing on August 14, 2026, since that page loads its prices with JavaScript. Ratings and review text came from Trustpilot, Capterra and Software Advice the same day. G2 blocks automated access, so its rating appears here only as Adaptify states it. I sell a competing AI SEO product, which is disclosed at the top of this post.* --- ## How to Build Landing Pages With Claude Code (No Coding) URL: https://ryandoser.com/claude-code-landing-pages/ Markdown: https://ryandoser.com/claude-code-landing-pages.md Published: 2026-08-14 | Updated: 2026-09-30 Categories: Claude Code > Learn how to build landing pages with Claude Code without any coding. Step-by-step guide covering setup, prompting, and free deployment. **Claude Code landing pages** are one of the fastest ways to go from idea to a live, conversion-ready page without writing a single line of code yourself. ### **How Claude Code Landing Pages Actually Work** Most people overthink landing pages. They spend weeks picking templates, hiring designers, or wrestling with drag-and-drop builders that never quite look right. Claude Code flips that process. You describe what you want in plain English, and it generates the full HTML, CSS, and JavaScript locally on your machine. I tested this myself by building a landing page for a $47 digital product from scratch. The entire first draft took minutes, not days. Here's what you actually need to get started: - A paid Claude plan (Pro is $17 a month billed annually or $20 monthly, and the free plan does not include Claude Code) - Claude Code running in VS Code, Cursor, or your terminal - A web designer skill markdown file (Anthropic offers a [free one in their docs](https://docs.anthropic.com/en/docs/claude-code/skills)) - Opus 5.5 as your model, which is already the Claude Code default on paid plans (not Sonnet, not Haiku) The skill file is the secret ingredient. It acts like an SOP for Claude Code, giving it design principles, layout rules, and your personal preferences. Without one, you'll get generic output. If you're already using Claude Code for marketing workflows, my [Claude Code marketing guide](/claude-code-for-marketing/) covers the broader setup. *The web designer skill markdown file in VS Code gives Claude Code the design instructions it needs to build polished landing pages.* ### **The Prompt That Makes or Breaks Your Landing Page** You've probably tried asking AI to "make me a landing page" and gotten something that looks like a 2018 WordPress theme. The fix is context. Your prompt needs four things: - **Reference URL.** Give Claude Code a landing page you like. Maybe it converts well, or maybe a competitor's design caught your eye. This gives the AI a visual target. - **Product details.** Name, price, payment link (I use [Stripe](https://stripe.com/) checkout), and a tagline. - **Content in HTML format.** Copy the raw HTML of your existing content rather than pasting plain text. Claude Code interprets structured markup far better than raw copy. - **Specific design instructions.** Colors, layout preferences, sections you want included. For my AI Automations Vault page, I fed Claude Code a reference URL from an existing product, the Stripe checkout link, and the HTML content from my free guide. That level of detail produced a polished first draft that already had correct product names, accurate pricing, and working payment links. One thing that separates vibe coding landing pages from traditional builders: you can iterate in natural language. "Remove the terminal image below the hero." "Change 'What's Inside the Vault' to 'What's Inside the AI Automations Vault.'" Each instruction refines the page without touching code. [My Claude Code Skills Stack](https://skills.ryandoser.com/) has 20+ skills I use daily to automate marketing and content creation with a one time fee and lifetime updates. *The AI Automations Vault landing page generated by Claude Code, showing a before-and-after comparison section with working Stripe checkout.* ### **Designing in Claude Design First, Then Handing Off to Claude Code** Anthropic added a second front door to this workflow after I first published this guide. [Claude Design](https://claude.com/product/design) arrived in April 2026, and the piece that matters here is how it connects to Claude Code. It is still in beta. You describe a design in chat and Claude builds it on a canvas next to you, so you can see and edit the layout before any code exists. It is included on the Pro, Max, Team, and Enterprise plans, and it is off by default on Enterprise until an admin turns it on. The reason this matters for landing pages: the prompt section above is you describing a design in words and hoping the first render is close. Claude Design lets you settle the layout visually first, then hand the finished thing to Claude Code to build and deploy. Anthropic's own framing is that Claude Code "continues from your existing work instead of starting over from a screenshot." There are two commands worth knowing: - **`/design`** runs inside Claude Code and drafts mockups or landing pages as artboards on a Claude Design canvas, which you then edit in your browser. It needs Claude Code v2.1.265 or later. - **`/design-sync`** pulls your React design system out of your codebase and into Claude Design, so what it generates uses your real components, colors, and typography instead of generic defaults. That second command addresses the same problem the web designer skill file solves, from the opposite direction. The skill file is you writing your design rules down by hand. `/design-sync` reads them out of code you already wrote. Per Anthropic's docs, it can pull a design system from a GitHub repo, design files, or raw uploads, and Claude then checks its output against that system before you see it. Claude Design will also export straight to HTML, PDF, or PowerPoint, and it can send work to tools like Vercel and Replit. For the workflow in this post, HTML export or the Claude Code handoff is what you want, because the deploy path below expects files on your machine. One limitation to plan around: neither `/design` nor `/design-sync` is available if you run Claude Code through Amazon Bedrock, Google Cloud's Agent Platform, Microsoft Foundry, or Claude Platform on AWS. On a normal Claude subscription, which is what most people reading this are using, it works. To be straight with you: the $47 product page above was built before Claude Design existed, so I have not rebuilt it that way. What I can tell you is where the extra step is worth taking. If you can already picture the page, adding a canvas stage in front of Claude Code is work you do not need. If the layout is the part you keep getting wrong, or the page has to sit next to an existing brand without looking off, that is what the design stage is there for. ### **Going Live With GitHub and Cloudflare** Building a landing page locally is satisfying. But nobody can see it until you deploy. Here's how I push Claude Code websites live for free. #### **Step 1: Create a GitHub Repository** Set up a free [GitHub](https://github.com/) account if you don't have one. Create a new public repository named after your product. Skip the README and license options. #### **Step 2: Upload Your Files** Ask Claude Code to provide your index.html and any asset files. It will open them in your Finder (or file explorer on Windows). Drag those files into your GitHub repository and commit the changes. #### **Step 3: Connect to Cloudflare Pages** Create a free [Cloudflare](https://www.cloudflare.com/) account. Go to Build, then Workers and Pages. Click "Create Application," connect your GitHub account, select your repository, and deploy. Within seconds, Cloudflare generates a public URL for your landing page. That's three steps to go from a local file to a live, publicly accessible landing page. No hosting fees. No server configuration. If you're curious how Claude Code handles other marketing tasks like [SEO optimization](/claude-code-seo/), I broke that down separately. *Creating a public GitHub repository to host the Claude Code landing page files before connecting to Cloudflare Pages.* ### **Custom Domains and Shipping Fast** Cloudflare gives you a URL like `ai-automations-vault.pages.dev`. Functional, but not exactly branded. You can purchase a cheap domain ($1-$10/year for .shop or .store extensions) and connect it through Cloudflare's domain management. The full DNS propagation takes a few hours, but after that, your landing page lives on a clean, branded URL. Here's my honest take on this: don't wait for the perfect domain before you ship. I would rather launch on a Cloudflare subdomain, validate whether the product sells, and worry about branding later. Too many people stall at the domain-buying stage and never test their offer. The whole point of using Claude Code for [building things without coding experience](/ai-for-non-coders/) is speed. Get the page live. Run traffic to it. See what converts. Then refine. ### **What Claude Code Won't Do for You** No tool is perfect, and Claude Code has real limitations for landing pages. Your first output won't be flawless. Expect 5-10 small tweaks on the initial version. Text that needs rewording, sections that need reordering, images that don't fit right. That's normal, and the iterative prompting handles it well. Payment processing stays external. I route all transactions through Stripe instead of trying to build checkout functionality into a vibe-coded page. That keeps things simple and secure. Mobile responsiveness varies. Some generated pages look great on phones out of the box. Others need a follow-up prompt like "make this fully responsive on mobile devices." Always check. And if you're already using [Claude Code skills](/claude-skills/) for other workflows, the web designer skill slots right into your existing setup. ### **Ryan's Final Thoughts** Building landing pages with Claude Code removes the biggest friction point for marketers and creators: the gap between having an idea and getting it in front of real people. You describe what you want, iterate in plain English, and deploy for free through GitHub and Cloudflare. The speed advantage is real. Ship first, refine later, and let the market tell you what works. ### **Claude Code Landing Pages FAQs** #### **Do I need coding experience to build landing pages with Claude Code?** No. Claude Code generates all the HTML, CSS, and JavaScript for you based on plain English prompts. You never touch the code directly. The skill markdown file handles design logic, and you iterate by describing changes conversationally. A paid Claude plan and VS Code are the only technical requirements. #### **What does it cost to build and host a Claude Code landing page?** Claude Code needs a paid Claude plan, and Pro is $17 a month billed annually or $20 billed monthly. GitHub and Cloudflare Pages hosting are both free. If you want a custom domain, expect $1-$10/year for budget extensions like .shop or .store. So beyond the Claude plan, a live, production-ready landing page costs little more than the domain. #### **Can Claude Code handle payment processing on landing pages?** Not directly. The best approach is using a third-party processor like Stripe. You create a checkout link in Stripe, feed that URL into your Claude Code prompt, and the generated page links directly to Stripe's hosted checkout. This keeps payments secure without any custom integration work. #### **How long does it take to build a landing page with Claude Code?** The first draft generates in about 3-5 minutes. Plan another 10-15 minutes for iterative refinements like adjusting text, removing sections, or swapping images. Full deployment to Cloudflare takes under a minute. Start to finish, you can have a live landing page in under 30 minutes. #### **Should I use Claude Design or Claude Code to build a landing page?** Use Claude Design when the layout is the hard part or the page has to match an existing brand, since it lets you settle the design on a canvas and then hand it to Claude Code to build and deploy. Go straight to Claude Code when you can already picture the page, because the canvas stage adds a step you do not need. Claude Design is in beta on the Pro, Max, Team, and Enterprise plans, and `/design-sync` pulls your existing design system out of your codebase so the output uses your real components. #### **Which Claude model works best for designing landing pages?** Use Opus 5.5, the current Claude Code default. The Opus tier (Opus 4.6 when I first wrote this guide) handled layout logic, responsive CSS, and visual hierarchy better than Sonnet or Haiku. You can't turn thinking off on Opus 5.5, so use /effort to control how hard it works, and start with "ask before edits" permission mode until you're comfortable with the workflow. --- ## 6 Best Zernio Alternatives Priced at 5, 20 and 100 Accounts URL: https://ryandoser.com/zernio-alternatives/ Markdown: https://ryandoser.com/zernio-alternatives.md Published: 2026-08-14 | Updated: 2026-09-30 Categories: AI Tool Reviews > Zernio bills per connected account. I priced six alternatives at 5, 20 and 100 accounts to find where that curve stops being a bargain. Most **Zernio alternatives** pages are written by a vendor who wants your migration, and they tend to price Zernio at whichever account count makes their own product look best. So I did the boring thing instead. I priced six tools at three account counts, 5, 20 and 100, using each vendor's live rate card, with every pricing page switched to monthly billing. The cheapest option changes four times between 5 accounts and 100, because every flat plan has a tier cliff waiting for you. That is the whole story, and it is why a single winner does not exist here. Conflicts up front. [Blotato](https://www.blotato.com/?ref=rdoser) is my daily driver, it is a client of mine, my account is comped, and its links here are affiliate links. I have no relationship with any other tool on this list. One boundary I want to be straight about. I run Blotato in production every week and I have used Zernio, Upload-Post, Postiz and Buffer directly. Ayrshare and bundle.social I have set up and evaluated but never run at scale, so I priced those from their published rate cards and say so in their entries. I am not a developer, and I picked these apart the way a marketer does, by connecting accounts and watching what the bill did. That turned out to be the part most of these pages get wrong. ### **The Number That Decides This** Zernio charges per connected account, per month. The first 2 are free, accounts 3 through 10 cost $6 each, 11 through 100 cost $3, and anything past 101 costs $1. One connected profile on one platform is one account. Your Instagram and your TikTok is two, not one. Run that curve and the shape appears. Five accounts is $18 a month. Twenty is $78. One hundred is $318. Zernio is the cheapest option on this page through 6 accounts, and most alternatives pages skip that sentence because it costs them the sale. At 7 accounts Blotato takes over by a dollar, which is a rounding error rather than a reason to move. The gap only becomes real money past 20. There is a second limit worth knowing before you price anything, because it quietly multiplies your account count. Zernio's own documentation states that each profile holds one account per platform, so running ten Instagram accounts means ten profiles, not one profile with ten connections. The product itself holds up better than its marketing does, and I fact-checked its loudest claim in [my full Zernio review](/zernio-review/). ### **Zernio Alternatives Compared at 5, 20 and 100 Accounts** All prices are monthly billing, checked live on each vendor's own pricing page. Where a page defaulted to annual billing, I switched it to monthly first, which changes the number on Buffer and Upload-Post. | Tool | Cost at 5 | Cost at 20 | Cost at 100 | Billing unit | Writes the post | | Zernio | $18/mo | $78/mo | $318/mo | Per connected account | No | | Blotato | $29/mo | $29/mo | $499/mo | Flat, by plan tier | Yes | | Upload-Post | $24/mo | $50/mo | $438/mo | Per profile | Captions only | | Postiz cloud | $29/mo | $49/mo | $99/mo | Per channel tier | AI assist | | bundle.social | $100/mo | $100/mo | $100/mo | Per organization | No | | Ayrshare | $149/mo | $299/mo | $299/mo | Per customer profile | No | | Buffer | $30/mo | $100/mo | $245/mo | Per channel | AI assist | Two columns in that table do more work than the prices. The billing unit tells you which direction your bill moves as you grow, and whether the tool writes the post tells you if you are buying one service or two. #### **1. Blotato (Best for one agent that writes and publishes)** *Blotato's plans are flat, so the bill does not move when you add accounts inside a tier.* Blotato is the one I actually run. It publishes to 9 platforms from one hosted API and MCP server, and it generates the copy and the image before it posts, which is why I stopped orchestrating two services. The long version of that story is in [my Blotato review](/blotato-review/). **Pros:** - Flat pricing, so 20 accounts costs the same as 3 on the $29 Starter tier - Writes the post and makes the image, no separate content service to maintain - 36 MCP tools on one endpoint, so an agent can run the whole loop in one conversation **Cons:** - 9 platforms, fewer than Zernio reaches, with no Discord, Telegram or WhatsApp - Comments and DMs reach Instagram and Facebook only, and analytics skips LinkedIn (if [automating Instagram DMs](/best-instagram-dm-automation-tools/) is the main job, a dedicated tool goes deeper) - No free tier, and the 7-day trial excludes the API entirely **Best for:** Anyone who wants an AI agent to write and publish in one step, at 10 to 20 accounts. **Pricing:** Starter $29/mo (20 accounts), Creator $97/mo (40), Agency $499/mo (100). Monthly billing, flat. **Free trial:** 7 days with 60 AI credits, card required. Generating an API key ends the trial and starts the paid subscription, so API users should plan to subscribe rather than trial. **Bottom line:** If 9 platforms cover your stack and you are anywhere from 7 to 20 accounts, Blotato is the lowest bill in this table and the only one bundling content generation into it. At 6 accounts or fewer on platforms Zernio already covers, staying put is the better call. #### **2. Postiz (Best for the lowest bill at 100 channels)** *Postiz caps at $99 for 100 channels, the lowest hosted bill here at that count.* [Postiz](https://postiz.com/pricing) is open source, and its cloud pricing is the lowest at the top end of this list. At 100 channels it is $99 against Zernio's $318, with bundle.social's flat $100 sitting a dollar behind it. **Pros:** - $99 for 100 channels, roughly a third of Zernio at the same count - Open source, so self-hosting removes the recurring bill for teams willing to run it - Reaches destinations the big APIs skip, including Mastodon and Discord **Cons:** - Self-hosting trades the bill for maintenance, and the setup docs are candid about the platform approvals involved - AI features assist with copy rather than producing finished posts - The cheapest tier covers 5 channels, so small setups see no saving over Zernio **Best for:** Agencies running many channels who want a predictable ceiling. **Pricing:** Standard $29/mo (5 channels), Team $39 (10), Pro $49 (30), Ultimate $99 (100). Self-hosting is free. **Free trial:** 7 days on the cloud plans. Self-hosting is free and needs no card. **Bottom line:** Postiz is the cheapest hosted option here from 21 to 30 channels and again past 40, so if cost per channel decides it and you do not need generated content, this is the switch. I run the cloud version rather than self-hosting, and I wrote up [why that $0 self-hosted number is not really $0](/postiz-alternatives/). #### **3. Upload-Post (Best for platform breadth per dollar)** *Upload-Post counts profiles, and each profile holds one account per platform.* [Upload-Post](https://www.upload-post.com/pricing) reaches more platforms than anything else on this page, and it has a genuine free tier with no card. Watch the pricing toggle, because the page opens on annual and shows $16 where the monthly rate is $24. **Pros:** - The widest platform list here, including Reddit, Discord, Telegram and Mastodon - Free tier gives 2 profiles and 10 uploads a month, no card required - Whitelabel integration from the $50 tier, useful if you resell publishing **Cons:** - The unit is profiles, not accounts, so comparing it to Zernio needs care - Posting links on X costs an extra $19/mo on top of any plan - Extra profile packs do not stack, so you buy one bundle or the next tier **Best for:** Publishing to platforms the mainstream APIs skip. **Pricing:** Free $0 (2 profiles), Basic $24/mo (5), Professional $50 (25), Advanced $147 (75), Business $438 (225). Monthly billing. **Free trial:** Yes, a permanent free tier plus trials on paid plans. **Bottom line:** If you need the widest platform list in one plan, Upload-Post is the pick at $50 for 25 profiles. If you only publish to the big networks, you are paying for reach you will not use. #### **4. bundle.social (Best when you publish for your own customers)** *bundle.social bills per organization, so connected accounts are uncapped on paid plans.* [bundle.social](https://bundle.social/pricing) prices by publishing volume rather than by connection, and its paid plans place no cap on connected accounts. For a SaaS whose customers each connect several profiles, that is a different cost curve entirely. **Pros:** - Unlimited connected accounts on every paid plan, so onboarding a big customer changes nothing - Flat $100/mo covers 10,000 posts, which is where it beats per-account billing outright - Ships SDKs, a CLI and an MCP server for agent use **Cons:** - The $100 floor is steep for small setups, with only Ayrshare starting higher - Quotas are per organization, so heavy posting volume moves you to the $400 tier - The free plan caps at 3 social sets (teams) and 20 posts a month **Best for:** Multi-tenant products where each customer brings their own accounts. **Pricing:** Free $0, Pro $100/mo, Business $400/mo, Enterprise custom. Monthly billing, per organization. **Free trial:** Yes, a free plan with no payment details required. **Bottom line:** From 28 accounts the flat $100 beats Zernio's curve, which reaches $102 at that count, and the gap widens with every customer you add. For a small single-brand setup it is the wrong shape entirely. I evaluated this from its rate card rather than running it in production. #### **5. Ayrshare (Best for embedding publishing in a product you sell)** *Ayrshare's unit is the customer, so one profile spans every network they connect.* [Ayrshare](https://www.ayrshare.com/pricing/) starts at $149/mo, which looks indefensible next to a free tier until you read the unit. One profile is one customer across every network they connect, so a customer on six platforms counts once. **Pros:** - One profile covers a customer across every network they connect, so multi-network customers do not multiply the bill - Built for embedding, with the compliance and uptime posture that implies - Billing stops when you delete a profile, so costs shrink when a customer churns **Cons:** - $149 entry is the highest floor here by a wide margin - Premium covers 13 accounts, so scaling means the $299 Launch tier - Overkill for anyone publishing only their own brand **Best for:** Companies putting publishing inside a product their own customers pay for. **Pricing:** Premium $149/mo (up to 13 accounts), Launch $299/mo (up to 130 accounts), higher tiers on request. **Free trial:** A 28-day free trial on the Launch plan. **Bottom line:** The per-customer unit starts to make sense when each customer connects several networks, and is hard to justify before that. I set this up and priced it from the published card rather than running it at scale, so treat my read as documentation analysis. I went deeper in my [Ayrshare comparison](/ayrshare-alternatives/). #### **6. Buffer (Best for a dashboard your team already knows)** *Buffer's monthly rate is $6 per channel. The page opens on Yearly, which shows $5.* [Buffer](https://buffer.com/pricing) is the option a marketing team will actually adopt without training, and it does now ship an API and an MCP server, which is a change most comparison pages have not caught up with. **Pros:** - Free plan covers 3 channels permanently with 10 scheduled posts each - Per-channel rate drops to $4 from 11 channels and lower again past 26 - The interface needs no explaining to a non-technical team **Cons:** - API requests are capped by plan, at 3,000 a month on Free and 7,500 on Essentials - Per-channel billing means the bill still grows with every channel you add - Built dashboard-first, so agent-driven publishing is not the primary path **Best for:** A team that wants a calendar and a person clicking publish. **Pricing:** Free $0 (3 channels), Essentials from $6/channel/mo, Team from $12/channel/mo. Confirm the toggle reads Monthly, since the page defaults to Yearly and prints the annual rate with a /month suffix. **Free trial:** Yes, 14 days on paid plans, plus a permanent free tier. **Bottom line:** Buffer wins when the constraint is who has to operate the thing, not what it costs per account. For a scripted or agent-driven workflow the request caps make it the wrong shape. ### **What About PostPeer, Postproxy and Bolta?** These three rank well for this keyword and I have not run any of them, so I am not ranking them. [PostPeer](https://www.postpeer.dev/alternatives/zernio) advertises a flat $43/mo with unlimited same-platform accounts. [Postproxy](https://postproxy.dev/compare/zernio/) sells predictable per-group billing with a published uptime SLA. [Bolta](https://bolta.ai/alternative/zernio) positions around content review workflows. On paper each targets the same complaint that drives people off per-account pricing. I have no firsthand read on how they behave once accounts are connected, and that is the part that matters, so I would rather say nothing than rank software I have not used. ### **How to Choose a Zernio Alternative** These are the questions I work through on every client build, in this order. **How many accounts will you connect twelve months from now?** Price that number, not today's. The ranking above reorders completely between 5 and 100. **Do you need the post written, or only delivered?** If something else already writes your copy, you are shopping for a publisher and half this list is overpriced for you. **Are the accounts yours or your customers'?** Publishing for other people makes per-account billing the wrong shape, whatever the rate. **Which platforms are non-negotiable?** One required destination outside a tool's list ends the conversation regardless of price. **Who operates it day to day?** An API is worthless if the person posting wants a calendar, and a dashboard is friction if an agent does the work. ### **Which Should You Pick?** At 6 accounts or fewer on platforms Zernio covers, stay on Zernio. From 7 to 20 accounts, or wanting content generated too, Blotato at $29 flat. Past 40 channels on pure publishing, Postiz at $99 for 100. Publishing for your own customers, bundle.social at $100 flat, or Ayrshare if each customer spans several networks. Needing the widest platform spread, Upload-Post. Handing it to a non-technical team, Buffer. ### **Ryan's Final Thoughts** Zernio is a good product with a loud marketing department, and those two things are unrelated. The free tier is real and the graduated pricing is honest about what it does. What it does is climb. That is fine at 5 accounts and expensive at 40, and where each alternative overtakes it is marked in the table above. Count your connections, decide whether you need words or just delivery, then price the shortlist at the number you expect next year. Every figure here came off the vendors' own pricing pages, with monthly billing selected. ### **Zernio Alternatives FAQs** #### **What is the best Zernio alternative?** It depends on account count. Through 6 connected accounts Zernio is cheapest and switching costs you money. From 7 to 20 accounts Blotato at $29/mo flat is the lowest bill here, and it bundles content generation. At 100 channels Postiz's $99 tier is the lowest hosted price on this list. #### **Is there a free Zernio alternative?** Upload-Post gives 2 profiles and 10 uploads a month with no card, Buffer covers 3 channels permanently, and bundle.social has a free plan capped at 3 social sets (teams). Postiz can be self-hosted at no license cost, and its cloud plans run a 7-day trial. Zernio's own 2 free accounts stay free with no card, though X API calls are billed as pass-through at X's own rates. #### **How much does Zernio cost at 100 accounts?** $318 a month. The first 2 accounts are free, accounts 3 through 10 cost $6 each, and 11 through 100 cost $3 each. Past 101 accounts the rate drops to $1. Zernio publishes these figures on its own rate card. #### **Do Zernio alternatives have MCP servers?** Most of them do. Blotato, bundle.social, Postiz, Ayrshare and Buffer all ship MCP servers, as does Zernio. MCP support is table stakes across this category now, so it is not a reason to pick one over another. Compare what sits behind the endpoint instead. #### **Is Zernio the same as Late or GetLate?** Yes. Late rebranded to Zernio without breaking its API endpoints or response schemas. Some directories still list it under the old name, so older reviews describing GetLate are describing the same product. #### **Why did my Zernio bill grow faster than my account count?** Each Zernio profile holds one account per platform, so ten Instagram accounts require ten profiles rather than one. Teams managing several accounts on the same network hit that multiplier without expecting it, and it is the most common reason a bill outruns the estimate. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine and my account there is comped rather than paid. I have no relationship with Zernio, Postiz, Upload-Post, bundle.social, Ayrshare or Buffer. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## Why AI Anxiety Is Real (And How I Handle It) URL: https://ryandoser.com/ai-anxiety/ Markdown: https://ryandoser.com/ai-anxiety.md Published: 2026-08-13 Categories: AI Resources > AI anxiety isn't the problem. Feeling nothing about new AI releases is the real red flag, and here's what to do instead of chasing them. I am about to step away from all of this for a few weeks, and nothing has tested what I believe about **AI anxiety** more than deciding to disconnect. ### **Watch: What Stepping Away Exposes About AI Anxiety** My first child arrives shortly, so I am heading into paternity leave. No release-day testing, no checking what shipped while I slept, just gone. I recorded this one unscripted before leaving, including a walkthrough of the system that makes stepping away possible at all. Here is what deciding to disconnect already exposed, before I have even left. Almost none of the daily scramble is going to matter across those weeks, and I could not tell you which release from the last month would. I am a six-figure AI entrepreneur with most of that coming from my marketing agency, and I still feel it every time I open YouTube, X, or LinkedIn. New model out, better go test it. New tool, better go look. That reflex does not disappear because you have been doing this a decade. ### **Why AI Anxiety Is a Signal, Not a Problem** Here is what nobody tells you about AI anxiety: it means you are paying attention. The people who should actually worry are the ones who feel nothing when a new model ships. Feeling nothing means you have stopped tracking a space that is still moving fast enough to change your income. Anxiety means part of you already suspects something out there could replace an hour of your week, and that instinct is usually right. The failure is not the anxious feeling, it is what most people do with it next. ### **The Panic-Consumption Loop That Burns You Out** New release drops, and panic sets in. You go watch three videos about it, bookmark a tool, maybe open it once, and close the tab feeling slightly worse than before you started. Nothing in your actual business moved. I watched this play out in real time when [Fable 5 access was suspended](https://www.anthropic.com/news/redeploying-fable-5) on June 12. US export controls forced it, Anthropic had no way to verify nationality in real time, and the model was gone for 18 days before returning July 1. The reaction was not people calmly switching to another model. It was panic about losing access to something most of them had been using for days. The model came back, the work people were "behind" on was still there, and almost none of that scramble produced anything usable. That is the loop. Consume, panic, dabble, close the tab, repeat with the next release. It feels like progress because you are "staying current." It is not progress, it is a treadmill dressed up as diligence. Most of what gets rewarded on that treadmill is not useful either. The demos that go viral are usually someone building a video game or some other impressive-looking novelty. Almost nobody watching actually needs to build a video game. Being able to do it proves the model is capable, not that the demo has anything to do with your Tuesday. ### **The One Question That Breaks the Loop** The fix is not another tool, and it is not forcing yourself to try every release the day it ships. It is a single question, asked before you open anything new: what is actually broken in my business right now, and could AI fix it? It gives you a filter, and a filter is what AI anxiety is really missing. Most releases will fail that filter immediately, and that is fine. You are not supposed to use everything, just the handful of things that solve a real bottleneck you already have. If you do not know the answer to something, open Claude or Claude Code and either type out the problem or voice dump it with a tool like [Wispr Flow](https://wisprflow.ai/). It will not solve everything on the first pass, but it points you toward an answer faster than another comparison video will. Start from your actual bottleneck, not from the leaderboard of whatever launched this week. ### **The Work That Buys You the Right to Disconnect** There is a version of this advice that is just "log off and relax," and it is useless. You cannot walk away from a business that only runs while you are watching it. What made this leave possible was boring, unglamorous work I did months ago. I moved my existing workflows off scattered web apps and into one place: VS Code on my own machine, with my tools connected through API, MCP, and CLI connections. *The workspace tour from the video: client work, notes, and config files living as folders on my machine, not in chat histories.* About 95% of my work runs through there now. Before that: cloud projects here, ChatGPT threads there, Gemini somewhere else, and no way to hand any of it off or automate it. Every task started with remembering where I had left it. I have written the full breakdown of that setup in [why I run Claude Code and Codex together](/claude-code-and-codex-together/), so I will not repeat it here. The relevant part for anxiety is what the structure changes, not which tools are in it. When your work lives in folders and files instead of chat histories, a new model release stops being an event. You point the folder at a different model and keep going, with nothing to migrate and nothing lost when a vendor changes its mind. That is the actual cure for release-day panic, not discipline and not ignoring the news. Structure makes any single release a small decision instead of a threat to everything you have built. ### **What Actually Separates the People Who Profit** I have gone deeper on the systems side of this, including why the model race matters less than people think, in [the reality of AI in 2026](/reality-of-ai-in-2026/). The short version: everyone has the same models, and almost nobody has your context. That is the moat, not which model you picked this week. Knowing the moat and acting on it are two different skills. I built the **[Claude Code Skills Stack](https://skills.ryandoser.com)** out of exactly this filter. I did not chase a trend, I packaged the marketing skills I already had a decade of proof behind. *Skill files organized by category in the same workspace. Expertise saved as files, which any model can read.* That product has done over $18,000 in revenue precisely because it started from expertise I already owned, not from a tool I panicked into learning. The same logic applies to whatever you are already good at, once you know [how to get that expertise into a skill file](/claude-skills/). The tool changes. The filter does not. I get asked constantly by people in my community how to make money with AI, and my answer disappoints people who wanted a shortcut. I tell them to ignore the faceless YouTube channels selling AI ebooks and PDFs, and instead ask what they are already good at. Once you know that, the question becomes how AI amplifies it, not whether you have found the right tool yet. Reverse that order and you end up with a stack of tools, a case of AI anxiety, and no actual skill behind any of it. ### **Ryan's Final Thoughts** AI anxiety is not going away, and it should not. What separates the people who make money from this and the people who stay stuck on the treadmill is whether they stopped consuming long enough to ask what is actually broken in their business, then used AI to go fix that one thing. I am going to go be a dad for a few weeks. Models will ship while I am gone, and I do not plan to test a single one of them on release day. That is the whole point. If stepping away for a few weeks would break what you have built, the problem was never the pace of AI releases. ### **AI Anxiety FAQs** #### **What causes AI anxiety in marketers and business owners?** AI anxiety usually comes from watching new model releases and tool launches faster than anyone can realistically test them. It gets worse when people measure themselves against demos and hype videos instead of against their own actual bottlenecks. #### **How do I stop the cycle of chasing every new AI release?** Ask one question before opening anything new: what is broken in my business right now, and could this fix it? Most releases fail that filter immediately, and the few that pass earn a real test instead of another bookmark. #### **Can you take time off without falling behind on AI?** Yes, if your work lives in files and folders rather than in chat histories you have to be present to use. I am taking weeks off for paternity leave and do not plan to test releases while I am out. A release you skip is recoverable in an afternoon. A business that only runs while you watch it is the actual risk. #### **What should I focus on instead of trying every new AI tool?** Focus on the subject matter expertise you already have and let AI amplify that, rather than treating AI itself as the skill. My deeper breakdown of [why the model race matters less than people think](/reality-of-ai-in-2026/) covers how to pick where that focus goes. #### **Does AI anxiety mean I am behind everyone else?** No. Most people chasing every release are not moving their business forward either, they are just further along the same treadmill. Feeling behind because of a demo video is not the same as actually being behind on a problem that matters to your income. --- ## I Put 10 Years of SEO Into a Folder (My New AI SEO System) URL: https://ryandoser.com/ai-seo-system-launch/ Markdown: https://ryandoser.com/ai-seo-system-launch.md Published: 2026-08-11 | Updated: 2026-08-11 Categories: AI News, AI Resources > A decade of SEO judgment, including the client work behind 7 and 8 figure accounts, turned into a system your AI runs on your site. I have spent 10+ years doing SEO, and the last stretch of it figuring out how to get businesses cited in AI search. My new **AI SEO System** is that decade, written down. Not the theory. The judgment: what to fix first, what to leave alone, and what this industry sells that does not work. It is the same practice I run for 7 and 8 figure clients, packaged so it runs inside the AI tool you already use. The hard part of this work was never knowing the tactics. It is knowing which five things out of fifty actually move the needle for a business like yours, and in what order. That judgment is what people normally hire me by the hour for, and it is the part I have never been able to hand anyone. Now I can. You can grab the **[AI SEO System for $199 one-time here](https://seo.ryandoser.com/)**, with lifetime updates included and no subscription. ### **What You Get in the AI SEO System** You give the folder to an AI assistant, and it becomes your AI search consultant. It reads your site, runs the audit I run on paying clients, and hands you a prioritized fix list instead of a grade. - **The full AI search audit.** Whether AI crawlers can even reach your site, whether your pages are written so a model can lift them into an answer, whether the web gives AI any reason to trust you, and whether the visitors who arrive can become customers. - **45 findings it can diagnose**, each with a fix recipe: what it means, what to do, a copy-paste prompt, and how to verify it worked. - **16 AI SEO skills** covering keyword research on live results, content strategy, page and listicle drafting in your voice, competitor teardowns, outreach, Google Business Profile, schema, and llms.txt. - **A refresh skill that knows when to leave a page alone**, so you never break something that is quietly winning. - **The buyer-question scoreboard**, so you can see who the models name in your category, you or your competitor. - **The Don't-Chase List**, six things this industry sells that do not work. Because it is all plain files, it is not locked to one app. It runs in Claude, ChatGPT's Codex, Cursor, Google Antigravity, and any other AI that reads files. On [Claude Code](https://claude.com/product/claude-code) it installs as a plugin with its own slash commands. You do not need to know any SEO to use it. If you can describe your business and copy-paste, you are qualified. That was the hardest design constraint and the one I am most proud of. ### **The Receipts Behind the System** Start with a client, because a marketer ranking his own marketing site is the easiest thing in the world to discount. This is a 7 figure dental IT and cybersecurity company. Look at the left half of the chart: nine months of flat. Then the work goes in around May and the curve changes shape. Trailing 12 months: **5.87K clicks and 1.23M impressions**. Entity signals, page structure, and content built to be quotable, on a site that had stopped moving. Same fixes, written down in this System. On an 8 figure SaaS client, Search Console's Generative AI features report shows **95.5K impressions inside Google's AI experiences** since mid-May. That is the report most agencies still are not opening. Then there is my own site, which started at zero in February 2026 with no backlinks and no domain history. Six months from a standing start: **5.77K clicks and 890K impressions** in Google Search Console, and **12.1K AI citations** across Microsoft Copilot and its partners in Bing Webmaster Tools. That last number is the one this System optimizes for, and every citation behind it was measured with free reports, [without paying for an AI visibility tracker](/best-ai-visibility-tools/). And this is not an impressions trophy. That visibility has driven over **$100K in revenue** through new clients, digital product sales, and affiliate commissions. ### **Who Should Not Buy This** Here is what this will not do for you. It will not get you a guarantee. Nobody controls what a model says, and anyone selling guaranteed placement inside ChatGPT cannot deliver it. What I can show you is the mechanics that move the odds, measured honestly, including the months where the answer is "not yet." It will not work fast. In my own data the curve changed months in, not days in. If you have a launch in ten days, buy ads. The other honest limit is you. Most of what wins here is structural, so if nobody can ship changes to your site, the plan will sit in a folder and nothing will move. And if you would rather not drive at all, do not buy the $199 version to be polite. Either book [AI SEO consulting](/ai-seo-consulting/) and have me do it, or take the $600 bundle, which is the System plus a private hour prioritizing your fix list together. ### **Ryan's Final Thoughts** Anyone can publish now. Almost nobody gets cited. That gap is the whole job, and it is why so much of the old checklist SEO advice stopped moving the needle. My breakdown of [AI SEO strategy](/ai-seo-strategy/) covers the mechanics if you want the thinking before the tool. This System is the version of that work I wish I could have handed clients five years ago: the audit, the fixes, and the judgment about which pages to leave alone, all written down. Grab the AI SEO System for **[$199 one-time here](https://seo.ryandoser.com/)**, lifetime updates included, no subscription. --- ## Why I Use Claude Code & Codex Together as a Marketer URL: https://ryandoser.com/claude-code-and-codex-together/ Markdown: https://ryandoser.com/claude-code-and-codex-together.md Published: 2026-08-11 | Updated: 2026-08-11 Categories: Claude Code > How I run Claude Code and Codex together for marketing work, which jobs go to each, and why the split is not the one developers use. I run **Claude Code and Codex together** in the same window, and the split between them is not the one developers write about. ### **Watch Me Run Claude Code and Codex Together** I walked through this on Ryan Hanley's [Finding Peak podcast](https://ryanhanley.com/podcast), including a live screen share of how my workspace is organized. Search this topic and every result is written for engineers. They cover handoff files, git worktrees, and warnings about two agents editing the same code at once. None of that is my problem. I am not shipping software, I am shipping blog posts, thumbnails, and client work. If you have never opened Claude Code at all, start with my [beginner guide to Claude Code for marketing](/claude-code-for-marketing/) and come back for the second agent. *Both extensions live in the same window, alongside the folders they work on.* ### **The Split That Actually Matters for Marketers** Developers split these two agents by task complexity. I split mine by what each one physically can and cannot do. Claude gets the writing, the SEO work, and anything where marketing judgment decides whether the output is good. That is most of my week. Codex gets images, because Claude models do not generate them natively. One step of my blog workflow calls the Codex CLI, which runs GPT Image 2 to make the featured image. That is the whole rule. Words and judgment go left, pictures go right. Here is what the handoff looks like in practice. Claude drafts the post, runs it past my anti-slop and brand-voice checks, and gets the copy to a place I would actually publish. Then the same workflow calls Codex with the post's title and angle, and Codex returns the featured image. I never leave the editor or open a separate design tool. The reason that matters is that the featured image is usually the step where a content workflow stalls. One agent finishing the words and handing off to another for the visual is the difference between a finished post and a draft waiting on a graphic. There is a second way to run this pairing that I did not invent. You can have Codex adversarially review whatever Claude produced, which is one of the [Claude Code hacks](/claude-code-hacks/) I picked up from someone smarter than me. ### **Codex Is Also Your Insurance Policy** Usage limits are the thing nobody plans for until they hit one mid-task. When Claude Code goes down or I burn through my usage, the other extension is already installed and signed in. I keep working instead of waiting for a reset. The same setup carried me through a summer of weak Opus 5 drafts, with Codex as the critic, until [Opus 5.5 fixed Claude's writing](/best-claude-model-for-writing/). A later [Opus 5.5 vs GPT-6 blind test](/opus-5-5-vs-gpt-6/) showed why the critic should come from the other family, because each model's judge favored its own family's writing. The math surprised me. On a $20 ChatGPT Plus plan you get a lot more usage out of [Codex](https://developers.openai.com/codex/ide/) than you would expect, and I would argue more than a $100 a month Claude Max plan gives you if you are running Opus around the clock. I broke that comparison down properly in [ChatGPT Pro vs Claude Max](/chatgpt-pro-vs-claude-max/), where the metering difference turns out to be the whole story. If you are weighing which Claude tier to pay for in the first place, I broke that down in my guide to [which Claude model to use](/which-claude-model-to-use/). ### **Why Both Live Inside VS Code** Two agents need somewhere neutral to sit. [VS Code](https://code.visualstudio.com/) is free, and more importantly it does not care which AI you point at it. Working inside Anthropic's own app or OpenAI's own app means using a room built by a company with a favorite. A neutral editor gives both a fair shot. [Cursor](https://cursor.com/pricing) is a good product, especially for more technical developers. It is more pay-to-play than VS Code, which is why I did not land there. Google's Antigravity is where I get cautious. Google owns Gemini, so Google has an incentive to make every other model feel slightly worse inside their editor. *Skill files sorted by category, which is what both agents read from.* ### **What Both Agents Read From** Running two agents only pays off if they share the same source material. Mine both read from one folder of markdown files. Skills are plain markdown, so the same file works in Claude Code, Codex, OpenClaw, or Hermes without a rewrite. [Nothing is trapped in one vendor's chat history](/ai-anxiety/). I keep mine split by category. Image skills, marketing skills, YouTube skills, and system skills, each in its own folder. Granularity matters more than people think, which is why I push for [separate skill files per job](/claude-skills-best-practices/) instead of one bloated mega-prompt. *A skill file open in the editor. Plain markdown, which is why both agents can use it.* Plenty of good skills are free on GitHub, including Anthropic's own. The reason mine sell is that over 10 years of SEO and marketing decisions are baked into the file, so you are not asking a model to invent best practices it does not have. That is what the **[Claude Code Skills Stack](https://skills.ryandoser.com)** is. Take them, add your own brand assets, and the output gets better than anything a generic prompt returns. ### **What the Shared Folder Unlocks** Once both agents read from folders instead of a chat history, you can point scheduled jobs at the same files. One of mine watches Google algorithm updates and reports back on publishing cadence. It exists because [Google's spam policies](https://developers.google.com/search/docs/essentials/spam-policies) target scaled content abuse, meaning large amounts of unoriginal content built to game rankings rather than help anyone. Volume alone is not the trigger, but volume is what makes a site look like it is doing that. So the job comes back and tells me to post two, three, or five times a day instead of the ten I was running. Acting on that is a risk call, not a rule Google published. The point is that a folder can be automated against and a chat window cannot. ### **Where Two Agents Is the Wrong Answer** This setup is overkill if you are still learning. Two agents means two logins, two bills, and two sets of quirks to figure out. Start in the Claude web app, build a project, write one skill file, then come to an editor once that feels routine. Adding a second agent before the first one earns its keep is just more surface area to manage. The pairing also does not improve your output. It removes a bottleneck and gives you a backup, which is a different thing from knowing what good marketing looks like. ### **Ryan's Final Thoughts** Most people treat this as a choice between Claude Code and Codex. For marketing work it is not a choice, because only one of them makes images and only one of them is up when the other is down. Install both extensions, point them at the same folder of markdown files, and let each do the half it is actually built for. ### **Claude Code and Codex Together FAQs** #### **Can you run Claude Code and Codex at the same time?** Yes. Both ship official VS Code extensions and they run side by side in one window, reading from the same folders. Developers usually warn about two agents editing the same code at once, but that risk barely applies to marketing work like drafting posts or generating images. Keep them on separate jobs and there is no conflict. #### **Why use Codex if you already pay for Claude?** Two reasons. Claude models do not generate images natively, so Codex covers the visual half of a content workflow through GPT Image 2. It also works as a backup when Claude Code is down or you hit a usage limit, so a stalled task costs you a few seconds instead of the rest of the afternoon. #### **Do you need to know how to code to run both?** No. You type plain English into both and each handles the technical part on its own. Marketers use this pairing for blog drafts, SEO research, and image generation rather than software. The editor is just a window with your files visible on the left. #### **Do your skill files work in both Claude Code and Codex?** Yes, because skills are plain markdown documents rather than vendor-specific settings. The same file can be read by Claude Code, Codex, OpenClaw, or Hermes. That portability is the reason to keep instructions in your own folders instead of inside a chat window. --- ## Claude Watermarks Are Here: Why Good Marketers Shouldn't Panic URL: https://ryandoser.com/claude-watermark/ Markdown: https://ryandoser.com/claude-watermark.md Published: 2026-08-11 | Updated: 2026-08-18 Categories: AI News, Claude Code > Anthropic now embeds a Claude watermark in AI-generated text. Here's how it works, what it can't prove, and why quality still decides rankings. Anthropic just announced that every new model will embed a **Claude watermark** in generated text, and half the internet is treating it like a scarlet letter. ### **What the Claude Watermark Actually Does** Before you panic, look at what Anthropic actually shipped. The reality is narrower and less scary than the headlines suggest. Anthropic signed the EU AI Act's Article 50(2) Code of Practice on Transparency of AI-Generated Content. To comply, [Claude models launched on or after August 2, 2026](https://support.claude.com/en/articles/16266773-how-claude-marks-ai-generated-content) mark their output in two ways. First, generated text carries an imperceptible watermark woven into the words themselves. You can't see it or feel it while reading, yet it travels with the text when copied elsewhere. Second, generated files like .png, .jpg, and .svg get signed provenance metadata following the [C2PA open standard](https://c2pa.org/). That metadata records the file was processed by Claude and whether anyone tampered with it afterward. The marking happens at the model level, so it applies across the API, the Claude apps, Claude Code, and Claude Cowork, worldwide. Older models are getting retrofitted, which means the safe assumption is that any Claude output may carry a mark. If you want to go deeper on how I run AI content systems that hold up under this kind of scrutiny, I put together a free resource with my Claude Code skills, automation templates, and systems. Grab the **[AI Marketing Essentials Guide](/ai-marketing-guide/)** to follow along. *Anthropic's four marking commitments for Claude under the EU AI Act's Code of Practice.* ### **Can You Remove or Detect a Claude Watermark?** Here is the part almost everyone gets wrong. A detected mark does not prove Claude wrote something, and a missing mark does not prove a human did. Anthropic says this directly in its own limitations section. A mark only signals that content "may have been processed by Claude," because people use Claude to proofread, translate, and summarize material they wrote themselves. The signal also degrades. Heavy editing, paraphrasing, translation, and short passages can weaken the text watermark, and file metadata gets stripped by screenshots, format conversion, or a simple re-save. *Anthropic's help center page, including its sections on detecting marks and their limitations.* So should you try to scrub it out? No, and not for ethical reasons alone. There is currently no penalty attached to the mark, so stripping it solves a problem that does not exist. Rewriting good copy through another model just to dodge detection is how you turn strong content into mush. ### **Will Google Penalize Watermarked AI Content?** This is the fear driving the freakout, and the evidence says it is misplaced. Neither Google nor Bing has announced any web search ranking treatment tied to provenance marks. [Google's published guidance on AI-generated content](https://developers.google.com/search/blog/2023/02/google-search-and-ai-content) rewards helpful material regardless of how it gets produced. What Google punishes is scaled content abuse: mass-produced pages built to game search rather than help a reader. If you want to see what that looks like as a purchasable product, [I reviewed one that publishes 30 unreviewed articles a month](/outrank-review/). Notice what that distinction means. A human pumping out templated garbage gets hit by the same policy as a bot doing it. I broke down how Google actually treats AI content in my post on [Google's AI search guidelines](/google-ai-search-guidelines-exposed/). The short version holds here: the quality bar is the ranking system, not the authorship test. That could change someday, and I'm watching for it. Until Google announces provenance-based rankings, changing your workflow over watermarks is solving an imaginary problem. ### **My Honest Take on AI Content Watermarks** While everyone freaks out about the announcement, here is what I keep coming back to. Four things, none of them comfortable for the panic crowd. You should always assume AI-generated content carries watermarks. Anthropic told us, but every major lab is under the same EU transparency pressure, so treat marking as the default condition of working with these tools. AI-generated content can still provide value. A watermark records which tool touched the text, and it says nothing about whether the reader got what they came for. AI content ≠ AI slop. Slop is a quality failure, and lazy output earns that label no matter what produced it. Human slop still exists. The thin, keyword-stuffed articles that polluted search for a decade were written by people, and no watermark scheme addresses them at all. My position as an AI-first marketer is simple, and I'm obviously biased here since AI runs half my business. I'm not hiding that I build content with Claude, because the work is reviewed, fact-checked, and published under my name. ### **How I Updated My Claude Skills for This** You've probably wondered whether your own AI workflows need a rethink after this news. Mine needed about twenty minutes of edits, and none of them touch the watermark itself. I added context to my Claude Skill markdown files covering exactly what this policy changes and what it leaves alone. The instructions are blunt: never attempt to strip or launder a mark, never claim content is human-written, and never degrade a draft chasing undetectability. Then the same files double down on preventing the slop fingerprints I can control. Banned-word lists, structure rules that kill templated patterns, mandatory fact verification against primary sources, and a review gate before anything goes live. One line from my internal policy doc sums up the whole stance: "Quality is the defense, not mark-avoidance." Every content skill I run loads that rule before drafting a word. The focus is producing relevant, highly valuable content for your ICP anyway. If your stuff only survives because nobody can tell a machine helped, the watermark was never your real problem. This skill-file approach is the same one I use across my whole content operation. You can see how I structure those instruction files in my **[Claude Code Skills Stack](https://skills.ryandoser.com)**, and my guide to [AI SEO strategy](/ai-seo-strategy/) covers where quality gates fit in the bigger picture. ### **Ryan's Final Thoughts** Watermarks make AI usage visible, and the marketers with the most to lose are the ones betting nobody finds out. Keep publishing content that earns its ranking, disclose honestly, and let the panic crowd burn their energy on detection arms races. It will be interesting to see how this plays out, especially once Anthropic ships its detection tools and other labs follow. My bet stays the same: quality wins, provenance is just context. ### **Claude Watermark FAQs** #### **Does Claude watermark all of its output?** Models Anthropic has launched since August 2, 2026 support marking from day one, with text watermarking applied at the model level rather than per product. That coverage spans everything from the consumer app to the developer surfaces. Generated files get C2PA provenance metadata where supported, and Anthropic is retrofitting older models too, so treat marking as the default across every generation. #### **Can you remove the Claude watermark from text?** Anthropic acknowledges the signal fades when text gets substantially rewritten, translated, or blended into other writing, so it is not indestructible. Trying to defeat it on purpose is still a bad trade. No search engine penalizes the mark today, and rewrites aimed at dodging detection reliably damage the quality that actually determines whether content performs. #### **Does a Claude watermark prove content was written by AI?** No. Anthropic's own documentation frames a detected mark as evidence Claude may have touched the content, which covers proofreading, translating, or summarizing text a human wrote. The reverse holds as well, since an unmarked passage could come from an older model or edited output. Treat the mark as one provenance signal, never as an authorship verdict. #### **Will watermarked AI content hurt my SEO?** Not based on any current policy. Google and Bing evaluate whether content is helpful and original, and neither has tied web search rankings to provenance marks. The real SEO risk remains scaled, low-value publishing, which gets penalized whether a human or a machine produced it. Watch for official announcements before changing your workflow over watermarks. --- ## 7 Best SEO MCP Servers in 2026 (Tested by Agency Owner) URL: https://ryandoser.com/best-seo-mcp-servers/ Markdown: https://ryandoser.com/best-seo-mcp-servers.md Published: 2026-08-10 | Updated: 2026-09-23 Categories: AI SEO > The SEO MCP servers I actually connect to Claude, what each one really costs, and the pricing trap that catches people on the way in. The best **SEO MCP servers** turn your AI assistant from a tool that guesses about your rankings into one that reads your actual data. I connected all seven and I run two of them every single day. Here is what works, what costs more than the pricing page suggests, and which one to install first. Everything here is scoped to SEO work: rank tracking, keyword data, SERP and backlink analysis. If you want the wider marketing stack instead, publishing, video, scraping and analytics, I priced those in [the MCP servers I run for marketing work](/mcp-servers-for-marketers/). ### **What an SEO MCP Server Actually Does** MCP stands for Model Context Protocol. In plain terms, it is a connector that lets Claude or ChatGPT pull live data from a tool instead of relying on training data. That distinction matters more in SEO than almost anywhere else. Ask a chatbot about your rankings without a connector and you get a plausible-sounding answer built from nothing. Ask it with one connected and it reads your Search Console property, your position history, and your click data directly. I use this daily. A typical morning is asking Claude to pull my last 28 days from Search Console, flag pages where position improved but clicks fell, then cross-check the current SERP to see whether an AI Overview now sits above my result. That used to be an hour in three browser tabs. Now it is one prompt. It took me longer than I would like to admit to trust the output. My first instinct was to go re-check everything in the Search Console interface anyway, which rather defeated the point. But the market filled up fast, and most roundups you will find are published by the vendors themselves. SEOptimer ranks its own server first. SE Ranking sells one. Serpstat wrote a comparison that happens to favor Serpstat. I build none of these, so nothing here is me ranking my own product. One link below is an affiliate link, flagged at the bottom, and it did not change the order. Here is the version with the pricing traps left in. ### **The 7 Best SEO MCP Servers in 2026** Ranked on what each one gives you for what it costs to get in, with the two I use daily at the top. Not on how much the vendor charges. The last column is the one to read twice. Advertised price and real entry price are not the same number on every row. | # | Server | Best for | Free option | Real entry price | | 1 | Google Search Console MCP | Reading your own ranking and click data | Yes, permanently | $0, genuinely free and open source | | 2 | DataForSEO | Live SERP pulls and keyword volume | $1 trial credit | Pennies per request, but the minimum top-up is $50 | | 3 | Google Analytics MCP | What visitors do after they land | Yes, permanently | $0, genuinely free and open source | | 4 | OpenSEO | Rank tracking and a simple dashboard on a small budget | $0.50 in credits | $10 per month, usage included | | 5 | SE Ranking | An all-in-one suite behind one connector | 14-day trial, 100K credits | $50 pay-as-you-go for MCP alone, or $103.20 per month billed annually for the suite | | 6 | Semrush | Teams already paying for Semrush | Trial varies by plan | A qualifying paid plan with API units, not a flat connector fee | | 7 | Ahrefs | Backlink analysis inside a chat window | No | $129 per month, because the $29 Starter plan excludes MCP | #### **1. Google Search Console MCP (Free)** *Suganthan Mohanadasan's GSC MCP server, Apache-2.0 licensed with 20 tools built in.* This is the one I open first every morning, and it is free. Built by Suganthan Mohanadasan, it connects Claude straight to your Search Console property and ships [20 purpose-built tools](https://github.com/Suganthan-Mohanadasan/Suganthans-GSC-MCP) rather than a thin API wrapper. The tools are what separate it. Instead of raw query exports, you get named analyses: quick wins, CTR opportunities, content decay, cannibalization checks, traffic drops. I lean on the decay and CTR tools constantly, because they surface the thing raw data hides, which is a page holding its ranking while quietly losing clicks. **Pros:** - Completely free, Apache-2.0 licensed, no usage meter - 20 named analysis tools, not just a raw data pipe - Reads your own Search Console data rather than a third-party estimate of it **Cons:** - Setup needs Google Cloud OAuth credentials, which is the fiddliest install here - The README still documents the clone-and-build path, so the quicker npx install is easy to miss - Last code push was May 2026, so development has slowed **Best for:** Anyone who owns a site and wants their assistant reading real performance data. **Pricing:** Free. Search Console data costs nothing. **Free trial:** Not applicable, the whole thing is free. **Bottom line:** If you install exactly one server from this list, make it this one. Your own data beats any third-party estimate, and it costs nothing. One caveat worth knowing before you rely on it: the submit-URL tools use Google's Indexing API, which Google officially supports only for job posting and broadcast event pages. Treat general-purpose indexing submissions as unsupported rather than guaranteed. #### **2. DataForSEO (Pay as you go)** *The DataForSEO MCP connects through Claude, Claude Code, Cursor, ChatGPT, and Docker.* Search Console tells you how you are doing. [DataForSEO](https://dataforseo.com/?aff=245611) tells you what is happening in the search results themselves, and it is the second server I run daily. It wraps ten API modules covering SERP data, keyword volume, backlinks, on-page audits, content analysis, and an AI optimization module that reads AI Overview citations. The AI optimization piece is why it earns its place in 2026. I use it to check whether a page is being cited inside an AI Overview, which is now a separate question from whether it ranks. Those two answers regularly disagree on my own pages. **Pros:** - Genuinely cheap per request, starting at $0.0006 per SERP - Ten modules behind one connector, including AI Overview citation data - The MCP server itself is free and open source, so you pay only for data **Cons:** - The $50 minimum top-up is a real barrier for casual use - Credit-based billing makes monthly cost hard to predict up front - Raw data output needs interpretation, it will not hand you a strategy **Best for:** SEOs who want live SERP and keyword data without a subscription. **Pricing:** Pay as you go from a prepaid balance. A queued standard SERP request runs $0.0006, priority $0.0012, and live mode $0.002. Worth knowing that MCP tools calling the live endpoint hit that $0.002 rate rather than the headline figure, and deeper result sets cost more than the base ten results. **Free trial:** Yes, a $1 credit on signup with no card required, plus a free sandbox for structural testing. **Bottom line:** The best value on this list if you can clear the deposit. That $1 credit buys hundreds of SERP pulls, which is plenty to decide whether it fits your workflow. Read the pricing carefully, because two true facts sit in tension. You genuinely can start free with a $1 credit and no card. But the minimum payment once you want to add funds is $50, not $1. Both are accurate, and only quoting the first one sets people up for a surprise. #### **3. Google Analytics MCP (Free)** *Google's own Analytics MCP server, actively maintained under the official googleanalytics org.* Published under Google's own GitHub organization, this one pairs naturally with the Search Console server. Search Console covers acquisition and GA4 covers on-site behavior. The two data sets do not join cleanly at the query level, but having both connected means your assistant can reason across them instead of you exporting from two dashboards. It carries 2,900 stars and had code pushed within the last week. That matters in a category where plenty of servers were built once and abandoned. **Pros:** - First-party Google, published by the official googleanalytics org - Free and Apache-2.0 licensed, with no data charges on the GA4 API - Actively maintained, with releases shipping regularly **Cons:** - Google labels it experimental in the repo README - Needs Google Cloud credentials, same setup friction as the GSC server - Only useful if you already run GA4 properly **Best for:** Pairing with the Search Console server for a full picture. **Pricing:** Free. **Free trial:** Not applicable. **Bottom line:** Install it alongside the GSC server. Two free connectors covering acquisition and behavior are a strong base before you pay for anything. #### **4. OpenSEO ($10 per month)** *OpenSEO bills itself as the open source alternative to the big SEO suites.* [OpenSEO](https://openseo.so/) is the newest entry here and the cheapest paid one. A single $10 monthly plan includes $10 of usage, and there are no tiers to compare, which is refreshing in a category that loves a pricing matrix. What it adds is a workflow layer: scheduled rank tracking with history, its own site audit crawler, saved project context your agent reads, and reports you can share. The underlying SEO data comes from DataForSEO, and the hosted plan adds a 28% markup, so if you already run that server you are mostly paying for the tracking and the interface. It also tracks AI mentions and compares prompts across models, but those features live in OpenSEO's web app, and its MCP server does not expose them yet. I went through what the $10 actually buys in my full [OpenSEO review](/openseo-review/). **Pros:** - One $10 plan with no tier puzzle, and usage included in it - Scheduled rank tracking with history, which a raw data connection does not keep - Free to self-host, though you bring your own DataForSEO key and pay that usage directly **Cons:** - Core SEO data comes from DataForSEO, so there is overlap if you run both - Newest and least battle-tested option on this list - Credit-based usage means heavy months cost more than $10 - AI visibility lives in the web app, not in the MCP server **Best for:** Scheduled rank tracking and a simple SEO dashboard without a suite subscription. **Pricing:** $10 per month including $10 of usage, with top-ups that roll over. **Free trial:** Yes, $0.50 in credits with no card required. **Bottom line:** A low-cost way to add rank tracking history and a dashboard on top of DataForSEO data. Skip it if you already run DataForSEO in your agent and do not need tracking history. #### **5. SE Ranking ($103.20 per month, billed annually)** *SE Ranking bundles MCP access into every subscription tier.* [SE Ranking](https://seranking.com/) puts 180-plus SEO and GEO tools behind one connector, covering keyword data, backlinks, audits, and AI search visibility. Setup is among the easiest here, because it is a hosted remote server. You authorize it and you are running, with no local install or Docker. The pricing structure is the friendliest of the paid suites. MCP access is bundled into every subscription rather than sold as an add-on, and how much you can pull depends on the API credits in your plan. **Pros:** - MCP bundled into every plan, never an upsell - Hosted setup takes minutes, no terminal required - Generous 14-day trial with 100,000 credits and no card **Cons:** - Real cost is a full suite subscription, not a connector fee - Credit ceilings mean heavy API use can outrun your plan - Overkill if you only want data piped into Claude **Best for:** Agencies that want a full suite and a connector on one bill. **Pricing:** Core is $103.20 per month billed annually, or $129 month to month. Growth is $223.20 annually or $279 monthly. There is also a standalone API path at $50 for 250,000 credits with no subscription. **Free trial:** Yes, 14 days with 100,000 credits and no card required. **Bottom line:** The best paid pick if you want one vendor for everything. If you already own a suite you like, the connector alone does not justify switching. #### **6. Semrush (Requires a qualifying paid plan)** *Semrush's MCP docs list Claude, Claude Code, ChatGPT, Cursor, and more.* If your team already pays for [Semrush](https://www.semrush.com/), the MCP server is the obvious move, and the documented client support is broad. Claude, Claude Code, ChatGPT, Cursor, VS Code, Antigravity 2.0, Antigravity CLI, Perplexity, and Lovable all have their own setup guides. Note that Gemini CLI support has been discontinued, since Google is moving that tooling to Antigravity. It runs as a hosted remote server with OAuth, so setup is straightforward. The complication is eligibility, which depends on a specific combination of plan and API units rather than a simple tier check. I untangled which plan actually carries it, and why Semrush's own pages disagree, in [Semrush API pricing](/semrush-api-pricing/). **Pros:** - Setup guides published for nine different AI clients - Hosted with OAuth, no local install - Taps the same data an existing Semrush workflow already trusts **Cons:** - Access depends on which plan you hold plus available API units - Traffic and market data needs a separate Trends subscription - No standalone free tier for the connector **Best for:** Teams already inside the Semrush ecosystem. **Pricing:** Requires an active qualifying subscription with API units included. Check your plan against their docs before assuming access. **Free trial:** Semrush advertises a seven-day trial on eligible plans, but there is no free MCP tier on its own. **Bottom line:** Sensible if Semrush is already your stack. Not a reason to become a Semrush customer. One setup detail that trips people up: the current endpoint is version two, and a number of third-party tutorials still publish the version one path. Use the official docs rather than a blog post. #### **7. Ahrefs ($129 per month)** *Ahrefs MCP pulling an organic traffic dashboard directly into a chat window.* [Ahrefs](https://ahrefs.com/mcp/) has backlink data that few competitors match, and querying it conversationally is genuinely useful. Ask for a traffic timeline and it builds one. No separate API purchase is needed, since MCP access comes with the subscription and runs on your monthly API units. It lands last purely on cost. It sits in the same price band as the other paid suites here, but the entry price is not the number most people have in their heads. Choosing between this and the pick above it is a question I answered separately in [DataForSEO vs Ahrefs](/dataforseo-vs-ahrefs/). If the $50 minimum top-up is what is stopping you, [a few of the alternatives start smaller](/dataforseo-alternatives/). Semrush sits in a different category again, since most of what its plan covers has no per-request equivalent, which I broke down in [this comparison of the two](/dataforseo-vs-semrush/). **Pros:** - Backlink index that remains an industry benchmark - No separate API contract, it is included in the plan - Clean conversational output, including chart building **Cons:** - The $129 Lite plan is the real floor, which is steep for a connector - Row caps limit Lite to 100 rows per request - No free tier, and Webmaster Tools does not grant access **Best for:** Backlink and competitive analysis at agency budgets. **Pricing:** Lite at $129 per month, Standard $249, Advanced $449. API units and row caps scale with the plan. **Free trial:** No. **Bottom line:** Worth it if backlink data drives your work and you already pay for Ahrefs. Otherwise the price is hard to justify for a connector. Here is the trap, and it is the single most useful thing in this post. Ahrefs sells a Starter plan at $29 per month, and Starter does **not** include MCP access. The eligible plans are Lite, Standard, Advanced, and Enterprise. Starter is still a real product with Site Explorer and Keywords Explorer in it, so you would not be buying nothing. You would be buying a plan that cannot do the one thing you came for, and the fix is a jump to $129. Most of the confusion around this comes from third-party pages quoting retired figures, which I untangled in [Ahrefs API pricing](/ahrefs-api-pricing/). ### **How to Choose an SEO MCP Server** These are the questions I work through on every client setup, and they apply regardless of which tools you are weighing. - **Do you need your data or the market's data?** Search Console and GA4 read your own measured performance. The paid suites add competitor and market data you cannot get from your own properties. - **Is the pricing a subscription or a meter?** A meter like DataForSEO costs almost nothing on light use and scales with you. A subscription costs the same in a quiet month. - **What is the real entry price, not the advertised one?** Check which specific plan includes MCP access. Ahrefs is the clearest example of a gap between the two. - **Hosted or local?** Hosted servers take minutes. Local ones need a terminal, and sometimes Google Cloud credentials. - **Does it cover AI search?** Blue-link rankings no longer tell the whole story. DataForSEO and SE Ranking read AI visibility, OpenSEO covers it in its web app rather than its MCP server, and the [standalone AI visibility trackers](/best-ai-visibility-tools/) are a separate purchase with their own pricing traps. - **Is it still maintained?** Check the last commit date before trusting a free server with your workflow. I run the Search Console and DataForSEO servers daily, and I have connected and tested every other pick on this list. Every price was checked live on each vendor's own page the day this published. Where a figure could not be verified from a primary source, I left it out rather than guess. ### **Which SEO MCP Server Should You Install First?** Start with the Google Search Console MCP. It is free, it reads your own Search Console data rather than an estimate of it, and it changed how I audit. Add DataForSEO second if you can clear the $50 deposit, because live SERP and AI Overview data is what turns your own numbers into decisions. Add the Google Analytics server third, since it is free and completes the picture. Only then consider a paid suite, and only if you want the suite anyway. If you are building a broader stack, my roundup of the [best AI SEO tools](/best-ai-seo-tools/) covers the tools that sit outside the MCP category, and my [AI SEO strategy guide](/ai-seo-strategy/) covers what to do with the data once it is flowing. ### **What About Free Community Servers?** There are open-source SEO MCP servers on GitHub that scrape paid tools rather than using official APIs, and some are genuinely popular. I am leaving them off deliberately. The most prominent one, cnych/seo-mcp, scrapes Ahrefs and requires a paid CapSolver account to defeat bot protection. Its own README asks you not to misuse it, and it has not been updated since April 2025. Building client workflows on a scraper that violates another company's terms is a risk I would not take on, and not one I would recommend to a reader. The free servers I do recommend here, from Google and Suganthan, use official APIs. ### **Ryan's Final Thoughts** The server I run daily and pay nothing for is Search Console, and it is the one I would install first. DataForSEO is the other daily one, and it costs me pennies per pull, which I break down properly in my [DataForSEO review](/dataforseo-review/). That combination is the part most roundups skip past, because most roundups are written by companies with a subscription to sell. So my advice is boring. Start free, prove the workflow, then pay for data you have already confirmed you need. If you want help building this into a real system, that is what my [AI SEO consulting](/ai-seo-consulting/) work covers, and you can see who else is doing serious work in this space in my list of the [best AI SEO experts](/best-ai-seo-experts/). Some links in this post are affiliate links. If you sign up through them I may earn a commission at no extra cost to you. I only recommend tools I have connected and used myself. See my [full disclosure](/disclosure/). --- ## How to Create Claude Skills: 4 Methods That Actually Work URL: https://ryandoser.com/claude-skills/ Markdown: https://ryandoser.com/claude-skills.md Published: 2026-08-10 | Updated: 2026-09-25 Categories: Claude Code > How to create Claude Skills 4 ways, from a blank prompt to screen recording. Which method to pick, what breaks, and how to update one. If you want to know **how to create Claude Skills**, there are four methods, and the right one depends on what you already have. Here's each one, and how to pick. Claude Skills are the fastest way to stop repeating yourself every time you open a chat. ### **How Claude Skills Actually Work** Most people using AI in 2026 are still working without context. They paste the same instructions over and over, rebuilding preferences from scratch every session. That's a slow, broken workflow. Claude Skills fix that. A skill is a Markdown file that acts as an instruction manual for Claude Code. You write your style rules, output format, and preferences once. Claude follows them consistently every time. I have 15 to 20 skills in my Claude Code setup. An anti-slop skill that catches generic AI phrases before they ship. An email newsletter skill that knows my exact voice. A social media skill that handles post formatting without re-explaining anything. Well-organized instructions, saved as Markdown files. I've written up [the ten marketing skills in that set](/best-claude-marketing-skills/) if you want to see what each one actually does. One thing to call out first: you need a paid Claude plan for Claude Code. I'm on Claude Max at $100 a month. Claude Pro at $20 a month caps out fast. That's just the reality. ### **Method 1: Build a Claude Skill With No Existing Context** You don't need existing work to create a useful skill. This method works from scratch. Open Claude Code or [Claude.ai](https://claude.ai) and run a prompt like: "I need you to create a skill.md file for writing high-quality email newsletters in my writing style and tone." The more specific the prompt, the better the output. If you have one example of what you want, paste it in. A sample email, a blog post, a social caption. Also add Anthropic's official [best practices for creating Claude skills](https://code.claude.com/docs/en/skills) to your prompt. It gives Claude a framework to follow when building your skill file. I used Opus 5 with extended thinking on. A few minutes later: a full Markdown file covering voice, structure, sign-off patterns, and banned phrases. Download it, drag it into your skills folder in Claude Code, and it's ready. The real power is refinement. If Claude writes an email that misses the mark, tell it what to fix and add: "Update this skill Markdown file going forward." Claude shows you a diff and asks for confirmation before saving. Every fix improves the skill permanently. You're not correcting one output. You're improving the instruction manual for every future one. [My Claude Code Skills Stack](https://skills.ryandoser.com/) has 20+ skills I use daily to automate marketing and content creation with a one time fee and lifetime updates. #### **How to Activate Your Skill in Claude Code** Once the file is in your skills folder, reference it in chat: "Write an email on the best AI tools. Use the email-writer-skill.md." Claude confirms it read the file and follows those instructions for the session. ### **Method 2: Create a Claude Skill From an Existing Project** This method produces a much richer skill. If you already have a [Claude Code](https://code.claude.com/docs/en/overview) project, a ChatGPT custom GPT, or a Google Gem with chat history and uploaded files, don't start over. Use what you've already built. The prompt: "Create a skill.md file for this Claude project using best practices. Use my chat history, instructions, and files in this project to help." Add Anthropic's skill documentation, set it to Opus 5 with extended thinking, and run it. What you get back is noticeably better than Method 1. My email newsletter project had months of refinements, subject line data, and dozens of real examples. The skill Claude generated was far more detailed than anything it could have produced cold. You're converting existing work into a portable instruction file that works anywhere in Claude Code. ### **Method 3: Use a Skill Creator Skill Inside Claude Code** This is the method most people skip, and my favorite. Inside Claude Code, I have a folder called system skills, separate from my main skills folder. It holds three files: a troubleshooting skill, an MCP setup skill, and a skill creator skill. The skill creator does exactly what it sounds like. It builds other skills. Anthropic offers their own version in the [official Claude Code GitHub repository](https://github.com/anthropics/claude-code). Grab it from there, or build a customized version like mine. Here's how it works in practice. Start a fresh chat in Claude Code and run a prompt like: "Use the skill-creator.md skill to create a new skill for writing email newsletters. Use my examples in the past email newsletters folder for reference. Name this skill email-newsletter-writer-demo and save it in my skills folder." Three things matter in that prompt: point to real examples in your file system, name the output file, and specify where to save it. When you give Claude Code that level of specificity, it does exactly what you asked. The new skill file appeared in my skills folder automatically, named correctly. The advantage over Methods 1 and 2: everything stays inside Claude Code. No copy-pasting between windows, no downloading and dragging files. Claude writes the skill, saves it to the right folder, and it's available in your next chat. ### **Method 4: Record a Skill by Screen Recording (New)** Anthropic shipped a fourth path in July 2026, and it is the easiest yet. It is called Record a Skill, and it lives in the + menu of the Claude desktop app under Cowork. Instead of writing instructions, you record your screen while you do the task and narrate what you are doing out loud. Claude watches the clicks, keystrokes, and your commentary, then turns the whole demonstration into a reusable skill. It is available on Pro, Max, and Team plans. This is the option to hand a non-technical teammate. If someone can talk through their own job while doing it once, they can build a skill now. No Markdown, no prompt structure, no file paths. ### **Final Notes from Ryan** Claude Skills are instruction manuals saved as Markdown files. Using them consistently is what separates people getting great AI results from people still copy-pasting prompts every day. Start with one skill for a task you repeat. Refine it, then build the next one. Pick the method that fits where you are and ship it. ### **Where to Go After Your First Skill** Building one skill is the easy part. Deciding what to build next, and whether to build it at all, is where most people stall. Here is the rest of what I have written on skills, grouped by what you are actually trying to do. **If you are still deciding whether skills are the right tool:** I compared them against [Custom GPTs](/claude-skills-vs-custom-gpts/), [Gemini Gems](/claude-skills-vs-gemini-gems/), and [Perplexity Spaces](/claude-skills-vs-perplexity-spaces/). The Perplexity one is the odd comparison of the group, because Spaces and Skills are not competitors at all. One helps you research, the other helps you ship, and using both in sequence beats picking one. **If the vocabulary is the problem:** skills, agents, MCP servers, and slash commands get used interchangeably by people who should know better. I untangled [what each one actually does and which to learn first](/claude-skills-vs-mcp-vs-agents/), including the one that quietly got absorbed into another this year. **If you already have a Claude Project you rely on:** you do not have to start over. [Rebuilding a Project as a portable skill file](/turn-claude-projects-into-skills/) takes an afternoon and hands you something you can version, back up, and move. If you are still deciding between the two, I compared [Claude Skills vs Projects](/claude-skills-vs-claude-projects/) and where each one actually fits. **If you want skills without writing them yourself:** start with the free route. I ranked [the seven GitHub repos worth your time](/best-free-claude-skill-repos/) and which ones are graveyards, then covered [the eight worth installing first](/best-claude-skills/) across free and paid. There is [no official marketplace yet](/claude-skills-marketplace/), so knowing how to vet one before you run it matters more than it should. And before you buy anything, my [free vs paid test](/free-vs-paid-claude-skills/) is three questions long. I sell a paid stack and I still tell most people to start free. **If your skills work but the output is mediocre:** that is usually the skill file, not the model. The [nine rules I follow](/claude-skills-best-practices/) cover one skill per task and self-improving files, and the [personalization step](/claude-code-skills-hack/) is the one people skip when they install someone else's skill and wonder why it sounds like someone else. **If you want to point skills at a specific job:** I have written up [the eight I use for SEO work](/claude-skills-for-seo/) and [the ten marketing skills I run in production](/best-claude-marketing-skills/). **If you want to sell what you build:** packaging skills as a digital product is a real path, and I have documented mine end to end in [how to sell Claude skills](/sell-claude-skills/), [the first $5K](/claude-ai-side-hustle/), and [the $10K version with the Stripe screenshots](/make-money-with-claude/). If you would rather skip the building entirely, my [Claude Code Skills Stack](https://skills.ryandoser.com/) is the set I actually run, and [V2 covers what changed](/claude-code-skills-stack-v2-update/) in the latest update. ### **Claude Skills FAQs** #### **What are Claude Skills and how do they work?** Claude Skills are Markdown files that act as instruction manuals for Claude Code. You write your preferences, style rules, and output structure, save the file in your skills folder, and reference it in chat. Claude reads the file and follows those instructions for the session. They carry over across every conversation. #### **Do I need a paid plan to use Claude Skills?** Not for the Claude web app. Anthropic lists Skills on the Free, Pro, Max, Team, and Enterprise plans with code execution turned on, and you add them under Customize > Skills. Claude Code is where skills do the most, and there Claude Max at $100 per month is the plan worth using, since Claude Pro at $20 per month ($17 billed annually) caps out quickly. #### **How is a Claude Skill different from a Claude Project or custom GPT?** Projects and GPTs keep your instructions inside a hosted app, and updating them is tedious. OpenAI now migrates retiring GPTs into plugins, but those still live on its servers. Claude Skills are portable Markdown files that live in your file system. They update through natural conversation, carry over between sessions, and aren't platform-dependent. #### **What's the best method for creating a Claude Skill?** Start with Method 1 if you have no existing context. Use Method 2 if you already have a Claude project or custom GPT with history to convert. Use Method 3 if you're already inside Claude Code and want everything managed in one place. Method 4, Record a Skill, is the fastest for non-technical users since you just screen record the task. See the sections above for the full breakdown. #### **Can I update a Claude Skill after I create it?** Yes. Give Claude feedback on an output, add "update this skill Markdown file going forward," and Claude shows you a diff of proposed changes before saving. Each session improves the skill. Over time, you get better outputs with less back-and-forth. #### **Where are Claude Skills stored?** In Claude Code, which is how I run mine, skills live as folders on your own machine, each containing a `SKILL.md` file. That is the practical difference from a Project or a custom GPT: because a skill is just a file in a folder, you can version it, back it up, copy it to another machine, or hand it to someone else. Anthropic's docs cover the web app path separately, where uploaded skills live in your account under Customize > Skills rather than on disk. #### **Can I create Claude Skills without Claude Code?** Yes. Per Anthropic's documentation, the Claude web app lets you create a skill under Customize > Skills, and you can upload a skill folder as a ZIP. The structural difference is file system access. A skill that only shapes how Claude writes does not need it. A skill that reads your project files, runs scripts, or chains into a build does. That is why all four methods above are written for Claude Code, which is where I build mine. --- ## Why Most Online Communities Go Quiet (And How to Fix It) URL: https://ryandoser.com/how-to-build-an-online-community/ Markdown: https://ryandoser.com/how-to-build-an-online-community.md Published: 2026-08-10 | Updated: 2026-08-10 Categories: AI Rabbit Holes > Why most online communities go quiet, and how to build an online community people actually post in, from my admin who has run one for a decade. If you are about to launch a Skool community, most advice on **how to build an online community** skips the first question you should answer, which is whether you should build one at all. I sat down with [Catherine Eadie](https://www.linkedin.com/in/catherinemhscot/), the admin behind my AI Marketing Insiders community, who has been part of online communities since the late 1990s and ran one of her own for over a decade. ### **How to Build an Online Community Video Guide** Catherine and I recorded this episode because every AI creator on the internet seems to be launching a Skool community right now. She has watched this exact pattern play out before, with different topics, going back to newsgroups. Her opening argument was not the one I expected from someone who runs a community for a living. If you want the setup my members actually learn once they are inside, I put together a **[Claude Code Skills Stack](https://skills.ryandoser.com)** with the workflows and templates I run my own business on. ### **Start By Asking If You Should Join Instead** Catherine's first point was blunt, and it undercuts most of the launch advice out there. "I look at a lot of communities and think they could go and join someone else's," she said. "They don't need to create their own necessarily." The distinction she draws is between wanting a community and having your own idea for one. She calls that second thing community ownership, and thinks the honest reason to own rather than join is controlling the narrative. A lot of the current wave, in her words, is "kind of a lot of it is are echo chambers." I keep a running list of the ones I think are worth paying for in my roundup of the [best AI communities](/best-ai-communities/), and it is a short list for exactly this reason. "AI communities are the thing just as many years ago something else was the thing for communities," she said. "And then they eventually dwindled off." That history matters if you are deciding where to spend the next two years. The theme has changed more than once in her experience while the underlying dynamics stayed identical. My own reason for owning one is economics. You control the distribution and the revenue recurs, which a one-off course sale does not. Both things can be true. The wave will pass, and owning the room is still better than renting attention on someone else's platform. ### **Get Your ICP Right Before You Chase Growth** The fastest way to wreck a community is to fill it with the wrong people. Instead of telling everyone interested in AI to join, you need a narrow ideal customer profile. Shotgun recruiting is what makes churn rates terrible. Here is the mechanic. Someone joins, decides the room is not relevant to them, and then either lurks forever or cancels outright. I will admit on the record that mine is still too wide. Business owners, marketers, and content creators is three audiences, and saying it out loud made me realize we need to narrow it further. Catherine added a churn cause I had not considered, which is that some people join because they feel obligated to. "People thinking that they need to be looking at AI," she said. "Everyone's being told to upskill themselves and find out about AI." Those members were never going to stay. They joined out of fear of falling behind, not because they had a problem your community solves. She suspects AI-era churn numbers are probably inflated by people who never needed to be there in the first place. ### **Lower Your Expectations on Engagement** Catherine cited a participation split that stops most new community owners cold. "Around about 90% of people lurk in communities, just generally, wherever they're based," she said. "About 9% comment and only 1% do actually create the most of it." She was working from community engagement material she had been reading rather than her own data. The ratio matches the [90-9-1 rule of participation inequality](https://www.nngroup.com/articles/participation-inequality/) that Jakob Nielsen documented in 2006, which is worth knowing before you panic about your own numbers. Her advice is to lower your expectations a little rather than fight it, because lurking is a given. She also pointed out that raw member counts hide dead accounts, because cancelling a subscription is annoying enough that people simply forget. I would add a warning about the numbers you see advertised. You can invite people for free, pad the roster with friends, and present a five-figure member count that nobody is paying for. *Catherine's own MHScot site, which she moved off WordPress using what she learned in the community.* ### **Facilitate Instead of Telling People What to Do** Catherine's operating philosophy comes from education, and it is the sharpest distinction in the whole episode. "I always talk about being a facilitator, not a trainer," she said. "I'm not there from a university to lecture." The failure pattern she sees everywhere is a feed of instructions. Do this, try that, go to this website, use this tool. Facilitating looks different. You guide someone toward working out what will actually move them forward, then let them do it. She has a concrete test for whether it is working, and it is not the like count. "A lot of communities the comments are very short," she said. "Oh, that was great. Thanks very much. Doesn't add a lot of value." What she wants instead is a thread that keeps going. Someone posts what they built with a screenshot, another member says they do not understand a piece of it, and the conversation continues from there. Screenshots do a lot of work in that pattern, because showing the thing beats describing it. *Catherine's applied learnings log, where corrections become candidate rules with the date each was approved. She stresses that some get rejected.* ### **Show Up Yourself, on Calls and in DMs** The single biggest thing we do is the weekly live call I host for VIP members. It is real-time Q&A where people can put me on the spot, which is the opposite of what most communities offer. In too many rooms you get an AI-generated reply to your comment, or you never speak to the creator at all. Catherine's signal that these calls are working, pointing at our recent Friday catch-ups, is that they run long. "We've often got the time and we're still chatting away when time's up," she said. "Often you're having to call time and say, no, I need to head off now." She rates direct messages just as highly as the calls. She described a member flagging a spam DM in our community a few weeks back, which she sorted out. That small exchange does more for retention than any automated sequence would. Her summary of the whole retention problem is almost aggressively simple. "It's that personal interactions through your live calls, your DMs, and just being a nice person," she said. "Be human. Be nice. Be kind. Be respectful. Help people out." There is a reason that lands harder now than it would have three years ago. As AI floods every channel, people are craving proof they are talking to an actual human. ### **Promise a Real Deliverable, Not Autopilot** The most common lie in community marketing is that you will join, receive a swarm of agents, and run your business hands-off. That is not how any of this works. Agentic setups without context produce slop, which I have said enough times that my members can probably recite it. People need direction, then they need to do the work themselves. Ours is specific: get comfortable setting up Claude Code, [build your own skills](/claude-skills/), and move off the chat-window habit toward tools that actually run your knowledge work. Catherine is the proof that it lands. She moved her [workplace wellbeing site](https://www.mentalhealthscot.land/), established since 2014 and running to what she estimated at 23 or 24 pages, off WordPress onto a modern stack. She says the transition itself is done, with finer tweaks still ahead, and reports getting through her priorities in roughly 70% less time than before. One change she showed me took under a minute. She had switched from Zoom to Teams, and the word "Zoom" was still sitting on eight pages of her site. Eight pages, one word, done in under 60 seconds. She started from one of my Astro walkthroughs, and if you want the same workflow my [AI website tutorial](https://youtu.be/xgt5K13Km7k) covers it, alongside my written guide to [building a website with Claude](/build-a-website-with-claude/). She now documents her own AI work at [AI Runs My Business](https://airunsmybusiness.co.uk/) and on her [YouTube channel](https://www.youtube.com/@CatherineEadieMHScot). *The weekly briefing Catherine runs on Mondays and Fridays, which surfaces what needs her attention.* That is what a deliverable looks like. Not a promise about agents, but a member with a shipped thing she can point at. ### **Measure Member Outcomes, Not Member Counts** Catherine kept returning to one instruction about metrics. "We need to move away from metrics," she said. "Forget the numbers." Her version of a win is one person who got somewhere, which she rates above thousands of accounts doing nothing at all. Mine works the same way. A member took [the SEO skills I share](/claude-skills-for-seo/) and used them to run an audit and win a client worth 10 to 15 thousand dollars. That is worth more to me than the subscription revenue, because somebody actually built something with what we taught. Catherine's twelve-month prediction is the reason this matters more every month. "AI kind of makes writing a good post free," she said. "But it's not evidence of anything really. It's people being there." Read that twice if you run a community. When a polished post costs nothing to produce, post quality stops proving your room is alive. What survives as a signal is the richness of the content and whether people actually learned something from it. She is not predicting the weaker rooms disappear. Her view is that they probably stick around, and it comes down to the person running each one. ### **Final Thoughts from Ryan** If you are deciding whether to launch, take Catherine's test seriously and check whether you could just join someone else's room instead. Already running one? The work is narrower than most advice suggests. Tighten your ICP, show up on calls and in DMs, hand people direction they can act on, and judge yourself on what members ship. The AI wave will pass like every theme before it. Communities built on a real person helping real people are the ones still standing when it does. ### **How to Build an Online Community FAQs** #### **Should I start my own online community or join an existing one?** Join an existing one unless you have a specific idea you want to develop yourself. Catherine Eadie's test is whether you actually need your own room or whether an existing community already serves that need. The legitimate reason to own rather than join is controlling the narrative around your own concept, not simply wanting a community to exist. #### **What percentage of community members actually participate?** Roughly 90% lurk, 9% comment occasionally, and 1% create most of the content. This split is known as the 90-9-1 rule of participation inequality, documented by Jakob Nielsen in 2006. Catherine Eadie cited the same ratio on the episode and her advice is to lower your expectations accordingly, because lurking is the normal default rather than a sign your community is failing. #### **How do you reduce churn in a paid community?** Start with a narrow ideal customer profile instead of recruiting everyone interested in the topic. Members who join a room that does not match their situation either lurk or cancel. After that, churn comes down to showing up personally through live calls and direct messages, plus giving members direction specific enough that they can act on it and see a result. #### **Does a high member count mean a community is good?** No. Ryan Doser warns that counts can be padded with free invitations, so a roster in the tens of thousands can represent very few paying members. Catherine Eadie adds that dead accounts accumulate because cancelling is inconvenient enough that people forget. Look instead at whether conversations continue past a single comment and whether the creator responds personally. #### **How is AI changing online communities?** AI makes a well-written post free to produce, so post quality no longer proves a community is active. Catherine Eadie's prediction is that the differentiator becomes the richness of the content and the valuable learning members get from it. She adds that weaker communities will probably stick around anyway, since it comes down to the person running each one. Ryan Doser's related argument is that as AI content spreads, members increasingly crave live human interaction. --- ## 12 AI Content Creators to Follow in 2026 (No Hype) URL: https://ryandoser.com/ai-content-creators-to-follow/ Markdown: https://ryandoser.com/ai-content-creators-to-follow.md Published: 2026-08-07 | Updated: 2026-08-10 Categories: AI Resources > 12 AI content creators to follow, ranked by what they ship off YouTube instead of subscriber count. Credentials checked live, plus who to skip. Picking **AI content creators to follow** off subscriber count alone is how you end up with a feed full of people reacting to model releases they have never used. So I judged this list on a different signal. Not the channel. What each person publishes everywhere else. Every number below came off a live page in August 2026, and I say plainly who each person is wrong for. Here is the short version, including why I think most of this category is not worth your time. ### **Why subscriber count is a weak signal on its own** Almost every roundup in this category ranks people by how many subscribers they have. Reach is real, and I am not going to pretend it means nothing. It just does not tell you whether someone has done the thing they are teaching. That is the gap I care about. Audience size and demonstrated practice are two different measurements, and the second one is hard to fake. So I looked for evidence of practice outside the channel. Something with a price on it. A back catalog long enough to show the work is a habit. A community where people can ask follow-up questions in public. A credential issued by somebody other than the person claiming it. None of that proves someone teaches well. It does prove they are exposed to being wrong, which is the part reach alone never guarantees. One honest exception up front. Matt Wolfe is on this list precisely for news-cycle coverage, which is the behavior I just described as weak evidence. He earns it a different way, and I explain how in his entry. The result is a list where the smallest channel might teach you the most. One person here has 635 subscribers and a PBS feature. Another has 992K and earns the spot for a completely different reason. ### **Which of my lists do you actually want?** I have written about this territory twice before, and the three pages answer different questions. Rather than make you guess, here is the fork. If you want **which channels to subscribe to**, judged as channels, read my [best AI YouTube channels](/ai-youtube-channels/) roundup. That one ranks the viewing experience and is the right starting point if you are building a watch list. If you want **software that makes content** rather than people who teach it, read the [best AI tools for content creators](/best-ai-tools-for-content-creators/). Repurposing, video editing, voiceovers and images, with the limits on each. This page is the third question. Not which channel is good, but which of these people has evidence of doing the work off the channel, and where that evidence lives. Some names appear on both lists, and the reason each one is here is different from the reason it is there. ### **The 12 best AI content creators to follow in 2026** The AI content creators to follow in 2026 are Sabrina Ramonov, Chris Koerner, Ryan Doser, Mark Kashef, Riley Brown, Authority Hacker, Matt Wolfe, Corey Ganim, Sandy Lee, Corbin Brown, Brooke Wright and Aaron Makelky. Each entry below names where they publish besides YouTube, and each one says who should skip them. This is not a scored ranking and I am not going to pretend it is. It runs roughly from the broadest teachers toward the most specialised. Read the "skip if" line as carefully as the rest, including on my own entry. | Creator | YouTube | Where else they publish | Best for | | Sabrina Ramonov | 347K | Substack past 236K subscribers, ships Blotato | Solopreneurs wanting agent systems that run | | Chris Koerner | 655K | Weekly newsletter, 400+ episode podcast, 3 communities | Business ideas, not AI tutorials | | Ryan Doser | 39.2K | Newsletter, Skool, Claude Skills Stack, consulting | Marketers using Claude Code | | Mark Kashef | 81.7K | O'Reilly courses, Microsoft Learn, consultancy | Prompting and agent depth | | Riley Brown | 269K | 636K on TikTok, co-founded Vibecode ($9.4M seed) | Building apps with AI | | Authority Hacker | 47.2K | 400+ episode podcast, AI Accelerator membership, newsletter | SEO and affiliate operators moving to AI | | Matt Wolfe | 992K | FutureTools.io, newsletter, HubSpot-published podcast | Knowing what launched this week | | Corey Ganim | 22.1K | 188-episode podcast, newsletter, co-founded Return My Time | Operators who already run a business | | Sandy Lee | 66.1K | Skool community, Substack, podcast | Non-technical people starting from zero | | Corbin Brown | 181K | Ships Thumio, sells Boost OS one-time | Building software without coding | | Brooke Wright | 9.1K | Skool membership, 31-episode podcast, live event | Women founders scaling with AI | | Aaron Makelky | 635 | PBS-featured classroom work, workshops, school training | Teachers and non-coders adopting AI | #### **1. Sabrina Ramonov (Best for agent systems that actually run)** *Sabrina Ramonov's channel covers AI prompts, playbooks and agent systems.* [Sabrina Ramonov](https://www.youtube.com/@sabrina_ramonov) sits at 347K YouTube subscribers, and the channel is the smallest part of what she does. She writes long technical walkthroughs at [sabrina.dev](https://sabrina.dev), where the newsletter reports over 236,000 subscribers, and she ships an actual product in [Blotato](https://www.blotato.com/?ref=rdoser). Running the software means customers report the failure modes to her directly, which is a feedback loop tutorials alone do not create. The credentials hold up to checking, which is rarer here than it should be. She studied Computer Science and Physics at UC Berkeley, made the [Forbes 30 Under 30](https://www.forbes.com/profile/qurious/) list for enterprise technology, and the NLP startup she co-founded was acquired by Pegasystems in 2021. Pega never disclosed the terms, so ignore any dollar figure attached to that exit. **Skip if:** you want short videos. Her best material is long and assumes you will follow along at a keyboard. #### **2. Chris Koerner (Best for business ideas, not AI tutorials)** *Chris Koerner runs The Koerner Office across YouTube, podcast and newsletter.* [Chris Koerner](https://www.youtube.com/@thekoerneroffice) has 655K subscribers and over 900 videos, and the channel is still only one of the places he publishes. His podcast domain now redirects to [The Koerner Office newsletter](https://newsletter.chrisjkoerner.com/), which promises one business idea deep dive per week. The podcast itself is past 400 episodes and still shipping. He runs several other YouTube channels, posts to X, Instagram, LinkedIn and Facebook, and operates three paid communities. Be clear about what he is. Koerner is a business-idea guy who uses AI, not an AI teacher. He will tell you about a $10K per month appliance-rental business before he mentions a model release, and he has publicly pushed back on AI agent hype. That framing is why he is worth the follow. **Skip if:** you want step-by-step AI tooling. He works at the level of the opportunity, not the build. #### **3. Ryan Doser (Best for marketers using Claude Code)** *My channel covers Claude Code and AI marketing systems.* This one is me, so weigh it accordingly. I sit at number three here while running one of the smaller channels on the list, 39.2K against Matt Wolfe's 992K. If that ordering looks convenient, judge it against the fact that I am the only person here who had to write his own downside. Off YouTube I publish a weekly newsletter to 10,000+ subscribers, run the AI Marketing Insiders community on Skool, and sell a Claude Skills Stack at [skills.ryandoser.com](https://skills.ryandoser.com). Before working for myself in 2019 I ran paid media at Meredith Corporation for titles including People and Better Homes & Gardens, and I have a marketing degree from the University of Northern Iowa. That decade of marketing work is the actual reason the paid skills are worth anything. The subject-matter expertise is the product, not the file format, and you can start with the free ones. I teach Claude Code to marketers who do not write code, which is a narrow lane on purpose. If you want the unvarnished version of that, read [how I run social media with Claude Code](/claude-code-social-media/). **Skip if:** you want breadth. I cover one stack in depth and I will not be the person who tells you what launched this week, and unlike Sabrina or Koerner I do not have a long written archive to work through. #### **4. Mark Kashef (Best for prompting and agent depth)** *Mark Kashef teaches AI agents and multi-step prompting.* [Mark Kashef](https://www.youtube.com/@Mark_Kashef) runs an 81.7K subscriber channel and describes himself as having over ten years in data science and machine learning. His social accounts are close to dormant, which is worth saying because it shows the test I am using is not really "post everywhere." Kashef publishes almost nothing on X or TikTok and still clears the bar. He clears it on third-party vetting instead. He teaches live courses through O'Reilly, holds a listing in the Microsoft Learn creator community, runs the [Prompt Advisers](https://www.promptadvisers.com/) consultancy, and has a Skool community past 1,300 members. Somebody other than Kashef decided he was qualified, and that is the signal, not the platform count. His teaching runs closer to the engineering end, covering how a multi-step system behaves when it breaks. **Skip if:** you want marketing strategy rather than engineering, or you are looking to learn entirely from free material. #### **5. Riley Brown (Best for building apps with AI)** *Riley Brown teaches building software with AI agents.* [Riley Brown](https://www.youtube.com/@rileybrownai) has 269K YouTube subscribers, and YouTube is not even his biggest room. [TikTok](https://www.tiktok.com/@rileybrown.ai) is, at 636K followers, and he runs [Instagram](https://www.instagram.com/realrileybrown/) and [X](https://x.com/rileybrown) at real scale alongside it. The material changes shape on each one rather than being cross-posted. On the vetting test he clears it twice. He co-founded [Vibecode](https://vibecodeapp.com), which raised a $9.4 million seed round led by Alexis Ohanian's Seven Seven Six, and Forbes featured him on vibe coding alongside Andrej Karpathy. Investors doing diligence is a harder filter than an audience clicking subscribe. Worth knowing going in. His educational videos and his own products live in the same territory, and he has been criticized publicly for pointing viewers toward his own app inside content framed as neutral teaching. I still rank him here because the underlying work is real and the tutorials genuinely teach, but it helps to notice which product a given video is built around. **Skip if:** you want a reviewer with no stake in the tools. He builds in the category he teaches, which is exactly why the builds are good and also why you should know it going in. #### **6. Authority Hacker (Best for SEO operators moving into AI)** *Mark Webster and Gael Breton run the Authority Hacker Podcast.* [Mark Webster and Gael Breton](https://www.youtube.com/@AuthorityHackerPodcast) run [Authority Hacker](https://www.authorityhacker.com/), at 47.2K subscribers across 651 videos, and they are the longest-running operation on this list. The company dates to 2014, which in this category is close to prehistoric. They earn the spot for something most creators never do: they killed their own flagship product. Their contact page states plainly that the legacy SEO courses, including the Authority Site System, "were discontinued in 2024 as we shifted our focus to AI and automation." That was the business that built them, retired because they judged the niche-site model no longer worked after Google's changes. Walking away from a proven seller is the most expensive form of being honest, and it is the exact behavior the "can you find them being critical?" test is looking for. They now sell an AI Accelerator membership with pricing published openly at $99, $199 and $1,000 per month billed annually, rather than hidden behind a call. The podcast is past 400 episodes. Weigh the affiliate context. They built their name in affiliate marketing and their site carries a testimonial from Ahrefs' CMO, a tool they also cover, so read tool recommendations as informed rather than neutral. Their audience figures, including 15,000+ customers and 80,000+ email subscribers, are self-reported and unaudited. **Skip if:** you have never done SEO. Their material assumes you know what a SERP is and are adapting existing skills, not starting from scratch. #### **7. Matt Wolfe (Best for knowing what shipped this week)** *Matt Wolfe posts weekly AI news breakdowns alongside FutureTools.io.* [Matt Wolfe](https://www.youtube.com/@mreflow) is at 992K subscribers with 760 videos, and he is the exception I flagged earlier. His main output is news-cycle coverage, which I said is weak evidence on its own. The difference is that he does the boring maintenance work underneath it. He built [FutureTools.io](https://www.futuretools.io/), a directory tracking thousands of AI tools that has to be kept current every week, with a newsletter its own signup page puts at 250,000 readers. He also co-hosts The Next Wave, published through the HubSpot Media Network, which is a credential somebody else issued him. Reacting to launches is easy. Maintaining a catalog that is wrong in public the moment it goes stale is not, and that is what earns him the spot. One caveat worth holding. FutureTools carries affiliate relationships and he openly describes himself as an investor in AI companies, including Canva and Replit. Tool-roundup content is commission-shaped by nature, so read his recommendations as informed rather than disinterested. **Skip if:** you want depth on one workflow. His job is breadth, and breadth has a cost. #### **8. Corey Ganim (Best for operators who already run a business)** *Corey Ganim helps non-technical entrepreneurs apply AI.* [Corey Ganim](https://www.youtube.com/@coreyganim) has 22.1K subscribers against roughly 1,100 videos, which tells you where his effort goes. His [Build With AI podcast](https://podcasts.apple.com/us/podcast/build-with-ai/id1689819329) is 188 episodes deep and still publishing, and the format is operators sharing a screen and building live. He also writes a newsletter, runs a paid community, and co-founded [Return My Time](https://returnmytime.com/), which builds AI agents that answer leads and follow up with customers for other businesses. That is the off-YouTube evidence this list looks for: he is selling the thing, not just describing it. One thing to weigh. His own site and his LinkedIn give different lifetime revenue figures, both self-reported, so treat any number he quotes as a claim rather than a verified fact. The podcast and the company are the parts you can check. **Skip if:** you have not started a business yet. His material assumes you already have operations to point AI at. #### **9. Sandy Lee (Best for starting with no technical background)** *Sandy Lee teaches AI content strategy for business and personal brand.* [Sandy Lee](https://www.youtube.com/@sandyleeai) has 66.1K subscribers on a channel that only opened in October 2025, the shortest tenure of anyone here. The backstory is the reason she is here. She previously grew an audience she puts at 550K across three platforms teaching Spanish to Korean speakers, and says she barely monetized any of it before burning out. She is rebuilding from zero with the monetization figured out first, and that scar tissue shows up in what she teaches. Alongside the channel she runs a paid Skool community, a Substack and a podcast, and teaches Claude Code and Claude Cowork to people with no technical background. I had her on my own channel to walk through the rebuild. **Skip if:** you want a long track record. The channel is under a year old, so if you prefer someone with years of archive behind them, start elsewhere and come back. #### **10. Corbin Brown (Best for building software without coding)** *Corbin Brown teaches building real software with AI coding agents.* [Corbin Brown](https://www.youtube.com/@Corbin_Brown) has 181K subscribers under the tagline "build real software without learning to code." He runs [Thumio](https://thumio.com), an AI thumbnail tool, and sells Boost OS as a one-time purchase rather than a subscription. That pricing choice is worth noting on its own, because a one-time fee gives him no recurring revenue to protect if the product disappoints. One caveat on credentials. His verifiable biography is the thinnest of anyone here, with no confirmable education or employment history, and I could not find independent reviews of either product. He is the one person on this list who does not clear my "did somebody else vet them" question, which is why the shipped software carries the weight. **Skip if:** you want a documented pedigree before you take advice. He is here on what he has shipped, so judge him on the software rather than the resume. #### **11. Brooke Wright (Best for women founders scaling with AI)** *Brooke Wright teaches AI and automation to women founders.* [Brooke Wright](https://www.youtube.com/@WrightMode) has 9.1K YouTube subscribers, one of the smallest channels on this list, and 781 videos published against it. A subscriber ranking filters her out entirely, and that is the case for reading this list differently. The work sits elsewhere: a paid Skool membership, a 31-episode podcast, a newsletter, and her own live event in Sydney this November. On outside vetting she clears the bar through AI-CON Australia, which put her on its speaker roster. She teaches AI systems to women founders and neurodivergent entrepreneurs, and her consulting page carries an explicit "not a fit if" section with pricing published rather than hidden behind a sales call. On that note, treat her audience figures with care. Her site, YouTube and Threads bios each give a different total, so I am not repeating any of them as fact. **Skip if:** you are not the reader she writes for. She has picked a specific audience and serves it closely, which is a feature if you are in it. #### **12. Aaron Makelky (Best for teachers and non-coders)** *Aaron Makelky teaches AI to people who do not write code.* [Aaron Makelky](https://www.youtube.com/@AaronMakelky) has 635 YouTube subscribers, and putting him on a list like this is the clearest test of whether I actually mean what I said at the top. A subscriber ranking does not just filter him out, it never sees him. What he has instead is the strongest single piece of outside vetting on this page. PBS featured him on Wyoming Chronicle in October 2025, introducing him as a Casper world history teacher who is "ahead of the curve on the uses and impact of artificial intelligence in Wyoming classrooms." A public broadcaster chose him. Nobody buys that. He describes himself now as a former Wyoming teacher and football coach who tests AI tools on real work, and he runs [workshops and school training](https://aaronmakelky.com/) for people who do not write code. That audience is genuinely underserved. Most AI teaching assumes a technical baseline, and classroom staff are handed policy instead of practice. Two things to know. He sells kits built around specific tools while also publicly praising some of those tools, which sits awkwardly next to his stated "no brand deals" position, so treat it as a commercial interest rather than a neutral review. And his channel is by far the smallest here, so expect a working practitioner posting what he tests, not a polished production. **Skip if:** you want scale as a proxy for quality, or you need advanced agent engineering. He teaches the first mile, and he teaches it to people the rest of this list talks past. ### **How to choose who to actually follow** You do not need a dozen subscriptions. You need two or three that match what you are trying to do this quarter. These are the questions I apply before following anyone in this category. - **Did somebody else vet them?** A publisher, a conference, an acquirer or a platform partner applies a standard the creator does not control. - **Have they shipped something with a price on it?** Selling the thing exposes you to refunds, support tickets and reviews. Teaching about it does not. - **Is the advice specific enough to be wrong?** Vague advice cannot fail, which is what makes it useless. - **Can you find them being critical?** Not contrarian for sport. One documented case of them saying a popular tool was not worth it. - **Does the archive show a habit?** A long back catalog with consistent dates is harder to stage than a good month. Every count on this page came off a live channel or site in August 2026, and where a figure is self-reported I have said so rather than laundering it into a fact. ### **Who I left off, and why** Most lists in this category are built from the research and academic tier. Andrej Karpathy, Grant Sanderson, Yannic Kilcher, Lex Fridman and Two Minute Papers show up on nearly every one. They are genuinely excellent and I left them off on purpose. This list is for people trying to apply AI to a business, and that tier teaches how the models work rather than what to do on Monday. Different job, different list. I also left off anyone whose income claims trace back mainly to selling the course rather than doing the work. That pattern is common in AI automation right now, and it is the exact thing this list exists to filter. ### **Ryan's Final Thoughts** Follow two people from this list, not twelve. Pick the ones whose off-YouTube work matches what you are building, then read the newsletter or join the community rather than only watching. The channel is the advertisement. The newsletter, the podcast and the paid product are where someone has to be right in front of people who can ask follow-up questions, which is [the part of running a community most people underestimate](/how-to-build-an-online-community/). Once you have picked your two, the same test applies to what lands in your inbox and which rooms you pay to sit in. I put the [best AI newsletters](/best-ai-newsletters/) and the [best AI communities](/best-ai-communities/) through it separately. *Disclosure: I am on this list, and I sell AI marketing products and consulting, which makes me a competitor to several people named here. Some links in this post are affiliate links, and I may earn a commission at no extra cost to you. Nobody paid or was asked to be included. [Full disclosure](/disclosure/).* --- ## 10 Best AI SEO Experts in 2026 (Ranked by Real Work) URL: https://ryandoser.com/best-ai-seo-experts/ Markdown: https://ryandoser.com/best-ai-seo-experts.md Published: 2026-08-06 | Updated: 2026-09-30 Categories: AI Tool Reviews > The 10 best AI SEO experts in 2026, with what each one has actually shipped on AI search and who each is wrong for. Every credential checked. Almost every list of the **best AI SEO experts** recycles the same general SEO names under a new title, and most of those people have not published anything specific to AI search. I went looking for who has actually shipped work on [how ChatGPT, Claude and Google AI Overviews decide who gets named](/how-to-manipulate-ai-search/). Original research, named frameworks, dated talks, products people can use. That is the bar for this list. ### **What is an AI SEO expert?** An AI SEO expert makes a brand visible inside AI-generated answers rather than only in the blue links. The work covers Google AI Overviews, ChatGPT, Claude, Gemini and Perplexity, and it turns on entity clarity, extractable page structure, schema, and being mentioned across sources those systems already trust. It overlaps with SEO but is not the same job. Ranking first and being named in the answer are separate outcomes, and a page can hold one while losing the other. That is the gap the people below work on. ### **Why most AI SEO expert lists are useless** Read a few of these roundups and the same problem shows up. The title says AI search, the roster says 2019. [Percepture's roundup](https://percepture.com/seo-insights/best-seo-professionals/) gives its own founder around 300 words of dedicated write-up, while Aleyda Solis and Rand Fishkin get about a dozen words each. That is not a list. It is a landing page wearing a list costume. The self-ranking habit runs deep here. I read six of these pages: Percepture, SEO Discovery, Julian Goldie, Searchbloom, Usama Khan and Kasra Dash's own roundup. In all six, the person who wrote it, or the firm they work for, came out on top. Search any of those names and see for yourself. So a fair question to ask me: why am I on my own list? Because I do this work for money, and you deserve to know that when you weigh what I say about everyone else. I put myself at number three, gave my entry the same length as the rest, and named my own limitation like everyone else got. On the order: this is not a scored ranking and I am not going to pretend it is one. It runs roughly from the people selling AI search work you can actually buy today, through the people producing the research the rest of us build on, down to people worth reading for one specific thing I name in their entry. Every entry says who it is not for. Read those lines as carefully as the rest. ### **The 10 best AI SEO experts in 2026** The best AI SEO experts in 2026 are Nathan Gotch, Charles Floate, Ryan Doser, Wil Reynolds, Mike King, Aleyda Solis, Andrew Holland, Kyle Roof, Rand Fishkin and Kasra Dash. Each one below is there for a specific, dated piece of AI search work, and each entry says plainly who should not hire them. I checked each credential below against a primary source, and I link each person's own site so you can verify it yourself. Where someone is better to learn from than to hire, I say so. Several publish no rates at all, so it is worth knowing [what AI consultants actually cost](/ai-consultant-cost/) before you start those conversations. After the ten you will find six honorable mentions, held to the same standard. | Expert | Best for | What they shipped on AI search | Not for | | Nathan Gotch | SaaS and B2B teams wanting a defined AEO engagement | AEOconsultant.ai, plus AI SEO For Dummies (Wiley, September 2026) | Anyone needing public pricing or a non-SaaS fit | | Charles Floate | Understanding aggressive tactics | Ranking In AI training webinar, May 2026 | Anyone who wants a playbook safe to copy | | Ryan Doser | Solo operators and small teams | Zero to 12.1K AI citations in six months (self-reported) | Anyone who wants a team to run the work | | Wil Reynolds | Original AI search data | Seer's GEO Olympics study, 231,000-plus LLM responses | Solo operators, it is enterprise priced | | Mike King | Enterprise technical AI search | Named relevance engineering, analyzed the 2024 Google leak | Anyone without an enterprise budget | | Aleyda Solis | Free AI search education | LearningAIsearch.com, launched July 2025 | Anyone needing a large delivery team | | Andrew Holland | The brand-mentions side of GEO | Search Engine Land GEO column, fame engineering | Anyone needing schema and technical work | | Kyle Roof | On-page testing methodology | US patent 10,540,263, POP AI visibility tracker | Anyone wanting advice independent of a tool | | Rand Fishkin | Understanding zero-click search | 2026 zero-click study, 68.01% of US searches | Anyone trying to hire him, he left SEO in 2018 | | Kasra Dash | Meeting practitioners in person | The Masterminders Conference, June 2026 | Anyone wanting published AI search research | #### **1. Nathan Gotch (Best for a productized AEO engagement)** *Gotch's AEO consultancy targets SaaS and B2B companies.* Nathan Gotch is co-founder and CEO of [Rankability](/rankability-review/) and has repositioned around answer engine optimization through [AEOconsultant.ai](https://aeoconsultant.ai), which sells tiered AEO consulting to SaaS and B2B companies. His book *AI SEO For Dummies* is out now from Wiley. He closed the Gotch SEO agency in late 2025 to focus on software and education, so treat that brand as past tense. **Best for:** SaaS and B2B teams that want a defined engagement rather than advice. **Read the fine print:** The site's headline claims, a 99% success rate and 1,000% visibility growth in 30 days, are self-reported and not independently verified. Engagements are application-gated with no public pricing. #### **2. Charles Floate (Best for understanding aggressive tactics)** *Floate's own navigation puts link buying front and center.* [Charles Floate](https://charlesfloate.com) describes his own career as spanning white, grey and black hat SEO, and his product line matches that: parasite SEO, private blog networks and paid links. He ran a Ranking In AI training webinar in May 2026, so the AI search material is real. He has been penalized by Google twice and wrote both up himself. A pure spam manual action deindexed seven of his public-facing sites, and a [link-based penalty in December 2016](https://www.charlesfloate.com/google-target-me) demoted his main blog along with 28 network sites. **Best for:** Knowing what aggressive operators are doing, so you recognize it. **My honest take:** These are tactics I would not run on a business I cared about, and the penalty history is the evidence. Read him to understand what is being done to your SERPs, not to copy the playbook. #### **3. Ryan Doser (Best for solo operators and small teams)** *My consulting page, including the results I based the offer on.* I am an AI-first marketer with over a decade in digital marketing, and I took this site from zero to 12.1K AI citations in six months, alongside 5.77K clicks and 890K impressions in Search Console over that period. Those are my own numbers from my own dashboards, so weigh them the same way you weigh anyone else's self-reported results on this page. I run [one-off AI search strategy sessions](/ai-seo-consulting/) at $500 an hour rather than retainers, and I got a dental IT client to number one in AI search for their category's head term. My approach is entity clarity, schema, and [content structured so an assistant can lift an answer out of it](/ai-seo-strategy/) and name you. **Best for:** Founders and consultants who want a roadmap they can run themselves. **Where I fall short:** I sell hours, not delivery. If you want a team to run the roadmap for you, I am the wrong call and Seer or iPullRank are better fits. If you want the roadmap without the hours, I packaged the same audit and fix list into [my AI SEO System](/ai-seo-system-launch/). #### **4. Wil Reynolds (Best for original AI search data)** *Seer Interactive lists GEO alongside organic search and paid media.* Wil Reynolds founded [Seer Interactive](https://www.seerinteractive.com) in 2002, and Seer publishes some of the largest AI search datasets anyone is sharing publicly. Their [GEO Olympics study](https://www.seerinteractive.com/insights/what-ai-thinks-about-your-brand-is-already-written) analyzed over 231,000 LLM responses across seven platforms and found seven-day Wikipedia views were the strongest predictor of LLM visibility. What earns him the position is that he argues against his own sales pitch. On the No Hacks podcast in April 2026 he called AI visibility a vanity metric and disclosed Seer's own 80% organic traffic loss over two years while pipeline revenue grew. The published research largely backs him on the daily numbers, which I worked through in my [Searchable review](/searchable-review/). **Best for:** Marketers who want evidence over opinion. **The limitation:** You cannot hire him directly, only Seer, at enterprise pricing. He is here for the culture that produces this research and for saying the unprofitable thing out loud. Seer's research team authored the studies themselves. #### **5. Mike King (Best for enterprise technical AI search)** *iPullRank sells AI search, GEO and relevance engineering as named services.* Mike King founded [iPullRank](https://ipullrank.com) and does the most technically demanding work I have found in this space. He named and popularized [relevance engineering](https://ipullrank.com/relevance-engineering) as an SEO discipline, reframing the job around embeddings, query fan-out and information retrieval rather than keywords. His own framing is careful about this, he calls it "the reinvention I'm calling relevance engineering" rather than claiming he invented the term. He also verified the 2024 Google Content Warehouse API leak. Rand Fishkin received the documents and King analyzed them. Both published in late May 2024, and Google confirmed the documents were real on 29 May. **Best for:** Enterprise teams that need the actual retrieval mechanics, not tips. **Who it is not for:** This is the most demanding material in the field and iPullRank is enterprise priced with no public rates. A solo operator will not get through the door or through the reading. #### **6. Aleyda Solis (Best for free AI search education)** *Aleyda Solis describes herself as an SEO and AI search consultant.* [Aleyda Solis](https://www.aleydasolis.com/en/) runs the boutique consultancy Orainti and launched LearningAIsearch.com in July 2025, a free AI search optimization roadmap covering GEO, AEO and LLMO with no ads and no paid placements. She also publishes [SEOFOMO](https://seofomo.co/), a free newsletter that goes out every Sunday and claims over 45,000 subscribers on its own signup page. She gives away more genuinely useful material than most people in this space sell. **Best for:** Anyone who wants to learn AI search properly without paying for a course. **The limitation:** Capacity is deliberately small and enterprise-leaning. Worth noting that Orainti's own service pages still describe SEO only, so the AI search positioning lives on her personal brand. #### **7. Andrew Holland (Best for the brand-mentions side of GEO)** *JBH now lists GEO as a top-level service beside digital PR.* Andrew Holland is Director of SEO at [JBH](https://www.jbh.co.uk), a digital PR agency that now sells GEO as a named service. He spent 17 years as a police officer, including covert intelligence work, before moving into search. He writes a running Search Engine Land column on GEO, where he makes the case for [fame engineering](https://searchengineland.com/fame-engineering-key-generative-engine-optimization-461969) and develops the idea of [AI availability](https://searchengineland.com/ai-availability-brands-battleground-464484), which he credits to Byron Sharp of the Ehrenberg-Bass Institute, who raised it in a comment on one of Holland's LinkedIn posts. His argument is that brand mentions do work in AI search that links alone cannot. **Best for:** Brands that need to be talked about across the web, not just tuned up on it. **The blind spot:** His thesis is PR-led rather than technical, so it skips schema, crawler access and entity plumbing. He also comes as part of a JBH retainer. Without that budget, [automated pitching](/backlinker-ai-review/) is the cheap version of the same job. #### **8. Kyle Roof (Best for on-page testing methodology)** *PageOptimizer Pro now positions around visibility across Google and LLMs.* Kyle Roof founded [PageOptimizer Pro](https://pageoptimizer.pro) and holds US patent 10,540,263, granted in January 2020 with co-inventor Dorianne Marie Friend. It covers a method for testing individual ranking variables in isolation, which is narrower than the on-page patent people often describe. He is best known for the 2018 lorem ipsum test, where he ranked a page of dummy text by placing keywords inside the gibberish. POP now ships an AI visibility tracker, and pricing starts at $40 a month, which puts it just under the dedicated trackers like [AIclicks](/aiclicks-review/) at $59 and well under [Profound](/profound-review/), which now quotes brand plans through sales, though [Otterly undercuts both](/otterly-ai-review/) at $29. **Best for:** SEOs who want testing discipline instead of received wisdom. **The blind spot:** His edge is reverse-engineering Google specifically, which is a shrinking surface as AI answers take over. His advice also runs through his own tool. #### **9. Rand Fishkin (Best for understanding zero-click search)** *Fishkin now runs SparkToro, an audience research tool, not an SEO practice.* Rand Fishkin co-founded Moz, left in 2018, and now runs [SparkToro](https://sparktoro.com). His 2026 zero-click study found 68.01% of US Google searches ended without a click in the first four months of the year, up from 60.45% in 2024. His book with Amanda Natividad, *Zero Click Marketing*, is due in fall 2026. He has also since cofounded the brand monitoring tool Alertmouse, which I broke down in my [Alertmouse review](/alertmouse-review/). He is on this list because he measures the collapse in search traffic better than anyone. He is also explicit about his own limits. He left SEO in February 2018 and told Search Engine Land in December 2024 that he had not been in the field for seven years. **Best for:** Understanding why your traffic fell even though your rankings held. **Set expectations:** He is not available for SEO work and says so plainly. Learn from him, do not try to hire him for this. #### **10. Kasra Dash (Best for meeting the people doing the work)** *Dash founded The Masterminders, which draws SEOs from 25 countries.* [Kasra Dash](https://kasradash.com) is a consultant and affiliate site builder who founded The Masterminders Conference, running 24 to 26 June 2026 in Manchester, which advertises 250-plus attendees from more than 25 countries. Andrew Holland speaks there this year, which tells you something about the room. He also built mySEO.app, a learning and community platform, and works publicly on SEO and AI search. **Best for:** Getting in the room with practitioners instead of reading about them. **The limitation:** His centre of gravity is link building and affiliate SEO. Compared to the top of this list, there is less published AI search research to point at. ### **Honorable mentions** Six more worth knowing about, held to the same standard as everyone above. Brian Dean and Koray Tuğberk Gübür are established names whose AI search output is thinner or older than their reputations suggest. Edward Sturm and Sam Dunning are working practitioners publishing real material right now. Dan Petrovic publishes his own AI search research and shows the method behind it. Nesil Ozer is the one I have worked with directly, and the only one here I am vouching for on private evidence rather than published proof. Same rules as above. Dated work, a link so you can check it, and the limitation stated plainly. #### **Brian Dean (Best for the argument that AI is not the whole story)** [Brian Dean](https://backlinko.com/blog/authors/brian-dean) built Backlinko into the most imitated SEO blog on the internet, sold it to Semrush, then built and sold Exploding Topics to Semrush as well. He is now co-founder and CEO of Exploding Topics. Here is the part other roundups leave out. The GEO and LLM visibility articles on Backlinko today are written by Semrush staff, not by Dean, and the site carries a disclosure saying so. His own recent work argues the opposite of the AI search consensus. His June 2026 video lays out a 2026 playbook built around what he calls search everywhere optimization, spreading across Amazon, YouTube and Reddit, and his July 2026 follow-up is titled "The Biggest Change in SEO (It's Not AI)." **Best for:** A credible counterweight if you think the GEO conversation has gotten ahead of itself. **The limitation:** His AI search output is thin, with no study carrying a sample size and no named framework of his own, so read him for the counterargument rather than for a GEO playbook. #### **Edward Sturm (Best for tactical LLM citation methods)** [Edward Sturm](https://edwardsturm.com/) has the most consistent publishing record on AI search of anyone in this section. Through 2026 he shipped dated pieces on [getting shown in LLMs](https://edwardsturm.com/articles/ai-seo-geo-aeo-get-shown-llms-2026/) (March), using Bing's AI Performance report to chase citations (February), press releases for LLM visibility (January), and getting AI to recommend you as the expert (June). The methods are specific and testable rather than conceptual. He shows you how to see which search queries ChatGPT actually runs behind an answer, a Google Analytics regex that isolates traffic arriving from AI tools, and a Search Console filter that treats seven-word-plus queries as a rough proxy for AI-assisted search. He sells AI consulting, and his Compact Keywords course is publicly priced at $1,199. **Best for:** Operators who want concrete things to try this week. **The limitation:** No original research with a sample size, and his June 2026 piece advises publishing self-promotional listicles that rank you first on your own site, which is the tactic this entire post exists to criticize. #### **Sam Dunning (Best for revenue-first B2B SaaS SEO)** [Sam Dunning](https://www.breakingb2b.com/) runs Breaking B2B, which is an agency and a podcast now approaching 500 episodes. He sells GEO, AEO and LLM SEO as named service lines, and unusually for this field, he publishes his pricing: plans from $4,000 a month on 90-day sprints with no annual lock-in. His AI search material is current, not retrofitted. Episode 494 in July 2026 walks through his system for ranking SaaS companies inside ChatGPT, Claude and Perplexity. The more useful one is episode 486 from May 2026, where he works through Google's own AI search optimization guide and lands on a deflating conclusion: solid fundamentals still win, and AEO tricks do not. He sells AEO, and he published that anyway. He also walked me through a live alternatives page teardown in our [SaaS SEO conversation](/saas-seo/). **Best for:** B2B SaaS teams who want AI search work tied to pipeline rather than citation counts. **The limitation:** He is B2B SaaS specific, and the headline 90-day page-one ranking guarantee is really a growth guarantee tied to agreed milestones, so pin those down on the intro call. #### **Koray Tuğberk Gübür (Best for the theory underneath topical authority)** [Koray Tuğberk Gübür](https://www.holisticseo.digital/author/koray-tugberk-gubur/) is CEO and founder of Holistic SEO and Digital, and he is the source of the terms "topical authority" and "topical map" as most SEOs now use them. He documents both as his own methodology, built on top of semantic SEO, a term that predates him and that he does not claim. His AI search framing follows from that theory rather than chasing the trend. In a September 2025 piece he argues topical authority is not about publishing more pages but about reducing the cost of retrieval for a search engine. That is a sharper way to frame why entity-consistent sites tend to get pulled into AI answers, and it gives you something to reason from instead of a tactic to copy. **Best for:** People who want the underlying model, not a checklist. **The limitation:** His Semantic SEO course lists at $5,000 with a no-refund policy and roughly eighteen hours of lectures before you apply anything, and the case study numbers behind it are self-published rather than independently audited. #### **Dan Petrovic (Best for the mechanics under AI search)** [Dan Petrovic](https://dejan.ai/) runs DEJAN, a Brisbane consultancy, and he publishes the methodology behind his own research instead of just the conclusions. He presented at Ahrefs Evolve Singapore in May 2026, where [Casey Burridge's write-up](https://caseyrb.com/blog/ahrefs-evolve-singapore-2026/) singled him out for bringing first-party data he collected himself. He explains mechanics rather than selling tactics. On the [Ahrefs Podcast in August 2026](https://www.youtube.com/watch?v=roTPZBj4JSc) he separates grounding from citation from mention, three things that routinely get blurred together, and argues the linked mention is the one worth chasing. He then walks through a spam classifier built on gzip compression with no machine learning at all, puts it at 90 to 99 percent accuracy on his own test, and tells you to go replicate it yourself. **Best for:** Technical readers who want to understand why AI search behaves the way it does, not a checklist to run. **The limitation:** Almost everything he publishes is self-run research on his own site, so you are trusting his methodology rather than an independent audit. The figures also shift between formats: the "million queries" line he uses on stage does not match the run counts in his own write-up of that study. His recent output is narrow too, so for classic technical, local or ecommerce SEO, look elsewhere. #### **Nesil Ozer (Best for AI SEO work that has not gone public yet)** [Nesil Ozer](https://nesilozer.com/) is an AI search and SEO consultant in Germany who built a free [AI Visibility Audit](https://nesilozer.com/free-seo-tools/ai-visibility-audit/) tool. No signup, three domains per run. It checks AI crawler access for GPTBot and ClaudeBot, your Common Crawl page count, Web Graph domain rank, homepage structured data, and whether your homepage is readable without JavaScript. It runs on Common Crawl's published datasets rather than a vendor's black box, and he credits the underlying five-check method to Stephen Burns at the Common Crawl Foundation instead of passing it off as his own. His FAQ then volunteers that the crawler test fires from his server rather than OpenAI's real IPs, so a block it finds is a strong signal and not final proof. Most tools in this category tell you the opposite, that their number is the truth. I am also breaking my own rule here, because this is the one entry on the page I cannot ask you to verify. I have worked with Nesil personally on seven-figure client projects, and he is the real deal on AI SEO. He is the rare case where the private track record is well ahead of the public one, and I am genuinely excited to see where he goes from here. **Best for:** A fast, free first look at whether AI crawlers can even reach you, and worth watching closely from here. **The limitation:** His public footprint is still one tool and an empty blog, so unlike everyone else here you are partly taking my word for it. ### **How to judge an AI SEO expert yourself** These are the questions I use before I take anyone's advice on AI search. - What have they published on AI search specifically, and when? A 2021 SEO post does not count. - Do they show data, or only conclusions? Ask for the sample size. - Are they selling the thing they are teaching? That is fine, as long as you know. - Do they name a limitation of their own approach without being asked? - Would they tell you not to hire them if you are a bad fit? That last one is the fastest filter. Anyone who thinks they are right for every business is right for none of them. If you would rather run the work yourself before paying anyone, the [tooling side is covered separately](/best-ai-seo-tools/). ### **Which of these AI search consultants should you actually pick?** Running an enterprise site and need the retrieval mechanics? That is Mike King. Want evidence before you commit budget, read Seer's research first. Founders and consultants who want a plan they can run themselves are my lane. With no budget at all, start with Aleyda Solis, who has given away more than most people sell. And if you are not yet sure an expert is the role you need, work out [whether you want a coach, a consultant or an executive](/ai-consultant-vs-ai-coach/) before you shortlist anyone. For a defined AEO engagement at a SaaS company, Nathan Gotch, or Sam Dunning in the honorable mentions if you want published pricing and a 90-day sprint instead of an application form. For brand mentions and press, Andrew Holland. Four names here are not hiring recommendations and I am not going to dress them up as such. Kyle Roof for testing discipline, Charles Floate for knowing what the aggressive end of the market is doing, Rand Fishkin for the traffic data, Kasra Dash for the room he puts together. Read them for those reasons. ### **Ryan's Final Thoughts** The honest state of this field is that almost nobody has been doing AI search long enough to have a decade of results. What separates the people above from the rest of the roundups is that they published something checkable and put a date on it. I checked every credential here against a primary source, the patent record, each person's own write-up or the published study, and I flagged the self-reported figures as self-reported, including my own. Where a claim would not hold up, I left it out or said what I could not confirm, which is why every honorable mention carries a stated limitation alongside the reason it is worth your time. The single exception is Nesil Ozer, where I vouched for work I have seen firsthand rather than work you can go and check, and I flagged it as exactly that. Judge the rest of the internet's lists by that standard, this one included. ### **Best AI SEO experts FAQs** #### **Who are the most popular AI search optimization experts?** Mike King, Aleyda Solis and Wil Reynolds are the names that come up most across AI answers and industry roundups, mainly because each has published dated, checkable work on how AI systems pick sources. King named and popularized relevance engineering, Solis runs the free LearningAIsearch.com roadmap, and Reynolds' agency Seer publishes large-scale studies of LLM citation behavior. #### **How much does an AI SEO consultant cost?** The best public benchmark is [Ahrefs' poll of 439 SEO service providers](https://ahrefs.com/blog/seo-pricing/), last updated in August 2024, which put consultancies at $171 an hour and $3,250 a month on average, with $75 to $100 the single most common hourly rate. Published agency rates run higher: Breaking B2B lists plans from $4,000 a month, while iPullRank and Seer do not publish rates at all. I charge $500 an hour for one-off strategy sessions, above that band because it is a single working session with a prioritized roadmap rather than a monthly retainer. Automated platforms sit below the consultancy band and above the tool band, which is where a product like [Adaptify at $499 a month](/adaptify-seo-review/) lands. [Search Atlas](/search-atlas-review/) now bundles its OTTO automation from $79 a month billed annually, which puts it closer to tool pricing. Treat all of it as a general SEO benchmark, because no reliable public survey of AI search pricing exists yet. #### **Which AI is best for SEO?** For the actual work, Claude and ChatGPT are the two most used for content structuring, schema and technical audits. For visibility, the question is different: you want to appear in Google AI Overviews, ChatGPT, Claude, Gemini and Perplexity, and those surfaces disagree with each other constantly. A brand named first by one is often absent from another, so treat each as its own channel. #### **Is SEO dead or evolving in 2026?** Evolving, and the numbers say how. Rand Fishkin's 2026 SparkToro study found 68.01% of US Google searches ended without a click, up from 60.45% in 2024. Rankings still exist and still matter, but a top position that never gets clicked is worth less than being the source an AI answer names. The job shifted from earning the click to [earning the citation](/seo-content-strategy/). #### **Do I need an AI SEO expert or a regular SEO?** If your traffic is falling while your rankings hold, that is an AI search problem and a specialist is worth the money. If you have technical debt, thin content or no rankings at all, a regular SEO fixes more for less. AI visibility is built on the same foundation, so paying for GEO work before the fundamentals are in place tends to waste both. If the problem is your marketing as a whole rather than search, look at [independent AI marketing consultants](/best-ai-marketing-consultants/) instead. *Disclosure: I sell AI SEO consulting, which makes me a competitor to several people on this list. I have no financial relationship with anyone else named here, and nobody paid or was asked to be included. [Full disclosure](/disclosure/).* --- ## Blotato Review: My Favorite AI Tool for Social Media (2026) URL: https://ryandoser.com/blotato-review/ Markdown: https://ryandoser.com/blotato-review.md Published: 2026-08-06 | Updated: 2026-09-30 Categories: AI Tool Reviews > An honest Blotato review: real pricing at 5 vs 20 accounts, what the 7-day trial excludes, and where Upload-Post and Zernio beat it. Blotato is a $29/month AI social media tool that turns one piece of content into platform-ready posts for 9 networks, and publishes them through a web app, an API, or an MCP server your AI agent can call directly. This **Blotato review** covers what it does well, the two places competitors genuinely beat it, and who should skip it. I have been using Blotato since early 2025, and I run it both ways: inside the web app for one-off posts, and through the API for the automations that publish most of my content. This review reflects both. ### **What Makes Blotato Different from Every Other AI Content Tool** My inbox gets flooded with AI tool pitches every single day. I turn down almost all of them because most are white-labeled ChatGPT wrappers with a fresh coat of paint. Blotato earned a spot on my channel because the product genuinely delivers. #### **[Start a 7-day free trial of Blotato](https://www.blotato.com/?ref=rdoser)** One thing to know before you sign up: the 7-day free trial covers everything *except* the API. Generating an API key ends the trial immediately and starts your paid subscription. If you came here for the API or the MCP server, plan on paying for the first month rather than trialing it. Blotato repositioned in 2026, and it matters for whether this tool is for you. The headline now reads "social media automation for AI agents," and the pitch is that your agent writes the content while Blotato handles publishing. It works with Claude Code, Claude Cowork, ChatGPT, Cursor and Codex, plus n8n and Make. The web app is still there and still good. But the product is now built API-first, and the MCP server is the part people are actually excited about. I put it up against nine competing [social media APIs](/social-media-api/) at two different volumes. At its core, [Blotato](https://www.blotato.com/?ref=rdoser) replaces your AI writer, your social scheduler, and your repurposing tool with one system. Feed it a YouTube video, blog post, PDF, or audio file. It spits out ready-to-publish posts tailored to each platform across all 9 it supports: Instagram, TikTok, LinkedIn, Facebook, X, Threads, Bluesky, Pinterest, and YouTube. ![Blotato homepage in 2026 showing social media automation for AI agents](/images/2026/07/blotato-review-homepage-2026.jpg) The founder matters here. Sabrina Ramonov built her audience teaching AI automation, and her tutorials are genuinely technical rather than surface-level hype. When someone who actually publishes at volume builds a publishing tool, I pay attention, because the design decisions tend to reflect real use rather than a feature checklist. ![Sabrina Ramonov Blotato Founder](/images/2026/03/Blotato-Review-Sabrina-Ramonov.jpg) ### **What Other Blotato Users Actually Say** My opinion is one data point, and I have an affiliate relationship, so weigh it accordingly. Here is what the independent review sites show. On [Trustpilot](https://www.trustpilot.com/review/blotato.com) Blotato holds **4.8 out of 5 across 387 reviews**. On [SourceForge](https://sourceforge.net/software/product/Blotato/) it sits at **4.7 out of 5 from 73 reviews**. Those are unusually strong numbers for a bootstrapped tool in a crowded category, and the volume is high enough that it is not a handful of friends leaving five stars. The praise clusters where you would expect: setup is fast, cross-posting works, and support is responsive. The criticism clusters where I landed too. Reviewers mention the UI needing polish, occasional sync issues with deleted posts, and needing to watch credit consumption so it does not surprise you. When independent reviewers and I independently flag the same two weaknesses, that is probably the real shape of the product. ### **How Blotato's Pricing Stacks Up Against Competitors** I ran the numbers against three popular alternatives, and the gap surprised me. I put it head to head with seven others in my [roundup of social media automation tools](/social-media-automation-tools/). Most social media tools charge a premium once you start connecting more than a handful of accounts. Blotato takes a different approach with flat, month-to-month billing and no annual lock-in tricks. ![Blotato pricing page showing Starter $29, Creator $97, and Agency $499 plans](/images/2026/07/blotato-review-pricing-2026.jpg) On the $29/month Starter tier you get unlimited text-based AI writing, connections for up to 20 social accounts, 1,250 AI credits for images and video, and full API access. That last item is the one that matters most. Plenty of tools at this price will schedule posts for you. Very few hand you a production API on the entry plan. The Creator tier bumps to $97/month with 40 social accounts and 5,000 AI credits. Agencies can go to $499/month for 28,000 credits plus dedicated video processing and a dedicated support channel. To put that in context: [Buffer](https://buffer.com/pricing) bills per channel, starting at $6 per channel per month on Essentials with a lower rate on channels past the tenth, so 20 accounts lands at exactly $100 a month. [Sprout Social](https://sproutsocial.com/pricing/) starts at $199 per seat per month on annual billing and caps that tier at five profiles. [Blotato](https://www.blotato.com/?ref=rdoser) is cheaper than both at 20 accounts, and it bundles in AI writing that neither one offers. ### **Blotato AI Features That Actually Matter** You can tell a tool was built by a practitioner when the features solve real problems instead of chasing feature-list vanity. Here is what stood out during my testing. #### **Content Repurposing Across Platforms** Drop in a YouTube video link and Blotato generates platform-specific posts for up to five channels at once. Each post adapts to the format and tone that performs on its respective platform. If you don't like the output, a built-in chatbot lets you refine posts in real time without starting over. ![Blotato Content Creation Interface](/images/2026/03/Blotato-Review-Interface.jpg) #### **Brand Voice and AI Twin** Rather than making you pick a model, Blotato has you set up a Brand Kit and one or more Brand Voices. AI Twin then writes captions in your style based on those settings, so you are tuning the output to sound like you instead of guessing whether GPT or Claude writes a better hook today. If you run more than one brand, you can hold several voices and pick which one to write with before you generate. Under the hood Blotato routes to providers including OpenAI and Anthropic, and its docs confirm it does not train on your uploaded content. #### **Built-In Scheduling Across 20 Accounts** Instead of exporting posts to a separate scheduler, you publish directly from the same screen where you wrote them. Set up recurring time slots, assign platforms to each slot, and Blotato queues everything automatically. It's not the prettiest calendar view (more on that below), but having [AI content creation](/ai-agent-for-content-creation/) and distribution in one place saves real time. ![Blotato Social Media Platform Integrations](/images/2026/03/Blotato-Review-Social-Integrations.jpg) #### **Claude Code Automation via MCP** This is the setup I actually use most, and it is the reason Blotato stuck for me. Blotato ships an MCP server, so Claude Code can create and publish posts without me ever opening the dashboard. I walked through the whole build in this video. The connection itself is straightforward. Inside Blotato you go to Settings, then API, and you get MCP setup options for the Claude web app, Claude Desktop and Cowork, Claude Code in the terminal, and other MCP clients. I use the last one because I run Claude Code inside VS Code. You paste those instructions into Claude Code and let it wire up the connection. Expect to answer a couple of troubleshooting questions rather than a clean one-shot. Once it is connected, the workflow is just conversation. I point Claude Code at one of my own YouTube videos and ask for five posts each for X and LinkedIn, written against a skill file that holds my tone and caption rules. Blotato can scrape the YouTube transcript itself through the MCP, so the source material never leaves the chat. Publishing works the same way. I can tell it to post one straight to X and schedule another to LinkedIn for tomorrow at 1pm Central, and it does both. When I tried that, it checked my Blotato calendar, spotted an existing post at that time, and asked me to pick a different slot instead of silently double-booking. That is the kind of detail that separates a real integration from a demo. The more useful version is batch work. I keep a Google Drive folder where my editor drops finished short-form videos, and I can ask Claude Code to read that folder, pull each transcript, and write platform-specific captions for every clip. It splits them correctly too: one caption style for Instagram, TikTok and YouTube Shorts, a different one for X, LinkedIn and Threads. That does require connecting the Google Workspace CLI first, which is a separate setup step and not something the Drive URL does on its own. #### **Make.com Automation via API** This is where [Blotato](https://www.blotato.com/?ref=rdoser) pulls ahead of beginner-focused tools. The starter plan includes API access, which connects directly to [Make.com](https://www.make.com/) for advanced automation. I tested a workflow that monitors a Google Sheet for article URLs, processes them through OpenAI, and publishes finished posts across all connected accounts automatically. ![Blotato Social Media Automation with Make.com](/images/2026/03/Blotato-Review-Automation.jpg) The automation ran on the first attempt with zero errors across Facebook, Instagram, LinkedIn, and X. That rarely happens with multi-platform workflows. If you're interested in building [AI marketing agents](/claude-code-ai-marketing-agents/) that handle content distribution, Blotato's API makes it possible at the starter tier. ### **Blotato vs Upload-Post vs Zernio** These are the three tools people actually cross-shop when they want to publish to social platforms from code or from an AI agent. If open source is on your list too, I put Blotato head to head with [Postiz, the self-hostable option](/postiz-vs-blotato/), separately. The pricing models are completely different shapes, so a headline price tells you almost nothing. What matters is how many accounts you connect. | | Blotato | Upload-Post | Zernio | | Entry price | $29/mo | $0 free tier, $24/mo Basic | First 2 accounts free | | Pricing model | Flat, by tier | Flat, by tier | Per connected account | | Cost at 5 accounts | $29/mo | $24/mo | $18/mo | | Cost at 20 accounts | $29/mo | $50/mo | $78/mo | | Free plan | No, 7-day trial only | Yes, 2 profiles and 10 uploads/mo | Yes, first 2 accounts | | API on entry plan | Yes, paid plans only | Yes, including free tier | Yes | | Platforms | 9 | 22 | 16+ | | AI content generation | Yes, text, images, video | AI Shorts, capped by plan | No, publishing layer | Read that 20-account row again, because it is the whole argument. Blotato stays at $29 while [Zernio](https://zernio.com/pricing) climbs to $78 and [Upload-Post](https://www.upload-post.com/pricing) reaches $50. Flat pricing is not a marketing line here, it is the reason the bill stops moving. #### **Blotato vs Upload-Post** Upload-Post genuinely beats Blotato on two things, and I am not going to pretend otherwise because both objections come up constantly. First, it has a real free plan. Two profiles, 10 uploads a month, no credit card. Blotato has no free tier at all, only the 7-day trial. Second, Basic is $24/month against Blotato's $29, and it supports 22 platforms including Discord, Telegram, Mastodon and WordPress that Blotato does not touch. So if you publish to a handful of accounts, want to test without a card, or need one of those long-tail destinations, Upload-Post is the better buy and you should go take it. Where it flips: Upload-Post Basic caps you at 5 profiles and 1 seat. Cross 5 accounts and you are on Professional at $50/month, which is where Blotato's $29 for 20 accounts wins outright. Upload-Post is also a publishing pipe. It moves media you already made. Blotato generates the post, the image, and the video before publishing it, so you are comparing a distribution layer against a creation-plus-distribution layer. #### **Blotato vs Zernio** The Zernio pitch you will see repeated is faster rate limits and no TikTok throttling on the entry plan. That is a fair point for high-volume publishing, and Zernio's pay-per-account model is genuinely elegant. The first 2 accounts are free with full API access, which is a better on-ramp than a 7-day trial. The catch is what happens as you grow. Zernio charges $6 per account for accounts 3 through 10 and $3 for 11 through 100. Twenty accounts costs $78/month against Blotato's flat $29. Zernio also does not generate content. It is a unified publishing API, so you still need something upstream writing the posts and making the visuals. Pick Zernio if you are a developer with a couple of accounts publishing at volume and you already have content generation solved. Pick Blotato if you want the writing, the visuals, and the publishing behind one flat bill. I later tested Zernio properly and fact-checked its headline marketing claim in a full [Zernio review](/zernio-review/). ### **Blotato vs Buffer and the Traditional Schedulers** Buffer, Hootsuite and Sprout Social are a different category, and comparing them on price alone misses the point. [Buffer](https://buffer.com/pricing) bills per channel starting at $6 each on monthly billing, so 20 accounts lands at $100/month. [Sprout Social](https://sproutsocial.com/pricing/) starts at $199 per seat per month on annual billing and caps that tier at five profiles. Neither writes your content the way Blotato does, and that is the real divide. If you want a polished calendar and approval workflows for a team of humans, Buffer and Sprout are more mature products. If you want a system where an agent creates and publishes without you opening a dashboard, they are not competing for that job. Buffer is the closest call of the three, and it has moved: it now ships its own API and MCP server, so the old "it cannot talk to an AI agent" objection no longer holds. I broke the two down properly in [Blotato vs Buffer](/blotato-vs-buffer/), including where Buffer is genuinely the better buy. Blotato also runs comment-to-DM automation on Instagram and Facebook, which I compared against seven dedicated tools in my roundup of [the best tools for automating Instagram DMs](/best-instagram-dm-automation-tools/). ### **Where Blotato Still Needs Work** No tool is perfect, and I'm not going to pretend otherwise. Here's what bothered me during testing. The scheduling calendar lacks visual clarity. When I loaded a full week of posts across four platforms, it was hard to scan what was going where. Dedicated tools like Hootsuite lay this out more cleanly. Blotato works, but you have to click around more than you should. If you plan to generate lots of images or videos, watch your credit balance. Writing posts costs nothing on any plan, but every AI-generated image or video clips your monthly allotment. On the starter tier, heavy multimedia users could burn through credits in the first two weeks. ![Blotato Faceless Video Creation Feature](/images/2026/03/Blotato-Review-Faceless-Video.jpg) The platform pushes faceless AI videos hard, with templates, sample clips, and a built-in video editor. The editing tools work, but I'm skeptical about whether faceless videos drive real conversions. They rack up views. Whether those views turn into revenue is a different question. Treat Blotato as a writing and scheduling powerhouse first, video tool second. ### **Who Gets the Most Value from Blotato** If you're already using [Make.com](https://www.make.com/) or any automation platform, Blotato is a strong fit. The API access on the starter plan opens up workflows that tools twice the price don't support. Solo creators juggling four or more social accounts will save the most time. Same goes for [small business owners](/ai-for-small-businesses/) who need to post consistently but can't afford a full marketing hire. If you've never touched an API and the word "automation" makes you nervous, you might want to start with something simpler. And if you need granular analytics or enterprise-level reporting, Blotato isn't there yet. My take: if you are staying in the web app, start the [7-day free trial](https://www.blotato.com/?ref=rdoser) and run your actual content through it. The card is required and you are charged when the trial ends unless you cancel, so treat it as a paid month you can back out of rather than a free sample. If you are here for the API or MCP, skip the trial math entirely. Generating a key starts billing on day one, so just buy the first month at $29 and judge it on that. ### **Final Notes from Ryan** After weeks of testing, [Blotato](https://www.blotato.com/?ref=rdoser) earned a permanent spot in my toolkit. Most AI tools I review get uninstalled within a week. This one stuck because it solves a real problem: turning one piece of content into platform-ready posts without bouncing between five apps. The calendar needs polish, and I'd like credit costs to drop on media generation. But for what you pay, the output quality and automation depth are hard to beat. ### **Blotato Review FAQs** #### **Is Blotato worth it if I only manage two or three social accounts?** Probably not, and I would rather tell you that than sell you a plan you will cancel. At two or three accounts you are paying $29 for capacity you are not using. Upload-Post's free tier covers 2 profiles, and Zernio gives you your first 2 accounts free with API access. Blotato's flat pricing starts winning around 8 to 10 accounts and is clearly ahead at 20. #### **How does Blotato compare to just using ChatGPT for social posts?** ChatGPT can write posts, but it can't publish, schedule, or repurpose across platforms. Blotato wraps AI writing into a full distribution workflow. You go from source material to published posts without copy-pasting between tabs. #### **Can I choose which AI model Blotato writes with?** Blotato does not expose a model dropdown today. You shape output through Brand Kit and Brand Voice settings, which AI Twin writes from. Blotato routes to providers including OpenAI and Anthropic behind the scenes, and its docs state it does not train on your content. #### **Can I connect Blotato to my own automations through the API?** Yes, even on the starter plan. I built a Make.com workflow that pulls articles from a Google Sheet, processes them through OpenAI, and publishes across four platforms automatically. Setup took less than an hour. #### **Does Blotato have a free plan?** No. There is a 7-day free trial that requires a card and converts to a paid subscription unless you cancel. The trial includes everything except API access. If a genuinely free tier is a requirement, Upload-Post and Zernio both have one and Blotato does not. #### **Is Blotato cheaper than Upload-Post and Zernio?** It depends entirely on account count. At 5 accounts Zernio is $18 and Upload-Post is $24 against Blotato's $29, so Blotato is the most expensive of the three. At 20 accounts Blotato is still $29 while Upload-Post is $50 and Zernio is $78. Flat pricing loses at the low end and wins at scale. #### **Can I use Blotato with Claude or another AI agent?** Yes. Blotato ships an MCP server alongside the REST API, so Claude Code, Claude Desktop, and other MCP-capable agents can create and publish posts directly. It requires a paid subscription, because generating an API key ends the free trial and activates billing. #### **Will the 1,250 starter credits last a full month?** If you mainly write and schedule text posts, you won't touch your credits. Text generation is unlimited on every plan. Credits only get consumed by image generation, video creation, and premium AI features. Most text-focused creators won't come close to the cap. #### **What does the Blotato free trial include?** The catch first: generating an API key from Settings immediately ends your trial and activates your paid subscription, even with days left on it. So if you came for the API or the MCP server, budget for a paid first month rather than planning to trial those. Everything else is covered for the full 7 days, with one limit worth knowing. The trial hands you 60 AI credits instead of your plan's full monthly allotment, which is plenty to judge the writing and scheduling but thin for image and video generation. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## 7 Best AI Automation Tools in 2026 (Tested by a Founder) URL: https://ryandoser.com/best-ai-automation-tools/ Markdown: https://ryandoser.com/best-ai-automation-tools.md Published: 2026-08-05 | Updated: 2026-08-05 Categories: AI Tool Reviews > Most AI automation tools lists are written by the companies themselves. Here are my top AI automation tools after using them in my business. The **best AI automation tools** in 2026 are the ones that actually run your work while you sleep. I run SEO and content systems for a seven-figure SaaS, a cybersecurity brand, and affiliate clients, and I have automations firing in the background across all of them right now. I am not an engineer. I am a marketer who learned these tools the hard way, by wiring them up for real client work and eating the bill when I got it wrong. So this list is written for people like me: creators, solopreneurs, and lean teams who want automation that works without a computer-science degree. If you are shopping for enterprise RPA (UiPath, Microsoft Power Automate, Workato), this is not that list, and I will point you there at the end. ### **Why Most "Best AI Automation Tools" Lists Are Useless** Start with the dirty secret about this keyword. The top two results for it are published by two of the tools being ranked. Zapier's roundup concludes you should use Zapier. n8n's roundup concludes n8n is the best pick. You can smell the thumb on the scale. I do not sell any of these tools. I use them, break them, and pay for them with my own money. So this list ranks by what happens when real work hits the platform, not by who has the biggest ad budget. I took the same no-spin approach with the [best AI writing tools](/best-ai-writing-tools/), where most of the market turns out to be wrappers reselling the same models. One more thing the other lists miss. Automation is splitting into two camps. The classic no-code builders (Zapier, Make, n8n) still run most of the world's workflows, following a rigid if-this-then-that chain you map out in advance. If the specific job you are automating is social publishing, I worked through [why per-task billing is the wrong shape for that](/best-zapier-alternatives/) separately. The new camp is AI-agent-native automation, where a model like Claude reads the situation and decides what to do instead of following a fixed script. The old way follows your rules. The new way makes its own calls. I cover both, because your stack in 2026 probably needs one of each. ### **AI Automation Tools at a Glance** | Tool | Best for | Starts at | Self-host | AI-agent-native | | **n8n** | Self-hosting + high-volume AI work | Free (self-host) / $20/mo cloud | Yes | Yes | | **Make** | Visual builders who want power | $12/mo | No | Partial | | **Zapier** | Beginners + widest app coverage | $19.99/mo | No | Partial | | **Claude Code** | Agent-native reasoning, not rigid steps | Pro/Max plan | No | Yes | | **Gumloop** | AI-first no-code building | $37/mo | No | Yes | | **Lindy** | Standing up an "AI employee" | $49.99/mo | No | Yes | | **Relay.app** | Human-in-the-loop approvals | $19/mo | No | Yes | ### **The 7 Best AI Automation Tools in 2026** Every pick below gets the same treatment: pros, cons, who it fits, real pricing, and what the community actually says once the trial ends. #### **1. n8n (Best for Self-Hosting and High-Volume AI Workflows)** *n8n leads the list for self-hosting and high-volume AI workflows.* When a client's data cannot leave their own servers, I reach for [n8n](https://n8n.io). It is source-available, self-hostable, and built with native AI-agent nodes, so you can run multi-step LLM workflows without paying a toll on every action. **Pros:** - Self-host the Community Edition for free with no per-run execution limits. - Native AI-agent nodes for real multi-step LLM workflows. - The go-to recommendation on Hacker News over Make, Zapier, and Pipedream for high-volume work. **Cons:** - The steepest learning curve of any tool here. - Paid cloud and Business tiers draw pricing complaints (more below). **Best for:** self-hosters, developers, and anyone doing high-volume AI work. **Pricing:** Community Edition free to self-host. Cloud Starter is $20 per month billed annually for 2,500 workflow executions, and Pro is $50 for 10,000. Business runs $800 for 40,000 and is listed as a self-hosted plan rather than a hosted one. Every tier meters executions rather than active workflows, and steps inside an execution are unlimited. **Free trial:** Yes, plus a genuinely free self-hosted edition. **Bottom line:** If you can self-host, n8n is the cheapest and most private option on this list, and nothing else comes close on high-volume AI work. The recurring gripe is cloud pricing. n8n's own community forum has a long, heated thread about the paid tiers' execution ceilings, with users frustrated that even a pricey plan on their own compute still meters them. If you self-host the free edition, none of that touches you, which is the whole point. n8n raised a $180M round in late 2025 and took a strategic investment from SAP in 2026, so it is not going anywhere. If you want the deeper argument for why this platform is winning, I wrote a whole piece on [whether n8n is dead or dominating](/is-n8n-dead/). #### **2. Make (Best Value for Visual Builders)** *Make is the best-value visual builder for real branching logic.* Hand [Make](https://www.make.com) to a marketer who wants real branching logic without touching code, and they will build something useful the same day. Its scenario canvas lets you create loops, filters, and multi-path automations visually, and it runs genuinely cheaper than Zapier at volume. **Pros:** - Node-based canvas that HN builders rate as more powerful than Zapier's linear steps. - Real branching, loops, and filters without code. - Cheaper than Zapier once your volume climbs. **Cons:** - Every module burns a credit, including triggers and filters Zapier runs for free. - Auto-purchase of extra credits can produce surprise costs. - A single error can halt every future run if you do not build error branches. **Best for:** non-developers who want visual power on a budget. **Pricing:** Free tier of 1,000 credits per month. Core starts at $12 per month. Each module action counts as one credit, so complex scenarios burn faster than you expect. **Free trial:** Yes, a free tier you can stay on. **Bottom line:** The best value for anyone who wants visual power and real logic without paying Zapier's premium, as long as you watch your credit burn. One warning worth repeating. One user on Make's own community forum documented how a sequential-processing setup meant a single error halted every future run until he fixed it. Build with error branches from day one. #### **3. Zapier (Best for Beginners and App Coverage)** *Zapier still wins on app coverage and beginner-friendly setup.* For someone who has never automated anything, [Zapier](https://zapier.com) is still my recommendation. Nothing else touches its app catalog, and its Copilot lets you describe a workflow in plain English and get a working Zap back. **Pros:** - The widest integration catalog of any tool here, by a mile. - Copilot builds a working Zap from a plain-English description. - Rock-solid reliability that kept it the default for a decade. **Cons:** - Gets brutally expensive at scale, since retries and loops each burn a task. - AI Agents are priced separately from your main plan. - AI-heavy Zaps eat tasks faster thanks to mid-2026 model-tier multipliers. **Best for:** total beginners and anyone who needs the widest integration list. **Pricing:** Free tier of 100 tasks per month. Professional starts at $19.99 per month billed annually ($29.99 monthly), priced up through fixed task tiers as your volume grows. AI steps now carry model-based multipliers, so an AI-heavy Zap costs more than a plain one. **Free trial:** Yes, a permanent free tier. **Bottom line:** Still the best place to learn automation and the safest bet for app coverage, but budget carefully before you scale. The pain is the bill. Builders regularly report monthly invoices running into the hundreds once retries and loop iterations pile up, because each one burns a task. Zapier has pivoted hard toward AI, but the market perception is that n8n and the agent-native tools moved quicker, and n8n has overtaken it on search interest. #### **4. Claude Code (Best for AI-Agent-Native Automation)** *Claude Code Routines run prompts on a schedule, API call, or GitHub event.* This is the pick no other roundup makes, and it is the one my readers should watch closest. For the social-specific side of this, see my [breakdown of publishing and scheduling tools](/social-media-automation-tools/). Claude Code has grown past being a coding tool. With [Routines](https://code.claude.com/docs/en/routines) and [scheduled tasks](https://code.claude.com/docs/en/scheduled-tasks), it runs prompts on a schedule, on an API call, or on a GitHub event, with Claude doing the actual reasoning. **Pros:** - A model reasons through the task instead of following a rigid flowchart. - Triggers on a schedule, an API call, or a GitHub event. - Closer to hiring a junior operator than wiring a diagram. **Cons:** - Non-determinism makes it risky for correctness-critical jobs. - In routine mode, connected tools including writes run without asking permission. - No free tier, so it needs a paid Claude plan. **Best for:** builders who want a model, not a rigid workflow, doing the thinking. **Pricing:** No standalone free tier. Included with a paid Claude Pro or Max plan. Routines run on Anthropic's cloud. **Free trial:** No, it runs on a paid Claude plan. **Bottom line:** The pick that ages best for reasoning-heavy work, as long as you keep it away from jobs where one wrong number is a disaster. The difference is real. A Zap follows fixed steps. A Claude Routine reads the situation and decides what to do: groom your issue tracker every weeknight, triage an alert your monitoring tool POSTs to its endpoint, or run a weekly research sweep and open a draft. The catch is real too, and the community says so plainly. On Hacker News, developers point out that the same non-determinism that makes Claude flexible also makes it unpredictable. It can hallucinate, and in routine mode all connected tools including writes are allowed, so an agent can go off-script. One finance user said constant double-counting made it worthless for numbers he could not re-check. Use Claude Code automation for reasoning-heavy, review-friendly work. If you are new to it, start with [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) before you wire up a Routine. #### **5. Gumloop (Best AI-First No-Code Builder)** *Gumloop is the strongest AI-first no-code builder in the group.* [Gumloop](https://www.gumloop.com) feels like Zapier rebuilt from scratch around a model instead of bolting AI on afterward. It is a visual, no-code canvas built AI-first, so the automation and the reasoning live in the same place. **Pros:** - Built AI-first, so reasoning and automation live on the same canvas. - Model-agnostic routing and reusable Subflows few competitors match. - Marketers rate the build experience above most no-code AI tools. **Cons:** - Credit consumption is hard to predict. - A small change can jump a workflow from a couple of credits to dozens. **Best for:** teams that want an AI-native visual builder. **Pricing:** Free tier of 5,000 credits per month. Pro starts at $37 per month. **Free trial:** Yes, a free tier with monthly credits. **Bottom line:** The strongest AI-first builder here, backed by a $50M Benchmark round, as long as you test credit burn before you scale. Investors agree. Gumloop raised a $50M round led by Benchmark in early 2026. #### **6. Lindy (Best for Building an AI Employee)** *Lindy is built for standing up an AI employee, not a flowchart.* [Lindy](https://www.lindy.ai) is less a workflow builder and more an AI teammate. You describe the job in plain language, connect your inbox, calendar, and CRM, and it acts: drafting replies, booking meetings, and handling follow-ups without you mapping a single node. **Pros:** - Non-technical operators stand up a useful assistant in an afternoon. - Tight Google, HubSpot, and Slack integration. - A big template library to start from. **Cons:** - The credit system is the most-complained-about thing about it. - A single voice call can burn hundreds of credits. - Users report billing complaints, including charges after cancellation. **Best for:** people who want an AI employee, not a flowchart. **Pricing:** No free tier, just a 7-day trial. Plus starts at $49.99 per month. **Free trial:** Yes, 7 days, no permanent free tier. **Bottom line:** The fastest way to a working AI assistant, but watch the meter closely and cancel cleanly if you stop. #### **7. Relay.app (Best for Human-in-the-Loop AI)** *Relay.app builds a human approval step directly into AI workflows.* [Relay.app](https://www.relay.app) solves the one thing that scares people about AI automation: letting a model send something without a human seeing it first. Its whole engine is built around approval checkpoints, so an automation can pause, wait for you to edit or approve, then continue. **Pros:** - The strongest human-in-the-loop approval steps in the group. - 4.9 out of 5 across dozens of G2 reviews. - Perfect for automations that draft client emails or social posts. **Cons:** - 200+ integrations, far fewer than Zapier or Make. - A niche app you rely on may not be supported yet. **Best for:** teams that need a human approval step inside AI workflows. **Pricing:** Free tier of 500 AI credits and 200 steps per month. Professional starts at $19 per month billed annually. **Free trial:** Yes, a free tier with monthly credits. **Bottom line:** The safest way to put AI in front of your audience, as long as your must-have apps are among its 200-plus connectors. ### **Honorable Mentions (Community Darlings the Big Lists Skip)** These are the tools people who live in this space keep recommending, even though generic roundups bury them. - **Activepieces:** the open-source, self-hostable escape hatch from per-task billing. MIT-licensed with 700+ integrations, free to self-host, paid cloud from around $5 per active flow. See [Activepieces](https://www.activepieces.com). - **Pipedream:** developer-first, with real code steps in Node, Python, Go, and Bash, and a generous free tier. Loved for internal tools and side projects, though costs climb past the free plan. See [Pipedream](https://pipedream.com). - **Bardeen:** Zapier for your browser. One-click no-code scraping and lead enrichment right in Chrome, with a free tier and paid plans from $10 per month. It stops when Chrome closes, so it fits GTM tasks more than always-on pipelines. See [Bardeen](https://www.bardeen.ai). ### **How to Choose an AI Automation Tool** Before you commit to any platform, run your use case through these five questions. They are the same ones I ask on every client build. - **Does your data need to stay private?** If a client's data cannot leave their servers, you need self-hosting, which narrows you to n8n or Activepieces fast. - **How much do you plan to run?** Low volume favors Zapier's simplicity. High volume favors n8n's per-execution or self-hosted pricing before the bill gets scary. - **Do you want rules or reasoning?** A fixed if-this-then-that chain (Zapier, Make) is predictable. An agent that makes its own calls (Claude Code, Lindy, Gumloop) is flexible but non-deterministic. - **How much can you afford to get wrong?** For correctness-critical work, keep a human in the loop with Relay.app, or stick to rule-based tools. - **How technical are you, really?** Zapier and Lindy ask the least of you. n8n, Pipedream, and Claude Code reward people willing to get their hands dirty. ### **Which AI Automation Tool Should You Pick?** Ran your use case through the five questions above? Match your situation below. - **Never automated anything:** Zapier. - **Want visual power without a developer:** Make. - **Self-hosting, private client data, or high volume:** n8n. - **Want a model reasoning, not a rigid chain:** Claude Code. - **Want an AI employee, not a workflow:** Lindy. - **Need a human approval step before anything sends:** Relay.app. #### **n8n vs Make vs Zapier, in One Line Each** This is the comparison everyone actually searches. Zapier is the easiest with the most integrations and the priciest at scale. Make is the best value with the most visual power and a moderate learning curve. n8n is the cheapest at volume, the only real self-host and data-privacy option, and the steepest to learn. I broke the first two down properly, plus the option of skipping the workflow builder altogether, in [this head to head on billing models](/zapier-vs-n8n/). ### **n8n Alternatives, Ranked by Why You Are Leaving** Plenty of people arrive here already running n8n and wondering what else is out there. The honest answer depends entirely on which part of n8n is bothering you, so pick the row that matches your reason. | Why you are leaving n8n | Start with | What it costs to begin | | The learning curve beat you | Zapier | Free for 100 tasks a month, then $19.99/mo billed annually for 750 | | You want visual power without the complexity | Make | Free for 1,000 credits a month, then $12/mo | | You want an open-source builder you can host yourself | Activepieces | Free self-hosted Community Edition | | You would rather write real code than wire nodes | Pipedream | Free tier with a daily credit limit | | You want a model reasoning instead of a fixed chain | Claude Code | Included with a paid Claude plan | Two of those I run myself, and both get full cards above. Zapier is where I send anyone who found n8n's canvas overwhelming, and Make is where I send people who liked the canvas and wanted it cheaper. The rest of this section is documentation and pricing analysis rather than firsthand use, and I have labeled it that way on purpose. #### **The Meter Is the Real Difference, Not the Sticker Price** A five-step workflow running 150 times a month puts you exactly on Zapier's $19.99 ceiling with zero headroom. Triple that volume and you are not paying triple, you are paying $89. On n8n both versions of that workflow sit on the same $20 plan. That cliff is what the headline prices hide, because these platforms do not bill for the same thing at all. n8n bills per **workflow execution**, and steps inside that execution are unlimited. Zapier bills per **task**, where a task is each action that successfully runs. Make bills per **credit**, and every module action burns one. Here is the same job costed on all three. Take a workflow that fires 150 times a month and performs five actions each time. On n8n that is 150 executions, comfortably inside the $20 Starter tier's 2,500. On Zapier that is roughly 750 tasks, which lands exactly on the $19.99 Professional tier and leaves you nothing spare. Make counts about 750 credits for the same job, which still fits inside its free tier of 1,000. Now triple the volume to 450 runs a month. n8n is still 450 executions, so you are still on the $20 plan with room to spare. Zapier becomes roughly 2,250 tasks. That overshoots the 2,000-task tier at $49 and pushes you to the 5,000-task tier at $89 a month billed annually. That gap is why some people leave n8n over price and then come back. Your step count multiplies the bill on Zapier and Make, while it does nothing to the bill on n8n. Long workflows get relatively cheaper on n8n as they grow, which is the opposite of how the other two behave. #### **The Open-Source Options I Have Not Run** These come up constantly in the n8n subreddit, and naming them beats pretending the list is complete without them. I read the fine print on each one and I have not run any of them for a client, so treat this as research rather than a recommendation. - **[Activepieces](https://www.activepieces.com):** the closest thing to a drop-in replacement, and the tool cited most often when this question comes up. You can put it on your own server for free with no cap on runs, users, or flows. The catch is that the team and admin features are held back for paying customers, so "free" covers the building, not the governance. - **[Pipedream](https://pipedream.com):** the one most lists get wrong. It has a public code repository, which makes people assume they can host it themselves, and you cannot. There is no self-hosted version at all, so you are a cloud customer either way. Its free tier resets credits daily rather than monthly, and the published number has moved around, so check it before you plan a budget on it. Workday acquired the company. - **[Windmill](https://www.windmill.dev):** built for people who would rather write a script than drag a node. Instead of one monthly price you pay per person plus per unit of computing power, so there is no single number I can quote you. Budget for it as a variable cost, not a subscription. - **[Kestra](https://kestra.io):** aimed at data engineering teams rather than marketing stacks, and it shows in the setup. Hosting it yourself is genuinely free with no limit on how much you run. Their cloud version exists but does not publish a price, which tells you who it is sold to. - **[Node-RED](https://nodered.org):** the veteran here, free, and run by a foundation rather than a company, so there is no vendor with an incentive to reprice it on you. It is strongest for hardware and sensor projects, which makes it a slightly odd fit for a marketing workflow. One correction worth making, because most roundups get it backwards. Pipedream and Windmill both get filed under "open-source n8n alternatives" routinely, and neither one really earns the label. Pipedream cannot be self-hosted at all, and the ready-made Windmill package most people install ships with closed pieces mixed in. If getting off someone else's servers is the whole reason you are shopping, Activepieces, Kestra, and Node-RED are the three that actually deliver it. ### **What About Enterprise Tools Like UiPath and Power Automate?** If you landed here looking for heavyweight RPA, this is not your list, and that is on purpose. [UiPath](https://www.uipath.com), [Microsoft Power Automate](https://www.microsoft.com/en-us/power-platform/products/power-automate), and [Workato](https://www.workato.com) are built for enterprise IT teams with procurement departments and compliance requirements, not for a marketer wiring up their own stack on a Sunday. They are excellent at what they do. They are also overkill, over-budget, and over-complicated for the people I write for. If you have an IT department and a six-figure automation budget, start there. Power Automate is worth a closer look if your company already runs on Microsoft 365, and I broke down [when that ecosystem actually wins](/microsoft-copilot-for-business/) after interviewing someone who builds inside it daily. If you are a team of one to fifty who wants results this week, stay on the seven picks above. ### **Ryan's Final Thoughts** The best AI automation tool is the one that matches your constraint. Pick Zapier to learn, Make for value, n8n for control, and Claude Code when you want a model doing the thinking. Most serious stacks in 2026 run two of these, a classic builder for reliable plumbing and an agent-native layer for the judgment calls. Every pick above I have used in my own business, and I checked every price on each tool's own pricing page the week this was updated. Want the exact workflows and prompts I use to run this stack across client accounts? That is what I package inside my [AI Skills Stack](https://skills.ryandoser.com/), built on a decade of doing this work rather than a repo of generic templates. You can start free, then decide. ### **AI Automation Tools FAQs** #### **Which is better than n8n?** Nothing is better across the board, which is why this list has seven picks instead of one. Zapier is better if you found n8n's canvas overwhelming and you want the widest app catalog. Make is better if you want visual branching logic at a lower price. Claude Code is better when you want a model making judgment calls rather than following a fixed chain. n8n remains the cheapest of these three at high volume, and the one of them you can run on your own server. #### **Is n8n obsolete now?** No. n8n raised a $180M round in late 2025, took a strategic investment from SAP in 2026, and its self-hosted Community Edition still has no per-run execution limits. Deterministic workflow builders are not going away, because plenty of jobs need predictable, repeatable plumbing rather than a model improvising. What has changed is that agent-native tools now handle the reasoning-heavy work n8n was always awkward at. #### **Is there a free n8n alternative?** Yes, several, and they are free in different ways. Make gives you 1,000 credits a month on a permanent free tier. Zapier gives you 100 tasks a month, limited to two-step workflows. Activepieces, Kestra, and Node-RED are free to self-host with no run caps, though you are supplying the server and the maintenance. n8n's own Community Edition is also free to self-host, so leaving is not required to stop paying. #### **What is the best open-source n8n alternative?** Activepieces gets named most often, and it is the closest thing to a drop-in visual replacement. It is free to host yourself, though the team and admin features are reserved for paying customers. Kestra is the other genuinely free option, built for data work rather than marketing. Be careful with Pipedream here, because it gets misfiled as open source constantly and there is no way to host it yourself at all. #### **Which AI workflow automation tool is best for beginners?** Zapier, without much competition. Its Copilot turns a plain-English description into a working automation, the app catalog is the largest available, and the free tier lets you learn without a card. The tradeoff arrives later, because task-based billing gets expensive once retries and loops pile up. Learn on Zapier, then move the high-volume workflows somewhere cheaper. --- ## 8 Best Metricool Alternatives in 2026 (Tested) URL: https://ryandoser.com/metricool-alternatives/ Markdown: https://ryandoser.com/metricool-alternatives.md Published: 2026-08-05 | Updated: 2026-09-30 Categories: AI Tool Reviews > The 8 best Metricool alternatives, priced across six different billing units with the real cost worked out at two account sizes. Most **Metricool alternatives** lists rank tools by their starting price, which is the one number that cannot be compared across them. I tested and priced these myself rather than rewriting vendor copy. Every figure here was checked against each tool's own pricing page the day I wrote it, and each card tells you exactly how much hands-on time I have with that tool. That ordering matters here, so I will say it plainly up front. [Blotato](https://www.blotato.com/?ref=rdoser) sits first because it is the tool I actually run in production every day, and it is also a client of mine with a comped account and affiliate links. Weigh that placement accordingly. The tools below it I have used less, and the ones at the bottom I have not run at all, which I flag on each entry rather than burying. ### **Why Comparing Starting Prices Tells You Nothing** Metricool charges per brand. Buffer charges per channel and Hootsuite charges per seat, a split I ran into again when testing [social media automation tools](/social-media-automation-tools/). Later sells you a "social set" of eight profiles. Publer runs two separate multiplying sliders, one for accounts and one for teammates. That is Metricool plus the eight alternatives below, and six different billing units between them. So a table of starting prices puts $6 next to $99 and implies Buffer is sixteen times cheaper than Hootsuite. The real answer depends entirely on how many accounts and how many people you have. So this post does the arithmetic instead. I picked two situations, a solo creator running six accounts and a small agency running twenty-five, and priced every tool at both. The ranking changes between them, which is the whole point. ### **Metricool Alternatives at a Glance** | Tool | Best for | Starts at | What the bill scales with | Free plan | | **Blotato** | Publishing from an AI agent instead of a dashboard | $29/mo | Tier steps only, not per account or seat | No | | **Buffer** | A creator who wants the simplest scheduler | $6/mo per channel | Each channel you connect | Yes, 3 channels | | **Publer** | Cheapest per account at mid volume | $5/mo, then $4 per extra account | Accounts and teammates, separately | Yes, 3 accounts | | **SocialPilot** | Agencies that want accounts and seats bundled | $20/mo | Tier steps, 5 accounts at a time | No | | **Planable** | Teams where clients approve posts before they go out | $39/mo per workspace | Workspaces, with unlimited users | Yes, first 50 posts | | **SocialBee** | Recycling evergreen content on a schedule | $29/mo | Tier steps, profiles and seats together | No | | **Later** | Visual planning for Instagram-first brands | $25/mo | Social sets of 8 profiles | No | | **Hootsuite** | Larger teams that need social listening | $99/user/mo | Every person you add | No | Figures are the entry paid tier from each vendor's own page, monthly billing, except Hootsuite which publishes per-seat rates annually only. ### **The 8 Best Metricool Alternatives in 2026** Every entry gets the same treatment, including how much of the tool I have actually used. #### **1. Blotato (Best for Publishing From an AI Agent)** *Blotato leads with an API and MCP server rather than a dashboard.* [Blotato](https://www.blotato.com/?ref=rdoser) is the one tool here I use every working day, and it does not look much like Metricool. There is a dashboard, but I almost never open it, because everything publishes through its MCP server from Claude Code. **Pros:** - The bill does not move when you add accounts or teammates inside a tier. - An MCP server and API that an AI agent can drive directly, which is the whole reason I use it. - Nine platforms behind one key, so there is no per-network approval process to sit through. **Cons:** - No free plan, and the 7-day trial excludes the API, so the people most likely to want this cannot properly test it. - Analytics are far thinner than Metricool's, which is the main reason to stay put. - If you want a calendar to click around in, you are paying for machinery you will not touch. - Credits meter your AI usage, so heavy generation months cost more than the sticker price. **Best for:** people publishing through an agent or a script rather than a dashboard. If that is the job, the wider field of [social media APIs](/social-media-api/) is worth reading first. **Pricing:** Starter $29 per month for 20 social accounts and 1,250 AI credits. Creator $97 for 40 accounts and 5,000 credits. Annual billing saves around 17 percent. **Free trial:** 7 days, card required, and it does not include the API. **My experience:** Production use, daily, for over a year. It is also a client and my account is comped, and I wrote up the full picture in my [hands-on review](/blotato-review/). **Bottom line:** The right swap only if your reason for leaving Metricool is that you want a machine posting for you. If you want better reports, this is the wrong direction entirely. So if you are evaluating it for the API, plan on starting the subscription rather than trialling it. I went deeper on where each tool wins in my [full Blotato and Metricool comparison](/blotato-vs-metricool/). #### **2. Buffer (Best for the Simplest Possible Scheduler)** *Buffer keeps the simplest interface of any tool on this list.* [Buffer](https://buffer.com) is the tool I recommend when somebody wants a clean calendar and nothing else. Its pricing is also the most misread on this list. **Pros:** - A genuinely useful free plan covering three channels. - The cleanest interface of anything here, with almost no learning curve. - You pay only for the channels you actually connect. **Cons:** - That per-channel price multiplies fast, and most people do the math too late. - Reporting is shallow next to Metricool, which is probably why you are reading this. - One user on the entry plan, so collaboration means moving up a tier. **Best for:** a solo creator with a handful of channels who wants zero complexity. **Pricing:** Free for 3 channels. Essentials is $6 per month *per channel* on monthly billing, or $5 on annual. Team is $12 per channel, or $10 annual, with unlimited users. The rate drops above 10 channels, to $4 each between 11 and 25. **Free trial:** 14 days on paid plans. **My experience:** I have used Buffer and have recommended it publicly, though I do not run my publishing through it. **Bottom line:** The best product here for one person with few channels, and quietly expensive the moment that stops being true. I compared it directly against my own stack in [this Buffer breakdown](/blotato-vs-buffer/). The number to watch is the unit. Buffer's "$6" is a price per channel rather than a plan price, so ten channels is $60 a month. Their own rate card publishes the worked examples, which is more than most vendors here manage. #### **3. Publer (Best Value Once You Pass Ten Accounts)** *Publer prices per social account with every tenth account free.* [Publer](https://publer.com) also charges per account, but unlike Buffer the first one costs more than the rest, and then a volume rule kicks in that almost nobody mentions. **Pros:** - Every tenth social account is free, which quietly cuts the rate as you grow. - A real free plan with three accounts. - Cheaper per account than most of this list at double-digit volume. **Cons:** - Teammates are a second multiplying slider, so a team of five costs more than it first appears. - API access is locked to the Business tier. - The interface carries more clutter than Buffer's. **Best for:** one person or a small team running a lot of accounts on a budget. **Pricing:** Free for 3 accounts. Professional starts at $5 per month for the first social account, then $4 for each extra one and $2 per extra member. Business starts at $10, then $7 per extra account and $3 per extra member. Every 10th social account is free. **Free trial:** Yes, and the free plan lets you test most paid features without a card. **My experience:** Never run it. Everything above comes from their pricing page and help docs. **Bottom line:** The cheapest way to run many accounts here, as long as you are not also adding many people. #### **4. SocialPilot (Best for Agencies That Want One Predictable Number)** *SocialPilot bundles accounts and seats into predictable tiers.* [SocialPilot](https://www.socialpilot.co) bundles accounts and seats into tiers, which makes it boring to forecast in the best way. **Pros:** - Accounts and user seats move together, so there are no surprise per-unit add-ons. - Client-facing reporting aimed squarely at agencies. - 14-day trial with no card required. **Cons:** - Bundling cuts both ways, since you buy seats you may not need to get accounts you do. - No free plan. - Tiers step in jumps of five accounts, so being one over a limit costs a whole tier. **Best for:** small agencies that want a single predictable invoice. **Pricing:** Essentials $20 per month, or $17 billed annually, for 5 accounts and 1 seat. Standard $40 for 10 accounts and 3 seats. Premium $100 for 20 accounts and 6 seats. Ultimate $200 for 40 accounts with unlimited seats. **Free trial:** 14 days, no credit card. **My experience:** No hands-on time with it. I priced it and read the docs, nothing more. **Bottom line:** The most predictable bill on this list for an agency, provided your account count lands near a tier boundary rather than just above one. #### **5. Planable (Best for Client Approvals Before Anything Publishes)** *Planable builds client approvals into the publishing flow.* [Planable](https://planable.io) ranks first on this SERP for a reason, and it is the only tool here whose pricing gets cheaper as your team grows. **Pros:** - Unlimited users on every workspace, which inverts how everyone else charges. - Approval workflows built for showing a client work before it goes live. - The first 50 posts are free with no time limit and no card. **Cons:** - Analytics and the social inbox are paid add-ons rather than included features. - Post volume is capped per workspace, at 60 a month on the entry tier. - Social pages are capped too, at 4 on Basic, so six accounts already pushes you to Pro. **Best for:** teams and agencies where somebody signs off on posts before they publish. **Pricing:** Basic $39 per workspace per month billed monthly ($33 on yearly) for 60 posts, 4 social pages and unlimited users. Pro $59 per workspace ($49 on yearly) for 150 posts and 10 pages. Analytics and inbox add-ons cost extra per workspace. **Free trial:** First 50 posts free, no time limit, no credit card. **My experience:** Researched, not used. I have never had a client on it. **Bottom line:** The only tool here that gets relatively cheaper as headcount grows, which makes it the natural pick if approvals are your bottleneck. #### **6. SocialBee (Best for Recycling Evergreen Content)** *SocialBee is built around recycling evergreen content categories.* [SocialBee](https://socialbee.com) is built around content categories that refill themselves, which is a different job from what Metricool does. **Pros:** - Category-based recycling that keeps evergreen posts in rotation automatically. - 14-day trial with no card, plus a 30-day money-back guarantee. - Straightforward tiers with no per-unit surprises. **Cons:** - No free plan at all. - Profiles, users and workspaces all step together, so you overbuy on two axes to fix one. - Analytics do not approach Metricool's depth. **Best for:** people with a library of evergreen posts they want recirculated. **Pricing:** Bootstrap $29 per month, or $290 a year, for 5 profiles, 1 user and 1 workspace. Accelerate $49 for 10 profiles. Pro $99 for 25 profiles, 3 users and 5 workspaces. **Free trial:** 14 days, no credit card. **My experience:** Never signed up. This is a docs-and-pricing read. **Bottom line:** Worth it specifically for the recycling engine, and hard to justify if you post fresh content each time. #### **7. Later (Best for Instagram-First Visual Planning)** *Later sells plans in social sets of eight profiles.* [Later](https://later.com) sells its plans in "social sets," a unit nobody else on this list uses and the one most likely to catch you out. **Pros:** - Visual grid planning that genuinely suits Instagram-led brands. - A social set covers eight profiles, one per network, which is generous for a single brand. - Extra sets and users can be added individually rather than by jumping a tier. **Cons:** - A set holds one profile per network, so two Instagram accounts means two sets. - No free plan. - Post volume is capped per profile on the entry tier. **Best for:** one visual brand posting across many networks. **Pricing:** Starter $25 per month, or $18.75 billed annually, for 1 social set of 8 profiles and 1 user. Growth $50 for 2 sets, Scale $110 for 6 sets and 4 users. Extra sets and users can be bought individually, priced on their annual rates. **Free trial:** 14 days. **My experience:** No firsthand use. I only worked through what they publish. **Bottom line:** Excellent for a single visual brand, and structurally wrong for anyone running several accounts on the same network. #### **8. Hootsuite (Best for Teams That Need Social Listening)** *Hootsuite prices per seat rather than per social account.* [Hootsuite](https://www.hootsuite.com) is the most expensive entry point here by a wide margin, and it is priced per person rather than per account. **Pros:** - Social listening and analytics depth that most of this list does not attempt. - Unlimited social accounts from the Professional tier upward. - 14-day trial with no card and no automatic charge at the end. **Cons:** - Sold per seat, so the bill tracks headcount rather than workload. - $99 per user per month is a steep jump from every other tool here. - Overkill for a solo creator by a wide margin. **Best for:** established teams that need listening and governance, not just scheduling. **Pricing:** Standard $99 per user per month billed annually, covering up to 10 social accounts. Professional $199 per user with unlimited accounts. Advanced $399 per user. **Free trial:** 14 days, no credit card required. **My experience:** Never run it, and at this price I have never had reason to. **Bottom line:** The right answer only if listening is the feature you are missing, and an expensive mistake if you just want to schedule posts. ### **The Same Job, Priced at Two Real Volumes** Below is what each tool costs at two situations, every figure computed from the rates on each vendor's own page, using monthly billing wherever a vendor offers it. Hootsuite publishes annual-billed prices only. | Tool | Solo creator, 6 accounts, 1 person | Small agency, 25 accounts, 3 people | | **Publer** | $25 | $97 | | **Later** | $25 | $110 | | **Blotato** | $29 | $97 | | **Buffer** | $36 | $180 | | **SocialPilot** | $40 | $200 | | **SocialBee** | $49 | $99 | | **Planable** | $59 | $177 | | **Hootsuite** | $99 | $597 | How each figure is built, so you can check it. Publer is $5 for the first account plus $4 for each additional, with every 10th free, so 25 accounts means paying for 23, and the two extra teammates add $2 each. Later's $25 assumes those six accounts sit on six different networks, because a social set holds one profile per network. Its agency row is the Scale tier at $110 monthly, the first tier carrying enough sets and users for twenty-five accounts and three people. Blotato stays on Starter at six accounts and moves to Creator at twenty-five. Buffer charges $6 a channel on Essentials for the solo row, and the agency row uses its Team rate. On Buffer's Team plan the rate card lists $12 a channel for the first ten and $4 for eleven to twenty-five, and its published example table puts 25 channels at $180 a month. Planable's Basic covers only four social pages, so six accounts already needs Pro and twenty-five needs three Pro workspaces. SocialPilot jumps from Standard to Ultimate. Hootsuite is per seat, so three people on Professional is three times $199. Billing basis: Hootsuite publishes per-seat rates on annual billing only, and every other figure is the monthly rate. Later and SocialBee both display annual pricing by default on their sites, so their monthly figures run higher than the number you see first. Read the two columns against each other and the ranking scrambles. Publer and Later tie for cheapest at the solo end, and by twenty-five accounts Later has more than quadrupled while Publer lands level with Blotato. Buffer sits mid-pack at six channels and second-highest at twenty-five, because the unit that felt cheap is the unit that multiplies, even after its volume discount. SocialBee runs the opposite way, joint-most-expensive for one person and third-cheapest at agency scale. And Hootsuite goes from roughly three times the price of this list to six times it, purely because seats and accounts scale differently. Blotato moves the least across both columns in proportional terms, though Publer matches it on the agency figure. That is the honest argument for flat pricing, and it is an argument about billing rather than features. These are list prices at a snapshot. Confirm against the vendor's page before you commit, because several changed tiers in the last year. ### **Which Metricool Alternative Should You Pick?** Match your situation to the pick. The rule underneath all of these is to match the billing unit to whatever grows in your business, accounts or people. - **An agent or script does your posting:** Blotato. - **One person, few channels, wants simple:** Buffer. - **Many accounts, small budget:** Publer. - **Clients approve posts before they publish:** Planable. - **A library of evergreen posts to recycle:** SocialBee. - **One visual brand across many networks:** Later. - **You need social listening:** Hootsuite. - **Reporting is the actual deliverable:** stay on Metricool. - **You want a video mirrored automatically when you publish it:** none of these, that is a [different category of tool](/repurpose-io-alternatives/). ### **What About Sprout Social, Sendible, and SocialBu?** These three come up constantly on this query and are not ranked above, so here is why. [Sprout Social](https://sproutsocial.com) is a genuine Metricool alternative on features, and it sits well above this price bracket. It starts far north of Hootsuite for most teams, which puts it outside what the people reading this are shopping for. [Sendible](https://www.sendible.com) overlaps almost entirely with SocialPilot for the agency use case. I cannot separate them on anything except price, so ranking both would pad the list without helping you choose. [SocialBu](https://socialbu.com) ranks on this term largely through its own comparison page rather than through adoption I can verify. These three sit outside the ranking because they are out of this price bracket, redundant with something already ranked, or thin on evidence anyone is switching to them. ### **Ryan's Final Thoughts** Metricool is genuinely good at the thing it is built for, which is reporting. Most people leaving it are not leaving because the analytics failed, they are leaving because the bill stopped matching how they work. Pick the tool whose billing unit matches your growth axis, and check the arithmetic at the size you will be next year rather than the size you are now. If an AI agent is doing your posting, that changes the answer more than any feature comparison will. ### **Metricool Alternatives FAQs** #### **What is the best Metricool alternative?** There is no single best one, because these tools bill on six different units. Buffer is the best pick for a solo creator with a few channels. Publer is cheapest once you run more than ten accounts. Planable wins if clients approve your posts. Hootsuite is the answer only if you need social listening. If a machine does your publishing, Blotato is the closest fit, and that is the tool I use. #### **Is there a free Metricool alternative?** Yes, three of them. Buffer's free plan covers 3 channels with 10 scheduled posts each. Publer's free plan also covers 3 accounts, though it excludes X. Metricool's own free plan leaves out LinkedIn and X too. Planable gives you your first 50 posts free with no time limit and no credit card. Metricool itself has a free plan for 1 brand and 20 posts a month, so leaving is not required to stop paying. #### **Why is Metricool so cheap compared to alternatives?** Because it prices per brand rather than per account or per seat. One brand bundles all of that brand's connected networks under a single price, which is excellent value for a single business and gets expensive for an agency running many separate clients. The tools that look pricier next to it are often charging for a unit you do not need many of. #### **Does Metricool have an API?** Yes, but it is gated to the Advanced tier and above. Worth knowing that Metricool's MCP server is available on every plan including the free one, while the HTTP API that Zapier and Make connect through requires Advanced. Those are two separate products with two different requirements, so check which one your workflow actually needs. #### **Which Metricool alternative is best for agencies?** It depends on whether you are adding clients or staff. SocialPilot bundles accounts and seats into one predictable tier. Planable charges per workspace with unlimited users, so it gets relatively cheaper as your team grows. Avoid per-seat pricing like Hootsuite's if headcount is what expands. Three seats on Standard runs $297 a month billed annually, and $597 once you need Professional for unlimited accounts. Some links in this post are affiliate links, which means I may earn a commission at no extra cost to you. Blotato is also a client of mine and my account there is comped. I only recommend tools I have used or researched directly, and I have labeled on each entry above how much of it I have actually run. See my [full disclosure](/disclosure/). --- ## SEO Content Strategy in 2026: Why Volume is No Longer a Moat URL: https://ryandoser.com/seo-content-strategy/ Markdown: https://ryandoser.com/seo-content-strategy.md Published: 2026-08-05 | Updated: 2026-08-18 Categories: AI Tutorials > My SEO content strategy in 2026. Anyone can publish a hundred posts this afternoon, so volume stopped being a moat. Here is what separates sites now. Search **SEO content strategy** and page one hands you a glossary definition, a nine-step checklist, and a starter guide. Every one of them describes how to plan, and none describe how to publish. That split is the whole argument here. Volume and planning both got cheap, and what you publish is the only half left that decides whether you rank. ### **Why Volume Stopped Working as an SEO Content Strategy** The ranking pages are not wrong. They are thorough about a job that stopped being scarce. That gap is the whole problem in 2026. Anyone can generate a hundred blog posts this afternoon, so a plan for what to write is no longer scarce. The scarce thing is a reason for your specific page to exist. I walked through this full system on the [Big Moves AI](https://hub.bigmoves.ai/) podcast, including the parts that only work because of the SEO background underneath them. That background is the caveat I lead with every time. You cannot skip the fundamentals and expect a tool to cover for you. *Some links below are affiliate links, disclosed in full at the end of this post.* If you want the skill files I use to run this, they live in my **[Claude Code Skills Stack](https://skills.ryandoser.com)**. #### **The short version** - **Your video is the strategy.** Publishing from first-hand material beats planning what to write about. - **Subject matter expertise is the input, not the tool.** Volume without it produces pages nobody cites. - **One keyword per asset.** No persona map, no funnel diagram, no calendar. - **Own the distribution.** Traffic you rent through an algorithm is not an asset. - **Encode the plan as a file.** A strategy document gets ignored. An instruction file runs every time. ### **The SEO Content Strategy I Actually Run** Here are the four decisions that replaced the nine-step plan. #### **1. Start With the Video, Not the Keyword Map** Most strategy guides have you pick topics from a spreadsheet months ahead. I pick one target keyword before I record, then make the video. The research still happens. It just takes minutes now, because a skill file pulls the SERP, reads the top-ranking pages, and hands back the internal links while I go record. That is what commodity means here. The planning work did not disappear, it stopped being the thing that separates two sites. *The prompt that starts each post: one target keyword, a list of secondary keywords, and a skill file that holds the rules.* The video comes first because it is the part that cannot be faked. Recording forces you to actually know the topic. Everything downstream is a repackaging of material that already exists. That is a different job than inventing content to fill a calendar slot. The mechanics of that handoff are their own topic, and I covered them step by step in my guide to [repurposing YouTube videos into blog posts](/claude-code-repurpose-youtube-videos/). #### **2. Treat Expertise as the Bottleneck** We are in an age where AI agents can write a million blog posts. That makes quality and subject matter expertise matter more, not less. Pushing volume without either one produces pages that rank for nothing and get cited by nobody. That is not hypothetical anymore, and [I checked what a tool built purely for volume actually ranks for](/outrank-review/) on its own domain. If you want [people worth learning the craft from](/best-ai-seo-experts/), I keep a vetted list. Google's own [helpful content guidance](https://developers.google.com/search/docs/fundamentals/creating-helpful-content) asks whether a page demonstrates first-hand expertise. That question is much harder to fake than a word count. The honest limitation here is that this raises the floor rather than removing it. If you do not understand what an H1 does or why search intent matters, no workflow will save the output. #### **3. Write for Citations, Not Just Blue Links** The goal is to take up as much of the results page as possible, and a lot of that carries over into how models answer. *A review query returning an AI Overview above the video block. Citation surface and organic rank are separate wins.* Being named inside an answer is its own outcome. It does not always come with a click, and it still builds the association that gets you recommended later. Google documents [how pages surface in AI features](https://developers.google.com/search/docs/appearance/ai-features), and the requirements are ordinary indexable content rather than a separate track. Structure decides whether you get lifted. Clear headings, direct answers, and clean comparison tables give a model something extractable. I go deeper on the citation side in my [AI SEO strategy breakdown](/ai-seo-strategy/). #### **4. Own the Distribution You Build** The name of the game in 2026 and beyond is owning your distribution instead of renting it. Every post I publish points somewhere I control. An email list is the asset, and the ranking is just the delivery mechanism. Rankings move and algorithms change. A list of people who asked to hear from you does not reset when Google ships an update. ### **What Three Months of This SEO Content Strategy Looks Like** Here is the [Search Console](https://search.google.com/search-console/about) curve from the experiment, and the shape matters more than any single number on it. *Search Console at the time of recording. An early bump, a dip, and then the real climb starting in April.* Look at the dip through late March. Early results faded before anything compounded, which is exactly where most people quit and decide the approach does not work. The domain had little to no authority when this started, and no backlink campaign ran alongside it. The climb came from publishing against real search demand, repeatedly, with nothing else propping it up. I want to be careful about what that proves. It shows the approach works on a fresh domain in a niche I know well, not that it transfers to every industry at any competition level. The running cost is the part that surprises people. One [Claude Max plan](https://claude.com/pricing) at a hundred a month covers the whole publishing side. I have run the same fundamentals on a throwaway local service site to check they were not a fluke of this niche, and that build is covered in my [post on SEOmaxxing boring businesses](/seomaxxing/). ### **Where This Approach Falls Short** This is not a universal replacement for planning, and pretending otherwise would be dishonest. If you run content for a team of eight, you need shared documentation that a spreadsheet handles better than my head does. Skip the calendar there and people duplicate work. The approach also assumes you produce original material. Without video, podcasts, or genuine first-hand testing, there is nothing to repackage, and you are back to inventing topics from a keyword tool. One more limit worth naming. A single-operator system scales to the number of hours you have, which is the tradeoff you accept for skipping the process overhead. ### **Ryan's Final Thoughts** Keep the planning steps. They take an afternoon now instead of a quarter, and that is exactly the point. Deciding what to write stopped being the hard part the moment models could draft anything. Having something worth saying, and a repeatable path from saying it to publishing it, is where the advantage moved. Pick one keyword and make the thing only you can make. Then send the traffic somewhere you own. ### **SEO Content Strategy FAQs** #### **What is an SEO content strategy?** An SEO content strategy is the plan governing what you publish, how it targets search demand, and how it converts readers. Most published versions center on audits, personas, and content calendars. My version centers on publishing from first-hand material against one target keyword per asset, then routing that traffic to a channel you own. #### **Do I still need a content calendar for SEO in 2026?** Not if you work alone and produce original material. A calendar solves coordination across a team, which is a scheduling problem rather than a ranking one. When your publishing rate is limited by how much genuine expertise you can record, the calendar tracks capacity you already know. #### **How long does an SEO content strategy take to show results?** On my own site, Search Console showed steady click and impression growth roughly three months into the experiment, starting from zero on a domain with little to no authority and no backlink campaign behind it. That was a niche I know deeply, which matters more than the timeline. Competitive niches and unfamiliar topics take considerably longer. #### **Is AI-generated content bad for SEO?** The generation method matters less than whether the page deserves to exist. My view is that quality and subject matter expertise matter more now than ever, precisely because anyone can produce enormous volume cheaply. Content grounded in real testing and genuine expertise still wins, whether or not a model helped write it. #### **Should I write blog posts or make videos first?** Make the video first when you can. Recording forces a level of understanding that writing from a keyword tool does not, and it gives you a source asset to repackage into posts, email, and social. The hardest part of this whole system is producing consistent high-quality long-form video. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## Zapier vs n8n in 2026 (Just Use Claude Code) URL: https://ryandoser.com/zapier-vs-n8n/ Markdown: https://ryandoser.com/zapier-vs-n8n.md Published: 2026-08-04 | Updated: 2026-09-06 Categories: AI Tool Reviews, Claude Code > Zapier vs n8n is the wrong question for content automation. Real pricing on both, plus the option neither will put in a comparison table. I spent a year maintaining a **Zapier vs n8n** style workflow to do a job that no longer needed a workflow. That is the part these comparisons never get to. They argue about price per task and how hard the builder is to learn. Both are real, and neither is what decided it for me. So this comparison has three columns instead of two. Zapier, n8n, and the option both companies have a business reason to leave out, which is skipping the workflow builder entirely and letting an agent call the tools directly. My conflicts up front. [Blotato](https://www.blotato.com/?ref=rdoser) is a client of mine, my account there is comped, and links to it are affiliate links. I have no relationship with Zapier or n8n and I pay for neither today. Where my knowledge stops, so you can weigh the rest: I ran my publishing through n8n for a long stretch on their cloud plans, and I have used Zapier for years on smaller jobs. **I have never self-hosted n8n.** The self-hosting sections below come from their documentation, not from my own incidents. ### **Zapier vs n8n: What You Are Actually Choosing Between** Start with the thing that matters more than any feature list, which is what each company charges you for. [Zapier](https://zapier.com/pricing) bills by task. A task is roughly one action your workflow performs. The free plan gives you 100 tasks a month on two-step workflows. Paid pricing is indexed to volume, so the entry number only holds at the smallest tier. Professional starts at $19.99/month for 750 tasks and Team at $69/month, both on annual billing, and every tier costs more month to month. Zapier connects to 9,000+ apps, which is the widest library in the category by a distance. [n8n](https://n8n.io/pricing) bills by workflow execution instead. One execution is a single run of your entire workflow, no matter how many steps it contains. Starter is $20/month for 2,500 executions with unlimited steps, Pro is $50/month for 10,000, and Business is $800/month for 40,000. All are annual rates, and all include unlimited users. It reaches about 2,000 integrations, well short of Zapier's library, though an HTTP request node covers anything with an API. You can also self-host the community edition, where the software is free and you pay for the server instead. | | Zapier | n8n | Claude Code | | Billing unit | Per task (one action) | Per execution (one full run) | Model tokens | | Entry paid price | $19.99/mo annual | $20/mo annual | $20/mo Claude Pro, plus a publishing tool | | Cost of a 50-step job | Up to 50 tasks | 1 execution | Tokens for one conversation | | Free tier | 100 tasks/mo, 2 steps | Free trial, or self-host free | No | | Self-hostable | No | Yes, community edition | Already runs locally | | Behavior | Deterministic | Deterministic | Probabilistic, varies per run | | Breaks when | An app changes its API | A node or token expires | The model misreads the task | | Learning curve | Lowest | Steepest | You must be fine in a terminal | | Best at | Simple app-to-app triggers | Complex multi-step logic | Judgment calls on varied input | Read the billing row twice, because it is the whole ballgame for content work. A fifty-step social workflow costs one execution on n8n and up to fifty tasks on Zapier. Put real numbers on it. Say you publish 20 pieces of content a month and each one runs an eight-step workflow. That is 160 billable tasks on Zapier, which clears the free tier and puts you on a paid plan. On n8n it is 20 executions against an allowance of 2,500, so you are nowhere near the ceiling and the step count never entered the math. Scale it to 500 runs a month and the gap stops being academic. Zapier is metering 4,000 tasks while n8n is still counting 500 executions on a $20 plan. That gap is why I moved off Zapier for publishing years ago, and I wrote up the full reasoning in my guide to [Zapier alternatives for social posting](/best-zapier-alternatives/). *The billing unit, not the sticker price, is what separates these two.* ### **Where Zapier Genuinely Wins** Most comparisons written by n8n fans skip this part, which makes them useless to anyone actually deciding. Zapier has roughly 9,000 app connections. If the obscure tool your business depends on has an integration anywhere, it is probably here. It is also the only one of the three your non-technical teammate can maintain without you. That matters more than automation people admit. If your workflow is genuinely two or three steps, form fills to a spreadsheet, new customer to a Slack message, Zapier is the correct answer and the per-task model never bites you. The model only punishes you when one input triggers many actions. That is content work almost by definition, and it is exactly the shape Zapier prices worst. ### **Where n8n Genuinely Wins** The per-execution billing is the headline, and it is a real structural advantage rather than a marketing line. Complexity is free. Adding a twentieth step to a workflow costs nothing extra, so you build the logic the job actually needs instead of the logic your invoice can tolerate. You can also self-host it, which is the reason a lot of technical operators pick it. Your data stays on your infrastructure and there is no per-seat conversation. Two honest costs. It is the steepest of these to learn, and on the Starter cloud tier you only keep seven days of execution history, which is short when you are debugging something intermittent. The bigger cost is the one nobody prices. Every node you add is a node you maintain. ### **Both of Them Already Ship AI Features** Before the third option, deal with the obvious objection, because a comparison that ignores it is not worth reading. Both vendors shipped agent tooling, and it is genuinely good. [Zapier MCP](https://zapier.com/mcp) connects Claude, ChatGPT and Cursor to its 9,000+ app library, alongside Copilot for building Zaps from a description. n8n went further into the canvas. It has an AI Agent node, LangChain nodes, and the ability to expose a workflow as its own MCP server. So "can an agent drive it?" is no longer the question that separates these tools. The answer is yes on both. The distinction that survives is where the agent sits. Both vendors put an agent *inside* a workflow you still design, maintain and pay for per task or per execution. The third option removes the workflow. That is a different architecture, not a different feature, and it is the part neither company can sell you. ### **The Third Option: Skip the Workflow Builder** Here is the part that took me too long to work out, and it started as a complaint rather than a strategy. As I put it to my community at the time: we used to go back and troubleshoot all these nodes in n8n, API keys were broken, something did not work, and I would scratch my head and take screenshots and upload them to Claude to try to get through it. Read that again, because I did not notice what I was describing until later. I was using an AI agent to debug the automation that existed so I would not have to do the work manually. The agent was already the more capable half of that arrangement. It was just stuck in a support role. A workflow builder exists to solve one problem: software cannot make judgment calls, so you pre-decide every branch and encode it as nodes. That assumption held for a decade and it is the reason these tools are shaped the way they are. It stopped being universally true. When the thing running your automation can read a video, decide which moments matter, write a caption in your voice, and call a publishing API, most of the branching you were encoding by hand is work it can just do. Here is what mine actually is, since a vague description would be fair to criticize. A scheduled job fires on my own machine and opens a Claude Code session with a written instruction, not a diagram. It reads the source video, picks the moments worth clipping, writes a caption per platform in my voice, and calls a publishing API over MCP. In n8n that same job was a canvas of nodes: a trigger, a transcription step, branching logic per platform, a formatting node for each caption, and an error path I had to design in advance. The agent version is a paragraph of English and a cron entry. What it costs: a Claude subscription I already pay for, plus the publishing tool. There is no per-task meter and no per-execution meter, so the cost of a run scales with how much thinking it does rather than how many steps I drew. Now the failure modes, because they are real and the vendors never list theirs either. It fails differently than a workflow does. A broken node throws an error you can see, while an agent that misreads the task produces something plausible and wrong, which is worse because nothing alerts you. Mine once reported a finished run against an empty folder, because the rendering job was still processing when the conversation ended. A workflow builder would have caught that with a wait node I had explicitly drawn. So I write the checks back in. The agent has to confirm the files exist before it moves on, which is me re-adding, in English, the one thing the node graph gave me for free. That is the honest shape of this trade. You give up guaranteed repeatability and you get back the hours you spent maintaining branches. It is the least deterministic option of the three, and I go deeper on that tension in [my conversation with an automation expert about whether n8n is dead](/is-n8n-dead/). ### **Deterministic vs Probabilistic Is the Real Decision** One word separates these tools, and it is not price. Zapier and n8n are deterministic. You build the route and the workflow fires the same way every single time. An agent is probabilistic. Run the same instruction twice and you can get two slightly different results. For mission-critical work, deterministic wins and it is not close. If you are sending a thousand client invoices, you need the same output a thousand times, and a fresh roll of the dice on each run is unacceptable. Nobody cares if a morning content summary varies slightly in phrasing. People care enormously if a billing run does. So the question is not which tool is better. It is whether variation in your particular job is a defect or a feature. Content is the rare category where variation is closer to a feature. Ten captions that read slightly differently is the goal, not a bug report. ### **Which One Should You Pick?** Answer one question and this resolves faster than any feature table. **Does your automation require judgment, or just plumbing?** *Answer this one question and the rest of the comparison resolves itself.* Plumbing means moving data between apps with no decisions in the middle. Pick Zapier if it is simple and you want it maintained by anyone on your team, or n8n if it is complex and you want complexity to stay free. Judgment means something has to read, weigh, and decide before acting. That is where an agent earns its place, and where a node graph turns into a maintenance project. Most real setups are a mix, and mine still is. I keep deterministic tools for anything where a wrong result is expensive, and let the agent own the judgment-heavy content work. If the agent path is the one you want, the piece people underestimate is publishing. An agent that writes a great post still needs somewhere to send it, and per-platform API approvals are their own project. That is the job I hand to [Blotato](https://www.blotato.com/?ref=rdoser), at $29/month flat for 20 connected accounts, because the bill does not move when I add an account or post more often. I compared it honestly against the self-hosted option in [Postiz vs Blotato](/postiz-vs-blotato/), including where Postiz is the better pick. ### **Ryan's Final Thoughts** The Zapier vs n8n framing assumes you need a workflow builder and are only choosing which one. For a lot of content work in 2026, that assumption is the thing worth questioning. Zapier is right for simple plumbing maintained by a team. n8n is right for complex deterministic logic where you want the steps free and the data yours. An agent is right when the work needs judgment and you are tired of encoding every branch by hand. What I would not do is pick based on a comparison page written by either company, including the parts of this one where I have money on the table. Open both pricing pages, count what one piece of your content actually costs in tasks and in executions, and let that number decide. ### **Zapier vs n8n FAQs** #### **Is n8n cheaper than Zapier?** Usually, and the reason is the billing unit rather than the sticker price. Their entry tiers are close on paper, at $19.99/month for Zapier Professional and $20/month for n8n Starter, both on annual billing. Zapier charges per task, so a fifty-step workflow can bill many times over. n8n charges per execution, so that same workflow costs one. The more steps you run, the wider the gap. #### **Is n8n harder to learn than Zapier?** Yes, noticeably. Zapier is the easiest automation tool to hand to a non-technical teammate, and that is its genuine advantage. n8n expects you to think about data structures and node connections, which is why it handles complex logic better. Budget real time for n8n if you have never used a node-based builder. #### **Can Claude Code replace n8n?** For judgment-heavy work, often yes. For mission-critical deterministic work, no. n8n runs identically every time, while an agent is probabilistic and can vary between runs. Use an agent where variation is acceptable or even desirable, like content, and keep a deterministic tool where a wrong result is expensive, like billing or client deliverables. #### **Is n8n free?** The community edition is free to self-host, and you pay in server costs and maintenance instead of subscription fees. Cloud plans start at $20/month billed annually for 2,500 workflow executions. Zapier's free tier gives you 100 tasks a month on two-step workflows, which is enough to test the concept and not much else. #### **Can Zapier replace n8n?** **For simple app-to-app automation: yes.** Zapier is easier to build in and easier to hand to a teammate. **For high-volume or complex workflows: no.** Zapier bills every action while n8n bills the whole run once, so a 50-step job costs up to 50 tasks against 1 execution. **For self-hosting: never.** Zapier is cloud-only, so if your data must stay on your own infrastructure it cannot replace n8n at any price. #### **Which is better, n8n or Make or Zapier?** It depends on the billing shape your work has. Zapier wins on app coverage and ease, at roughly 9,000 integrations. Make sits in the middle, cheaper than Zapier because it bills per operation rather than per task, with a more visual builder than n8n. n8n wins at volume and complexity because one execution covers unlimited steps, and it is the only one of the three you can self-host. I ranked all three plus the agent-native options in [my guide to AI automation tools](/best-ai-automation-tools/). #### **Is there anything better than n8n?** For deterministic workflow automation, not really at the price. n8n is the cheapest option at volume and the only one of the three you can self-host. What beats it is a different architecture rather than a better builder: when the work needs judgment on varied input, an AI agent calling tools directly removes the workflow instead of optimizing it. For anything that must run identically every time, n8n still wins. #### **Is there anything better than Zapier?** For most high-volume work, yes. n8n is cheaper at scale because it bills per execution rather than per action, Make sits between the two on price, and an AI agent can replace the workflow entirely when the job needs judgment. Zapier stays the better answer for simple two-step automations, for the widest app library at 9,000+, and for teams without a technical maintainer. #### **Which is better for social media automation?** Neither one publishes for you, which is the detail most comparisons skip. Both are orchestration layers that still need a publishing tool with platform API access behind them. Social posting is many actions per piece of content, so per-task billing punishes it hardest, making n8n or an agent the better fit over Zapier. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine and my account there is comped rather than paid. I have no relationship with Zapier or n8n. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## My AI SEO Strategy in 2026 (Most Advice is Wrong) URL: https://ryandoser.com/ai-seo-strategy/ Markdown: https://ryandoser.com/ai-seo-strategy.md Published: 2026-08-03 | Updated: 2026-10-09 Categories: AI Tutorials > The AI SEO strategy I run for seven-figure clients: five moves that get a brand named inside AI answers, and the advice I think is wrong. My **AI SEO strategy** comes down to five moves, and the order matters more than any single tactic. This is the process I run for seven-figure clients across SaaS, cybersecurity, and affiliate sites, and it exists to answer one question: why does ChatGPT recommend a competitor and never say your name? I am assuming you already know what AI SEO is and do not need the acronym tour. If you want the definitions, the short version is that AEO, GEO, and LLMO all describe the same job. What follows is the part nobody hands you: what I actually do, in what order, and where I think most of the money in this category is being wasted. On that last point, I will be blunt early rather than bury it. Agencies publish AEO retainer rates from $1,500 a month up past $30,000 at enterprise, and it is worth knowing [who is actually worth paying for AI search work](/best-ai-seo-experts/) and [what each price tier actually buys you](/ai-consultant-cost/), and for most of the people reading this, that money buys schema, content structure, digital PR, and crawlability. Those are standard SEO deliverables with a new label on the invoice. I cover exactly when a retainer *is* worth it further down, but plan on running this yourself. Some of what follows is my read on a full AI SEO playbook that [Sabrina Ramonov published](https://www.sabrina.dev/p/ai-seo-for-beginners-full-playbook) and walked through on a livestream. I agree with most of it. I disagree with one part loudly, and I will show you where. #### **The short version** - **AI SEO is getting named, not ranked.** An answer names a few brands and has no page two. - **Being cited and being mentioned are different wins.** Only 21% of the most-cited domains were also the most-mentioned brand, and readers act on the mention. - **Nothing technical got replaced.** A site that cannot rank generally does not get cited either. - **Most of the deciding evidence is off your site.** Podcasts, press, and other people's articles do the heavy lifting. - **You probably do not need an AEO retainer.** Published rates start around $1,500 a month for work that is mostly standard SEO. ### **Why Most AI SEO Strategies Fail Before They Start** The strategies I get asked to fix usually fail for the same reason: they were built to chase citations without first deciding what the brand should be cited *as*. That ordering mistake is expensive, and it is why Step 1 below is positioning rather than a tactic. The mechanical difference between AI SEO and the SEO you already do is smaller than the acronym sellers want you to believe. The behavioral difference is enormous, and it changes how you should allocate effort. Old search gave you ten blue links per page, plus page two, plus page three. Ranking fourth still earned real traffic. An AI answer names a few brands and stops, and how few depends heavily on your category. Semrush's [AI visibility research](https://www.semrush.com/blog/ai-search-visibility-study-findings/) measured brand diversity per query and found ChatGPT naming 4.72 brands in business services but only 1.22 in consumer electronics. Check your own category before you assume you have room. In a low-diversity category, the answer names one brand, and everyone else is invisible for that question. #### **Being cited and being mentioned are not the same win** A separate Semrush study, covering more than 600,000 citations across 1,094 categories, found the thing that should actually reorganize your priorities. Only [21% of the most-cited domains](https://www.semrush.com/blog/chatgpt-topic-authority-study/) in a category were also the most-mentioned brand, and the two correlate slightly negatively. Readers act on the mention, not the footnote. Kevin Indig's consumer research found that [74% of participants chose the item ranked first](https://www.growth-memo.com/p/does-topical-authority-matter-in) in the AI's response as their top pick. So chasing a link under the answer is a different job from being the brand the answer talks about first, and the second one is what converts. ### **AI SEO vs Traditional SEO: What Actually Changes** Here is the honest comparison, including the parts that did not change. *What actually changed. The technical foundation is the same; the scoreboard is not.* Read that last row carefully, because it is the one the hype crowd skips. The technical foundation did not get replaced. AI engines retrieve live search results when they answer, so a site that cannot rank generally does not get cited either. Every case study I have seen of a site winning AI citations also had working traditional SEO underneath it. I have written before about [what actually moves AI search citations](/how-to-manipulate-ai-search/), and the pattern held there too: skipping SEO fundamentals to chase a GEO tactic is the most overrated move in the industry right now. ### **Why AI SEO Favors Small Sites** This is the genuinely good news, and it is structural. Ranking a new site against an established brand is a years-long fight over domain authority. Getting cited is a different contest. AI engines are looking for the most specific, most quotable, most clearly-sourced answer to a narrow question. A 400-word page that answers one question precisely can get pulled into an answer over a 4,000-word corporate guide that hedges. Precision beats page count here, which is the opposite of how the old game rewarded you. That is exactly the edge [rank and rent SEO](/rank-and-rent-seo/) operators exploit: a focused niche site beating a big brand on one specific question. You can check this for yourself in about a minute, which is the point. Run your own category question in ChatGPT or Perplexity and read which sources it leans on. On the AI SEO queries I track for client work, the cited set regularly mixes Reddit threads and YouTube videos in with the big publishers. Forum posts and videos are not domains you have to outspend. They are formats you can produce this week. ### **The AI SEO Workflow in Five Moves** The rest of this guide is one process. Here it is on a single screen before we go step by step. *The five moves, in order. Step four is the biggest lever because most of what a model knows comes from sites you do not control.* ### **Step 1: Pick the One Thing You Want to Be Known For** Before any tactic, you need a positioning line short enough that a model can repeat it without garbling it. Sabrina frames this as a specific claim about the value you provide to a specific group of people, rather than a job title, backed by proof points. Hers is "#1 AI Educator for Entrepreneurs." Mine is AI-first marketer. Short enough to survive being repeated by a machine, specific enough to mean something. The mistake I see most often is the opposite: a ten-page brand document with pillars and archetypes that nobody, human or model, can compress into one sentence. If it takes a page to explain, it will not survive a paraphrase. The reason this matters more with AI than it did with Google is confusion cost. If your LinkedIn says one thing, your site says another, and a podcast host introduced you as a third thing, the model has no confident answer about what you are. Models resolve that ambiguity by naming someone else. ### **Step 2: Say the Same Thing Everywhere** Once you have the line, repeat it on every surface a crawler can reach. Your site, every social bio, review profiles like G2 and Trustpilot, directory listings, podcast bios, and your email signature. Updating your LinkedIn and stopping is the common failure. Consistency across sources is the signal. One updated profile is not. While you are in the technical layer, open your `robots.txt` and confirm you are not blocking the crawlers that feed AI answers. The three that decide whether you can be quoted in a live answer are `OAI-SearchBot` (ChatGPT search), `Claude-SearchBot`, and `PerplexityBot`. I have audited client sites that spent months chasing AI visibility while quietly blocking the exact bots they were trying to reach, usually while paying for [tactics that were never going to work anyway](/ai-search-myths/). Those three bots also read three different indexes, which I broke down in [what search engine each AI actually uses](/what-search-engine-does-claude-use/). One correction worth making, because plenty of guides get it wrong: `Google-Extended` is not in that list. Per [Google's own crawler documentation](https://developers.google.com/search/docs/crawling-indexing/google-common-crawlers), it controls whether your content trains and grounds Gemini models. Google says so directly. *Straight from Google's crawler docs: Google-Extended governs Gemini training and grounding, not Search.* Blocking it is a training decision, not an AI Overview decision. Treat those as separate choices, and ignore any guide that tells you unblocking it will win you AI Overview citations. ### **Step 3: Build the Page Formats AI Actually Quotes** Three formats get pulled into AI answers far more than anything else, because they map to how people ask buying questions: - **"Best X" lists** for category questions - **"X vs Y" comparisons** for decision questions - **"X alternatives" pages** for switching questions For a section-by-section example, Sam Dunning walked me through [an alternatives page that ranked and got cited](/saas-seo/) for his SaaS client. There is a trap here, and I learned it the expensive way on client work. An even-handed comparison page gets cited constantly, because fairness is exactly what makes it quotable. But a model can lift one sentence out of your honest write-up of a competitor and serve it as a recommendation for that competitor. You supplied the research and your rival got the customer. The fix is not to lie about competitors. It is to keep every qualifying condition inside the same sentence as any recommendation. Write "Tool X wins if you need Y and have Z" rather than a clean sentence praising Tool X followed by a separate sentence listing its limits. A lifted chunk should not be able to travel without its condition attached. #### **Then format those pages so a model can lift them cleanly** This is the part people overthink. Five changes do most of the work: - **Make headings the questions people actually ask.** Not "Our Methodology" but "How much does AI SEO cost?" - **Answer in the first two sentences under the heading.** Models extract chunks, not whole pages. - **Replace vague phrases with specific numbers and named sources.** "Significantly faster" is unquotable. "Cut it from 40 minutes to 6" is quotable. - **Keep table rows self-contained.** Every cell should make sense pulled out of the table alone. - **Add Organization and FAQ schema.** It makes your content machine-readable and costs almost nothing. The unifying rule: assume any single paragraph will be quoted with zero surrounding context. Write so that lifting it does not misrepresent you. ### **Step 4: Get Mentioned on Sites You Do Not Own** Most of what a model knows about your brand comes from sources you do not control. That is why on-page work alone stalls. The workflow I use is straightforward: - **Ask the models the buying question.** Run your buyer's category question in ChatGPT, Claude, and Perplexity. - **Read which articles get cited.** Those specific pages feed the answer, so they are your target list. - **Pitch those authors.** Give them a real reason you belong in the piece, not a link request. Two channels compound faster than outreach, because they create permanent pages on domains that already have trust. **Podcast appearances.** Twelve guest spots is twelve indexed pages on other people's trusted domains, each one describing you in your own positioning language. This is the single most underrated AI SEO tactic I know. **Press releases through a wire service.** A real announcement pushed through a wire gets syndicated across news sites, which is a cheap way to create third-party sources that say what you want said. Keep it to genuine news, front-load the who and what, and write it in third person. ### **Where I Disagree: Do Not Buy an "AEO Service"** Here is my loud disagreement with how this whole category is being sold. Look at what agencies publish for this work. [Stackmatix puts small-business AEO retainers](https://www.stackmatix.com/blog/aeo-services-pricing) at $1,500 to $5,000 a month, and [Digital Elevator's guide](https://thedigitalelevator.com/blog/aeo-and-geo-pricing-guide/) has mid-market companies paying $2,000 to $10,000 a month, with enterprise programs running $10,000 to $30,000 and up. A large share of that spend buys renamed SEO fundamentals plus a visibility dashboard. Before you pay for one of those dashboards, it is worth checking whether the vendor keeps its own numbers straight, which is what I found when I went through [AIclicks](/aiclicks-review/). If someone pitches you a dedicated AEO retainer as a replacement for your marketing, be skeptical. Ask them one question: what are you doing that is not schema, content structure, digital PR, and technical crawlability? If the answer is a tracking dashboard, you are paying a premium for a rename. The same question is worth asking of the platforms that automate this work, which is why I went through [what Search Atlas actually charges and what it does for the money](/search-atlas-review/) rather than taking the pitch at face value. The demand is real because the confusion is real. Everybody is asking what AEO and GEO mean, which makes it an easy thing to sell. That does not make it a new discipline. To be fair to the other side, there are real cases where hiring it out is the right call. Here is how I split it. *When a retainer earns its money and when it does not.* The digital PR piece is the one part I would actually pay for separately, because an attributed expert quote on a publication the models already trust is the cleanest citation signal you can buy. I run that through an automated pitching tool rather than an agency retainer, and I show the real numbers in my [Backlinker AI review](/backlinker-ai-review/). ### **Step 5: Track Whether AI Is Actually Recommending You** Tracking this by hand gets old fast. Connecting a [Search Console or SERP data server](/best-seo-mcp-servers/) to Claude turns the weekly check into one prompt. Most people never measure this, which is how they end up paying for a service with no defined outcome. Here is the whole scorecard on one screen, including the two numbers I deliberately ignore. *The monthly check. Sessions and rank position are context, not the scoreboard.* Three checks are enough to start: **Ask the models yourself, monthly.** Write down ten questions a buyer would really ask. Run them in ChatGPT, Claude, Perplexity, and Google in a fresh incognito window. Log whether your brand got named. That spreadsheet is your scoreboard, and it takes about twenty minutes. Paid trackers automate this, and it is worth knowing how thinly they sample before you buy one, which I worked out in my [Searchable review](/searchable-review/). Run those checks in a browser, not through the API. Chris Panteli of Linkifi says API results come out "wildly different" from what a buyer sees, as he explains in [my episode on getting ChatGPT to recommend a local business](/how-to-get-chatgpt-to-recommend-your-business/). **Watch branded search in Google Search Console.** When AI recommends you without a click, people go look you up. Rising branded impressions is often the first visible sign that citations are working. **Measure signups, not sessions.** AI referral traffic shows up small in volume, so a session-count dashboard makes it look like nothing is happening. [Ahrefs found](https://ahrefs.com/blog/ai-search-traffic-conversions-ahrefs/) AI search accounted for 0.5% of its traffic while producing 12.1% of its signups, a conversion rate roughly 23 times higher than regular organic. Judge this channel on what it converts, or you will kill something that is working. That gap is the practical answer to the zero-click worry. Fewer visitors arriving pre-sold by an AI recommendation can be worth more than a larger number who wandered in from a listicle, and only conversion tracking will show you that. ### **Turn the Repeatable Parts Into a Skill** Part of this automates well and part of it does not. Positioning, earning a podcast seat, and convincing a writer to add you are judgment and relationships, and no script does them for you. The page-level work is different, because it is a checklist that has to run identically every time. That part I run through Claude Code skills, which are markdown instruction files that execute the same job the same way on every post: check live pricing before writing, search the target question, note which articles get cited, pull real strengths and weaknesses from reviews, build the comparison table. Quotable formatting is exactly the kind of rule a human drops on deadline and a file never does. I broke down the specific ones I use in my guide to [Claude Skills for SEO](/claude-skills-for-seo/), and the full set lives in my **[Claude Code Skills Stack](https://skills.ryandoser.com)**. If you want the publishing side of this rather than the strategy, my [AI SEO system](/ai-seo-system/) covers how I ship daily content without producing slop, and my roundup of the [best AI SEO tools](/best-ai-seo-tools/) covers the tracking software. If you would rather run this whole strategy on your own site than read about it, I packaged the audit and the fix list into [a system your AI tool can run](/ai-seo-system-launch/). ### **Ryan's Final Thoughts** AI SEO is not a new discipline that replaces SEO. It is SEO judged on a much shorter list, where a handful of brands get named with no page two behind them, and where most of the evidence deciding that list sits on websites you do not own. I put that claim to the test on a local query and [logged every source ChatGPT actually cited](/how-to-rank-in-chatgpt/). If you take one thing from this, make it the mention-versus-citation split. A link under the answer is worth far less than being the brand the answer names first, and 74% of people in Indig's research picked that first-ranked item. Optimize to be talked about, not merely footnoted. Pick the one thing you want to be known for, repeat it everywhere a crawler can reach, build the comparison pages buyers actually ask for, and check monthly whether the models say your name. Skip the five-figure retainer for a rename. Think first about who you want to be cited as. Then go make that easy for a machine to repeat. ### **The Rest of the AI SEO Work** The five moves are the strategy. What follows is the work that sits underneath it, kept separate because tool prices rot and strategy should not. Start with the argument itself if you are not sold. An 18-year SEO reads [Google's published AI search guidance as misdirection](/google-ai-search-guidelines-exposed/) and names what he thinks actually wins instead. And if publishing more is still the plan, [volume stopped being a moat](/seo-content-strategy/) argues that anyone can ship a hundred posts this afternoon, so the separation has to come from somewhere else. On execution, [the full SEO workflow I run on this site](/claude-code-seo/) is the closest thing to a walkthrough of the moves above, including the ranking results with zero backlinks pointing at it, and [keyword research inside Claude Code](/claude-code-keyword-research/) is where every one of those posts starts. Turning the same workflow into $5K-a-month local retainers is [SEOmaxxing](/seomaxxing/). On data, the decision is mostly about what you pay per lookup. [DataForSEO](/dataforseo-review/) is what I run daily, priced per request rather than per seat. Against the incumbents, [DataForSEO vs Ahrefs](/dataforseo-vs-ahrefs/) covers where the data quality actually loses and why both shipping MCP servers killed the old developer-versus-marketer split, and [DataForSEO vs Semrush](/dataforseo-vs-semrush/) is a bundle against a single slice at $0.0006 a request. If neither fits, [seven alternatives priced off each live rate card](/dataforseo-alternatives/). If you are buying API access directly, the headline price is not the price. [Ahrefs API access starts at $129 a month](/ahrefs-api-pricing/), not the $1,499 Google's AI Overview quotes, and [Semrush names two plans](/semrush-api-pricing/) that each start you at zero API units without saying what a unit costs. On the tools promising to do this for you, I reviewed them because the category is full of $99 auto-publishers making the same claim. [Rankability](/rankability-review/) now starts at $97 a month with self-serve signup, though the free trial is still gone, and the review covers who should buy it over Surfer or Ahrefs. [Adaptify at $499 a month](/adaptify-seo-review/) is the agency-priced end, read against its own pricing page and 89 Trustpilot reviews. [BabyLoveGrowth](/babylovegrowth-review/) and [Outrank](/outrank-review/) both cost $99 a month to auto-publish thirty articles, and both run a backlink exchange. Trading links with strangers is the part that carries the risk, so both reviews go through the refund terms and the review data before you hand over a card. If you are comparing the wider category, I ranked [seven of these auto-publishers on real monthly pricing](/outrank-alternatives/). If you would rather not assemble all of that yourself, it is packaged as [my AI SEO System](https://seo.ryandoser.com/), and [a consulting call](/ai-seo-consulting/) is the version where I look at your site directly. I argued above that most AEO retainers are ordinary SEO with a new label. That applies to mine too. Run the five moves yourself first, and only pay someone, me included, if you genuinely will not. ### **AI SEO Strategy FAQs** #### **What should an AI SEO strategy prioritize first?** Positioning, before any tactic. Every later move compounds off one short claim about what you are and who you serve, and if your site, socials, and podcast bios describe you differently, the model has no confident answer and names someone else. After positioning, the order is consistency across crawlable sources, then quotable page formats, then earned mentions on sites you do not own. #### **How is an AI SEO strategy different from a regular SEO strategy?** The technical foundation is identical, since AI engines pull from live search results and a site that cannot rank generally does not get cited either. What changes is allocation. A regular strategy spends most of its effort on your own pages; an AI SEO strategy shifts significant effort to third-party sources, quotable formatting, and brand consistency, because Semrush measured ChatGPT naming 4.72 brands per query in business services and just 1.22 in consumer electronics, with no page two behind them. #### **Should I optimize for citations or for brand mentions?** Mentions, if you have to choose. Semrush found only 21% of the most-cited domains in a category were also the most-mentioned brand, and the two correlate slightly negatively. Kevin Indig's research found 74% of participants picked the item ranked first in the AI's answer. A link under the answer is worth far less than being the brand the answer talks about first. #### **How do I know if AI is recommending my brand?** Ask it directly. Write ten questions your buyers would actually ask, run them monthly in ChatGPT, Claude, Perplexity, and Google using a fresh incognito window, and record whether your brand is named. Pair that with branded search impressions in Google Search Console and tracked signups, since AI referral traffic converts at a much higher rate than it shows in raw session counts. Watching the open web where those answers get sourced is a separate job, and I broke down one tool for it in my [Alertmouse review](/alertmouse-review/). #### **How long does AI SEO take to work?** Fixing crawler access and page formatting can change citations within weeks, because those affect whether you are eligible to be quoted at all. Building the third-party mentions that most influence what a model believes about your brand takes months, since it depends on podcasts, press, and other people's articles. Positioning consistency should come first because everything else compounds off it. #### **Do I need to pay for an AEO service?** Usually not. Published agency rates run from about $1,500 a month for small business up to $10,000 for mid-market and $10,000 to $30,000 and up for enterprise, and much of that covers schema, content structure, digital PR, and technical crawlability, which are standard SEO deliverables. Before signing, ask the provider what they do beyond those four things. If the answer is a visibility dashboard, you can get the same result from a monthly spreadsheet and the workflow above. --- ## Backlinker AI Review: How to Build Backlinks on Autopilot (2026) URL: https://ryandoser.com/backlinker-ai-review/ Markdown: https://ryandoser.com/backlinker-ai-review.md Published: 2026-08-03 | Updated: 2026-08-31 Categories: AI Tool Reviews > My honest Backlinker AI review after running it for clients. $300/month, 150+ pitches, DR 70+ links, and why the placements now earn AI search citations too. My **Backlinker AI review** covers the one tool I've been using to land real backlinks for clients without paying a link building agency $5,000 to $10,000 a month. *Some links below are affiliate links. [See my disclosure](/disclosure/).* ### **What Backlinker AI Actually Does for Your SEO** Most link building advice tells you to do outreach manually. You sign up for [Featured.com](https://featured.com/), browse opportunities, write responses, and hope someone publishes your quote. It works, but it's slow and tedious. Backlinker AI automates that entire process. The tool connects to outreach platforms like Featured.com, HelpAB2BWriter, and SOS, scans for journalist and editor queries that match your niche, and sends AI-written pitches on your behalf. You set it up once and it runs in the background. I've been using it for clients across several industries. In November alone, one client saw 480 pitches sent, 12 selected, and 14 published placements, including links from sites with Domain Ratings of 76, 71, 60, and several in the 50s. I did not write a single pitch. I just optimized the onboarding setup and let it run. That said, there's an honest caveat I need to address before you get excited. You will not land links on Forbes, CNN, or the BBC with this tool. The sub-1% chance of that happening applies to every automated outreach tool, not just Backlinker. A legitimate agency with real reporter relationships is the only path to tier-one placements. What Backlinker does well is deliver consistent DR 30 to DR 70 backlinks that stack up over time and compound your domain authority without the agency price tag. For [founders building a personal brand](/personal-branding-for-founders/) or small businesses trying to gain traction externally, that's a very good trade. *Ryan's November monthly report inside Backlinker AI showing 14 published placements, including several DR 70+ backlinks.* ### **How to Set Up Your Backlinker AI Account the Right Way** Setup takes about 20 minutes, but the quality of your onboarding directly affects how many pitches get accepted. Most people rush this part and wonder why results are slow. Here's the process I walk through in the video: - **Create your account** at [backlinker.ai](https://www.backlinker.ai/?ref=ryan) and log in via email. - **Choose solo or agency mode.** Solo works for one website. Agency mode lets you manage multiple client profiles from a single dashboard. - **Create a persona.** Enter full name, LinkedIn URL, company name, job title, and website URL. - **Write a professional bio.** This is the most important step. Use ChatGPT with agent mode or Gemini to generate a 300-500 word bio based on your LinkedIn profile and website. Read it, refine it, then paste it into Backlinker. Two things need to be in order before you start: your LinkedIn profile and your website. Backlinker's AI scrapes both to generate pitch responses. If your LinkedIn is thin or your website is outdated, the pitches it writes will reflect that. Update both before you set up the account. *The persona bio setup inside Backlinker AI, where an AI-written bio is pasted to help the tool craft personalized pitches on your behalf.* One more thing worth calling out: Backlinker gave my audience a coupon code that gets you 50% off your first month. Use code **RYANDOSERAI** at checkout. After you subscribe, the tool starts sending pitches automatically. Your dashboard tracks sent pitches, selections, and published placements in real time. You can also check out the [Backlinker AI pricing page](https://www.backlinker.ai/pricing) to review what's included before committing. *The Backlinker AI homepage highlights its done-for-you outreach model and a claimed 65% average monthly traffic increase for clients.* ### **Backlinker AI Pricing: Is $300 a Month Worth It?** There's one plan: $300/month. That's it, and it has held at that price since I first reviewed the tool. Here's what's included, verified against the live pricing page: - One profile or website - 150+ pitches sent monthly - **No maximum limit on backlinks earned.** The guarantee is a floor, not a cap, and this is the line most reviews miss. - Done-for-you outreach via Featured.com (a $100/month retail value on its own) - Custom done-for-you email outreach via HelpAB2BWriter and SOS - Advanced AI writer trained on your biography - Monthly progress reports - Money-back guarantee if you don't receive at least 3 backlinks from DR 30+ sites That "no max limit" line is worth sitting with, because it inverts how you should judge the tool. The guaranteed 3 links are what you get if the setup goes badly. The client month I describe below returned 14 placements against the same $300, which is where the economics actually get interesting: a single DR 70 placement bought through a link vendor typically costs more than the entire month. The comparison that matters: a link building agency charges between $5,000 and $10,000 a month. Based on my experience, many of those agencies use automated tools behind the scenes, charge premium prices, and deliver similar (or worse) results. At $300/month with a money-back guarantee, Backlinker AI is a straightforward bet for small to medium-sized businesses. The one real limitation is the single-website restriction. If you have multiple clients or properties, you'll need to pay for separate subscriptions or use the agency dashboard, which manages multiple personas but still bills per profile. *The Backlinker AI pricing page in August 2026. Still one plan at $300/month, and note the "No Max Limit on Backlinks (unlimited)" line under the guarantee.* ### **Real Results: What Backlinks Can Backlinker AI Actually Land?** The results I've personally seen span a range of niches. Links from [GoBankingRates](https://www.gobankingrates.com/investing/strategy/can-ai-help-your-investments-warren-buffett-partner-weighs-in/), which led to a pickup on [Yahoo Finance](https://finance.yahoo.com/news/ai-truly-help-investments-warren-151756982.html?). A placement on an [edu domain from the University of Richmond](https://careerservices.richmond.edu/blog/2025/02/18/15-key-benefits-of-mentorship-to-early-career-tech-professionals/). Several DR 50+ placements across marketing and finance publications. Not every backlink will be perfectly relevant to your niche. Some pitches will land in adjacent topics. That's the nature of automated outreach. But relevance improves when your bio is well-written and your website clearly signals your expertise area. The other thing to set your expectations on is time. Give Backlinker at least two to three months before judging it. The first month is mostly pitches going out. By month two and three, accepted placements start rolling in and the monthly reporting shows real data. Quitting after 30 days because you didn't see instant results is the wrong move. If you want to complement this approach with an SEO strategy on your own site, this guide on [using Claude Code for SEO](/claude-code-seo/) covers how to build rankings without expensive tools. ### **The Reason I Still Run This in 2026: AI Search Citations** Here's the angle I don't see anyone else making about this category, and it's why I kept the subscription running after the ranking case was already made. Expert-quote placements are not just backlinks anymore. When you answer a Featured.com query, your name, your company, and your specific claim get published on a real editorial page. Those pages are exactly the kind of source that shows up in AI answers, so you are not only passing link equity, you are putting a quotable, attributed sentence about your expertise somewhere an AI engine can retrieve it. That matters because AI search citation and blue-link ranking are separate outcomes. I have pages on this site that get cited inside AI Overviews while ranking modestly, and pages that rank well and never get quoted. In my experience the placements that get pulled into answers are the ones carrying a specific, attributable claim on an established publication, which is the pattern I dig into in my guide to [what AI SEO actually is](/ai-seo-strategy/). So judge the output on two axes, not one. The DR number is your proxy for link value. Whether the placement includes your name, your title, and a claim worth quoting is your proxy for AI visibility. Backlinker's pitches are written off your bio, which is exactly why the bio step earlier is worth an hour of real effort instead of ten minutes. A vague bio produces generic quotes that nothing wants to cite. ### **Final Thoughts from Ryan** Backlinker AI is not a shortcut to Forbes. But for small to medium businesses and anyone building a new website's authority, it's one of the most cost-efficient backlink tools I've used. The $300/month price point, money-back guarantee, and hands-off operation make it easy to justify, especially compared to agency fees that often deliver the same results with far less transparency. The reason I still run it in 2026 is the second job those placements do. Every accepted pitch puts an attributed quote from you on a publication that both Google and the AI engines already treat as a source. You are buying link equity and citation surface in the same $300, and almost nobody is pricing that second half correctly yet. If you're ready to try it, grab the [Backlinker AI free trial here](https://www.backlinker.ai/?ref=ryan) and use code **RYANDOSERAI** for 50% off your first month. ### **Backlinker AI Review FAQs** #### **What is Backlinker AI?** Backlinker AI is an AI-powered backlink automation tool that sends pitches to journalist and editor query platforms like Featured.com, HelpAB2BWriter, and SOS on your behalf. It matches your expertise profile to relevant media opportunities and handles outreach automatically, delivering editorial backlinks without manual effort. #### **How much does Backlinker AI cost?** Backlinker AI costs $300 per month for its single Pro plan, which includes one website profile, 150+ monthly pitches, done-for-you outreach, and a money-back guarantee if you don't receive at least 3 backlinks from sites with a Domain Rating of 30 or higher. #### **Does Backlinker AI actually work?** Yes, based on real client results. One client account generated 14 published placements in a single month, including links from DR 76 and DR 71 sites. Results vary by niche and how well the onboarding bio is optimized, but consistent DR 30 to DR 70 backlinks are achievable within 2-3 months. #### **What kind of backlinks does Backlinker AI get?** Backlinker AI typically delivers DR 30 to DR 70+ editorial placements from publications that use platforms like Featured.com for expert sourcing. You will not get links from Forbes, CNN, or similar tier-one outlets. Those require agency relationships that no automated tool can replicate. #### **How long does Backlinker AI take to show results?** Give it two to three months. The first month is mostly pitches going out with few placements landing, because editors work on their own timelines and a pitch sent in week one may get published in week six. By month two and three the accepted placements accumulate and the monthly report shows real data. Judging the tool at 30 days is the most common mistake I see people make with it. #### **Do AI-generated backlink pitches actually get accepted by editors?** Yes, but the acceptance rate depends almost entirely on your bio and website. In the client month I detail above, 480 pitches produced 12 selections and 14 published placements, so most pitches go nowhere and that is normal for the model. The pitches are written from your biography, so a specific, credential-heavy bio gets picked noticeably more often than a vague one. Editors are choosing between many expert responses, and specificity wins. #### **Does Backlinker AI help with AI search visibility, not just Google rankings?** That's a real secondary benefit and part of why I keep using it. Expert-quote placements put your name, title, and a specific claim on editorial pages that ChatGPT, Perplexity, and Google AI Overviews crawl and cite. Ranking and being cited are separate outcomes, and an attributed quote on a trusted publication is strong material for the citation side. Push for placements that name you and quote a specific claim, not just ones that pass a link. #### **Is Backlinker AI worth it for small businesses?** For small to medium businesses and new websites trying to build domain authority without paying agency prices, yes. At $300/month with a money-back guarantee, it's a lower-risk entry into link building than hiring an agency. What I would avoid at any price is the exchange model, where members trade links with each other, and I explain [why Google's spam policy names that mechanic by name](/outrank-review/). See the [Poppy AI review](/poppy-ai-review/) or [Blaze AI review](/blaze-ai-review/) for similar cost-vs-value breakdowns on other AI tools. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## Blaze AI Review: The Best AI Tool for Social Media? (2026) URL: https://ryandoser.com/blaze-ai-review/ Markdown: https://ryandoser.com/blaze-ai-review.md Published: 2026-08-03 | Updated: 2026-09-30 Categories: AI Tool Reviews > Blaze AI now starts at $79/mo, not $34. A hands-on review of the autopilot rebuild, 2026 pricing tiers, credit limits, and where it falls short. I spent several hours testing the new Blaze AI Autopilot, and this **Blaze AI review** breaks down whether the upgrade justifies the higher price tag. *Updated August 3, 2026: Blaze has replaced the single $65/month plan with three tiers starting at $79/month. Pricing was rechecked on September 30, 2026, when the All-In-One tier dropped to $999/month.* *Some links below are affiliate links. [See my disclosure](/disclosure/).* ### **My Blaze AI Review** Most AI marketing tools still operate as co-pilots. You type a prompt, tweak the output, schedule it manually, and repeat. Blaze AI made a bold move by switching its entire platform to what they call "autopilot." #### [**Try Blaze AI**](https://www.blaze.ai/?fpr=rtcxca) Once you finish onboarding, [Blaze AI](https://www.blaze.ai/?fpr=rtcxca) takes over. It reads your website, pulls in your logo, matches your brand colors, and starts generating a full week of posts without you typing a single prompt. The catch is that your initial inputs determine everything. Sloppy setup equals sloppy output. ![Blaze AI Autopilot Interface](/images/2026/03/Blaze-AI-Review-Autopilot-Interface.jpg) I tested this with a local home service business called CJ's Window Cleaning in Des Moines. Within minutes, Blaze scraped the website, built a brand profile, and generated a full week of social content across Instagram, Facebook, and LinkedIn. ### **Features I Tested Inside Blaze AI** The user interface earned high marks. Clean layout, easy to find what you need, and noticeably more polished than most AI marketing tools I've tested. #### **Content Calendar and Brand Plan** The calendar gives you a clear week-by-week view of scheduled posts across every connected platform. You can toggle between list view, week view, and month view. Filter by channel, account, or post status. For a tool at this price point, the calendar rivals what you'd find in dedicated schedulers. ![Blaze AI Content Calendar](/images/2026/03/Blaze-AI-Review-Content-Calendar.jpg) The brand plan feature adds a layer of human control on top of the autopilot system. Click into any week and you can adjust post frequency per platform, swap out topics, add short-form video, or include blog and email content. You're not surrendering full control to AI, which matters. #### **Brand Kit Setup** This is the feature that makes or breaks your entire Blaze AI experience. Think of it as your brand's instruction manual for the AI. You upload your logo, define your color palette with exact hex codes, set typography rules, and write out your brand voice guidelines. ![Blaze AI Brand Kit Setup](/images/2026/03/Blaze-AI-Review-Brand-Kit-Setup.png) Rushing through brand kit setup produces generic, off-brand posts. I'd recommend using [Google Gemini or ChatGPT](/google-gemini-vs-chatgpt/) to build a mini brand guide first, then transfer those details into Blaze. Getting the hex codes, typography, and voice settings right upfront saves hours of editing later. #### **Integrations and Paid Ads Beta** Blaze plugs into all the major platforms you'd expect, plus GoHighLevel and Zapier for custom workflows. The surprise addition is a paid ads beta for Meta, which would let you manage organic posts and ad campaigns from the same interface. That's a feature most [AI marketing tools](/ai-replacing-marketing-agencies/) skip entirely. ![Blaze AI Platform Integrations](/images/2026/03/Blaze-AI-Review-Integrations.png) ### **Blaze AI Pricing in 2026** Blaze has changed its pricing twice since I first reviewed it, and most of the reviews you will find online are quoting numbers that no longer exist. Here is what you actually pay today. There are three plans: - **Starter, $79/month.** 3 posting accounts, 600 generation credits per month, 1 user, automated ad campaigns. - **Growth, $149/month.** 10 posting accounts, 1,500 generation credits per month, unlimited users, and a yearly planning window. - **All-In-One, $999/month.** A fully managed marketing system run with a dedicated marketing expert: complete funnel, Google Business Profile, search ads, an AI receptionist, lead qualification, automated reviews, and reporting. ![Blaze AI pricing page in August 2026 showing the Starter plan at $79 per month and the Growth plan at $149 per month](/images/2026/08/blaze-ai-review-pricing-2026.jpg) Both self-serve plans include a 7-day free trial with no credit card required, which is a real improvement over how this used to work. The credit system is the part worth understanding before you pick a tier. Content draws down a monthly balance at different rates: a social post costs 1 credit, an email or a blog post costs 3, and an AI video costs 15. That last number is the one that catches people. If you lean on AI video, 600 credits on the Starter plan disappears faster than the headline number suggests, because 40 AI videos alone would consume the entire allowance. #### **The Old $34 and $65 Plans Are Gone** If you have read another Blaze review recently, you may have seen a Creator plan at $22 to $34/month, a Pro plan at $49, or the single $65/month autopilot plan I wrote about in my original review. Those are all dead. Blaze's own help documentation confirms the legacy Copilot plans [stopped being available to new users on September 15, 2025](https://help.blaze.ai/en/articles/9540712-blaze-plans-and-subscriptions-blaze-copilot-legacy-plans). This matters more than a normal price change. When I checked the Google AI Overview for "Blaze AI pricing" while updating this post, it was still confidently listing the retired $22 Creator plan and a $49 Pro tier as current options. Several review sites ranking on page one are quoting the same dead numbers. If you budgeted around $34/month based on one of those, the real entry price is more than double it. For context on where $79 sits in this market, the traditional schedulers cost more and do less of the writing: a [Hootsuite](https://www.hootsuite.com/plans) standard plan runs $149/month per user and [Sprout Social](https://sproutsocial.com/pricing/) prices higher still per seat, and with both you are buying scheduling and analytics, then paying separately for whatever writes the posts. So here is my actual verdict on the tiers. Starter at $79 is the one worth buying, and only if you will genuinely use the automated content generation, because that is the piece you cannot get from a cheaper scheduler. Skip it if you mainly need to queue posts you write yourself, since a $29/month tool covers that and I compare those in my roundup of [social media automation tools](/social-media-automation-tools/). Growth at $149 only makes sense once you need more than 3 posting accounts or you have a team that needs seats. The $999 All-In-One is a managed service, not software, and should be judged against agency quotes rather than against other apps. ### **Three Problems I Found During Testing** If you're new to AI tools altogether, $79/month is the wrong starting point. Grab [ChatGPT Plus or Claude Pro](/chatgpt-alternatives/) first for $20/month. Learn how AI content generation works at a lower price before committing to a specialized platform. The second issue is model opacity. I looked everywhere inside the editor and settings for any indication of which AI models generate the copy and images. Nothing. No way to select a model, no documentation on their website. When a platform hides what's under the hood, it usually means they're running cheaper model variants to save on API costs. Third, the autopilot framing sets wrong expectations. During my CJ's Window Cleaning test, I found posts where the AI-generated B-roll video had nothing to do with window cleaning. Some image selections missed the mark. You still need to open the calendar every Monday and scan what's scheduled before it goes live. ### **Who Actually Needs This Tool (And Who Doesn't)** Picture the owner of a plumbing company or a window cleaning service. They're booked solid six days a week. They know they should be posting on social media, but they don't have time and can't stomach paying an agency thousands per month. That's the exact person [Blaze AI](https://www.blaze.ai/?fpr=rtcxca) was built for. Busy coaches and solo operators who need their brand visible online without spending an hour each morning writing captions also fit the profile. The weekly brand plan gives enough control to keep content on track. Full transparency: I don't use Blaze for my own accounts. My setup runs on [Claude Code paired with Blotato](/ai-agent-for-content-creation/), which gives me deeper control over how long-form content gets repurposed. But that workflow requires technical comfort with APIs and automations that most small business owners don't have. ### **Final Notes from Ryan** After testing Blaze AI Autopilot with a real business, my takeaway is straightforward: if you spend the time on brand kit setup and review your calendar weekly, this tool can keep your social accounts active without dominating your schedule. The interface is polished, the autopilot concept works when you feed it good inputs, and the pricing sits well below traditional scheduling platforms. I'd like to see AI model transparency and a more honest framing around what "autopilot" actually means. But for business owners who'd otherwise post nothing, [Blaze AI](https://www.blaze.ai/?fpr=rtcxca) solves a real problem at a fair price. ### **Blaze AI Review FAQs** #### **How much does Blaze AI cost per month?** Blaze AI costs $79/month for the Starter plan (3 posting accounts, 600 generation credits, 1 user) and $149/month for the Growth plan (10 posting accounts, 1,500 credits, unlimited users). A fully managed All-In-One tier runs $999/month. Both self-serve plans include a 7-day free trial with no credit card required. The older $22 to $34 Creator plan and the $65/month autopilot plan are no longer sold to new users. #### **What are the limitations of Blaze AI?** Three stand out from my testing. Blaze does not disclose which AI models generate your copy and images, so you cannot pick a model or verify what you are paying for. The credit system prices AI video at 15 credits against a 600-credit Starter allowance, which drains fast if video is central to your plan. And "autopilot" oversells the automation: during my testing the AI attached B-roll that had nothing to do with the business, so you still need a weekly review pass before posts publish. #### **Is Blaze AI free?** No, but there is a genuine 7-day free trial that does not require a credit card. During the trial Blaze builds your brand identity, a custom content strategy, your first full week of posts, and topics for a second week. That is enough to judge output quality before any money changes hands, which is the right way to test it. #### **Should I get ChatGPT Plus or Blaze AI first?** Start with ChatGPT Plus at $20/month. It handles a wider range of tasks and teaches you how AI content generation works. Once you need automated scheduling and multi-platform publishing on top of AI writing, that's when Blaze AI starts making sense as an add-on investment. #### **How important is the brand kit setup in Blaze AI?** Critical. Every piece of content Blaze generates on autopilot pulls from your brand kit inputs. Spending 30-60 minutes dialing in your colors, fonts, voice, and content preferences upfront determines whether you get generic AI posts or content that actually matches your brand. #### **Is Blaze AI better than hiring a social media agency?** For businesses spending under $1,000/month on social media, yes. An agency charges $5,000-$10,000/month for what Blaze does at $79/month. The output quality won't match a skilled human strategist, but for maintaining a consistent presence, the ROI math works in Blaze's favor. #### **Can I turn off autopilot and use Blaze AI manually?** Yes. The settings panel includes an autopilot toggle you can disable. But at $79/month you'd be paying a premium for what the retired co-pilot version offered at $34, and that cheaper tier is no longer available to new users. If you want manual control above all else, consider whether the investment still makes sense for your workflow. #### **How much time does Blaze AI actually save per week?** In my CJ's Window Cleaning test, the initial setup took about 20 minutes. After that, Blaze generated five days of cross-platform content automatically. I'd estimate 15-20 minutes of weekly review time to check posts before they publish. Compare that to 5-10 hours of manual content creation and scheduling. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## Microsoft Copilot for Business: Worth It or Watered Down? URL: https://ryandoser.com/microsoft-copilot-for-business/ Markdown: https://ryandoser.com/microsoft-copilot-for-business.md Published: 2026-08-03 | Updated: 2026-09-30 Categories: AI Rabbit Holes > Microsoft Copilot for business is worth it in one specific case. A quality leader who builds with it daily on where it wins and loses. I have called **Microsoft Copilot for business** a watered down ChatGPT for about three years, and I had not opened it once in that time. Then I interviewed someone who builds with it every single day, and I had to update my take. There is also a career opening buried in this one that I did not see coming. ### **Microsoft Copilot for Business Video Guide** My guest is Mike Bryan, a quality leader who spent his career inside the Microsoft ecosystem and now builds AI agents, apps, and automations with Microsoft products. Mike is also a VIP member of my community, and he came on to show me what I had been dismissing. The short version is that I was judging the wrong thing. I kept comparing the chatbot to Claude and ChatGPT, which is a fight Copilot loses. That comparison misses where the product actually competes. If you want to go deeper on running AI inside a real business, I put together a guide on [how business owners can use Claude Code](/claude-code-for-business-owners/) that covers the other side of this stack. ### **Why I Was Wrong About Copilot** Here is the number that reframed the whole conversation for me. Roughly 80 to 85 percent of the thousand biggest companies in the United States run on the Microsoft ecosystem, according to Mike. Microsoft reports that [more than 90 percent of the Fortune 500 now use its AI tools](https://news.microsoft.com/ai-in-action). So this is not a niche tool. It is the default AI for millions of people who never got to pick. Mike put the design intent plainly. Microsoft never tried to win the frontier model race. They stayed centrally located inside their own ecosystem and optimized the Office suite for AI instead. Anthropic and OpenAI spent years building the best raw model. Microsoft spent those years asking a different question about the infrastructure it already owned. The question was how to make the tools people already open every morning better. *Mike walks through an agent workflow he built, chaining a file trigger into text recognition and a prompt.* ### **The Tenant Is the Whole Argument** Ask what Copilot does that Claude cannot, and the honest answer is not about output quality. It is about where your data sits when the work happens. Everything stays inside your Microsoft tenant. For a hospital system or a finance firm, that single property outranks every benchmark score. Mike connects client systems through what he counts as roughly 1,100 connectors, pulling in platforms like HubSpot and Workday. Microsoft's own library is larger now, so treat that as his working number. The data never leaves the boundary the compliance team already approved. I assumed this only mattered at Fortune 1000 scale. Mike corrected me with two examples that stuck. He has a friend who runs a wealth management agency with ten employees. Their insurance partner mandated they stay inside the Microsoft ecosystem. He also works with a tax accountant facing SEC filing requirements, where every third party tool added to the stack multiplies the complexity. Ten people. No enterprise budget. Still locked in. That is the reader most Copilot coverage ignores, and it is a much bigger group than I expected. ### **What Microsoft Copilot for Business Actually Replaces** The license math is where this gets interesting for a small team. Copilot is not one purchase. It quietly replaces a stack of subscriptions you may already pay for separately. Power Automate runs about $15 per user monthly and covers the ground Zapier and Make occupy. If you are weighing that trade, I broke down [where per-task billing stops making sense](/best-zapier-alternatives/) in more detail. [Copilot Studio](https://www.microsoft.com/en-us/microsoft-365-copilot/microsoft-copilot-studio) handles custom chatbots and agents at a higher tier. Here are the current published rates from [Microsoft's pricing page](https://www.microsoft.com/en-us/microsoft-365-copilot/pricing): - **Microsoft 365 Copilot Business:** $18 per user monthly paid yearly, a promotional first-year rate running through December 31, 2026, normally $21 - **Business Standard with Copilot:** $23.50 per user monthly paid yearly - **Business Premium with Copilot:** $32 per user monthly paid yearly - **Copilot Chat:** included at no extra cost with eligible Microsoft 365 plans One warning from Mike that the pricing page does not advertise. Microsoft has started folding credits into these licenses, and he hit a limit he did not know existed. He estimates he still spent under $100 sorting it out, but he called the credit system nebulous. Budget for that surprise before you roll out seats. *A training records manager Mike built, tracking course completion and attendance across departments.* ### **The Agent Layer Nobody Talks About** Every platform ships an agent feature now, and almost nobody defines the term. So I asked Mike how a Copilot Studio agent differs from an n8n workflow or a Claude Code subagent. His answer was refreshingly unglamorous. The agent holds the instructions and the knowledge, and you attach tools to it. He prompted it to send a daily report, tweaked the formatting, and now it emails him every morning. A more involved build converted SOPs trapped in PDFs into a training format called a job instruction breakdown. The workflow pulls text out of the PDF, runs it through the agent, composes the document, and triggers an Excel script to format it. Mike is blunt that Copilot Studio is complex. He also thinks the workflow builder looked easier than Zapier or Make, which surprised me watching it. Microsoft is also shipping app builders on top of this. One runs on SharePoint lists and stays deliberately light. A more capable version sits in preview at vibe.powerapps.com, built on Dataverse. ### **The Real Opportunity Is the Consultant Gap** This is the part I keep thinking about a week later. Fortune 1000 companies pay McKinsey style firms enormous sums for transformation work. Those same companies are full of people who genuinely struggle to operate a computer. If you become the person who actually understands Microsoft AI inside one of those organizations, you are holding rare leverage. Mike does not think this is a gold rush that evaporates. Microsoft keeps adding to the tool belt, so staying current is the job. His rapid fire advice for anyone sitting inside that ecosystem tomorrow morning was refreshingly simple. Identify your biggest pain point. Then ask Copilot which Microsoft tool solves it, because there is almost certainly one you have not found. *Copilot Notebooks pulling a summary and key insights from a collection of saved sources.* Notebooks is Microsoft's answer to NotebookLM, and Mike concedes Google is further along. You point it at references, then generate a study guide, a presentation, or an audio recap. Paired with Loop, which functions like Notion, you get a knowledge base that lives where your team already works. I have written before about building an [AI second brain](/ai-second-brain/), and this is that idea rebuilt inside a corporate tenant. ### **Ryan's Final Thoughts** I still would not use Copilot. As a solo operator with no red tape, Claude and Claude Code beat it comfortably. That is exactly the point I got wrong for three years. I was evaluating a compliance product against a creativity product. If you are weighing that same decision for your own business and would rather not make it alone, that is the job [your AI guy](/ai-concierge/) does. If your data has to stay inside the tenant, the model quality gap stops being the deciding factor. Mike's prediction for the next year is that the vague capability marketing gives way to specific proven use cases. Being the person with those receipts is the opportunity. The full conversation with Mike is in the episode above, including the screen shares where he walks through each build. ### **Microsoft Copilot for Business FAQs** #### **Is Microsoft Copilot for business worth it?** It is worth it when your organization already runs on Microsoft 365 and your data cannot leave the tenant for compliance reasons. In that case it is often the only approved option. If you are a solo operator or a small agency with no regulatory constraints, general purpose tools like Claude or ChatGPT deliver stronger output for less money. #### **How much does Microsoft Copilot for business cost?** Microsoft 365 Copilot Business runs $18 per user monthly paid yearly as a promotional first-year rate through December 31, 2026, normally $21. Business Standard with Copilot is $23.50 and Business Premium with Copilot is $32, both per user monthly paid yearly. Copilot Chat is included at no extra cost with eligible Microsoft 365 plans. #### **What is the difference between Copilot and Copilot for business?** The consumer version answers questions using web data. The business version is grounded in your organization's own content, meaning your emails, files, chats, and meetings inside the Microsoft tenant. Per [Microsoft's privacy documentation](https://learn.microsoft.com/en-us/microsoft-365/copilot/microsoft-365-copilot-privacy), it only surfaces data the individual user already has permission to view. #### **Can Microsoft Copilot replace Zapier or Make?** Power Automate covers most of the same automation ground at roughly $15 per user monthly, and it connects natively to Microsoft services. Mike Bryan found the workflow builder easier to use than expected. The tradeoff is that it works best when the systems you are connecting already live inside the Microsoft ecosystem. #### **Is Microsoft Copilot good for small businesses?** It depends entirely on whether you are required to stay in the ecosystem. A ten person wealth management firm mandated by its insurance partner has a real reason to adopt it. A small marketing agency with no compliance pressure will get more value from a general purpose AI tool at a lower price point. --- ## Poppy AI Review: Is This Popular AI Tool Worth the Hype? URL: https://ryandoser.com/poppy-ai-review/ Markdown: https://ryandoser.com/poppy-ai-review.md Published: 2026-08-03 | Updated: 2026-08-03 Categories: AI Tool Reviews > Poppy AI killed its public pricing page and now sells by demo call. A hands-on look at the board system, credit limits, and who should skip it. After testing Poppy AI for several weeks, this **Poppy AI review** separates the marketing hype from what the tool actually delivers. *Updated August 3, 2026: Poppy has moved to a new v2 site, removed public pricing entirely, and now sells through a booked demo with a 15% revenue guarantee. Details below.* *Some links below are affiliate links. [See my disclosure](/disclosure/).* ### **My Honest Review of Poppy AI** Poppy AI markets itself hard. Catchy Instagram rap ads, thumbnails claiming "$35,000 from one video," and countdown timers on the checkout page that reset every five minutes. The marketing machine behind this tool is impressive. The question is whether the product matches the pitch. #### [**Try This Poppy AI Alternative Instead**](https://www.blotato.com/?ref=rdoser) At its core, Poppy AI is a visual board-based content creation platform. You drag and drop content sources onto a canvas, connect them to an AI chatbot, and generate new content based on those inputs. Think of it as a mind map that talks back. You can feed it YouTube videos, TikTok clips, Instagram reels, documents, and website URLs. The AI transcribes everything and uses it as context for whatever you ask next. ![Poppy AI Website Homepage](/images/2026/03/Poppy-AI-Review-Website.jpg) The visual interface is genuinely one of the best I've tested across dozens of AI tools. Drag-and-drop organization, clean layout, and everything stays visually connected on the board. If you're someone who thinks better with spatial layouts than text prompts, this part of Poppy AI delivers. ### **Poppy AI Features Worth Knowing** #### **The Board System and Brand Voice Training** I built a board to generate video ideas by training two groups: one folder with my own YouTube videos and TikTok clips (my brand voice), and another with videos from a popular AI creator I wanted to study. Poppy transcribed everything automatically, and when I connected both folders to the chatbot, it blended the viral patterns from the competitor with my own voice. ![Creating a Board in Poppy AI](/images/2026/03/Poppy-AI-Review-Board.jpg) The output was solid. Ten video ideas with titles, keywords, and hooks that actually sounded like something I'd publish. You can apply the same approach to email newsletters, social captions, blog posts, or short-form scripts. #### **Multi-Model AI Access** Unlike tools that hide which models run in the background, Poppy AI lets you pick your engine. Poppy describes the current lineup as Claude, ChatGPT, Gemini, and the leading image models, and the specific versions rotate as the labs ship new ones. For content creation I still reach for Claude first, because it produces the cleanest copy with the least cleanup. Being able to see and switch the model is a real advantage, and it is the exact thing Blaze AI refuses to disclose, as I cover in my [Blaze AI review](/blaze-ai-review/). ![Choosing AI Models in Poppy AI](/images/2026/03/Poppy-AI-Review-AI-Models.png) #### **Strong Transcription from Multiple Platforms** Poppy handles YouTube, TikTok, and Instagram transcription better than most competitors. Paste a URL, and the transcript appears in seconds. [Most AI tools](/chatgpt-alternatives/) struggle with short-form video platforms, so this is a genuine advantage. ### **Poppy AI Pricing: What You Actually Get (Updated August 2026)** Poppy's pricing has changed in a way most reviews have not caught up to, and the change is structural rather than a simple price bump. You can no longer buy this tool without talking to someone. When I originally reviewed Poppy, you could buy it directly: $399 for the year, no monthly billing, no free trial. That self-serve checkout is gone. Poppy has moved to a new site at v2.getpoppy.ai, and the only route in through Poppy's own site is now a booked call. The homepage headline is now a guarantee ("increase your revenue by 15% from your content and ads in 90 days or you don't pay") and the single call to action is "book a 5-min prove it demo." ![Poppy AI v2 homepage in August 2026 showing a 15 percent revenue guarantee and a book a 5-minute demo call to action instead of a pricing page](/images/2026/08/poppy-ai-review-v2-homepage.jpg) Poppy's own FAQ still describes three credit tiers, Basic at 2,000 credits a month, Creator at 8,000, and Power User at 16,000, but it no longer publishes a price next to any of them. The guarantee is described as "tailored to your numbers," so the terms get set on the call rather than published on a page. Be honest with yourself about what that means for how you buy. Purchasing a tool at a listed price and negotiating one on a sales call are different experiences, even if the final number lands in the same place. If you want to see a price before talking to anyone, AppSumo is the route: lifetime tiers [start at $279 for 500 monthly credits](https://appsumo.com/products/poppy-ai/) and run up to $4,459, with a 60-day refund window. Check the credit math before you buy there, because 500 credits a month is a quarter of the 2,000 that the old $399 Basic tier included. On my test account with 2,000 monthly credits, I burned through a noticeable chunk just transcribing five longer YouTube videos and running a few chatbot sessions. Power users would hit the ceiling fast, and that ceiling is the number I would press hardest on if I were taking the demo call. The top tier has historically run into the thousands and is where API access sits. For context, [Blotato gives you API access on its $29/month plan](https://www.blotato.com/?ref=rdoser). That price difference is hard to justify unless the board workflow is genuinely the thing you are buying. After generating content, you still have to manually copy it to wherever you want to post. There's no publish button, no scheduler, no connected social accounts. You write inside Poppy and paste outside it. If your workflow depends on [automated content distribution](/ai-agent-for-content-creation/), you'll need a second tool on top of this one. ### **My Honest Take on Whether Poppy AI Is Worth It** I'll give you two answers depending on where you are with AI. If you haven't used AI tools much yet, skip Poppy entirely. [ChatGPT Plus or Claude Pro](/switch-from-chatgpt-to-claude/) at $20/month gives you access to the same models, higher usage limits, image generation, and projects. Google's free [NotebookLM](/ai-for-non-coders/) handles video transcription and summarization without spending a dollar. If you're a working creator or marketer, the board system has genuine value for content ideation and competitor research. I built boards that blended another creator's viral patterns with my own voice, and the output was actionable. That specific workflow is unique to Poppy. But before you book the demo call, test [Blotato at $29/month](https://www.blotato.com/?ref=rdoser) with no annual commitment. It handles content generation, social scheduling, and API access in one platform. If Blotato covers your needs, Poppy becomes a hard sell at several times the effective cost. I keep a wider list of options in my roundup of [the best AI tools for content creators](/best-ai-tools-for-content-creators/). ### **Ryan's Final Verdict on Poppy AI** I wanted to like this tool more than I do. The board interface is the most creative approach to AI content generation I've seen, and the competitor analysis workflow produced results I couldn't replicate anywhere else. If Poppy offered a $30/month plan with transparent credit limits, I'd recommend it without hesitation. Instead, the annual lock-in, hidden credit math, and expensive API tier undercut what's otherwise a well-built product. The move to demo-call-only pricing pushes it further in that direction: the product got better, but buying it got harder. Test it with the 30-day money-back guarantee if the visual concept appeals to you. Just know that the marketing paints a rosier picture than what most users will experience. ### **Poppy AI Review FAQs** #### **How much does Poppy AI cost in 2026?** Poppy AI no longer publishes prices on its website. The new v2 site replaced the pricing page with a booked "prove it" demo, where the cost and the performance guarantee are set based on your business. Poppy's FAQ still lists three credit tiers, Basic at 2,000 credits per month, Creator at 8,000, and Power User at 16,000, without attaching a price to any of them. The old self-serve rate was $399 per year for Basic. The only published self-serve pricing today is the AppSumo lifetime listing, which starts at $279 for 500 monthly credits. #### **Is there a free version or free trial of Poppy AI?** No. There is no free tier and no free trial. What you get instead is a 30-day money-back guarantee, so you pay first and request a refund if it does not work out. Poppy also advertises a 90-day revenue guarantee that is customized during the demo call. If you want to try a visual AI canvas without paying, Google's NotebookLM handles multi-source research and video transcription for free. #### **Can I use Poppy AI to study what makes competitor content go viral?** Yes, and this is its strongest use case. Create a board with your competitor's YouTube videos or TikTok clips, connect them to the chatbot alongside your own content, and ask it to blend their viral patterns with your voice. I tested this approach and the output was genuinely actionable. #### **What happens if I don't like Poppy AI after signing up?** They offer a 30-day money-back guarantee: email support within 30 days and you get a full refund. No free trial exists, so you commit upfront and request a refund if it doesn't fit. Make sure to test the tool thoroughly within that first month, and get the refund terms confirmed in writing on the demo call before you pay. #### **How does Poppy AI's board system compare to regular AI chat tools?** Standard tools like ChatGPT process one conversation at a time. Poppy lets you connect multiple content sources on a visual canvas, then reference all of them simultaneously in one chatbot session. For single-question tasks, it's overkill. For multi-source research and ideation, the spatial layout adds real value. #### **Is Poppy AI worth the price?** The monthly math sounds fair when you divide an annual plan by twelve, but the commitment changes the equation. You pay for a year before knowing if the tool works for your specific workflow, and you now have to sit through a sales call to find out the number. Tools with month-to-month plans let you test for $29-$34 and cancel anytime, which is a lower-risk way to evaluate. Buy Poppy for the board workflow, not for the AI models, because you can get those anywhere for $20 a month. #### **Can Poppy AI post directly to my social media accounts?** No. Content stays inside the platform until you manually copy and paste it elsewhere. If you need creation and distribution in one tool, you'll need to pair Poppy with a separate scheduler or choose a platform that bundles both features together. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## Best Zapier Alternatives for Social Media Posting (I Moved Off It) URL: https://ryandoser.com/best-zapier-alternatives/ Markdown: https://ryandoser.com/best-zapier-alternatives.md Published: 2026-08-01 | Updated: 2026-08-01 Categories: AI Tool Reviews > Per-task billing punishes social posting specifically. The best Zapier alternatives for it, and what I moved my own posting to instead. Most lists of the **best Zapier alternatives** are written by a company that sells a Zapier alternative. Gumloop ranks itself first on its own list. Vellum ranks itself first on its own list. Lindy ranks Make first on its. Zapier ranks itself first on a page about alternatives to its competitor. I do not sell an automation platform, so this is a different kind of list. It is also narrower than most, because I want to answer one specific version of the question: what do you use instead of Zapier when the job is publishing social media posts? I moved my own posting off Zapier. Below is what I moved it to and what the move cost. ### **Why Zapier Is the Wrong Shape for Social Posting** Zapier is a good product. It has the widest app library in the category and it is the easiest thing in this space to get working on your first afternoon. None of that is in dispute, and I still recommend it for plenty of jobs. The problem is the billing model meeting this particular workload. [Zapier bills by task](https://zapier.com/pricing), where a task is roughly one action your workflow performs. The free plan gives you 100 tasks a month and caps you at two-step workflows. Professional starts around $19.99 a month billed annually for 750 tasks, and $29.99 if you pay monthly. Now count what one piece of content costs in tasks. Pull the video, generate a caption, format it for platform one, post it, format for platform two, post it, and so on across six platforms. A single video can burn a dozen tasks or more before anything is scheduled. Do that a few times a week and 750 tasks stops being a generous allowance. That is the whole problem in one sentence. Social publishing is inherently many small actions per piece of content, and Zapier prices exactly that pattern. ### **The Alternatives, by What You Are Actually Solving** #### **1. Make (if you want the same thing, cheaper)** [Make](https://www.make.com/en/pricing) is the closest like-for-like swap and the one most people should try first. Same visual builder concept, same trigger-and-action model, and the free plan gives you 1,000 credits a month against Zapier's 100 tasks. Core starts at $12 a month for 10,000 credits. Be clear-eyed about what the credit model is, though, because it is not free of the same trap. Every module action costs a credit, including triggers and filters, so a workflow that looks cheap on the canvas gets expensive at volume. It is a better rate, not a different philosophy. One note from getting it wrong. Build error branches into the first version rather than the fifth. I had an infographic workflow that fetched an image before it had finished rendering, the fetch failed, and because there was no error path the scenario sat dead until I happened to notice. A stalled automation looks exactly like a working one until you go looking. The fix was a 90-second wait module. #### **2. n8n (if you are running real volume)** [n8n](https://n8n.io/) changes the math rather than the price. It bills per workflow execution instead of per step, so a fifty-step social workflow costs one execution where a per-task tool would charge you fifty. For this use case specifically, that is the single biggest structural difference on this page. It is also self-hostable at no license cost. That is the reason I keep it around, and the reason is client work rather than my own posting: when a client's data is not allowed to leave their own servers, self-hosting is the only option on this page, and n8n is the only tool here that offers it. The trade is that it is the steepest thing here to learn, and the Starter cloud tier keeps only seven days of execution history, which is short if you are debugging something that fails intermittently. If you are automating your own posting and nothing else, Make is the friendlier starting point. I wrote more about where it fits in [whether n8n is dead in 2026](/is-n8n-dead/). #### **3. A dedicated posting tool (if the workflow was only ever posting)** This is the one the vendor lists never suggest, and for a lot of people it is the right answer. If your Zap does nothing except take content and publish it to social platforms, you may not need an automation platform at all. That is a scheduler's entire job, and schedulers are flat-priced. [Buffer](https://buffer.com/pricing) is free for three channels. [Blotato](https://www.blotato.com/?ref=rdoser) is $29 a month flat for 20 connected accounts, and the bill does not move when you add a profile or post more often. What that looks like in practice for me: a batch of ten short videos gets captions written, files uploaded, and slots scheduled across six platforms in one run, and the invoice is the same $29 whether that batch is ten videos or two. On a per-task tool the same batch is a few hundred tasks. Two limitations worth knowing before you switch, since I have hit both: the scheduling calendar is weaker than Buffer's, and the 7-day trial excludes API access, so if you want to drive it programmatically you are starting the subscription rather than trialing it. You give up the arbitrary if-this-then-that flexibility. In exchange your posting bill stops being a function of how much you post, which for a publishing workflow is usually the better trade. #### **4. Claude Code (if the captions were the actual bottleneck)** This is where mine ended up, and it is worth explaining why rather than just naming it. The reason I was paying Zapier was never the connecting. It was that I wanted captions written and scheduled without me sitting there doing it. But every caption a workflow tool generates comes out of a model that knows nothing about how I write. [Claude Code](https://www.claude.com/product/claude-code) reads my actual files. Voice rules, past posts, the transcript of whatever video I am repurposing. It drafts the captions from that context and hands them to Blotato over MCP, which publishes them. The full build is in my guide to [building an AI social media manager with Claude Code](/claude-code-social-media/). Two caveats. It is non-deterministic, so the same prompt can produce different output, and I would not point it at anything where a wrong result is expensive. And it is a terminal tool, so there is a learning curve if you have never worked that way. It is not a drop-in Zapier replacement, and I would not pretend otherwise. It replaced Zapier for me because the job I needed doing was writing, not connecting. ### **What the Move Actually Cost** Two things nobody mentions when they tell you to switch. Rebuilding takes longer than you estimate, because the workflow in the new tool is never a one-to-one copy. The logic transfers; the specific modules, the error handling, and the auth do not. And you lose the connector library. Zapier's app coverage is the widest in the category, and there will be some niche tool you rely on that Make or n8n does not support natively. Check the specific integrations you depend on before you cancel anything, not after. That check is five minutes and it is the one I would not skip. ### **Which One Should You Pick?** **Your Zap only publishes posts?** A flat-priced scheduler. Buffer if you are small, Blotato if you run a lot of accounts. **You want Zapier but cheaper?** Make, on the free plan first. **You are running high volume or client data?** n8n, for per-execution billing and self-hosting. **Your real problem is that the captions sound like AI wrote them?** No automation platform fixes that. That is a context problem, and it is what Claude Code solved for me. **You are on the free plan and it works?** Stay there. 100 tasks is thin, but if you are under it, switching costs you time and saves you nothing. ### **Ryan's Final Thoughts** The reason I left Zapier had nothing to do with Zapier being bad. It is that per-task billing and social publishing are a bad pairing, and I was paying a premium for flexibility I was not using. My workflow did the same six things every week. When your automation is branching and unpredictable, pay for a platform that handles branching and unpredictability. When it is the same publishing job on repeat, pay a flat rate and stop thinking about it. That is the whole decision. I compared the broader field, including the AI-first builders I left out here, in my roundup of the [best AI automation tools](/best-ai-automation-tools/). ### **Zapier Alternatives FAQs** #### **What is the best Zapier alternative for social media posting?** It depends on whether you need automation or just publishing. If the workflow is only taking content and posting it, a flat-priced scheduler beats any automation platform on cost, and Buffer or Blotato covers it. If you need real workflow logic around the posting, Make is the closest swap to Zapier and n8n is better at volume because it bills per execution rather than per step. #### **Is there a free Zapier alternative?** Make's free plan gives you 1,000 credits a month against Zapier's 100 tasks, which is the most generous free tier among the direct competitors. n8n is free if you self-host it, though you are then paying in maintenance time instead of dollars. If you are weighing those two specifically, I put them side by side in [Zapier vs n8n](/zapier-vs-n8n/). Both free plans have real constraints, and Make enforces a 15-minute minimum between runs on the free tier. #### **Why is Zapier so expensive for social media automation?** Because publishing is many small actions per piece of content, and Zapier bills per action. Generating a caption, formatting it per platform, and posting to six platforms can burn a dozen tasks from one video. Professional starts at 750 tasks a month on annual billing, which sounds like plenty until you count what a single piece of content consumes. #### **Should I switch from Zapier to Make?** Try Make's free plan alongside Zapier before cancelling anything. The builder concept is similar enough that the learning curve is mild, and the credit allowance is far more generous. Before you commit, check that Make natively supports the specific apps you depend on, because Zapier's connector library is the widest in the category and that is its main advantage. #### **Do I need an automation tool to post to social media at all?** Often not. If your workflow is content in, posts out, a scheduler does that natively and charges a flat rate for it. Automation platforms earn their price when there is branching logic, conditional routing, or a chain of tools involved. I broke down the tools that handle each half of that job in my guide to [social media automation tools](/social-media-automation-tools/). *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine and my account there is comped rather than paid. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## How to Post on All Social Media at Once (Without Killing Your Reach) URL: https://ryandoser.com/post-to-all-social-media-at-once/ Markdown: https://ryandoser.com/post-to-all-social-media-at-once.md Published: 2026-08-01 | Updated: 2026-08-31 Categories: AI Tool Reviews > Posting identical content everywhere quietly costs you reach. The one-caption-per-format setup I run across six platforms instead. Learning **how to post on all social media at once** takes about ten minutes. Learning to do it without quietly wrecking your reach takes considerably longer, and almost nobody writing about this will tell you the second part exists. I post to six platforms every week off one long-form video. It runs through a system I built rather than a dashboard I log into, and the thing that made it work was not the tool. It was giving up on the idea that one caption should go everywhere. ### **The Short Answer** You need a scheduling tool that connects to every platform you post on. You write the post once, tick the platforms you want, and it publishes or schedules everywhere in one action. There is no native way to do this across networks, so a third-party tool is the only route. The tools that do this well, and what each one is actually for: | Tool | Best for | Starts at | Free plan | | **[Buffer](https://buffer.com/pricing)** | Three channels or fewer, and you want it to be simple | Free, then $6/mo per channel | Yes, 3 channels | | **[Blotato](https://www.blotato.com/?ref=rdoser)** | Many accounts, or driving it from an AI agent | $29/mo flat, 20 accounts | No, 7-day trial | | **[Metricool](https://metricool.com/)** | Wanting to see which platform the post actually worked on | Free, then 16 euros/mo | Yes, no LinkedIn or X | | **[Hootsuite](https://www.hootsuite.com/)** | More than one person publishing, with approvals | $99/user/mo billed annually | No, 14-day trial | If you are under three channels, use Buffer's free plan and stop reading. That is the honest answer and it costs nothing. I ranked all of these against each other in my roundup of [social media automation tools I have actually tested](/social-media-automation-tools/). ### **The Part Every Other Guide Skips** Search this question and you get eight articles explaining which buttons to click. What none of them lead with is that posting the identical thing to every platform at once is a reach problem, not just a formatting one. If a dedicated cross-poster is what you are pricing, I broke one down in my [Repurpose.io review](/repurpose-io-review/), including the daily publishing cap its pricing page does not mention. Its [closest competitors are priced here](/repurpose-io-alternatives/), split by the job each one actually does. The tell is that even the tools selling you cross-posting admit it. SocialBee's own [cross-posting guide](https://help.socialbee.com/hc/en-us/articles/40043067283351-How-to-post-to-all-social-media-at-once-cross-posting-guide) recommends cross-posting identical content no more than once every four or five posts. That is a vendor telling you to use their headline feature sparingly, which is worth paying attention to. Here is the mechanical reason. A LinkedIn post that opens with a hook and breaks every line does badly on X, where it reads as padded. An X post at 280 characters looks thin on LinkedIn. A TikTok caption with five hashtags looks like spam on LinkedIn, where I do not use hashtags at all. Same words, four different results, and only one of the four was written for the platform it landed on. There is also a thing I noticed on my own accounts that I want to flag honestly rather than overstate. TikTok appears to give less reach to content pushed through an API than to the same clip uploaded by hand in the app. It does not seem to matter which tool does the pushing. I have not run a controlled test and TikTok has never confirmed it, so treat it as something to check on your own account before you automate that channel away rather than as an established fact. ### **What I Actually Run** My setup is one source, two caption formats, six platforms. Not one caption six times. The two groups split on how the platform treats hashtags and length. Group A is Instagram, TikTok, and YouTube Shorts: hashtags, shorter, punchier. Group B is X, LinkedIn, and Threads: no hashtags, different structure, and X capped at 280 characters with Threads at 500. Two versions covers the real differences without turning into six separate writing jobs. Writing both used to be the bottleneck, which is the actual reason people cross-post identically. It is not laziness, it is that nobody wants to write the same idea four ways on a Tuesday. That is the part I handed to [Claude Code](https://www.claude.com/product/claude-code), which reads my past posts and my voice rules from local files and drafts both groups from one video transcript. Then Blotato publishes them on a schedule. I walked through the whole build in my guide to [building an AI social media manager with Claude Code](/claude-code-social-media/). The packaged version of that writing step is my [**AI Content Engine**](https://engine.ryandoser.com/), which drafts the per-platform posts, the blog, and the newsletter from one transcript in your voice. The reason that combination matters is that generic captions are the failure mode here. Across roughly 500 of my own Shorts, the top third pulled a median of about 1,100 views against 458 for the bottom third, and the gap tracked how specific the idea was more than anything about scheduling. Posting everywhere at once amplifies whatever you feed it. If what you feed it is generic, you have automated the production of content nobody reads, which is [exactly the slop problem](/avoid-ai-slop/). ### **How to Set It Up** The mechanics are genuinely easy. This takes an afternoon at most. **Connect your accounts.** Whichever tool you picked, link each platform in its settings. This is the step that breaks most often, usually because a platform token expired or a business account is not properly linked to its page. Instagram in particular requires a Business or Creator account rather than a personal one, which is also what every one of the [Instagram DM automation tools](/best-instagram-dm-automation-tools/) needs before it can reply to anyone. **Decide your caption groups before you write anything.** Two is the right number for most people. Split them on hashtags and length, since those are the differences that actually change how a post performs. **Write the long version first.** It is much easier to cut a LinkedIn post down to 280 characters than to inflate a tweet into something worth reading on LinkedIn. **Schedule rather than blast.** Publishing the same idea to six platforms in the same minute looks like exactly what it is. Spacing them across a day costs nothing and reads better. **Check the results per platform, not in aggregate.** This is where a tool like Metricool earns its money. Total impressions across six platforms tells you nothing about which platform the post actually landed on. If you would rather do this from code than from a dashboard, two API-first tools cover most of that ground and I compared them in [this head to head of the two API-first tools](/postiz-vs-zernio/). ### **Ryan's Final Thoughts** Posting to everything at once is a solved problem, and it has been for years. Pick a tool that reaches your platforms, connect it, and get the plumbing out of the way. The part that is not solved is whether the thing you are posting six times is worth posting once. Cross-posting multiplies your distribution and does nothing at all for your point of view. I record takes on a walk and let the system handle the rest, which is how I [post consistently without a content calendar](/post-consistently-with-ai/), and the recording is still the part that matters. Start with the free plan on whatever tool fits your channel count. Add the automation layer once you are certain you have something worth automating. ### **Posting to All Social Media at Once FAQs** #### **What is the app that posts on all platforms?** There is no single app that natively posts everywhere, so you need a third-party scheduler. Buffer is the easiest starting point and free for three channels. Blotato is the one I use because it is flat-rated at $29 for 20 accounts and an AI agent can drive it directly. Hootsuite is the answer if more than one person publishes and you need approvals. All of them do the same core job of write once, publish to many. #### **Can I post to all social media at once for free?** Up to a point. Buffer's free plan covers three channels with ten scheduled posts per channel and no card required. Metricool has a free tier too, though it excludes LinkedIn and X, which makes it close to useless if you are a B2B creator. Free is genuinely workable for one to three platforms. Past that, every option starts charging, either per channel or per month. #### **Does posting the same content everywhere hurt your reach?** Identical cross-posting tends to underperform, and the reason is format rather than punishment. A post written for LinkedIn reads as padded on X, and an X-length post looks thin on LinkedIn. Hashtags that are normal on Instagram look like spam on LinkedIn. SocialBee's own guide recommends limiting identical cross-posts to roughly one in every four or five posts. Two caption variants covering your hashtag and length differences solves most of it. #### **How many platforms should I actually post on?** Fewer than you think, at least at the start. I run six, but I run six because one long-form video feeds all of them and the captions are drafted automatically. If you are writing every post by hand, two platforms done properly will beat six done generically. Add platforms when your production process can support them, not because a tool makes the checkbox available. #### **Should I use an AI tool to write the different versions?** It is the highest-leverage part of the whole setup, provided the AI has something to work from. A caption button inside a scheduler writes from nothing and it shows. What made this work for me was giving Claude Code my actual voice rules and past posts as local files, so the output starts from how I write rather than from a model's average of the internet. The tool matters less than what you feed it. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine and my account there is comped rather than paid. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## Postiz vs Zernio: The Comparison Neither of Them Will Write URL: https://ryandoser.com/postiz-vs-zernio/ Markdown: https://ryandoser.com/postiz-vs-zernio.md Published: 2026-08-01 | Updated: 2026-09-06 Categories: AI Tool Reviews > Postiz and Zernio both compare themselves to everyone else. The head to head from someone who sells neither, with real pricing. Here is something strange about **Postiz vs Zernio**. Postiz publishes comparison pages against a long list of competitors. Zernio publishes comparison pages against a long list of competitors, and both compare themselves to the same rivals. Neither has written a serious head to head against the other. That is not an accident. These two tools do not really compete for the same buyer, and both companies know it, which makes the comparison awkward to write when your goal is winning a switch. I sell neither one. I have no affiliate relationship with Postiz or Zernio and no business reason to prefer either. So here is the comparison, including the part where the honest answer is "you are asking the wrong question." One conflict to state plainly: [Blotato](https://www.blotato.com/?ref=rdoser) is a client of mine, my account there is comped, and I mention it once near the end because it is what I actually use. Links to it are affiliate links. Everything about Postiz and Zernio below is unaffiliated. My boundary on these two, so you can weigh the rest: I have run Postiz on its hosted cloud plan and I have used Zernio's free tier and dashboard. I have not self-hosted Postiz and I have not run Zernio in production, so where I make a claim about behavior under real load, I tell you whose evidence it is. What I can tell you firsthand is the thing that decides this comparison in practice, which is that these two tools fail in completely different ways. A self-hosted tool fails where you can see it, in your own logs, and you fix it. A managed tool fails silently, and you find out when someone asks why nothing posted on Tuesday. Neither is worse. But one of them costs you attention and the other costs you money, and knowing which currency you would rather pay in resolves this faster than any feature table. ### **Postiz vs Zernio at a Glance** | | Postiz | Zernio | | What it is | Open-source scheduling app | Developer-first publishing API | | Entry price | Free self-hosted, or $29/mo cloud | Free for 2 accounts | | Pricing unit | Channels per plan | Per connected account | | Cost at 5 connections | $29/mo cloud (5 channels) | $18/mo | | Cost at 30 connections | $49/mo cloud | $108/mo | | Self-hostable | Yes, that is the point | No, hosted service | | Platforms | Broad, varies by release | 16 social plus 7 ad networks | | MCP server | Yes | Yes, hosted | | Ad network management | No | Yes | | Generates content | AI assist features in cloud | No, publishing only | Read the "what it is" row before anything else, because it explains every other row. One of these is an application you run. The other is infrastructure you call. ### **They Are Not Actually Competing** The clean way to see this: Postiz has a user interface as its product, and Zernio has an endpoint as its product. [Postiz](https://postiz.com/pricing) is a full scheduling application: calendar, team members, approvals, a place to sit and plan a week of content. You can self-host it free on your own infrastructure or buy cloud plans at $29/month for 5 channels, $39 for 10, $49 for 30, or $99 for 100, all with unlimited posts. [Zernio](https://zernio.com/pricing) is a REST API and a hosted MCP server. Your first 2 accounts are free with no card, then $6/month per account for accounts 3 to 10, $3 for 11 to 100, and $1 past 101. There is no meaningful "using Zernio" experience for a non-developer, because the product is the API. So if you are a marketer who wants to plan and schedule posts, Zernio is not a candidate. If you are a developer wiring publishing into an app or an agent, Postiz's calendar is irrelevant to you. The overlap is a narrow band of technical solo operators who could genuinely go either way, and that band is who the rest of this post is for. ### **Where the Pricing Actually Diverges** The units are different, which makes headline comparison useless. Postiz counts channels per plan tier, and Zernio counts individual connected accounts on a graduated curve. For the wider field, I priced [six Zernio alternatives at 5, 20 and 100 accounts](/zernio-alternatives/). *Zernio is cheaper small, Postiz cheaper at scale. Neither fact should decide it for you.* At 5 connections, Zernio costs $18/month against Postiz cloud at $29. Zernio wins. At 30 connections, Zernio costs $108/month against Postiz cloud at $49. Postiz wins, and it is not close. The crossover sits somewhere around 10 to 12 connections. Below it, per-account pricing is cheaper. If a vendor is billing you per customer profile instead, I ran [the same math across six Ayrshare competitors](/ayrshare-alternatives/) at 1, 10 and 50 accounts. Above it, tiered plans pull ahead and keep pulling ahead. If you are anywhere near that line, count your real connections rather than trusting either company's example numbers. And if you self-host Postiz, the subscription goes to zero and the comparison changes completely, which brings us to the real trade. ### **The Trade Nobody Puts in a Table** Self-hosted Postiz is free in dollars and expensive in attention. You own the platform app approvals, the OAuth token refreshes, the version upgrades, the backups, and the monitoring. The worst failure mode is silent: a post that does not publish and does not tell you. Zernio is the opposite. You own nothing operationally, you pay per account forever, and somebody else gets paged when a platform changes its API. Worth knowing before you pick either: both ship an MCP server, so an agent can drive [Postiz](https://docs.postiz.com/mcp/introduction) or [Zernio](https://docs.zernio.com/mcp) directly. That is no longer a tiebreaker in this category. I went deep on this trade in [my post on the maintenance math](/postiz-alternatives/), because it is the single most underestimated cost in this category. The short version: price your own hour, then decide. ### **Read Both Companies' Comparison Pages Skeptically** Since neither will write this comparison, you will end up reading their pages about other tools. A caution from doing exactly that. Zernio's marketing runs a claim about having 40x faster rate limits than a competitor. I checked it against the documentation and it does not hold up. The figure it divides by does not match the competitor's published limit, and it does not even match the number in Zernio's own FAQ further down the same page. I showed the arithmetic in [my fact-check of that claim](/zernio-review/). That does not make Zernio a bad product. It makes its comparison pages a bad source. The same instruction applies to every vendor page you read on this topic, including this one: check the primary documentation yourself. ### **Which One Should You Pick?** **Pick Postiz if** you want a calendar and a team workflow, you already run infrastructure and self-hosting is nearly free for you, you need more than about a dozen connections, or you want to modify the tool because open source lets you. **Pick Zernio if** you are building software rather than using an app, you want zero operational burden, you have fewer than ten connections, or you need ad network management alongside organic publishing. **Pick neither if** what you actually want is for something to write the posts. Both of these move content you have already created. Postiz has AI assist features in its cloud product, but neither is built as a content generation engine. *The next sentence mentions a tool I have an affiliate relationship with and that is a client. [Full disclosure here](/disclosure/).* That third case is where I landed personally. I run [Blotato](https://www.blotato.com/?ref=rdoser) because I want an agent to write the post, make the image, and publish it in one conversation rather than orchestrating a writing service and a publishing service separately. That is a different job than either tool here is doing, and if it is not your job, it is not a reason to choose it. ### **Ryan's Final Thoughts** The reason neither company wrote this page is that the honest version does not produce a winner. Postiz and Zernio are answers to different questions, and the comparison only gets interesting for the small group of technical operators sitting between them. If you are in that group, the decision comes down to one question: do you want to own a server or a subscription? Everything else is detail. Own the server and Postiz is excellent and effectively free. Own the subscription and Zernio removes an entire category of problem from your life at a price that is fair below ten accounts. What I would not do is let either company's comparison pages make the choice for you. At least one of those pages is running a number that its own documentation contradicts, and that is a good reminder that on this keyword, everybody writing has something to sell. Except, on this one, me. ### **Postiz vs Zernio FAQs** #### **What is the main difference between Postiz and Zernio?** Postiz is a scheduling application with a calendar and team features that you can self-host or buy as cloud software. Zernio is a developer-first REST API and hosted MCP server with no real end-user interface. One is an app you use, the other is infrastructure you call from code. #### **Which is cheaper, Postiz or Zernio?** Below roughly ten connections Zernio is cheaper, at $18/month for 5 accounts against Postiz cloud at $29. Above that Postiz wins clearly: 30 connections costs $49/month on Postiz cloud against $108 on Zernio. Self-hosted Postiz costs nothing in subscription at any scale. #### **Can you self-host Zernio?** No. Zernio is a hosted service only. If self-hosting is a requirement for you, Postiz is the option of these two, since it is open source and designed to run on your own infrastructure. #### **Do both Postiz and Zernio work with AI agents?** Yes, both ship MCP servers that agents like Claude Code and Codex can call. Zernio's is hosted, which means less setup. MCP support is now common across this category, so it does not differentiate them much on its own. #### **Does Postiz or Zernio write content for you?** Neither is built as a content generation tool. Postiz includes AI assist features in its cloud product, and Zernio is explicitly publishing infrastructure that moves content you have already made. If you want posts and images generated, you need a separate tool upstream. #### **Why is there no official Postiz vs Zernio comparison?** Because they mostly serve different buyers. Postiz targets people who want a scheduling app they can control, Zernio targets developers embedding publishing into software. A comparison page works best when both tools are competing for the same switch, and these two usually are not. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine and my account there is comped rather than paid. I have no relationship with Postiz or Zernio and earn nothing if you choose either. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## 8 Best Social Media Automation Tools for Founders (I've Tested These) URL: https://ryandoser.com/social-media-automation-tools/ Markdown: https://ryandoser.com/social-media-automation-tools.md Published: 2026-08-01 | Updated: 2026-09-30 Categories: AI Tool Reviews > The 8 social media automation tools I have actually tested, what each costs as you scale, and the two I stopped recommending after running them. The best **social media automation tools** in 2026 are the ones that survive contact with a real posting schedule, and most of the ones you will read about today have never been tested by the person recommending them. I run this stack as a one-person operation, which is the lens for everything below. If you are a founder or a solo marketer doing your own posting between the actual job, you are the person I picked these for. I post to six platforms every week off one long-form YouTube video, using the [AI social media system](/ai-social-media-system/) I built for my own accounts. Everything below is running in that stack right now or ran in it long enough for me to form an opinion worth reading. ### **Why Most Social Media Automation Tool Lists Are Worthless** Look at who publishes the top results for this term. Buffer ranks for it. Blaze ranks for it. Gumloop ranks for it, and its own list opens with Gumloop at number one. Every one of those pages is a vendor explaining why the vendor wins. I have a conflict of my own and I would rather say it upfront than have you find it. Blotato is a client of mine, and my account is comped rather than paid. So take my Blotato pick with that in mind, read the two paragraphs where I explain what its interface gets wrong, and judge whether I am being straight with you. The more useful thing I can offer is the stuff I decided against. I left the biggest names in this category off the list because I have not run them, and I still pay a human editor for a job the category leader claims to automate. Those calls tell you more about what these tools do than a features table ever will. I took the same approach with the [best AI automation tools](/best-ai-automation-tools/), where the two top-ranking lists both happened to be published by tools in the ranking. ### **Social Media Automation Tools at a Glance** Eight tools, split into the two jobs they actually do. The first four publish your posts. The second four are the layer that feeds them, and they are the reason my stack runs without me. Affiliate links are marked in the disclosure at the end. **Publishing and scheduling** | Tool | Best for | Starts at | Billing unit | Free plan | | **[Blotato](https://www.blotato.com/?ref=rdoser)** | Posting to many accounts from an AI agent | $29/mo | Flat, 20 accounts included | No, 7-day trial | | **[Buffer](https://buffer.com/)** | A clean calendar and a free plan that works | Free, then $6/mo per channel | Per channel | Yes, 3 channels | | **[Metricool](https://metricool.com/)** | Analytics and competitor tracking on a budget | Free, then 16 euros/mo billed monthly | Per brand | Yes, no LinkedIn or X | | **[Hootsuite](https://www.hootsuite.com/)** | Teams that need approvals and one shared inbox | $99/user/mo billed annually | Per seat | No, 14-day trial | **The automation layer underneath** | Tool | Best for | Starts at | Billing unit | Free plan | | **[Claude Code](https://www.claude.com/product/claude-code)** | Writing captions in your own voice from your own files | $17/mo billed annually | Per user | No | | **[Make](https://www.make.com/en)** | Visual workflows that fire on a trigger | $12/mo | Credits per module action | Yes, 1,000 credits | | **[n8n](https://n8n.io/)** | High volume, or client data that cannot leave the server | Free self-hosted, or 20 euros/mo cloud | Per workflow execution | Free self-hosted | | **[Opus Clip](https://www.opus.pro/?via=aitips)** | Turning one long video into short clips | Free, then $15/mo | 150 processing minutes/mo | Yes, 60 minutes | ### **The 4 Tools I Publish Through** These four are the first half of the eight, and they are the ones that actually put a post on a platform. Every one is running in my stack now or ran in it long enough for me to have an opinion. I did not pad the list to ten with software I have never opened. #### **1. Blotato (Best for posting to many accounts from an AI agent)** *Blotato positions itself as a posting API for AI agents rather than a dashboard you log into.* [**Blotato**](https://www.blotato.com/?ref=rdoser) is the tool the rest of my stack posts through. I do not open it to write anything. Claude Code writes the captions, then hands them to Blotato over MCP, and Blotato pushes them to nine platforms on a schedule. Now the part a vendor list will not tell you. Judged purely as a web app, it is the weakest thing on this page. The calendar is cluttered. Scanning a full week across four platforms takes more clicking than it should. If all you want is a dashboard to schedule posts in, Buffer is the nicer product, and I have said exactly that to my own community. I put the two side by side in [Blotato vs Buffer](/blotato-vs-buffer/) if you are deciding between them. What earns it the top spot is the layer underneath. Twenty connected accounts for a flat $29 with no seat fees, and a hosted MCP endpoint that Claude Code, Cursor, and ChatGPT can drive directly. **Pros:** - Flat $29 for 20 accounts, so the bill does not move when you add profiles - Hosted MCP server plus verified [n8n](https://n8n.io/integrations/blotato/) and [Make](https://www.make.com/en/integrations/blotato) nodes - Lets you pick the underlying model instead of hiding it - Ran a four-platform automation for me on the first try with no errors **Cons:** - The calendar and scheduling UI genuinely lag Buffer and Hootsuite - Heavy image and video generation eats the 1,250 monthly credits fast - Analytics are thin next to Metricool or Sprout - The 7-day trial excludes API access, which is the reason most people want it **Best for:** Solo creators and small agencies running posting through an agent or an automation platform. **Pricing:** Starter $29/mo, Creator $97/mo, Agency $499/mo. Annual saves about 17 percent. **Free trial:** 7 days, card required. **Bottom line:** Buy it for the API and MCP layer, not for the dashboard. Here is the whole thing running end to end, before you spend anything. I broke the setup down step by step in my guide to building an [AI social media manager with Claude Code](/claude-code-social-media/). #### **2. Buffer (Best free plan and the cleanest calendar)** *Buffer connects to every major platform and is still the cleanest scheduling interface in the category.* [Buffer](https://buffer.com/) is the tool I point people to when they tell me they just want to schedule posts and stop thinking about it. The calendar is legitimately better than what I use daily, and the free plan covers three channels without asking for a card. Buffer has an [official MCP server](https://developers.buffer.com/guides/integrations/mcp.html) too, so an agent can drive it directly. Worth saying plainly, because a lot of posts imply otherwise: MCP is not a differentiator anymore. Buffer has one, [Metricool](https://metricool.com/metricool-mcp-claude/) has one, [Hootsuite](https://www.hootsuite.com/integrations/mcp) has one. What still separates them is how the bill scales, not whether an agent can connect, which is the same lens I used when I broke down [what each server costs once you connect it](/mcp-servers-for-marketers/). If you have never set one up, I walked through [connecting MCPs to Claude Code](/claude-code-mcps/) step by step. The pricing model is where it breaks down for me. Buffer charges per channel, so the bill grows every time you add a profile. At my six accounts that is around $30 a month on Essentials billed annually, or $36 month to month, which is fine. Run an agency with twenty client profiles and you are into three figures for the same scheduling I get on a flat $29. **Pros:** - Genuinely free tier, three channels, no card required - Best calendar and scheduling interface in this roundup - Official MCP server documented for developers - Channels past the tenth are discounted **Cons:** - Per-channel pricing punishes anyone running many accounts - Free plan caps you at 10 scheduled posts per channel **Best for:** Creators on a handful of channels who want a calendar they enjoy using. **Pricing:** Free for 3 channels. Essentials $5/mo per channel, or $60 per channel billed yearly. Team $10/mo per channel. **Free trial:** Yes, 14 days on paid plans, and the free tier never expires. **Bottom line:** The best pure scheduler here. Do the per-channel math before you scale past ten profiles. #### **3. Metricool (Best analytics for the money)** *Metricool combines scheduling, analytics, and competitor tracking in one view.* [Metricool](https://metricool.com/) is on this list for the half of the job the other tools do badly. Publishing is easy. Knowing which posts worked is the part that changes what you post next. I learned that the hard way on my own Shorts. Looking back across roughly 500 of them, the top third pulled a median of about 1,100 views and the bottom third around 458. The pattern only showed up because I went and looked, and no scheduler was ever going to tell me. The competitor tracking is the part I would pay for. Five competitor profiles on the free plan beats what most paid tools include. One catch worth knowing before you sign up expecting a free ride. LinkedIn and X are not connectable on the free plan. If you are a B2B creator, the free tier is close to useless and you are looking at the paid plan from day one. **Pros:** - Free plan includes analytics and 5 competitor profiles - Official MCP server that works on any plan, including the free one - Best analytics per dollar in this roundup - Scheduling and reporting live in the same view **Cons:** - LinkedIn and X are excluded from the free plan - The REST API is locked to the Advanced tier, though the MCP works on any plan - Priced in EUR, and the tier you need depends on your brand count **Best for:** Creators and small agencies who want to know what is working, not just what shipped. **Pricing:** Free plan available. Starter from 16 euros/mo and Advanced from 43 euros/mo on monthly billing. Metricool tiers scale by how many brands you manage, so check the toggle for your brand count before comparing it to anything else here. **Free trial:** The free plan is the entry point. **Bottom line:** Pair it with whatever you post through. If that pairing is the decision you are actually weighing, I put the two head to head in [Blotato vs Metricool](/blotato-vs-metricool/). #### **4. Hootsuite (Best for teams with approval chains)** *Hootsuite remains the default for teams that need approvals and a shared inbox.* [Hootsuite](https://www.hootsuite.com/) is the default answer for people who have never shopped this category, and for a solo creator it is the wrong one. At $99 per user per month billed annually, a single seat costs more per year than my entire posting stack. It stays on the list because seats are exactly the point when more than one person touches the account. Approval workflows, a shared inbox, and role permissions are things creator-priced tools mostly do not have, and an agency running client accounts genuinely needs them. Its calendar is also better laid out than most, which I will give it even though I am not the buyer. **Pros:** - Approvals, permissions, and a shared inbox built for teams - Clean, scannable calendar - 14-day trial with no card required - Mature analytics and listening **Cons:** - $99/user/mo billed annually, with no month-to-month price published - Entry plan caps you at 10 social accounts - Trial imposes daily posting limits and blocks bulk scheduling **Best for:** Teams and agencies where more than one person publishes. **Pricing:** Standard $99/user/mo billed annually. Professional $199, Advanced $399. **Free trial:** Yes, 14 days, no card required. **Bottom line:** Right for teams. Solo creators should skip it. ### **The Other 4: The Automation Layer Nobody Puts on These Lists** Every roundup for this term lists schedulers and stops. That is the part I think they get wrong, because a scheduler only solves the last step. It publishes whatever you hand it, and if what you hand it is generic, you have automated the production of content nobody reads. These four are not scheduling tools and I am not ranking them as such. They are what sits upstream in my stack: one writes the captions, two fire the workflow, one cuts the video. If you only take one idea from this post, take this one, because it is the difference between posting more and posting better. #### **Claude Code (Writes the captions)** *Claude Code runs in the terminal and reads your local files, which is what makes the captions sound like you.* Nobody else puts a coding tool on a social media list. It belongs here because caption quality is the whole game, and every scheduler on this page writes captions from nothing. I went further on that in a ranking of [which AI agents can publish without you](/ai-agent-for-content-creation/). It is the one tool I would not swap out, and it shows up in almost everything I build, including my roundup of the [best AI tools for content creators](/best-ai-tools-for-content-creators/). Claude Code reads my actual files. My brand voice document, my past posts, the transcript of the video I am repurposing. That context is the difference between a post that sounds like me and the generic output you get from a caption button inside a scheduler. The real limit is that it is non-deterministic. It reasons its way to an answer, so the same prompt can produce different results. I would not point it at anything where a wrong output is expensive. **Pros:** - Reads your own files, so the voice is yours instead of a model's average - Connects to Blotato and other tools over MCP with no glue code - Replaces several single-purpose subscriptions at once - Handles the messy middle steps like transcribing and pulling frames **Cons:** - Non-deterministic, so it is a poor fit for correctness-critical jobs - Steep learning curve if you have never touched a terminal - Burns usage limits quickly on long batch jobs **Best for:** Anyone whose posts underperform because the copy sounds like AI wrote it. **Pricing:** Included with Claude Pro at $17/mo billed annually, or $20/mo billed monthly. Max plans start at $100/mo. **Free trial:** No. The free Claude tier does not include Claude Code. **Bottom line:** The captions are the bottleneck, not the scheduling. This is the tool that fixes the captions. On long batch runs, switch to Sonnet and set effort to low with /effort. Thinking can't be turned off on Sonnet 5.5, so effort is the dial, and on caption work it burns far less usage. #### **Make (Fires the workflow)** *Make builds automations visually, which is why non-developers get further with it than with code.* [Make](https://www.make.com/en) is what I reach for when posting needs to fire off an event rather than a prompt. New video hits a Drive folder, workflow wakes up, content gets generated and scheduled. No one types anything. The trap is the credit model. Every module action burns a credit, including triggers and filters, so a workflow that looks cheap on paper gets expensive at volume. Build error branches from the first version. One of my infographic workflows fetched an image before Blotato had finished rendering it, the fetch step failed, and because I had no error path the whole scenario sat dead until I noticed. The fix was a 90-second wait module. The lesson was that a stalled automation looks exactly like a working one until you go looking. **Pros:** - Visual canvas that non-developers can actually reason about - Deep integration library including a Blotato app maintained by the vendor - Free plan with 1,000 credits a month and no time limit - Cheaper than Zapier at comparable volume **Cons:** - Every module action costs a credit, including triggers and filters - Free plan enforces a 15-minute minimum between runs - Errors halt future runs unless you build error handling yourself **Best for:** Event-driven posting workflows built by someone who does not want to write code. **Pricing:** Free at 1,000 credits/mo. Core starts around $12/mo, with Pro and Teams above it. Check the monthly and annual toggle, the two rates differ. **Free trial:** The free plan runs indefinitely. **Bottom line:** The right pick for scheduled and triggered posting. Watch the credit math as volume grows. #### **n8n (Same job, cheaper at volume)** *n8n bills per workflow execution and can be self-hosted, which changes the math at volume.* [n8n](https://n8n.io/) earns its place on one pricing detail. It charges per workflow execution, not per step. A fifty-step social workflow costs one execution, where the same thing on a per-task tool costs fifty. The other reason I keep it around is client work. When a client's data cannot leave their own servers, self-hosting is the only answer, and n8n is the one tool here that offers it. It is also the steepest to learn. For most people posting to their own accounts, Make is the better starting point. **Pros:** - Per-execution billing, so multi-step workflows stay cheap - Self-hosting available at no license cost - Unlimited active workflows on every paid tier - Verified Blotato node maintained by a partner **Cons:** - Steepest learning curve of anything on this list - Starter keeps only 7 days of execution history - Self-hosting means you own the maintenance - Priced in EUR, which moves the real cost for US buyers **Best for:** High-volume posting and any client whose data has to stay put. **Pricing:** Free self-hosted. Cloud Starter 20 euros/mo billed annually, Pro 50 euros/mo, Business 667 euros/mo. **Free trial:** Yes, and Starter and Pro trials need no card. **Bottom line:** Start on Make and move here when the credit bill stops making sense. #### **Opus Clip (Cuts the video, if you have no editor)** *Opus Clip converts one long video into short vertical clips and can publish them straight out.* [**Opus Clip**](https://www.opus.pro/?via=aitips) sits at number four because of a decision I made against it, which is a more useful data point than another glowing paragraph. I tested it, and I still ship my long-form video to a human editor instead. The b-roll choices, the transitions, the sense of where a clip should actually start and stop, those are the things it has not matched yet in my testing. My shorts do better with a person cutting them. Since October 2026, Claude Code cuts my long-form podcast episodes, and the shorts are the part my editor still owns. The [four places AI editing still broke](/ai-video-editing/) explain why. If you do not have an editor and are not going to hire one, this is the fastest path from one long video to ten posts. It is the same job I now do with [Claude Code to repurpose YouTube videos](/claude-code-repurpose-youtube-videos/), just with less control over the cut. The free tier is enough to judge it. Feed it a 60-minute podcast and you will get usable clips out. Expect to reject most of them and keep the few that land. **Pros:** - Free tier with 60 processing minutes a month - Turns one long video into a week of short-form in minutes - Auto-captions and reframing are solid out of the box - Publishes directly to social platforms **Cons:** - A human editor still beats it on b-roll, transitions, and clip selection - Most generated clips get discarded, so plan on a review pass - Free exports carry a watermark and expire after 3 days - Starter caps AI b-roll at 3 clips a month **Best for:** Creators producing long-form video with no editor and no budget for one. **Pricing:** Free at 60 processing minutes/mo. Starter $15/mo for 150 minutes. Pro $29/mo for 300 minutes, or 3,600 minutes on an annual Pro plan. **Free trial:** No trial as such. The free tier is the trial. **Bottom line:** The right call when the alternative is no clips at all. If the output never quite lands, I ran through the competing clippers in [the competing clipping tools](/opus-clip-alternatives/). ### **How to Choose Social Media Automation Tools** These are the questions I run on every client build before anything gets bought. **How does the bill scale?** Per channel, per seat, per task, or flat. This decides your cost in a year more than the sticker price does. **Where do the captions come from?** If the tool writes them from nothing, they will sound like nothing. Something in your stack has to hold your voice. **What happens when a run fails?** Silent failures are worse than loud ones. Know how you find out. **Can it reach the platforms you actually post to?** Check the specific ones. Free tiers routinely exclude LinkedIn and X. **Are you replacing a person or a tab?** Replacing a tab is realistic. Replacing judgment is not. **What is the exit cost?** Scheduled posts, templates, and analytics history rarely export cleanly. ### **The Thing Nobody Tells You About Posting Through an API** TikTok appears to penalize API-posted content. I have noticed a reach hit on posts pushed through an API versus the same clip uploaded by hand in the app. It does not seem to matter which tool does the pushing. Blotato, Hootsuite, anything. Worth saying that the wider version of this claim does not hold up well. I went looking for the evidence behind it in my [Repurpose.io review](/repurpose-io-review/) and found the sourcing much thinner than its popularity suggests. If you are shopping that category specifically, I compared [what the cheaper cross-posting tools actually cost](/repurpose-io-alternatives/) at different brand counts. I cannot tell you why, and I am not going to pretend I ran a controlled test. This is a pattern I noticed on my own accounts, not something TikTok has confirmed or that I have measured properly. Treat it as a thing to check on your account before you automate that channel away. On every other platform I post to, I have not seen the same gap. ### **Which One Should You Actually Pick?** **Just want to schedule posts?** Buffer, free tier. **Posting the same thing to six platforms?** Read [the reach cost of identical cross-posting](/post-to-all-social-media-at-once/) before you automate it. **Running 10 or more accounts?** Blotato, for the flat rate. **Your posts sound like AI wrote them?** Claude Code, from the layer section above. **Have long videos and no editor?** Opus Clip, though read why I still pay an editor. It now runs from an agent too, which I cover in my [OpusClip MCP tutorial](/opusclip-mcp/). **More than one person publishing?** Hootsuite. **Need to know what is working?** [Metricool](/blotato-vs-metricool/) alongside any of the above. ### **Buffer Alternatives, Ranked by Why You Are Leaving** Buffer is the tool most people on this page are already paying for, so it is worth answering the question directly. Nearly every Buffer alternatives list you will find ranks the same eleven tools in a slightly different order without asking the only question that matters, which is why you are leaving in the first place. There are really only three reasons, and they point at different tools. **You are leaving because of the per-channel bill.** This is the common one. [Buffer's Essentials plan](https://buffer.com/pricing) is $5 per channel per month billed annually, or $60 per channel per year. Six channels is around $30 a month, which is genuinely fine. Twenty channels is not, and that is the wall agencies hit. A flat-rate tool is the fix, which is where [Blotato](https://www.blotato.com/?ref=rdoser) at $29 for 20 accounts comes in, or [Metricool](https://metricool.com/) if you would rather pay per brand than per channel. **You are leaving because you want an agent to do the posting.** Buffer actually handles this fine now. It ships an [official MCP server](https://developers.buffer.com/guides/integrations/mcp.html), so if this is your only complaint, you may not need to leave at all. Switch only if the channel math is also against you. **You are leaving because you want to own the software.** Then you want [Postiz](https://postiz.com/), which is open source and self-hostable. I compared it against my own stack in [Postiz vs Blotato](/postiz-vs-blotato/). Be honest with yourself about the trade, though. You are swapping a subscription for server maintenance, and that bill gets paid in evenings. Two tools show up on every competing list that I deliberately have not ranked here. [Publer](https://publer.com/pricing) and [SocialBee](https://socialbee.com/pricing/) both get recommended constantly, and Google's own AI Overview for this term names Publer first. I have not run either on a real posting schedule, so I am not going to tell you how they feel to use. Publer is the one I would trial first if the flat-rate options above do not fit, and SocialBee is the pick if category-based evergreen recycling is the specific thing you want. One last thing worth saying, since almost nobody selling you a Buffer alternative will. Buffer's free plan is real. Three channels, ten scheduled posts per channel, no card. If you are under three channels, the correct Buffer alternative is Buffer. ### **What About Sprout Social, Agorapulse, Later, and SocialBee?** They are missing on purpose, and they are missing from a list where almost every competing article includes them. [Sprout Social](https://sproutsocial.com/pricing/) shows up on nearly every roundup for this term. [Agorapulse](https://www.agorapulse.com/pricing/), [SocialBee](https://socialbee.com/pricing/), [Later](https://later.com/pricing/), and [Sendible](https://www.sendible.com/pricing) are close behind. I have not run any of them on a real posting schedule, so ranking them would make this the same kind of list I complained about at the top. What I can tell you is where I would look first. Sprout Social is the one to shortlist if you outgrow this list and have the budget. Its entry tier is Essentials at $79 per seat per month billed annually, which is well below the $199 figure a lot of roundups still quote, though listening and premium analytics are paid add-ons that push the real number up. Sendible and Agorapulse are the two that come up most for agencies managing client accounts, and SocialBee gets recommended constantly for evergreen category-based queues. Take those as pointers for your own shortlist, not as recommendations from me. ### **Ryan's Final Thoughts** Picking off this list is the easy part. I have watched people wire up flawless automations that publish content nobody reads, and volume without a point of view is just [expensive AI slop](/avoid-ai-slop/). The habit matters more than the stack, which is why I record takes on a walk and let the system handle the rest. That workflow is how I [post consistently without a content calendar](/post-consistently-with-ai/). So buy the cheapest thing that reaches your platforms and get the plumbing out of the way. The tools here will carry your opinion to nine platforms on a schedule. Not one of them will supply the opinion. Developers comparing publishing APIs rather than dashboards should start with my breakdown of [Ayrshare alternatives and what they really cost](/ayrshare-alternatives/). ### **Going Deeper on Any One Piece** This list is the shortlist. If you have already picked a tool, the rest of my writing on this covers the three things that decide whether it works: what it bills you, what you feed it, and what you hear back. Cost comes first, because the API-first version of this decision is a different list entirely and the billing units do not compare to dashboard pricing. [Ten social media APIs priced on five different billing units](/social-media-api/) works the cost out at 5 and 50 accounts, and [why per-task billing punishes social posting specifically](/best-zapier-alternatives/) is why I moved my own posting off Zapier. Zernio is the tool readers ask me about most that did not make the list above, so it gets its own treatment. [The review fact-checks its headline 40x rate limit claim](/zernio-review/), which does not survive the math. [Six alternatives priced at 5, 20 and 100 connected accounts](/zernio-alternatives/) is the one to read if you are on per-account billing, because that curve stops being a bargain at a specific point. [Postiz vs Zernio](/postiz-vs-zernio/) is the head to head from someone who sells neither. [Blaze AI](/blaze-ai-review/) is the other one people ask about, and the number to know before you shortlist it is that it now starts at $79 a month rather than the $34 still quoted around the web. The review covers the autopilot rebuild, the 2026 tiers and where the credit limits actually bite. Scheduling is the solved half. Supply is the part that actually breaks. [Turning one idea into a week of content in your own voice](/ai-content-engine/) is the repurposing system I run, built on a voice file instead of a prompt, which is what stops the output reading like every other AI post in the feed. Then there is the half nobody automates, which is hearing what gets said back. [Alertmouse](/alertmouse-review/) is the brand mention tracker I landed on after Google Alerts stopped catching things, and the review covers its real pricing and the annual-billing catch. This matters more than it used to, because the pages other people write about you are the ones AI answers tend to quote. ### **Social Media Automation Tools FAQs** #### **What is the best social media automation tool for one person?** For a solo creator posting to a handful of accounts, start on Buffer's free tier and stop there until it hurts. Three channels, no card. The moment you pass roughly ten connected accounts, per-channel billing stops making sense and a flat rate wins, which is where Blotato takes over at $29 a month for 20 accounts. I broke the pricing down against its closest competitors in my [full Blotato review](/blotato-review/). Buy the cheap thing first. You can always move. #### **Can I automate social media posting for free?** Partly. Buffer's free plan covers three channels, Metricool has a free tier, and n8n is open source and free if you self-host it. [Postiz is the open-source scheduler in this category](/postiz-vs-blotato/), though self-hosting trades the subscription for maintenance time. What you cannot get for free is the whole chain at volume. Free plans cap channels, and the self-hosted route trades the subscription for your own time maintaining it. Free is real for one or two platforms and gets expensive in hours past that. #### **Do these tools need an API or coding knowledge?** The scheduling tools do not. Buffer, Hootsuite, Metricool, and Blotato all work from a normal dashboard with nothing technical involved. If Metricool is the one you are leaving, I priced [eight replacements at two different account counts](/metricool-alternatives/) separately. Make, n8n, and the Claude Code workflow are a different category, and that is where the real leverage is. Make is the gentlest entry point of the three because it is visual. Also worth knowing before you plan around it: Blotato's 7-day trial excludes API access, so generating an API key starts the paid subscription. #### **Is AI-generated social content penalized by the platforms?** Not for being AI-generated as such. The penalty is for being boring, and generic AI output is reliably boring. My own Shorts data across 498 videos backs this up: the top third averaged around 1,100 median views against 458 for the bottom third, and the gap tracked how specific the idea was rather than how it was produced. Automate the distribution. Do not automate the point of view. #### **What is the best Buffer alternative in 2026?** It depends on why you are leaving Buffer, and most lists skip that question. If the per-channel bill is the problem, a flat-rate tool fixes it, and Blotato at $29 for 20 accounts is where I landed. If you want to self-host and own the software, Postiz is the open-source option, and I priced [what it actually costs to run against the hosted options](/postiz-alternatives/) separately. If you want an agent to drive the posting, Buffer already ships an official MCP server, so you may not need to switch at all. And if you are running three channels or fewer, Buffer's free plan is genuinely hard to beat. #### **What is MCP, and does it matter when picking a tool?** MCP lets an AI assistant like Claude talk directly to a tool, so you can draft and schedule without touching a dashboard. It mattered as a differentiator for about a year. It does not now. Buffer, Metricool, and Hootsuite all ship official MCP servers alongside Blotato, so treat MCP as table stakes and pick on price, platform coverage, and whether the interface annoys you. *Disclosure: some links in this post are affiliate links, specifically Blotato and Opus Clip. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine and my account there is comped rather than paid. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## Zernio Review: A Fact Check of Its Biggest Marketing Claim URL: https://ryandoser.com/zernio-review/ Markdown: https://ryandoser.com/zernio-review.md Published: 2026-08-01 | Updated: 2026-09-30 Categories: AI Tool Reviews > An independent Zernio review. Real pricing math, what the API does well, and why its headline 40x rate limit claim does not survive a fact check. **Zernio** is a developer-first social media API and hosted MCP server that publishes, schedules, and pulls analytics across 16 social platforms and 7 ad networks. This **Zernio review** covers what it genuinely does well, who it is built for, and one marketing claim of theirs I could not make add up. Set my credentials correctly before you weigh any of it. I signed up, connected the free accounts and went through the dashboard and the docs. **I have not run Zernio in production.** So this is a pricing, documentation and positioning review from someone who runs a competing tool every day, not a six-month field report. Where I make a claim about how it behaves under real load, I will tell you whose evidence that is. Let me be upfront about my position before you read another sentence. I use [Blotato](https://www.blotato.com/?ref=rdoser) as my daily driver, it is a client of mine, my account there is comped rather than paid, and some links below are affiliate links. You should read everything that follows with that in mind. I am telling you this at the top rather than the bottom because the whole point of this post is checking a claim against documentation. It would be strange to ask you to verify Zernio's math while hiding my own conflicts until the footer. Here is the short version. Zernio is a decent tool for social media automation. The free tier is genuinely generous, the API is clean, and the platform coverage is broader than Blotato's. Where it lost me was managing social media through an MCP with AI agents like Claude Code and Codex, which is how I actually work. I will show you the specifics. It is worth being precise about what that phrase means, because "has an MCP server" has stopped being a useful signal. Nearly everything in this category ships one now, including Zernio, so the checkbox tells you almost nothing. What I care about is narrower. When I ask an agent to publish something, how many separate services does that one sentence have to touch before a post exists? Zernio delivers. It does not create. So the agent still needs somewhere to write the copy and something to make the image, and I am back to stitching services together in a conversation that should have been one instruction. That is a preference, not a defect, and if you already have generation solved it is not a reason to avoid Zernio at all. But it is the specific thing that kept me from switching, and it is more useful to you than another paragraph about response times. ### **What Zernio Actually Is** Zernio positions itself as "a developer-first REST API and hosted MCP server that lets apps and AI agents post, schedule, and analyze content across 16 social platforms plus 7 ad networks." Read that again, because the important word is *infrastructure*. Zernio does not write your posts. It does not make your images. It is a pipe, and a well-built one. You bring the content, it handles the messy business of talking to fifteen different platform APIs so you never have to apply for TikTok developer access yourself. That is a real problem worth solving. Anyone who has tried to get approved for a platform API directly knows the process is genuinely miserable. #### **The Late and GetLate Rebrand** If you researched this category more than a few months ago you probably met this product under a different name. [Zernio's own rebrand page](https://zernio.com/rebrand) confirms it: Late is now Zernio, same API, same team, same `/api/v1` endpoints, no breaking changes. This matters when you are researching. Plenty of third-party pages about this product still file it under the old name. [Capterra](https://www.capterra.com/p/10036198/Late/) and [Software Advice](https://www.softwareadvice.com/product/537327-Late/) both still host their Zernio listings at `/Late/` URLs. If a review seems oddly stale, check whether it was written pre-rebrand. ### **Zernio Pricing Is the Best Thing About It** I want to lead with praise here because it is deserved, and because a review that only criticizes a competitor is not a review, it is an ad. [Zernio's pricing](https://zernio.com/pricing) is one of the more honest structures I have seen in this category. Your first 2 accounts are free with no credit card. After that it is graduated per account: $6/month each for accounts 3 through 10, $3/month each for 11 through 100, and $1/month each past 101. No plans, no seats, no feature gating. Every capability is available on every account. That last part is rarer than it sounds. Most tools in this space put the API behind a higher tier, or lock analytics behind Business. Zernio does not do that, and I respect it. If you are a developer with two accounts who wants to test a real publishing API without a credit card, Zernio's free tier is the easiest on-ramp I found while researching this category. That is not a backhanded compliment, it is the strongest thing about the product and you should take advantage of it. #### **Where the Per-Account Math Turns** The graduated model is elegant at small scale and expensive at large scale. That is just arithmetic, not a criticism. I priced that curve against six competitors at 5, 20 and 100 accounts in [my Zernio alternatives breakdown](/zernio-alternatives/). | Connected accounts | Zernio monthly cost | | 2 | $0 | | 5 | $18 | | 10 | $48 | | 20 | $78 | | 50 | $168 | So the decision rule is simple. Under about 8 accounts, Zernio's per-account pricing beats most flat-rate competitors outright. Past roughly 10 accounts, a flat plan starts winning and the gap widens fast. The same crossover logic decides whether [Ayrshare's $149 single-profile entry price](/ayrshare-alternatives/) is absurd or reasonable, which comes down entirely to who you are publishing for. If you want the full head-to-head on that crossover point, I broke the pricing down against the tool I use in my [Blotato review](/blotato-review/), including the exact account counts where each one wins. ### **The 40x Faster Claim Does Not Hold Up** Now the part that made me want to write this post. Zernio runs a comparison page arguing you should switch from Blotato, and its headline number is that Zernio has "40x faster rate limits than Blotato." The phrase also shows up in their search snippets, so it is the first thing a lot of people read about both tools. I went to verify it, expecting to confirm it and move on. It does not survive contact with the documentation. Here is how they get to 40x. Their page states "Zernio: 60 req/min on free tier. Blotato: 1.5 posts/min." Sixty divided by 1.5 is forty. The arithmetic is fine. The input is not. *Three sources, one page. The claim and its own correction sit a few scrolls apart.* ![Zernio comparison page claiming 40x faster rate limits than Blotato, captured 1 August 2026](/images/2026/08/zernio-review-40x-claim.jpg) I am screenshotting this because a marketing page can change. Claim verified live on **1 August 2026**, and archived at the [Wayback Machine](https://web.archive.org/web/20260802001012/https://zernio.com/alternatives/blotato) so you can check it yourself even if the page is edited later. If Zernio corrects it, good, and this paragraph is why you will still be able to tell what it said today. [Blotato's own API documentation](https://help.blotato.com/api/llm) puts `POST /posts` at **30 requests per minute**. I confirmed that figure in two separate places in their docs, including the error reference. Not 1.5. Thirty. Sixty against thirty is 2x. Not 40x. To be fair to Zernio on the underlying point, its rate limits do climb with the tier, up to 1,200 requests per minute at the top end, so a paying customer gets considerably more headroom than 2x. That is a legitimate advantage and they could have simply said so. But the comparison they published comes from their free tier, and 40x is not the number that falls out of it on any reading. Here is the detail that convinced me this was worth writing about: **further down that same page, Zernio's own FAQ says "Blotato caps at 30 posts/min globally, regardless of plan."** Their comparison table above it lists 1.5. So the correct figure and the one that produces the 40x headline both appear on a single page, a few scrolls apart. So where does 1.5 come from? I genuinely do not know, and I am not going to invent a theory to fill the gap. It does not appear in Blotato's documentation, and Zernio does not show its work. The same page separately claims Blotato's Starter plan caps you at 3 unique TikTok accounts per 24 hours, which would be a platform-level posting restriction rather than an API throughput number, but I could not verify that limit in Blotato's docs either. What I can say with confidence is narrower and still damning: the number Zernio divides by does not match the documented figure, and it does not match the figure in Zernio's own table. I am not going to tell you Zernio is a bad tool because of this. It is not. But when a company's central marketing claim is off by a factor of twenty against a number printed in its own table, that tells you something about how carefully to read the rest of the comparison. Check the vendor's actual docs, every time. That habit has saved me more than once. ### **Why It Did Not Replace What I Run** *Heads up: the next section links to a tool I have an affiliate relationship with. [Full disclosure here](/disclosure/).* My honest summary after working through the product and its docs is that Zernio is a decent tool for social media automation. If your job is "move media I already made to fifteen platforms," it is built for that and it is cheap at low account counts. Where it did not fit was the specific way I work. I manage social media through an MCP with AI agents, mostly Claude Code and Codex, and on that dimension [Blotato](https://www.blotato.com/?ref=rdoser) does more of the job. My agent does not just need somewhere to send a finished post. It needs to generate the post, make the image, and publish it, all inside one conversation without me opening a dashboard. Zernio is publishing infrastructure by design. Their own page says so plainly, and I think that focus is a legitimate product decision rather than a gap. But it means an agent workflow built on Zernio needs a content generation layer bolted on upstream, which is one more service, one more key, and one more thing to debug at 11pm. I wrote up how that agent setup actually works in my guide to [running social media from Claude Code](/claude-code-social-media/), if you want to see the workflow rather than take my word for it. #### **Pick Zernio If** You are a developer with a handful of accounts who already has content generation solved. You want a clean REST API and a free on-ramp with no card. You publish to Telegram, Discord, WhatsApp, Snapchat or Google Business, none of which Blotato reaches. Or you need ad network management alongside organic publishing, which Blotato does not do at all. #### **Skip Zernio If** You want the tool to write the post and make the visual, not just deliver it. You are running more than 10 accounts and want the bill to stop moving. Or you want one MCP surface where an agent handles creation and publishing in a single conversation. ### **What Real Zernio Users Say** My experience is one data point from someone with an obvious bias, so weigh the independent signals too. On [Trustpilot](https://www.trustpilot.com/review/zernio.com) Zernio rates well, at 4.8 out of 5 across 191 reviews. The praise concentrates on customer service and responsiveness. I cannot vouch for that from long use, but it is consistent across enough reviews to be worth something. The picture is less flattering elsewhere, though the sample sizes are tiny enough that I would not weight them heavily. [Software Advice](https://www.softwareadvice.com/product/537327-Late/) shows a single 1.0 review calling it an "interesting concept, not the best user experience" and flagging pricing. [Capterra](https://www.capterra.com/p/10036198/Late/) also carries a lone 1-star rating. One review is an anecdote, not a pattern. On [Product Hunt](https://www.producthunt.com/products/zernio) the feedback is positive and specifically mentions the MCP responding reliably, which lines up with my testing. The connection itself was not the problem for me. #### **A Note on the Platform Count** One thing to watch if you are comparing spec sheets. Zernio's homepage currently says 16 social platforms. [Capterra](https://www.capterra.com/p/10036198/Late/) says 14+, and several roundups say 15. Those directory pages may simply reflect older coverage rather than a different count today. Trust the vendor's current page over any roundup, including this one by the time you read it. Then verify the two or three platforms you actually need rather than the headline count, because "16 platforms" means nothing if the one you care about is the missing one. ### **Ryan's Final Thoughts** Zernio is a good product with a marketing problem. The free tier is real, the graduated pricing is honest, the API is clean, and the team is responsive. If I were building a SaaS that needed to publish on behalf of users, it would be on my shortlist, and the two free accounts make testing it cost nothing but an afternoon. What I cannot get past is that its loudest claim about a competitor is off by a factor of twenty, with the correct number sitting in its own FAQ a few scrolls below. Good products do not need that. The pricing argument alone is strong enough to stand on. For my own work I stayed with Blotato, because I run everything through an MCP and I want creation and publishing behind one surface. Your workflow may weigh that differently, and if you already have content generation solved, the calculus genuinely changes. Whichever way you go, verify the claim before you believe it. That is the actual lesson here, and it applies to my posts as much as theirs. ### **Zernio Review FAQs** #### **What is Zernio?** Zernio is a developer-first social media API and hosted MCP server that lets applications and AI agents publish, schedule, and analyze content across 16 social platforms and 7 ad networks, a count worth re-checking on their site (see the platform-count note above). It is publishing infrastructure rather than a content creation tool, so it moves content you have already made. #### **Is Zernio the same as Late or GetLate?** Yes. Late rebranded to Zernio, and its rebrand page confirms the API, endpoints, and response schemas did not change. Existing integrations kept working. Some directory sites still list it under the old name. #### **Does Zernio have a free plan?** Yes, and it is genuinely useful. Your first 2 connected accounts are free with no credit card required, and every feature including full API access is available on those accounts. For testing a real publishing API without committing a card, it is hard to beat. #### **How much does Zernio cost?** Pricing is graduated per connected account after the first 2 free ones: $6/month each for accounts 3 through 10, $3/month each for 11 through 100, and $1/month each past 101. Five accounts costs $18/month and twenty costs $78/month. #### **Is Zernio really 40x faster than Blotato?** The claim does not hold up as written. It divides Zernio's 60 requests per minute by a figure of 1.5 posts per minute for Blotato, but Blotato's API documentation lists 30 requests per minute for publishing, and Zernio's own comparison table on that same page also lists 30. Comparing the two documented publish limits gives roughly 2x, not 40x. #### **Does Zernio work with Claude Code?** Yes. Zernio ships a hosted MCP server, so Claude Code, Codex, and other MCP-capable agents can call it directly. In my testing the connection worked reliably. The limitation is that Zernio does not generate content, so your agent still needs a separate writing and image layer. #### **Which platforms does Zernio support that Blotato does not?** Zernio covers Telegram, Discord, WhatsApp, Snapchat, and Google Business, which Blotato does not reach. It also manages ad networks alongside organic publishing. Blotato covers 9 platforms and adds AI writing, image, and video generation that Zernio does not offer at all. #### **Should I use Zernio or Blotato?** Use Zernio if you are a developer with under 10 accounts, already have content generation handled, and need its broader platform list or ad network support. Use Blotato if you want one MCP surface where an AI agent writes the post, makes the visual, and publishes it, or if you run enough accounts that flat pricing wins. *Disclosure: some links in this post are affiliate links, specifically Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine and my account there is comped rather than paid. I have no relationship with Zernio. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## 10 Best AI YouTube Channels to Follow in 2026 (Avoid Hype) URL: https://ryandoser.com/ai-youtube-channels/ Markdown: https://ryandoser.com/ai-youtube-channels.md Published: 2026-07-31 | Updated: 2026-08-31 Categories: AI Resources > Most AI YouTubers are hype grifters. These 10 channels teach practical AI skills you can apply the same day you watch. Finding the right **AI YouTube channels** can save you months of trial and error when learning how to apply artificial intelligence to your business or career. ### **Why Most AI YouTubers Are Wasting Your Time** Here is something nobody wants to say out loud. Most AI YouTubers are what I call "hype grifters." Every new model update is INSANE. Every tool release will CHANGE EVERYTHING. Every AI feature is going to REPLACE YOUR JOB TOMORROW. These creators are playing the YouTube game. Their goal is not to teach you anything useful. Their goal is to get as many eyeballs as possible by scaring you, confusing you, and keeping you glued to the screen. The thumbnails are [designed to trigger panic](/ai-anxiety/). The titles are built for clicks, not clarity. Consuming this type of content is actually hurting you. You walk away more confused than when you started. You jump from tool to tool without mastering any of them. You spend hours watching videos that give you zero actionable takeaways. I made a full video breaking down this problem and how to spot the difference between hype channels and channels that actually teach you something. The 10 channels below are the opposite of hype grifters. I selected every one of them because they are practical, anti-hype, and focused on real-world results. You will walk away from their videos with something you can apply immediately. ### **Why Quality AI Channels Matter More Than Ever in 2026** The timing here is not an accident. On July 16, 2026, YouTube clarified its monetization rules to crack down on mass-produced "AI slop," according to [TechCrunch](https://techcrunch.com/2026/07/20/youtube-clarifies-policies-around-ai-slop-and-upsetting-videos/). Channels with too much generic, repetitive, or template-based content can lose the ability to monetize. That fits Aaron Makelky's rule for AI video: use it as the salt and pepper on real footage of a real person. Here is [how he and I use AI B-roll](/ai-video-editing/). Read the fine print and the message is clear. YouTube did not ban AI. It targeted content farms that use AI as an industrial substitute for real creative work. Human-led channels that use AI to teach something real still monetize just fine. That is the whole point of this list. The creators below use AI to add value, not to flood your feed. As the low-effort channels get cleaned out, the practical, human-led ones are exactly where you want to spend your watch time. ### **Best AI YouTube Channels in 2026** Most "best AI channels" lists recommend the same technical, research-heavy creators. Those are fine if you want to study neural network architecture. But if you want to actually use AI to grow a business, create content, or automate your workflow, you need a different kind of channel. I put together this list based on channels I personally watch, learn from, or collaborate with. Every creator here teaches practical AI skills you can apply the same day you watch their video. Subscriber counts below were checked against each live channel page, because most roundups in this category are quoting numbers from a year ago. #### **1. Sabrina Ramonov** *Sabrina Ramonov's YouTube channel covers AI prompts, playbooks, and agent systems for business owners.* [Sabrina Ramonov](https://www.youtube.com/@sabrina_ramonov) is one of the most recognized AI educators on the internet right now, with 3M+ followers across platforms and 347K subscribers on YouTube. Her channel focuses on AI prompts, agent systems, and automation workflows built specifically for solopreneurs and business owners. Sabrina studied Computer Science and Physics at UC Berkeley and co-founded an NLP startup that was acquired by Pegasystems in 2021, so her tutorials come from real technical depth without feeling overly academic. #### **2. Ryan Doser** *My YouTube channel shares AI tips, reviews, and proven marketing systems.* [Ryan Doser](https://www.youtube.com/@RyanDoserAI) is the channel to watch if you are a marketer who wants to build AI systems without learning to code, with 39.4K subscribers and over 1,000 videos covering Claude Code workflows, content repurposing across every platform, and honest tool reviews. This is my channel, so weigh that accordingly. Every build I publish is one I run in my own marketing business, which is also why I show the parts that break rather than only the demo that worked. If you want to go deeper on AI marketing, I put together a guide with my full toolkit and workflows. **[Grab my free AI Marketing Guide here.](https://guide.ryandoser.com/)** #### **3. Grace Leung** *Grace Leung's YouTube channel breaks down AI tools for digital marketers and consultants.* [Grace Leung](https://www.youtube.com/@graceleungyl) brings over a decade of digital marketing experience across APAC and North American markets to her AI content. Her channel breaks down tools like ChatGPT, Claude, Gemini, and Perplexity with real marketing workflows and side-by-side comparisons. Grace teaches from the perspective of a working [digital marketing consultant](/ai-marketing-stack/), which means her tutorials always connect back to actual business outcomes. #### **4. Mark Kashef** *Mark Kashef's YouTube channel teaches AI agents and practical automation for businesses.* [Mark Kashef](https://www.youtube.com/@Mark_Kashef) is the founder of Prompt Advisers and has trained over 700 professionals on AI implementation. His channel specializes in building AI agents, multi-step prompting, and automating repetitive business tasks. Mark holds a Master's in AI with a focus on Natural Language Processing, and his 3.5M+ views on YouTube prove that his practical, no-hype teaching style connects with people who want results over theory. #### **5. Authority Hacker** *Authority Hacker's YouTube channel covers SEO, AI marketing, and online business strategy.* [Authority Hacker](https://www.youtube.com/@AuthorityHackerPodcast) is run by Gael Breton and Mark Webster, whose podcast has been downloaded over 3.5 million times across 120+ countries. Their YouTube channel covers the intersection of AI, SEO, and building profitable online businesses. If you want to understand how AI is reshaping content marketing, affiliate sites, and search rankings, Authority Hacker gives you the week-by-week playbook from two operators who test everything themselves. #### **6. Corbin Brown** *Corbin Brown's YouTube channel focuses on AI coding tutorials and building with AI tools.* [Corbin Brown](https://www.youtube.com/@Corbin_Brown) has built a following of over 180K subscribers with deep tutorials on AI coding and automation tools. His channel bridges the gap between "I want to build with AI" and "I don't know where to start coding." Corbin's step-by-step approach using tools like Claude and Cursor AI makes complex AI development feel approachable for builders at every level. #### **7. Matt Wolfe** *Matt Wolfe's YouTube channel covers the latest AI news, tool reviews, and industry trends.* [Matt Wolfe](https://www.youtube.com/@mreflow) created [FutureTools.io](https://www.futuretools.io/) and hosts The Next Wave Podcast, making him one of the go-to voices for AI news and tool discovery. His channel is closing in on 1M subscribers. His channel covers new AI releases, tool comparisons, and industry trends with a content volume that few creators match. If you need to stay current on what tools are launching and which ones actually matter, Matt's weekly breakdowns are worth adding to your rotation. For the same reason, the [best AI newsletters](/best-ai-newsletters/) deserve a spot in your inbox. #### **8. Nate Herk** *Nate Herk's YouTube channel teaches AI automation workflows and building an AI business.* [Nate Herk](https://www.youtube.com/@nateherk) went from his first YouTube video to more than 870K subscribers in under three years, which tells you something about the demand for his content. He left Goldman Sachs to focus on AI automation full-time and now teaches n8n workflows, [AI agent building](/ai-for-small-businesses/), and how to turn automation skills into a real income stream. Nate's tutorials are perfect if you want to learn AI automation from someone who built a business around it as a non-coder. #### **9. Jack Roberts** *Jack Roberts' YouTube channel covers AI automation and no-code agent building for businesses.* [Jack Roberts](https://www.youtube.com/@Itssssss_Jack) is a top-100 UK entrepreneur who built a 7-figure AI automation business after selling his startup Glaido to over 60,000 customers. His channel covers no-code AI agent systems, appointment scheduling automation, and practical business workflows. Jack's content stands out because he shows the business model behind the automation, not just how to connect two tools together. #### **10. Nathan Gotch** *Nathan Gotch's YouTube channel focuses on AI SEO and AI search strategy.* [Nathan Gotch](https://www.youtube.com/@nathangotch) has built a 127K subscriber channel focused almost entirely on SEO and AI search strategy. He founded Gotch SEO Academy (now Search OS), trained over 3,000 clients, and generated millions in revenue selling SEO services in competitive niches like local, SaaS, and ecommerce. If you want to understand how AI is changing search rankings and how to adapt your content strategy for both Google and AI-powered search engines, Nathan's channel is the one to watch. ### **Honorable Mentions** These AI YouTubers also produce solid content worth checking out. They did not make the top 10, but each brings a unique angle to AI education. #### **AI Luke** *AI Luke's YouTube channel teaches AI coding and building with tools like Claude Code.* [AI Luke](https://www.youtube.com/@ai-luke) runs a daily upload channel with over 100K subscribers focused on AI coding and building with tools like Claude Code and other AI platforms. His channel is perfect for people who want to build alongside someone in real time. The sheer volume of tutorials means you can find a walkthrough for almost any AI coding scenario. #### **Brooke Wright** *Brooke Wright's WrightMode YouTube channel teaches AI strategy for women founders and small businesses.* [Brooke Wright](https://www.youtube.com/@WrightMode) runs the WrightMode channel, where she teaches women founders and neurodivergent entrepreneurs how to scale with AI and automation. She earned over $100K in her first six months of AI consulting with zero formal tech training, and her tutorials reflect that self-taught, practical perspective. #### **Solomon Christ** *Solomon Christ's YouTube channel covers AI, machine learning, and life automation.* [Solomon Christ](https://www.youtube.com/@SolomonChristAI) is a game and software developer who creates content at the intersection of AI, machine learning, and life automation. His channel explores how AI can automate tedious tasks so you can focus on higher-level creative and strategic work. Solomon also runs a podcast and newsletter covering the same topics. #### **The AI Automators** *The AI Automators YouTube channel covers practical AI automation workflows and tools.* [The AI Automators](https://www.youtube.com/@TheAIAutomators) produce focused tutorials on practical AI automation workflows and tool integrations. Their content skips the hype and jumps straight into building real systems. If you want no-nonsense automation walkthroughs without 10 minutes of preamble, this channel delivers. #### **Corey Ganim** *Corey Ganim's YouTube channel simplifies AI for non-technical entrepreneurs.* [Corey Ganim](https://www.youtube.com/@coreyganim) built a $16M+ e-commerce business and now teaches non-technical entrepreneurs how to put AI to work. His "Build With AI" podcast brings on operators who share their screen and build real automations live. Corey's angle is unique because he approaches AI from the perspective of someone running a real product business, not just teaching about tools. He broke down his [two-call Claude coaching offer, prices included](/how-to-start-an-ai-business/), when he came on my podcast. ### **Ryan's Final Thoughts** The best AI YouTube channels are the ones that match where you are right now. If you need marketing-focused AI, start with channels 1 through 5 on this list. If automation and agent building is your priority, channels 6 through 10 will get you there faster. Subscribe to two or three that fit your goals and actually watch the tutorials. Passive consumption does not build AI skills. Applying what you learn does. Video is one channel. If you want the same filtering applied to your inbox and to the rooms where people answer questions, I keep parallel lists of the [best AI newsletters](/best-ai-newsletters/) and the [best AI communities](/best-ai-communities/). I also ranked several of these same people by [what they publish away from YouTube](/ai-content-creators-to-follow/), which sorts them differently. ### **AI YouTube Channels FAQs** #### **What are the best YouTube channels to learn AI for marketing?** Sabrina Ramonov, Ryan Doser, Grace Leung, and Authority Hacker all focus on AI applied to marketing, content creation, and business growth. Each channel takes a different angle, from prompting and agents to SEO and affiliate marketing, so picking two or three gives you a well-rounded foundation. #### **Are AI YouTube channels better than paid AI courses?** For practical, up-to-date AI skills, YouTube channels often outperform paid courses because the content stays current. Paid courses recorded six months ago may already reference outdated tools or deprecated features. The channels on this list publish weekly, which means you learn what works right now. #### **How do I pick the right AI YouTube channel for my skill level?** Start with channels that match your use case, not your technical level. Nate Herk and Jack Roberts focus on no-code automation. Corbin Brown covers more technical builds. Matt Wolfe gives high-level tool overviews. Watch one video from each and see which teaching style clicks with how you learn. #### **What AI topics do these YouTube channels cover?** This list spans AI marketing, AI agents, workflow automation, AI coding, tool reviews, SEO, content creation, and AI consulting. Some channels go deep on one area. Others cover the full spectrum of AI applications for business owners and creators. #### **What AI YouTube channels should content creators follow?** Content creators get the most from channels that show a full publishing pipeline rather than isolated tool demos. On Ryan Doser I cover turning one video into content across every platform, which is the specific problem most creators hit once they are publishing consistently. Pair that with a discovery channel so you hear about new tools early, and an automation channel so you can wire the pipeline together without hiring anyone. #### **Did YouTube ban AI YouTube channels in 2026?** No. On July 16, 2026, YouTube clarified its monetization rules to crack down on mass-produced "AI slop," meaning generic, repetitive, or template-based content. It did not ban AI itself. Human-led channels that use AI to teach real skills, like the ones on this list, remain fully eligible for monetization. --- ## Best AI Marketing Tools in 2026 (After Testing 100+ Tools) URL: https://ryandoser.com/best-ai-marketing-tools/ Markdown: https://ryandoser.com/best-ai-marketing-tools.md Published: 2026-07-31 | Updated: 2026-08-31 Categories: AI Tool Reviews > I tested 100+ AI marketing tools and now pay for six. Here is what survived once coding agents absorbed the rest of the stack. After testing more than 100 AI tools throughout my life, my list of the **best AI marketing tools** has shrunk a lot. Six tools now do the work that used to take fifteen. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* ### **My Best AI Marketing Tools in 2026** Five months ago my paid stack was bloated. ChatGPT Plus, Claude Pro, Gemini Advanced, Perplexity Pro, Opus Clip, HeyGen, ElevenLabs, plus another half-dozen single-purpose tools. Most of them got used once a week at best. The reason for the cut is simple. AI coding agents like Claude Code and Codex now handle the writing, design, image generation, and automation work that used to require separate point tools. So the question is no longer "which tool does X." It is "what do I still pay for once a coding agent can do most of it." Here is the short list that survived, with every price re-checked against the live pricing pages. Free where it makes sense, paid where it earns the spot. ### **1. Claude Code** Claude Code is Anthropic's [agentic coding tool](https://code.claude.com/docs/en/overview), and it is the single AI product I use more than anything else. It runs locally, reads my files, and lets me build skills as Markdown files I reuse forever. I do not use it for code in the traditional sense. I use it for SEO audits, blog writing, social posts, keyword research, email drafts, image generation through APIs, and landing page design for clients. One interface, one set of skill files, no copy-paste between tabs. Those files are the whole trick, and I've listed [the ten that do the most work](/best-claude-marketing-skills/). *Claude Code's overview page, the agentic coding tool I use most for marketing work.* The honest catch is the price. The $20 Claude Pro plan gives you decent web-app usage, but to actually live inside Claude Code you need the $100 Max plan. Worth it if you use it daily. Overkill if you do not. **A client landing page I built end-to-end inside Claude Code using a web design skill file.** New to this workflow? I wrote a deeper breakdown of [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) with real examples. ### **2. Codex (via ChatGPT Plus)** I pay $20 a month for ChatGPT Plus, but almost none of that usage is on chatgpt.com. It is for [Codex](https://openai.com/codex/), OpenAI's coding agent. *OpenAI's Codex landing page, the coding agent that ships with ChatGPT Plus.* Codex has improved a lot, especially since GPT-5.6 landed in July 2026 and became the default across ChatGPT, Codex, and the API. I lean on it for image generation through GPT Image 2, technical troubleshooting, and research tasks where I want a second opinion on whatever Claude Code just produced. The pricing math is interesting. For $20 a month, Codex gives me more usage than the $100 Claude Max plan in a typical week. So I started with Codex as insurance against Claude outages. Now I run both agents side by side in VS Code. They can compare outputs on the same task, which is genuinely useful when you are not sure which one nailed it. ### **3. Blotato** [Blotato](https://www.blotato.com/?ref=rdoser) is the AI marketing tool I use every single day. Not because it has a calendar (Buffer and Hootsuite have those too), but because it natively connects to Claude Code, n8n, and Make.com through MCP. *Blotato's homepage, the social platform I run through Claude Code via MCP.* That connection is the entire point. I have Claude Code analyze my media files, generate captions tuned to each platform, and schedule everything to Blotato in one pass. Posts show up on the calendar already queued weeks out. No manual paste-and-tweak loop. Pricing starts at $29 a month with a 7-day trial. One caveat worth knowing if you are here for the MCP angle: the trial covers the app but not the API, so generating an API key starts the paid subscription. Cheaper than Buffer or Hootsuite once you are past about five accounts, and the integration story is the only reason it is on this list. ### **4. Google AI Pro** I will be honest. [Google AI Pro](https://gemini.google/subscriptions/) at $19.99 a month is on this list mostly for the storage. I get 5 TB shared across Drive, Gmail, and Photos, which matters when you are dumping raw 4K MP4 files for YouTube every week. *Google AI Pro's subscription page, mostly worth it for the 5 TB of storage.* I rarely open Gemini directly. The model is fine, but Claude Code and Codex cover that work for me already. So treat this as a hybrid pick: a Gemini subscription you use for everything-but-Gemini. Skip it if you do not produce video content at scale. ### **5. OpenRouter** [OpenRouter](https://openrouter.ai) is not a marketing tool in the normal sense. It is the layer that sits between you and [every major AI model](/best-ai-models-for-marketing/): Anthropic, OpenAI, Google, xAI, DeepSeek, Mistral, plus image and video models from each provider. *OpenRouter's homepage, one API key that covers every major model provider.* You generate one API key. That key works across every model. So instead of juggling separate API keys for Anthropic, OpenAI, and Google (which is a security headache), you point Claude Code, n8n, or Make.com at OpenRouter and use any model from one place. *OpenRouter's model directory, which I route through one API key for use inside Claude Code and Codex.* This is a quiet but huge upgrade if you build automations. My short video creator script switches between Seedance and Veo with no extra setup, and the same key powers GPT Image 2 calls inside Claude Code. Scaling AI workflows? This is the missing piece I see most marketers overlook. ### **6. VoiceInk** [VoiceInk](https://tryvoiceink.com) is my voice-to-text tool, and it is a one-time lifetime license rather than another subscription. Tiers start under $50 and are priced by how many devices you want it on. Check the current number before you buy, because they announced a price change taking effect August 1, 2026. *VoiceInk's homepage, my voice-to-text tool with a one-time lifetime license instead of a subscription.* I trigger it with a hotkey, brain-dump three paragraphs into Claude Code, and let the agent take it from there. That is faster than typing and less mentally taxing than holding a full prompt in my head before I write it. The catch is that the desktop app is macOS-only, though an iOS version now exists. Wispr Flow is the cross-device alternative at $15 per user per month, which is the right pick if you split work across Mac and Windows. For a Mac-first solo operator, VoiceInk is hard to beat. ### **Ryan's Final Thoughts** The pattern is consolidation. Two coding agents (Claude Code and Codex), one social media platform that integrates with them (Blotato), one model router (OpenRouter), one voice input (VoiceInk), and one storage subscription that came along for the ride (Google AI Pro). Six tools instead of fifteen. Faster outputs, fewer tabs, lower total cost. If you want to see how the agents fit together in practice, my [full AI marketing stack walkthrough](/ai-marketing-stack/) shows the day-to-day. ### **Best AI Marketing Tools FAQs** #### **What are the best AI marketing tools to start with in 2026?** Starting fresh? Pick one coding agent first. Claude Code or Codex. That single tool replaces five or six standalone AI products once you build a few skill files. Add a social scheduler that integrates with it (Blotato) and a model router (OpenRouter) once you start automating. Voice-to-text and storage are personal preference. #### **How much should I spend on AI marketing tools per month?** A working stack runs a little under $170 a month: $100 Claude Max, $20 ChatGPT Plus, $29 Blotato, and $19.99 Google AI Pro, plus a one-time lifetime license for VoiceInk. If you are weighing that Blotato line item, [here is where it wins and where it does not](/blotato-review/). OpenRouter is pay-as-you-go API usage on top. You can cut that in half by dropping to Claude Pro at $20 and skipping Google AI Pro when you do not need the storage. #### **Are AI coding agents really useful for non-technical marketers?** Yes, and that is the part most people miss. I am not a developer. I use Claude Code for SEO content, social posts, image generation, and client landing pages. The skill Markdown files do the heavy lifting. You write a workflow once, then reuse it. [My Claude Code AI marketing agents post](/claude-code-ai-marketing-agents/) shows how non-technical users get started. #### **Why did you drop tools like Perplexity Pro, HeyGen, and Opus Clip?** Each one became redundant once I had Claude Code and Codex. Research that once needed Perplexity now happens through web fetch tools inside the agent. Short video editing runs through API calls to OpenRouter video models. The AI tools I dropped were not bad. They were just one-trick products competing with agents that do the same thing plus ten others. Opus Clip is the one I later went back to, and I explain what changed my mind in my [roundup of clipping tools and what they cost](/opus-clip-alternatives/). #### **Should I use ChatGPT or Claude as my main AI marketing tool?** I use both, but Claude is my daily driver for marketing copy and content. Claude tends to follow brand voice better and produces less generic output on the first try. ChatGPT wins on real-time data and image generation. Pick the one that matches your most common task. Deciding between them? [Here is the full breakdown](/switch-from-chatgpt-to-claude/). --- ## 10 Best AI Newsletters to Read in 2026 (Ranked by an Expert) URL: https://ryandoser.com/best-ai-newsletters/ Markdown: https://ryandoser.com/best-ai-newsletters.md Published: 2026-07-31 | Updated: 2026-08-27 Categories: AI Resources > The best AI newsletters for marketers, ranked by one filter: does reading it make you better at your job, or just better informed? The **best AI newsletters** for marketers save you hours every week by filtering the AI firehose down to what actually helps you sell, rank, and grow. I subscribe to dozens of them. Most are noise. ### **Why Most AI Newsletters Waste Your Time** There are thousands of AI newsletters now. Nearly all of them cover the same five headlines from the same week. That is a problem if you are a marketer. You do not need another recap of a model release you already saw on X. You need to know what it changes about your content, your SEO, and your funnel. So I built this list around one filter: does reading it make you a better marketer, not just a more informed spectator? A few picks here are broad AI news for baseline literacy. The rest are written by operators who actually run marketing businesses. Consuming AI content is not the same as getting ahead. The newsletters below are the ones I read to close that gap. *Consuming AI content is not the same as getting ahead, which is exactly why the newsletter you pick matters.* I break down this whole idea in my AI marketing video, embedded below. ### **The Best AI Newsletters in 2026** I ranked these by how directly they help a marketer, not by raw subscriber count. Every pick is free to join. I use each one myself. | # | Newsletter | Best for | Cadence | | 1 | Ryan Doser (AI Insider Tips) | Copy-paste AI marketing workflows | Weekly | | 2 | Sabrina Ramonov | Creators and solo founders | Weekly | | 3 | Authority Hacker | SEO and authority sites | Weekly | | 4 | The Rundown AI | Daily AI news literacy | Daily | | 5 | TLDR AI | Technical daily brief | Daily | | 6 | This Week in AI | Marketing-native decisions | Weekly | | 7 | Growth Memo (Kevin Indig) | Senior SEO and growth | Weekly | | 8 | Superhuman AI | Tool discovery for operators | Daily | | 9 | Future Social | Social media strategy | Weekly | | 10 | The Neuron | Light daily brief for business | Daily | #### **1. Ryan Doser (Free)** *The AI Insider Tips signup page, my free weekly AI marketing newsletter.* This is my newsletter, so I will keep it honest. I write it for one type of reader: the marketer or founder who wants AI workflows they can copy the same day, not headlines. Each issue shares the actual systems I use to run a six-figure agency and grow my YouTube channel, from AI SEO to content scaling to personal branding. If you want the exact playbooks behind everything on this site, [you can join AI Insider Tips free here](https://guide.ryandoser.com/). It leans practical and marketing-first, which is the gap I could not fill with anyone else's list. #### **2. Sabrina Ramonov** *Sabrina Ramonov's newsletter subscribe page.* Sabrina Ramonov runs one of the sharpest AI newsletters for creators and solo founders, with over 258,000 subscribers per her page. She is a former startup founder who sold her AI company, Qurious, to Pegasystems, and now builds in public while teaching AI prompts, agents, and automations. Her [Substack](https://www.sabrina.dev/) skews toward hands-on AI systems for small teams, which makes it a strong read if you run lean and want to automate the boring parts of marketing. #### **3. Authority Hacker** *The Authority Hacker homepage, run by Gael Breton and Mark Webster.* Gael Breton and Mark Webster have run [Authority Hacker](https://www.authorityhacker.com/) since 2014, and they sold a real agency before teaching this stuff. Their emails focus on SEO, authority sites, and using AI to build online businesses that actually make money. The tone is refreshingly no-hype. If your marketing lives and dies by organic traffic, this belongs in your inbox. #### **4. The Rundown AI** *The Rundown AI, a daily AI news email with over 2 million readers.* Rowan Cheung grew [The Rundown AI](https://www.therundown.ai/) into the largest AI newsletter, with over 2 million readers on the page. This one is broad AI news rather than marketing-specific, so I include it for baseline literacy. It keeps you current on model releases and tools in five minutes a day, which frees your attention for the marketing-focused reads on this list. Skim it, do not study it. #### **5. TLDR AI** *TLDR AI delivers AI news in a five-minute daily email to 1.1 million readers.* [TLDR AI](https://tldr.tech/ai) is part of the TLDR newsletter network and lists 1,100,000 readers on its signup page. It leans more technical, so the audience is engineers and researchers as much as marketers. I keep it for the same reason as The Rundown: a fast, credible daily pulse on where AI is heading. If you already read one big daily AI brief, you probably do not need this too. #### **6. This Week in AI (Marketing AI Institute)** *This Week in AI from Marketing AI Institute, used by 40,000+ marketers.* If you want the single most marketing-native pick here, this is it. This Week in AI comes from the Marketing AI Institute, founded by Paul Roetzer, and the page states it reaches 40,000+ marketers and business leaders. Every issue is written for people who have to turn AI news into a marketing decision, paired with one of the category's best podcasts. It is weekly, so it respects your time. #### **7. Growth Memo (Kevin Indig)** *Growth Memo by Kevin Indig, a research-heavy SEO and growth read for senior marketers.* Kevin Indig led SEO and growth at companies like Atlassian, G2, and Shopify, and his newsletter shows that pedigree. Growth Memo delivers research-backed breakdowns of SEO, organic growth, and AI-driven search, aimed at senior marketers. Indig has publicly noted crossing 25,000 subscribers, and third-party trackers put it near 28,000. This is the one I read when I want depth on how AI is reshaping search, not a surface-level take. It pairs well with anything you are doing on [AI-driven SEO](/ai-seo-system/). #### **8. Superhuman AI (Zain Kahn)** *The Superhuman AI newsletter by Zain Kahn, read by over 1.5 million people.* Zain Kahn built [Superhuman AI](https://www.superhuman.ai/) into one of the largest daily AI newsletters, with over 1.5 million readers listed on its signup page. It is written for operators and creators, not researchers, so the tools and tactics tend to be things you can apply. The daily cadence is a lot, but each issue is a three-minute skim. Use it for tool discovery and quick wins. #### **9. Future Social (Jack Appleby)** *Future Social by Jack Appleby, covering social media strategy and honest case studies.* Jack Appleby writes [Future Social](https://futuresocial.beehiiv.com/), and it fills the lane most AI newsletters ignore: social media strategy. He breaks down real brand campaigns and platform shifts with honest takes, increasingly through an AI lens. If your job touches organic social or content, this is the read that keeps your creative sharp while everyone else chases the next tool. It is the most social-marketing-focused pick on this list. #### **10. The Neuron** *The Neuron, a daily AI newsletter read by over 700,000 professionals.* [The Neuron](https://www.theneuron.ai/) is a daily AI brief for business professionals, with 700,000+ subscribers listed on the page. It reads lighter and more applied than the research-heavy dailies, so a marketer can skim it without glazing over. Think of it as a friendlier alternative to the big technical briefs. Pick this or The Rundown, you do not need both daily emails. *The real edge in an AI era is trust, and the right newsletters help you build it faster.* ### **How to Actually Use These Newsletters** Do not subscribe to all ten and drown. Pick one daily brief for literacy, then one or two marketing-first reads for depth. Batch them. I read newsletters in one 20-minute block, not scattered across the day. Anything with a real tactic gets saved to a swipe file I pull from when I write or build. The goal is not to know more. It is to ship better marketing because of what you read. If a newsletter never changes what you do, cut it. ### **Ryan's Final Thoughts** The best AI newsletters are the ones that turn AI news into action you can take this week. Start with one daily brief for baseline literacy, add a marketing-first read like This Week in AI or Growth Memo, and cut anything that never changes your work. If you want the exact AI systems I use, that is what I share every week in my own newsletter. For more curated picks, see my guides to the [best AI communities](/best-ai-communities/), the [best AI YouTube channels](/ai-youtube-channels/), the [best AI marketing podcasts](/best-ai-marketing-podcasts/), and the [AI creators publishing the most useful work right now](/ai-content-creators-to-follow/). ### **Best AI Newsletters FAQs** #### **What is the best AI newsletter for marketers?** This Week in AI from the Marketing AI Institute is the most marketing-native pick on this list, because every issue is written for people who have to turn AI news into a marketing decision. Growth Memo by Kevin Indig is the better choice if your work centers on SEO and organic growth. If you want copy-paste AI workflows rather than news, that is the gap my own newsletter fills. #### **How many AI newsletters should I subscribe to?** Two or three. Pick one daily brief for baseline literacy, such as The Rundown AI or The Neuron, then add one or two marketing-first weekly reads for depth. Subscribing to all ten guarantees you skim everything and apply nothing. The test is simple: if a newsletter has never changed what you actually do, cut it. #### **Are AI newsletters free?** Every newsletter on this list is free to join. Some operators offer paid tiers with deeper research or community access, but the core email costs nothing in all ten cases. That is why the real cost of a bad subscription is attention, not money. #### **What is the largest AI newsletter?** The Rundown AI is the largest, with over 2,000,000 readers listed on its signup page. Superhuman AI lists over 1.5 million and TLDR AI lists 1,100,000. Size is a poor proxy for usefulness to a marketer though, since the biggest newsletters are broad AI news rather than marketing-specific. #### **Are AI newsletters still worth reading in 2026?** Yes, but for a narrower reason than in 2024. Raw AI news is now a commodity you can get from any chatbot on demand. What a good newsletter still provides is a filter run by an operator with judgment, someone deciding what matters and what to ignore. Read them for the editorial judgment, not the headlines. #### **What is the difference between an AI newsletter and just asking ChatGPT for AI news?** A chatbot answers the question you already knew to ask. A newsletter tells you about the thing you did not know existed, which is the entire value. Ask an assistant for "this week in AI" and you get a summary weighted toward whatever was most written about. A good operator-run newsletter is a judgment filter instead: someone who ships marketing work decided this one release changes your workflow and these nine do not. Use the chatbot for lookup, the newsletter for discovery. --- ## 10 Best AI Tools for Content Creators in 2026 (No AI Slop) URL: https://ryandoser.com/best-ai-tools-for-content-creators/ Markdown: https://ryandoser.com/best-ai-tools-for-content-creators.md Published: 2026-07-31 | Updated: 2026-08-31 Categories: AI Tool Reviews > The AI tools that let one creator produce what used to take a team. Repurposing, video editing, voiceovers, and images, with honest limits on each. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* The problem is that "AI tool" now describes everything from a grammar checker to a full video production suite. Most roundups dump 20 tools on you without telling you what any of them actually do well or where they fall short. This list is different. I tested and researched each of these tools specifically for creators: YouTubers, bloggers, solopreneurs, and marketers building audiences online. Every price below was re-checked against the live pricing pages, because tool pricing in this category moves constantly and most roundups never go back to fix it. Here is what made the cut. ### **10 Best AI Tools for Content Creators in 2026** These tools cover the full content workflow: from repurposing and scheduling to video editing, voiceovers, and image generation. Each one earns its spot on this list for a specific reason. #### **1. Blotato** *Blotato turns a single topic into a full week of social content in minutes.* Blotato is the first tool I point creators to when they tell me content distribution is killing them. Drop in a topic, and it generates a full week of platform-specific posts: captions, hooks, images, and short-form video from a single input. Over 10,000 business owners use it, and founder Sabrina Ramonov grew more than 3 million followers across platforms without spending a dollar on ads. That is a real proof point. The scheduling and repurposing stack lives in one dashboard. You are not stitching together three tools to get from idea to published post. API access makes it useful for anyone who wants to automate their posting workflow entirely. Pricing starts at $29 a month for the Starter plan, with a 7-day trial that requires a card. One limit worth knowing before you sign up: the trial covers the app but not the API, and generating an API key ends the trial and starts the paid plan. [Try Blotato free for 7 days](https://www.blotato.com/?ref=rdoser) and check out my full [Blotato review](/blotato-review/) for the complete breakdown. #### **2. Poppy AI** *Poppy AI helps content creators and marketers produce viral content with AI.* Poppy AI is built for creators who want viral-style content without the trial and error. It sits at the intersection of AI writing and visual content, helping marketers move from raw idea to polished post faster than a manual workflow allows. The platform is aimed at founders and content teams who need volume without sacrificing output quality. The speed advantage comes from keeping everything in one place. You are not bouncing between a generator, an editor, and a scheduler. It works best for social media content. It is less suited for long-form blog writing or video editing. My full [Poppy AI review](/poppy-ai-review/) covers the workflow in detail. [Check out Poppy AI](https://getpoppy.ai/) #### **3. Blaze AI** *Blaze AI positions itself as an AI marketing platform that handles content strategy and creation.* Blaze AI calls itself an AI marketing platform with "taste, power, and speed." Bold positioning, but the 4.8 out of 5 rating across 724 Capterra reviews suggests the market agrees. Blaze handles social content, blog drafts, video scripts, and newsletters, all trained on your brand voice so output sounds consistent rather than generic. Where Blaze separates itself from raw AI writing tools is the strategy layer. It does not just generate content. It helps you think about what to create and why. That is a meaningful difference for solopreneurs who do not have a content director. Pricing follows a fractional agency model, so you will need to check their site for current tiers. See my full [Blaze AI review](/blaze-ai-review/) for a side-by-side look at what it can and cannot do. [Start a free trial of Blaze AI](https://blaze.ai?fpr=rtcxca) #### **4. Opus Clip** *Opus Clip turns one long video into 10 viral short clips automatically.* Opus Clip handles what most creators dread: turning long-form video into short-form content. Feed it a YouTube video, a podcast recording, or a webinar, and it identifies the best moments, adds captions, formats for vertical, and delivers clips ready to publish. More than 16 million creators and businesses use it, including Grant Cardone and brands like NVIDIA. The free tier gives you 60 minutes of processing per month. That is enough to test the clip quality before committing to a paid plan. Paid plans start at $15 a month for Starter, with Pro at $29. The main limitation is the monthly quota. Heavy video producers will hit it and need to upgrade. For anyone producing long-form content who wants short-form clips without manual editing, this is the most direct path. [Try Opus Clip free](https://www.opus.pro/) #### **5. ElevenLabs** *ElevenLabs offers a library of 10,000+ studio-quality AI voices for creators and developers.* ElevenLabs is the benchmark for AI voice. The voice library runs into the thousands across 70+ languages, and the output sounds human in a way earlier text-to-speech tools never achieved. Epic Games, Meta, and Spotify use it at the enterprise level. For independent creators, it means professional voiceovers without a studio session or a freelance budget. The Creator plan at $22 per month unlocks instant voice cloning and 121,000 credits per month. That covers regular YouTube intros, podcast narration, or course content without running out mid-month. The free tier is worth trying just to hear the quality gap between ElevenLabs and cheaper alternatives. Pricing scales with character volume at higher tiers, so plan accordingly if you are generating content at scale. [Try ElevenLabs free](https://elevenlabs.io/) #### **6. Descript** *Descript lets you edit video and audio by editing the transcript text directly.* Descript changes how video editing works. You edit a transcript instead of a timeline. Delete a sentence from the text and that segment disappears from the video. That one feature makes the whole process accessible to people who find traditional editors frustrating. Figma, Spotify, and the New York Times all use Descript, which tells you it holds up in professional contexts. Descript also offers an MCP server now, so an agent like Claude Code can run edits from a chat window. I tried that approach through Riverside's MCP, and here is what happened when I [tested agent-driven editing on a full episode](/ai-video-editing/). Underlord, Descript's AI co-editor, goes further. It removes filler words in one click, corrects eye contact from webcam footage, and cleans rough audio to near-studio quality. The free plan covers one hour of media per month. Paid plans start at $16 per month on an annual plan. The free tier is tight for active creators, so treat it as a real trial rather than an ongoing option. [Try Descript free](https://www.descript.com/) #### **7. HeyGen** *HeyGen converts scripts and PDFs into full-length AI avatar videos in minutes.* HeyGen lets you make on-camera videos without going on camera. Feed it a script, a PDF, or a slide deck, and it produces a finished video with an AI avatar presenting the content. No camera, no studio, no recording sessions. The platform supports 175+ languages and dialects, with phoneme-level lip sync across all of them. Miro reported 10x faster video production after moving their workflow to HeyGen. For creators building courses, training content, or expanding into international markets, HeyGen removes the recording bottleneck entirely. The honest limitation: avatar realism varies by language. Outputs in less-supported languages are noticeably weaker than the English flagship. A free tier is available, with advanced features unlocked at paid plan levels. [Try HeyGen free](https://www.heygen.com/) #### **8. Midjourney** *Midjourney is a very popular AI media generator* Midjourney is still the best AI image generator for creators who care about visual quality. It runs through Discord and a web interface, producing images that most other generators cannot match for composition and artistic style. YouTubers use it for custom thumbnails, bloggers for featured images, marketers for ad creative that does not look like stock photography. Plans start at $10 per month on Basic. The Standard plan at $30 per month is the best value for active creators, because it adds unlimited Relax mode generations once your fast hours are spent. The friction point is the Discord-based workflow. It takes some adjustment if you have never used it, and the web interface is still catching up to the Discord experience. [Get started with Midjourney](https://www.midjourney.com/) #### **9. Runway** *Runway's Gen-4.5 model is built for creators who want cinematic AI video output.* Runway is the AI video generation tool for creators who want cinematic results. The Gen-4.5 model produces clips from text prompts or images with motion coherence that earlier AI video tools could not match. Partnerships with NVIDIA, Lionsgate, and UCLA's film program tell you where the quality ceiling sits. The practical use case for content creators is B-roll, visual effects, and atmospheric clips that would otherwise require expensive production. You are not replacing a camera operator. You are replacing hours of stock footage searching with something specific to your content. Pricing is not listed on the homepage. Check their pricing page for current plan details. A free trial is available. [Try Runway free](https://runwayml.com/) #### **10. Higgsfield AI** *Higgsfield AI bundles Seedance 2.0, Cinema Studio, and Marketing Studio in one platform.* Higgsfield AI is the emerging pick on this list. It bundles image generation, video creation, inpainting, and character animation into one platform, with access to frontier models including Seedance 2.0 and Kling 3.0. The Marketing Studio feature converts a URL directly into ad-ready video, which is a useful shortcut for creators who also run paid campaigns on the side. The honest caveat: Higgsfield lacks the third-party validation that tools like Runway or ElevenLabs have built up. Most quality claims are self-reported, and independent reviews are still sparse. That is normal for a newer platform. If you are comfortable being an early adopter and want access to multiple frontier video models in one place, it is worth testing. If you want proven reliability, start with Runway and treat Higgsfield as a supplement once you have the core workflow down. [Try Higgsfield AI](https://higgsfield.ai/) If short-form clipping is the part of your workflow you are trying to fix, I went deeper on the options in [my Opus Clip alternatives breakdown](/opus-clip-alternatives/). ### **Ryan's Final Thoughts** No single tool on this list does everything. That is the point. The creators winning in 2026 run a stack where each tool handles what it does best. Blotato covers repurposing and scheduling. Opus Clip handles short-form clipping. Descript handles editing. ElevenLabs handles voice. They work together, not in isolation. The layer most stacks are missing is the writing step between the recording and the scheduler, which is what I built the [**AI Content Engine**](https://engine.ryandoser.com/) for: one video or podcast becomes the blog, the posts, the newsletter, and the hooks in your voice before any of these tools touch it. Start with the tool that solves your biggest bottleneck right now. Distribution is the problem? Start with Blotato, and my [social media automation tools](/social-media-automation-tools/) breakdown covers the alternatives. Editing is eating your time? Start with Descript or Opus Clip. Building a video-first strategy? HeyGen or Runway belongs in the workflow, and I walk through the full pipeline in my guide to making [AI video with Claude Code](/claude-code-ai-video/). For a look at how these fit into a broader system, check out my breakdown of an [AI agent for content creation](/ai-agent-for-content-creation/) and my full [AI marketing stack](/ai-marketing-stack/). The tools are good. The strategy behind how you use them is what separates real results from a subscription graveyard. ### **Best AI Tools for Content Creators FAQs** #### **What is the best AI tool for content creators in 2026?** It depends on your biggest bottleneck. Blotato is the best all-in-one option for repurposing and scheduling content across platforms. If video editing is your pain point, Descript or Opus Clip are stronger picks. There is no single best tool because the best stack is the one that covers your specific workflow gaps. #### **Can AI tools replace a content team?** Not entirely, but they get you surprisingly close as a solo creator. Tools like Blotato, HeyGen, and ElevenLabs let one person handle content at a volume that previously required a team. The strategy and creative direction still need a human. The execution can be largely automated. #### **Which AI tools are best for YouTube creators?** Opus Clip for turning long videos into short-form clips, and it can now be [run from inside an AI agent](/opusclip-mcp/) instead of its dashboard. Descript for editing without a traditional timeline. Midjourney for custom thumbnails. ElevenLabs for voiceovers if you want to batch produce content without recording every video. Blotato for turning your YouTube content into a full week of social posts automatically. #### **Are free AI content creation tools worth using?** The free tiers on tools like Opus Clip, ElevenLabs, and Descript are genuinely useful for testing, but they are intentionally limited. Most serious creators will hit the cap within a few weeks. Think of free tiers as a real trial, not a long-term operating model. --- ## OpusClip MCP Tutorial: Connect Opus Clip to Any AI Agent URL: https://ryandoser.com/opusclip-mcp/ Markdown: https://ryandoser.com/opusclip-mcp.md Published: 2026-07-31 | Updated: 2026-08-01 Categories: Claude Code > I set up the OpusClip MCP in Claude Code, ran two real workflows, and asked it for 5 clips. It made 25 and charged me for all of them. The **OpusClip MCP** lets you run Opus Clip from inside Claude Code, Cursor, or any other agent that speaks the protocol. It also ignored me when I asked for five clips and rendered about 25, charging credits for every one. Here is the setup, the two workflows I actually run with it, and what to watch before you turn it loose on a batch. ### **OpusClip MCP Video Guide** I had not opened Opus Clip in about a year before this. Here is the full walkthrough of setting it up and running it against two real projects. The reason I stopped using [Opus Clip](https://opus.pro/?via=aitips) was never the clipping quality. It was the review tax. Every batch meant opening the dashboard, watching each short, judging whether it was any good, and rewriting headlines one at a time. I have a short-form editor that produces better output, so the trip was hard to justify. If you want the wider setup this plugs into, my **[Claude Code Skills Stack](https://skills.ryandoser.com)** has the 40+ skills I run daily, including the caption generator doing the work below. ### **How to Set Up the OpusClip MCP in Claude Code** One thing will stop you before you start, so check it first. Executing actions through the server requires a paid plan. Per [Opus Clip's own agent documentation](https://help.opus.pro/api-reference/agent-setup), browsing the tool catalog is free, but running a clip, caption, or reframe needs Pro Beta, Max, or Business access. Those tier names are worth a warning. They do not match the plans on the public [Opus Clip pricing page](https://www.opus.pro/pricing), which sells Free, Starter, Pro, and Business, so check what your account actually has before assuming you are covered. The server lives at `https://mcp.opus.pro/mcp`, and it authenticates with OAuth rather than an API key. There is no token to paste anywhere. Opus Clip keeps a [product page for the MCP server](https://www.opus.pro/mcp) if you want the marketing version first. I set mine up by handing Claude Code the URL and the documentation link together, then telling it to save the entry wherever it already keeps my MCP credentials. Feeding it the docs alongside the URL is a habit worth copying. It gives the agent and its sub-agents something concrete to read instead of guessing at a config shape. After the install you have one manual step. Run `/mcp` in Claude Code and the server will show up needing authentication. *The Claude Code MCP panel after authentication, with opusclip showing as connected.* Click through the prompt, sign in with your Opus Clip account, and the status flips to connected. That is the whole setup. If MCP servers are new to you, I broke down what they are and how they differ from skills and agents in my guide to [Claude Skills vs MCP vs agents](/claude-skills-vs-mcp-vs-agents/). ### **Build a Brand Template Before You Clip Anything** Do this before your first render or you will redo every clip. Inside Opus Clip you can save a brand template holding your logo, caption styling, B-roll behavior, and emoji rules. Mine carries the Ryan Doser logo and captions in my brand colors. Skip it and you inherit the default, which is the green and yellow caption style you have seen on thousands of shorts. I can spot it instantly, and so can your audience. The payoff shows up in the agent flow. When Claude Code ran my first clip it asked which template to use, so the branding decision was already made and I just confirmed it. ### **Workflow One: A Raw Phone Video to Every Platform** Here is the loop that made this worth writing about. I record short walk-and-talk videos on my phone, dump them in a Google Drive folder, and post them raw. Viewers told me they wanted captions and a logo, which is exactly the polish I did not want to add by hand. Now I copy the Drive link, run a saved slash command in Claude Code, and hand it the URL. The agent asks for aspect ratio and template, then sends the file to Opus Clip. About a minute later the render came back finished, along with a suggested social caption written by my own caption skill rather than by Opus Clip. *Claude Code reporting the finished render with a recommended caption and alternate hooks to choose from.* I checked the render in the Opus Clip dashboard before posting anything. Captions and logo landed correctly, though it missed a shade of blue I thought was in my brand guide. Then I told it to post everywhere with one instruction: no hashtags on X or LinkedIn. It called [Blotato](https://www.blotato.com/?ref=rdoser) and pushed the clip to all five accounts with live URLs returned. That platform-specific hashtag rule is the part I would never get from the Opus Clip website. It lives in my skills, and the agent applies it every time without being reminded. ### **Workflow Two: Podcast Clips, and the Bug That Cost Me Credits** This is where the honest part of the review starts. I pointed it at a long podcast episode in Drive and asked for five on-brand short clips, told it to use my caption skill, and let it run. Roughly five minutes later it returned a table of finished clips with viral scores of 88, 86, 94, 93, and 98. *The five requested clips returned with scores, topics, and captions in a single table.* Then I opened the dashboard and found it had actually generated about 25 clips, not the five I asked for. Every one of those renders spends credits. Asking for five and paying for 25 is a real cost, not a rounding error, and it is the thing I would want to know before running a batch. This is a first-generation MCP server, so I expect rough edges. Until it settles, treat your clip count as a suggestion the tool may ignore and check the dashboard after any large job. The output quality itself held up. I liked the Fortune 1000 segment enough to post it, though the captions sat at the bottom and covered my guest's mouth. For two-person footage, center the captions in your template. Bottom placement works when you are the only face on screen and fails the moment there are two. ### **Why Route Through an Agent at All?** The fair objection: why not just drop the file into Opus Clip and let it work? Efficiency is half the answer. The dashboard trip means uploading, waiting, reviewing, editing headlines, then moving to a scheduler. Quality control is the more important half. Running it through Claude Code means my caption skill writes the copy, my hashtag rules apply per platform, and my brand template is enforced before I look at anything. Opus Clip left alone writes its own captions in its own style. That is the difference between a clip that sounds like me and one that sounds like a tool. It also keeps me in one window. Clipping, captioning, and scheduling all happen where my skills already live, which is the same argument I made for the rest of my [MCP server stack](/mcp-servers-for-marketers/). Opus Clip also publishes a [skills repository on GitHub](https://github.com/opus-pro/opus-skills) if you would rather start from their prebuilt commands than write your own. ### **Ryan's Final Thoughts** The OpusClip MCP fixed the exact thing that made me quit the tool, which is the manual review and editing tax on every batch. One gap is still open: the MCP has no tools for music, sound effects or B-roll. That is why my [AI video editing workflow](/ai-video-editing/) still sends shorts to a human editor. It is not finished. It overshot my clip count and burned credits doing it, and caption placement still needs a human eye on two-person footage. Even so, a tool I had abandoned is back in my rotation because an agent can now drive it. I am curious what the team ships next. If that credit behavior put you off, I compared the field in [Opus Clip alternatives](/opus-clip-alternatives/), including why I still pay a human editor. ### **OpusClip MCP FAQs** #### **What is the OpusClip MCP server?** It is a hosted Model Context Protocol server at `https://mcp.opus.pro/mcp` that lets AI agents control Opus Clip through natural language. Instead of uploading a video in the dashboard, you tell Claude Code, Cursor, or another [MCP-compatible client](https://modelcontextprotocol.io/) to clip it. The agent creates the project, applies captions and reframing, and returns the finished clips with links. #### **Do I need a paid plan to use the OpusClip MCP?** Yes, to do anything useful. Connecting to the server and browsing its tool catalog is free, but executing actions like clipping, captioning, or reframing requires Pro Beta, Max, or Business access according to Opus Clip's documentation. Those names do not appear on the public Opus Clip pricing page, which lists Free, Starter, Pro, and Business, so confirm what your own account holds rather than trusting the tier label. #### **How do I connect the OpusClip MCP to Claude Code?** Add the server URL `https://mcp.opus.pro/mcp` as a streamable HTTP MCP server, then run `/mcp` in Claude Code. Opus Clip will appear with a status asking for authentication. Click it, complete the OAuth sign-in with your Opus Clip account, and the status changes to connected. There is no API key involved. #### **Does the OpusClip MCP respect how many clips you ask for?** Not reliably in my testing. I asked for five clips from a podcast episode and it generated roughly 25, all of which consumed credits. The five it reported back were correct and well scored, but the extras were rendered anyway. Check your dashboard after any batch job until this is fixed. #### **Can I post the clips automatically after they render?** Yes, but that is a separate connection. Opus Clip renders the clip, then I have Claude Code hand it to Blotato to schedule across platforms with per-platform caption rules. I walk through building that publishing side in my guide to [social media automation tools](/social-media-automation-tools/), and if you would rather a tool watch a channel and mirror posts for you, I priced [the trigger-based options](/repurpose-io-alternatives/) separately. *Disclosure: some links in this post are affiliate links, specifically Opus Clip and Blotato. If you buy through them I may earn a commission at no extra cost to you. Blotato is also a client of mine. I only recommend tools I actually use, and the credit issue above is exactly what I found when I tested it. [Full disclosure](/disclosure/).* --- ## My New Website Is Live (I Finally Left WordPress) URL: https://ryandoser.com/new-website-rebuild/ Markdown: https://ryandoser.com/new-website-rebuild.md Published: 2026-07-30 | Updated: 2026-07-30 Categories: AI News, Claude Code > I rebuilt ryandoser.com in a week with Claude Code, GitHub, Cloudflare, and Astro. Here is the full stack, the real cost, and what changed. **My new website is live.** I rebuilt ryandoser.com from scratch last week with Claude Code, and I could not be happier to be off WordPress. I did not hire anyone, I did not open a page builder, and I did not touch a single plugin. I described what I wanted, reviewed what came back, and shipped it. The whole thing took about a week of evenings. *The new homepage. The terminal panel on the right is real output from the Claude Code skills that run my content operation.* ### **The Stack Behind the New Site** Four tools, and only one of them costs me anything. [Claude Code](https://claude.com/product/claude-code) does the actual building. It reads my files, writes the code, and explains what it changed. [GitHub](https://github.com/) stores every file and every version, so nothing lives on a server I cannot see. [Cloudflare Pages](https://www.cloudflare.com/developer-platform/products/pages/) hosts and deploys it. And [Astro](https://astro.build/) is the framework underneath, which is built for content sites like a blog and ships almost no JavaScript by default. *Astro calls itself the framework for content-driven websites, which is exactly what a blog is. Note the logo wall: Cloudflare and Webflow both run on it.* I also ran the design work past [Codex](https://developers.openai.com/codex/) as a second opinion. Two models looking at the same layout catch different things, and it is cheap insurance when you are not a developer. The rebuild also turned into something reusable. I packaged the whole process as a Personal Brand Website skill and added it to my **[Claude Code Skills Stack](https://skills.ryandoser.com)**, alongside the 40+ other skills I run every day. Next time I build a site, I start from that skill instead of from scratch. #### **What it actually costs to run** - $10 per year for my domain - $0 for GitHub - $0 for Cloudflare - $0 for Astro That is the entire hosting bill. The only real line item is the [$100 per month Claude Max plan](https://claude.com/pricing), and I was already paying for that to run everything else in my business. It is not a website expense, it is the tool I work in all day. Compare that to what I was doing before: a monthly platform fee, plus premium plugins, plus a theme, plus whatever the next thing was that broke and needed a paid fix. ### **Why I Left WordPress** WordPress was not the problem on day one. It was the accumulation. And to be clear about where I landed: I am not touching WordPress, Webflow, Wix, or Squarespace again. Every plugin was another thing to update, another thing that could conflict, another thing with its own subscription. Moving a single button meant wrestling a visual editor that fought me on spacing. And the site got slower as it got older, which is exactly backwards. The part that finally pushed me out was ownership. On WordPress my content lived inside a database I could not read, wrapped in page-builder markup that only made sense to the page builder. Now every post on this site is a plain text file in a folder. I can read it, search it, back it up, or move it somewhere else tomorrow. I am not the only one who noticed this shift. I wrote about [Cloudflare's EmDash CMS and whether it kills WordPress](/cloudflare-emdash-cms/) when it launched, and the pattern is the same: the tooling got good enough that the tradeoff stopped making sense. I also wrote up [why the popular escape routes from WordPress are dead ends too](/wordpress-alternative/), from Wix to browser-based vibe-coding tools. ### **Changes Now Ship in Seconds** I describe a change in Claude Code. It edits the files. I push to GitHub, Cloudflare rebuilds the site, and it is live in about a minute. No dashboard, no cache to clear, no staging environment to sync, no plugin update to pray over. Fixing a typo used to be a five-minute round trip through wp-admin. Now it is one sentence. ### **You Can Do This Without Being a Developer** I am a marketer. I do not write code, and I did not learn to for this. What I did learn was how to describe what I wanted clearly, read what came back, and push back when it was wrong. That is the actual skill now, and it transfers to every site you will ever build. If you want to see the process rather than the result, I have two walkthroughs that cover it. [Watch me build a website with Claude in 30 minutes](/build-a-website-with-claude/) is the fast version, done live. [How to build websites with Claude Code](/vibe-code-websites-claude-code/) goes deeper on the GitHub and Cloudflare side, which is the part most people get stuck on. And if you are wondering whether a cheaper model could do this job, I put [six open source AI models up against Claude for web design](/open-source-ai-web-design/) using this exact site as the test case. ### **Ryan's Final Thoughts** The redesign is the small story here. The real one is that I own every file, my hosting is effectively free, and I can change anything on this site in the time it takes to type a sentence. If a non-technical marketer like me can figure this out, then anyone reading this can too. ### **New Website Rebuild FAQs** #### **What is ryandoser.com built with now?** The site runs on the Astro framework, with the code stored in a GitHub repository and hosted on Cloudflare Pages. I build and edit it through Claude Code. Astro is designed for content-heavy sites and ships very little JavaScript, which is why the pages load fast. #### **How much does it cost to run a website on this stack?** My hosting cost is $0. GitHub, Cloudflare Pages, and Astro all have free tiers that comfortably cover a blog, so the only mandatory expense is about $10 per year for the domain. I pay $100 per month for Claude Max, but that is a tool I use across my whole business, not a hosting cost. #### **Do I need to know how to code to build a site this way?** No. I do not code and I did not learn to for this rebuild. You need to be able to describe what you want, review what the model produces, and say when something is wrong. Being comfortable in a terminal helps, but Claude Code walks you through the parts that are unfamiliar. #### **How long did the rebuild take?** About a week, working in the evenings around client work. Most of that time went to migrating existing blog posts and checking that old URLs still resolved, not to building the design itself. #### **Is this better than WordPress for everyone?** No. If you need a membership portal, an ecommerce store, or a large team editing content through a visual interface, WordPress or a hosted platform still makes sense. This stack is a strong fit for a blog, a portfolio, a landing page, or a local business site, which covers most of what people actually need. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## 7 MCP Servers for Marketing Work (What Each One Costs) URL: https://ryandoser.com/mcp-servers-for-marketers/ Markdown: https://ryandoser.com/mcp-servers-for-marketers.md Published: 2026-07-29 | Updated: 2026-09-03 Categories: Claude Code > The 7 MCP servers I connect for marketing work, what each actually bills after setup, and what your agent gets back when it hits a limit. The lists of the best **MCP servers** for marketing will tell you what each one does. Almost none of them tell you what it costs you after you connect it. All seven below are connected in my own setup. This post is about the real bill and the real setup time: the publishing server whose free trial starts charging you the moment you generate the key you came for, and the video server that bills a 10-credit floor on every project an agent submits, however short the source video. One thing to settle first, because it decides which post you want. This list is the marketing stack: publishing, video, scraping, analytics, the tools a marketer wires into Claude to do the job. If you came specifically for rank tracking, keyword data, and SERP analysis, that is a different set and I ranked it separately in [the best SEO MCP servers](/best-seo-mcp-servers/). ### **What These Lists Never Tell You** MCP stands for Model Context Protocol. It is the open standard that lets an AI assistant reach outside its own chat window and touch real tools, real data, and real accounts. If that idea is new to you, I wrote a plain-English breakdown of [Claude Skills versus agents versus MCP](/claude-skills-vs-mcp-vs-agents/) that untangles which piece does what. There is no shortage of MCP server lists. The general ones are built for engineers and point you at GitHub, Postgres, and Sentry. Those are great servers for writing software and do very little for a marketing week. The marketing-specific lists are more useful, though several are published by vendors who rank their own server first. Worth checking who wrote the list before you trust the order. What they rarely cover is what happens after you connect. Two things decide whether a server is worth your afternoon, and both only show up once you have used it. The first is setup friction. A remote server usually means pasting a URL, though several still want OAuth or an API key. A local one needs a terminal and a runtime on your own machine. Those are very different afternoons. The second is what the server actually costs, which is rarely the number on the pricing page. One tool here bills you the instant you generate an API key, and another wants a $50 deposit before it returns a single result. Two of the free ones sit in front of metered usage that a looping agent can burn through while you make coffee. ### **The 7 Best MCP Servers for Marketing Work** All seven of these are connected in my setup right now, ordered by how often I reach for them rather than by any general measure of quality. Where a tool has a real drawback, it is in the card. | Server | Best for | Setup | What it costs | | Blotato | Publishing to 9 social platforms from an agent | Remote URL | $29/mo subscription | | Opus Clip | Turning long video into clips from an agent | Remote URL with OAuth | Pro $29/mo, and the MCP connector is Pro or Business only | | DataForSEO | Keyword volume and live SERP data | Terminal | Pay per call, $50 deposit to start | | Apify | Scraping competitors, SERPs, and Google Maps | Remote URL with OAuth | Free tier with $5 usage/mo, then metered | | Chrome DevTools | Page speed and Core Web Vitals audits | Terminal | Free | | Playwright | Repetitive browser tasks and form flows | Terminal | Free | | Google Workspace | Gmail, Sheets, Drive, and Calendar access | Terminal plus OAuth setup | Free | #### **1. Blotato (Best for publishing to social platforms)** *Blotato's hosted MCP server connects Claude to nine social platforms through one endpoint.* Claude can write you a post. It cannot publish one by itself. [Blotato](https://www.blotato.com/?ref=rdoser) is the layer that closes that gap, and it is the server I use more than any other on this list. I publish to six platforms a week through it without opening a single social app. I walked through the full build in the video above, from connecting the server to scheduling a week of posts in one pass. **Pros:** - Genuinely paste-a-URL setup, no terminal or Node.js required - Publishes through official platform APIs rather than browser automation, which is the more durable of the two approaches - Covers nine platforms behind one connection: X, LinkedIn, Facebook, Instagram, Pinterest, TikTok, Threads, Bluesky, and YouTube **Cons:** - Comments and DMs are limited to Instagram and Facebook, and analytics covers eight of the nine platforms because LinkedIn still returns no metrics - Closed source, so self-hosting is not an option **Best for:** Marketers and creators who want an agent to actually publish, not just draft. **Pricing:** Starter $29/mo (20 accounts, 1,250 credits), Creator $97/mo (40 accounts, 5,000 credits), Agency $499/mo (28,000 credits). Annual billing saves roughly 17 percent. Worth knowing before you sign up: the 7-day trial covers everything except the API, so generating the key the MCP server needs ends the trial and starts the paid Starter plan at $29/mo. **Free trial:** Yes for the web app, but not for MCP or API access. **Bottom line:** If your week is mostly social publishing, this is the one to connect first. Several tools now ship a publishing MCP server, so the choice is no longer about which one an agent can reach. I put the closest open-source option beside it in my [Postiz vs Blotato comparison](/postiz-vs-blotato/). #### **2. Opus Clip (Best for clipping long video from an agent)** *Opus Clip's MCP page lists the endpoint and the connector steps for each client, including Claude Code and Cursor.* This is the newest server on the list and the one that changed my week most. [Opus Clip](https://opus.pro/?via=aitips) turns long video into short clips, and its hosted MCP server at `https://mcp.opus.pro/mcp` lets an agent drive the whole job: submit the video, apply a brand template, edit captions, then hand the finished file to a publishing server. Video editors are joining in too: Riverside, Descript and DaVinci Resolve 21.1 all ship MCP servers now. I broke down the [podcast rough cut I ran through Riverside's MCP](/ai-video-editing/), plus where AI editing still breaks. I had stopped using Opus Clip for about a year before this. The clipping was never the problem. The problem was the review tax, which meant opening the dashboard after every batch and rewriting headlines one at a time. Routing it through an agent is what removed that, because my own caption skill writes the copy before I ever look at a clip. The setup detail worth having in advance: it authenticates with OAuth, so there is no API key to paste. Any account can connect and browse the tool catalog. Actually calling a tool needs a paid plan, and on the public pricing page the MCP connector is listed on Pro and Business only, with a dash next to it on Free and Starter. **Pros:** - Paste-a-URL setup with OAuth, no config file and no API key - Twenty-six workflow tools covering the full job, 12 read and 14 write, so an agent can list projects and inspect clips without an approval prompt on every call - The write tools include posting and scheduling, so a clip can go from raw footage to a scheduled post without a dashboard trip **Cons:** - Every project submitted through the API carries a 10-credit minimum, roughly ten minutes of clip time, whether or not your video is that long. The same job submitted in the web app is not charged that floor - It overshot my clip count badly. I asked for five clips from a podcast episode and it rendered about 25, and every one of those spent credits **Best for:** Anyone sitting on long video who wants clips produced and captioned to their own brand rules rather than the tool's defaults. **Pricing:** Free $0 (60 credits/mo, watermarked, clips expire after 3 days), Starter $15/mo (150 credits, monthly only), Pro $29/mo, or $14.50/mo billed annually at $174 for 3,600 credits released up front. Business is custom. The MCP connector sits on Pro and above. **Free trial:** Yes, and no credit card is required to start it. The connector itself is not part of the free tier. **Bottom line:** Worth connecting if you publish video weekly, and worth knowing the two limits before you point a batch at it. I wrote the full setup and both workflows in my [OpusClip MCP tutorial](/opusclip-mcp/), including the credit bug in detail. If the credit behavior is a dealbreaker, I priced the field in [Opus Clip alternatives](/opus-clip-alternatives/). #### **3. DataForSEO (Best for keyword and SERP data)** *DataForSEO's MCP server is free and open source, though the data behind it is metered.* This is the one that replaced a recurring SEO subscription for me. [DataForSEO's MCP server](https://github.com/dataforseo/mcp-server-typescript) gives an agent live search volume, real SERPs, backlink profiles, and competitor rankings. I broke the same workflow down in my post on [keyword research in Claude Code](/claude-code-keyword-research/). Ahrefs runs a hosted MCP server as well, so the choice is no longer about which one an agent can reach. I compared them in [DataForSEO vs Ahrefs](/dataforseo-vs-ahrefs/), and worked out what Ahrefs MCP actually costs to run in [Ahrefs API pricing](/ahrefs-api-pricing/). If you have never connected a server before, that video covers the setup process end to end. **Pros:** - Live SERP pulls, so you are reading what ranks today rather than a cached number from a dashboard - An AI optimization module that tracks brand mentions inside LLM answers - Pay only for the calls you make instead of a flat monthly seat **Cons:** - Requires a terminal, Node.js, and API credentials in a config file - Metered billing, so a looping agent can burn through credit unless you set a daily expense limit **Best for:** SEO work where you are comfortable in a terminal and want live data instead of a subscription dashboard. Worth separating two jobs that sound alike here. Tracking mentions inside LLM answers is a different product from watching the open web those answers draw on, which is what [Alertmouse](/alertmouse-review/) does for a fraction of the price. **Pricing:** Pay-as-you-go with a $50 minimum deposit. The server itself is free and open source. Per-call costs vary by endpoint. **Free trial:** You can register without paying, but the pricing page states a $50 minimum payment before you are pulling data. **Bottom line:** Set a daily expense limit in the dashboard on day one, before you point an agent at it. #### **4. Apify (Best for scraping competitors and lead lists)** *Apify's remote MCP server exposes thousands of prebuilt scrapers through one URL.* [Apify](https://mcp.apify.com) hands your agent thousands of prebuilt scrapers, called Actors. Google Maps listings, competitor sites, social profiles, SERPs. I used it to pull LinkedIn profile data for a client research project, which I broke down in my guide to [scraping LinkedIn profiles with Claude Code](/scrape-linkedin-profiles-claude-code/). The video shows the scrape running, including the part where you decide what is actually worth pulling. **Pros:** - Remote-hosted with OAuth, so Claude connects without you touching a config file - A real free tier with $5 of monthly usage, enough to properly evaluate it - Your agent can search for the right Actor itself rather than you hunting through a catalog **Cons:** - Compute-unit billing is hard to predict, so you cannot easily tell what a scrape costs before running it - A few third-party Actors still carry their own rental fee on top of compute, though Apify is phasing those out through 2026 **Best for:** Competitor research and lead sourcing. Check a site's terms before you point a scraper at it. **Pricing:** Free tier at $0 with $5 of included usage per month. Starter $19/mo, Scale $199/mo, Business $999/mo, each with that amount to spend on top. Compute units run $0.20 on Free and Starter, $0.16 on Scale, and $0.13 on Business. **Free trial:** Yes, and the free tier is actually usable. **Bottom line:** The easiest server here to try tonight. The free tier plus OAuth means you can be scraping in about five minutes. #### **5. Chrome DevTools (Best for page speed audits)** *Google's official Chrome DevTools MCP server drives a real Chrome instance for performance work.* Google maintains [this one officially](https://github.com/ChromeDevTools/chrome-devtools-mcp), and at over 50,000 GitHub stars it has the widest adoption of the open-source servers here. It drives a real Chrome browser, so your agent can run a performance trace and point you at the scripts costing you the most load time. Keep the distinction in mind: a local trace is lab data, and Core Web Vitals are ultimately measured from real visitors in the field. **Pros:** - Runs a real performance trace on your own machine, so you see the actual load behavior rather than a score out of 100 - Shows what actually renders on a JavaScript-heavy page, which matters for technical SEO - Completely free with no paid service behind it **Cons:** - It drives your browser, so a logged-in session is visible to the model - Usage statistics are collected by default until you pass the opt-out flag **Best for:** Technical SEO audits and diagnosing why a landing page feels slow. **Pricing:** Free and open source. **Free trial:** Not applicable, the whole thing is free. **Bottom line:** If you own a site and care about speed, install this one. Add `--no-usage-statistics` if you would rather not send telemetry to Google. #### **6. Playwright (Best for repetitive browser tasks)** *Microsoft's Playwright MCP server automates browser workflows across multiple browsers.* People confuse this with the previous entry constantly. Chrome DevTools diagnoses why a page is broken. [Playwright](https://github.com/microsoft/playwright-mcp) does a job in a browser: fill the form, walk the checkout, capture the screenshots. Microsoft maintains it, and I lean on it for the screenshot work behind most of my roundup posts. **Pros:** - Works from a structured snapshot of the page rather than screenshots, so it behaves predictably instead of guessing from pixels - Works across Chromium, Firefox, and WebKit rather than Chrome alone - Reliable for the repetitive click-and-capture work nobody wants to do by hand **Cons:** - That snapshot drops visual context, so it cannot judge whether a page actually looks right - Microsoft now suggests the Playwright CLI over the MCP server for some agent setups, since the tool schemas eat context **Best for:** Screenshot capture, form testing, and any browser task you repeat weekly. **Pricing:** Free and open source. **Free trial:** Not applicable. **Bottom line:** Install it alongside Chrome DevTools rather than instead of it. They solve different problems, though I switch them on for the job rather than leaving both connected. #### **7. Google Workspace (Best for Gmail, Sheets, and Drive)** *The most maintained community Google Workspace MCP server covers twelve Google services.* Google does publish official Workspace MCP servers, one per product, covering Gmail, Drive, Docs, Sheets, Slides, Calendar and Chat. The catch is that they sit behind the [Workspace Developer Preview Program](https://developers.google.com/workspace/guides/configure-mcp-servers), and standing them up means a Google Cloud project, the gcloud CLI, and enabling both the product API and a separate MCP service for each one. That is the official route, and it is not a paste-a-URL afternoon. So the practical choice today is still a community build. [Taylor Wilsdon's](https://github.com/taylorwilsdon/google_workspace_mcp) is the one I settled on: over 3,100 stars, MIT licensed so it is free to use commercially, and still shipping commits this week. It covers twelve services including Gmail, Sheets, Drive, and Calendar. **Pros:** - Free, with no metered service running up a bill behind it - Reads and writes Sheets directly, which kills a lot of copy-paste reporting work - Actively maintained, unlike most alternatives you will find in search results **Cons:** - Setup is the hardest here by a wide margin, on either route. You build a Google Cloud project, switch on each service one at a time, then generate your own credentials - Google Chat needs a Business or Enterprise Workspace account, so a personal Gmail address will not cover everything **Best for:** Marketers whose reporting lives in Sheets and who send a lot of email. **Pricing:** Free. Normal Google API quotas apply. **Free trial:** Not applicable. **Bottom line:** It killed the weekly hour I spent pasting numbers into a client reporting sheet, but the setup really does take an afternoon. Because it holds read and write access to your email and files, connect it with a dedicated Google account and grant only the services you need. ### **What Happens When an MCP Server Hits Its Usage Limit?** This is the part that separates running a server from reading about one. A metered server does not politely stop when you run out. It returns an error code, and which code it returns decides whether your agent gives up cleanly or spends the next twenty minutes retrying a call that will never succeed. Opus Clip is the clearest example because it documents the behavior. Your plan credits and your API allowance are two separate ceilings. However many credits the plan gives you, the API itself is capped at 15 hours, or 900 credits, per workspace per calendar month. Worth knowing that the docs describe that cap under tier names, Pro Beta and Max, that do not appear on the public pricing page, so confirm what your own account actually holds rather than matching the label. When you hit that ceiling it returns a 403 rather than a 429, and the docs say the choice is deliberate, so agent frameworks do not treat it as a rate limit and retry in a loop. Access resumes on the first of the following month, UTC, and the web app keeps working the whole time. A 429 from the same server means something different and recoverable: you have hit the concurrency limit of four simultaneous projects, and it clears as soon as an in-flight job finishes. Backing off and retrying is the correct response to that one, and the wrong response to the other. Three questions are worth answering before you point an agent at any metered server, and none of them are on a pricing page: - **Where is the spend cap, and is it on?** DataForSEO has a daily expense limit in its dashboard and Apify has per-plan usage limits. Both are opt-in. An agent will happily run to the ceiling you never set - **Does the API price differently from the app?** This is the one that surprises people, because the pricing page describes the app. Opus Clip's 10-credit project floor exists on the API and not in the web app, so the same work costs different amounts depending on which door it came through - **What does the tool return when it refuses?** A 403 and a 429 mean opposite things. One says stop until next month, the other says wait ninety seconds. An agent that treats them the same either quits early or loops ### **MCP Servers for Marketing FAQs** #### **What are the best MCP servers for marketers?** The best MCP servers for marketing work are Blotato for publishing to social platforms, Opus Clip for turning long video into clips, [DataForSEO](/dataforseo-review/) for keyword and SERP data, Apify for scraping, Chrome DevTools for page speed audits, Playwright for browser automation, and a Google Workspace server for Gmail and Sheets. Blotato, Opus Clip, and Apify are remote servers you connect by pasting a URL; the other four need a terminal. The developer-focused servers that dominate most lists, such as GitHub and Postgres, do very little for a marketing workflow. #### **Can Claude post to social media through an MCP server?** Yes. Claude cannot publish on its own, but connecting a publishing server gives it that ability. Blotato covers nine platforms through one hosted connection and posts through each platform's official API. Opus Clip can post too, though only to the social accounts you have connected inside Opus Clip, so the two solve different halves of the job. Publishing is the single most useful thing a marketer can add to Claude, and it takes about five minutes to connect. #### **Do you need to know how to code to use MCP servers?** Not for all of them. Blotato, Opus Clip, and Apify are remote servers, which means you paste a URL into Claude and you are finished. Opus Clip and Apify add an OAuth sign-in on first use, which is a click rather than a config file. DataForSEO, Chrome DevTools, Playwright, and Google Workspace all run locally and need a terminal. The first three want Node.js and a config entry; Google Workspace is heavier, because you build a Google Cloud project and generate your own credentials first. If you have never opened a terminal, start with the remote three. #### **Which MCP servers charge per use instead of a monthly subscription?** DataForSEO and Apify are the two metered options here. DataForSEO is pure pay-as-you-go with a $50 minimum payment and no monthly seat, so you pay per call and nothing when you are idle. Apify is a hybrid: the plan fee is credit you spend rather than a fee on top, and overage bills per compute unit at $0.20 on Free and Starter, $0.16 on Scale, and $0.13 on Business. Blotato and Opus Clip are flat subscriptions. Chrome DevTools, Playwright, and the Google Workspace servers are free, though the Google APIs behind the last one carry their own quotas. #### **What is the best MCP server for SEO work?** DataForSEO, for live SERP data, search volume, backlinks, and competitor rankings, with Chrome DevTools alongside it for the technical side. That pairing replaced a recurring SEO subscription for me. Ahrefs also runs a hosted MCP server now, so the choice is no longer about which one an agent can reach. I ranked the search-specific servers separately in [the best SEO MCP servers](/best-seo-mcp-servers/). ### **How to Choose an MCP Server** These are the questions I ask before adding anything to my own setup. They work regardless of which servers you are weighing. - **Remote or local?** Remote means pasting a URL. Local means a terminal and Node.js. Be honest about which one you will actually finish. - **What does the underlying service cost?** A free open-source server sitting in front of a metered API is not a free tool. - **Can it write, or only read?** Reading data is useful. Taking an action is what changes your week. - **Is it maintained?** Check the last commit date. Abandoned servers rank well in search long after they stop working. - **Does it replace something you pay for?** That is where the real return sits, not in adding another subscription. Every server here is connected in my own setup, and I checked pricing live on each tool's own page the day I updated this. The limits in the section above, the error codes, the caps and the credit floors, come from each vendor's published documentation rather than from me deliberately hitting every ceiling. Licence terms and telemetry defaults come from each project's documentation too. Any number I could not verify is not in the post. ### **Which MCP Server Should You Install First?** Pick by the job you are trying to finish this week. - **You want your agent to publish:** Blotato - **You are sitting on long video:** Opus Clip, on Pro or above - **You do SEO:** DataForSEO, then Chrome DevTools for the technical side - **You need data off other people's sites:** Apify - **You live in Sheets and Gmail:** Google Workspace, once you have a free afternoon - **You want a free win today:** Chrome DevTools or Playwright If you are setting up your first one, my walkthrough on [how to set up MCPs in Claude Code](/claude-code-mcps/) covers the connection process step by step. Start with one. Connecting all seven at once eats into your context window, one of the [Claude Code usage tips](/claude-code-usage-tips/) that saves the most tokens, so most weeks I keep only the two or three I am actually using switched on. ### **MCP Servers I Have Not Tested** This list covers marketing work broadly. If your job is specifically organic search, I ranked the [servers built for SEO data](/best-seo-mcp-servers/) separately, including the two I open every morning. A few marketing-adjacent servers come up often enough that leaving them unmentioned would be strange. I have not run these, so they are not ranked above. Recommending software I have not used is the fastest way to make a list like this worthless. - [Notion MCP](https://developers.notion.com/docs/mcp) for content calendars and team wikis - [Figma MCP](https://www.figma.com/blog/introducing-figmas-dev-mode-mcp-server/) for pulling design specs into an agent - [Slack MCP](https://github.com/zencoderai/slack-mcp-server) for reading and posting in team channels - [HubSpot MCP](https://developers.hubspot.com/ai-tools/mcp) for CRM records and contact data If you run one of these in a marketing workflow, tell me what it replaced. That is usually the detail that tells me whether something is worth a real test. Several of the publishing tools in this space now ship MCP servers, which makes choosing between them harder rather than easier. I compared them in [this look at Zernio and what beats it](/zernio-alternatives/). ### **Ryan's Final Thoughts** These seven cover the work I repeat every week: publishing, keyword research, scraping, and page audits. If you buy media or live in a CRM all day, your list looks different, and you should build it the way I built this one, by connecting things and watching what they cost. Start with one, get it working, then add the second. The list changes as tools ship and break. Opus Clip earned its slot on this update because an agent can now drive it end to end, and it displaced the open-source publishing server I had been running, which was doing a job Blotato already did in my week. If you want the case for hosting your own posting stack instead, that argument still stands and I made it in my [Postiz vs Blotato comparison](/postiz-vs-blotato/). *Disclosure: some links in this post are affiliate links, specifically Blotato and Opus Clip. If you subscribe through them I may earn a commission at no extra cost to you. Blotato is also a client of mine, and I pay for Opus Clip myself. The other five servers here are free or metered and I have no commercial relationship with any of them. I only recommend tools I actually use. [Full disclosure](/disclosure/).* --- ## Claude Skills vs MCP vs Agents vs Commands (Plain English) URL: https://ryandoser.com/claude-skills-vs-mcp-vs-agents/ Markdown: https://ryandoser.com/claude-skills-vs-mcp-vs-agents.md Published: 2026-07-28 | Updated: 2026-07-28 Categories: Claude Code > Claude Skills vs agents vs MCP vs commands, explained in plain English. What each one does, how they stack, and which to learn first. If you are confused about **Claude Skills vs agents** vs MCP vs commands, you are not alone. They overlap, the docs are dense, and in 2026 one of them quietly got absorbed into another. Most comparison posts still have not caught up. Here is the plain-English version. I'm a non-technical marketer, so I'll explain these the way I wish someone had explained them to me, with no jargon and a clear picture of when to use each one. ### **The Quick Answer** Think of Claude Code as a workshop. These four things are different parts of that workshop. A skill is an instruction manual for one job. MCP is the wiring that connects your tools to the bench. An agent is an extra worker you send off to handle a side task. A command is the button you press to start something. They're not competing options. They stack. Once you see how they fit together, the whole setup stops feeling complicated. You don't pick one. You learn where each fits. ### **What Is a Claude Skill?** A Claude skill is an SOP for AI. It is a folder with a markdown file inside, and that file teaches Claude how to do one task from start to finish. *A real skill file open in Claude Code, with my skills folder on the left.* The key detail is that Claude loads a skill on its own. Each skill has a short description, and when your request matches that description, Claude pulls the skill in and follows it. You don't have to call it by name. I keep my skills granular. One writes SEO blog posts, another writes email newsletters, another handles LinkedIn. One skill per task beats one giant skill that tries to do everything, because a focused instruction set gives cleaner output. If you want the build steps, I covered [three ways to create Claude Skills](/claude-skills/) separately. ### **What Is MCP?** MCP, or Model Context Protocol, is the standard that connects Claude to your outside tools and data. The official docs call it a USB-C port for AI, which is a good way to picture it. A skill tells Claude how to do something. MCP gives Claude something to reach. It connects Claude to GitHub, Notion, Google Sheets, a database, or in my case WordPress, so Claude can actually pull and push real data instead of guessing it. I use the same idea to run [an AI social media manager with Claude Code](/claude-code-social-media/) through a posting connection. The difference matters. A skill is knowledge. MCP is plumbing. A skill can tell Claude how to use an MCP connection, but the connection itself is MCP's job. It is also an open standard, so the same setup works in other tools, not just Claude. ### **What Are Claude Code Agents?** An agent, or subagent, is a separate worker with its own context window. You hand it a side task, it goes off and does the work, and it reports back a summary. This protects your main conversation. When I tell Claude to triple-check a draft, it spins up agents in parallel that each verify the work without flooding my main chat with their notes. Research, fact-checking, and searching are perfect agent jobs. I broke down running several at once in my guide to [Claude Code agent teams](/claude-code-agent-teams/). If research is the part you care about most, that job also belongs to a different tool entirely, which is the point I make in [Claude Skills vs Perplexity Spaces](/claude-skills-vs-perplexity-spaces/). *Correct a skill once and it updates the file, so the mistake does not come back.* The simple way to hold it: a skill loads instructions into your current conversation, while an agent is a whole separate conversation doing work for you. An agent can even use your skills and your MCP connections while it runs. #### **Claude Skills vs Agents: The Real Difference** This is the comparison people actually mean when they ask, so it's worth making blunt. A skill is a file. An agent is a worker. A skill changes *how* Claude does a task in the conversation you're already in. An agent gives you a *second* conversation with its own memory that runs a task and hands back the result. The practical tell is your context window. Load five skills and you're still in one chat. Send five agents and you have five chats working at once, none of them cluttering yours. That's why agents are the answer to "this task will bury my main thread in output" and skills are the answer to "Claude keeps doing this task differently every time." They also aren't exclusive. An agent with no skill is a generic worker who improvises. An agent with a skill is a worker who follows your SOP. I get the best results pairing them: the skill defines the standard, the agent supplies the isolated space to apply it. If you want to see several of them coordinating on one job, that's what [Claude Code agent teams](/claude-code-agent-teams/) are for. ### **What Are Slash Commands?** A command is something you trigger by typing a slash and a name, like `/commit` or `/deploy`. It runs a saved prompt on demand. This is the part most comparisons get wrong, and it's the thing the intro promised. In 2026, custom commands and skills became the same thing under the hood in Claude Code. A command file and a skill both create a `/name` you can type, and your older command files still work. So the real difference isn't two separate systems. It's who pulls the trigger. A skill runs automatically when Claude sees a matching request. A command is the version you fire yourself by name. You choose that behavior with one setting in the file, which is handy for actions you never want running without your say-so, like deploying code. ### **Claude Skills vs Agents vs MCP vs Commands: How They Fit** None of these replace each other. The payoff is in how they stack. And since commands are now just skills you trigger by name, you are really juggling three things, not four. MCP gives Claude reach to your tools. A skill gives Claude the procedure for a task. A command lets you start that task by name. An agent runs a piece of it in its own space and reports back. A single workflow can use all four at once. A real example from my own setup. I type a command to kick off a blog post. That loads a skill with my SEO process. The skill tells Claude to pull the live site through an MCP connection, and it sends agents to verify facts in parallel. Four concepts, one smooth job, and I never leave the interface. ### **Which One Should You Learn First?** Start with skills. They give you the most payback for the least effort, and they are the easiest entry point for a non-coder. Build one skill for a task you do every week. Once that clicks, add an MCP connection so Claude can touch your real tools. If you are not sure which one to add first, I priced and ranked [the servers I actually run for marketing work](/mcp-servers-for-marketers/), including what each bills after you connect it. Agents and commands come naturally after that, because by then you understand the workshop and just want to move faster in it. This is the whole reason I keep pushing marketers toward this setup. The people who learn to build real systems pull ahead of the people still pasting prompts, which is the bigger argument behind [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) at all. ### **Final Thoughts** Claude Skills vs MCP vs agents vs commands isn't a battle. It's a stack, and one of those four already folded into the others. Skills are the SOPs, MCP is the wiring, and agents are the extra hands. If you only take one thing from this, make it a skill. It's the piece that turns Claude from a chatbot into a system that does your work the same way every time. When you want a head start, I packaged 25+ of the marketing and content skills I use daily into my [Claude Code Skills Stack](https://skills.ryandoser.com/), ready to drop into your own folder. --- ## How I Post on Social Media Consistently (I Record on Walks) URL: https://ryandoser.com/post-consistently-with-ai/ Markdown: https://ryandoser.com/post-consistently-with-ai.md Published: 2026-07-26 | Updated: 2026-07-26 Categories: AI Automations > How I post on social media consistently without a content calendar. I record unscripted takes on daily walks and automate everything after. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* ### **Why I Stopped Planning Content to Post Consistently** Most advice about posting consistently starts with a content calendar. This workflow starts somewhere else entirely. The same logic applies on the blog side, where I argue the [planning half of a content strategy has become the cheap part](/seo-content-strategy/). The bottleneck was never ideas. I have opinions about AI marketing constantly. The bottleneck is everything that sits between having the thought and getting it published. So the order flips. I record at the moment I actually have something to say. Then the workflow removes the steps between that moment and the post going live. That is the whole system. The habit replaces the planning. If you want to go deeper on the systems behind this, [**my Claude Code Skills Stack**](https://skills.ryandoser.com) has 40+ skills I use daily to automate marketing and content creation. If you only want the repurposing half of it, the [**AI Content Engine**](https://engine.ryandoser.com/) does that one job: one recording in, a week of content out, in your voice. ### **The Daily Walk Is the Content System** You have probably been told to find your best creative hours. Mine turned out to be the ones where I was not at a desk at all. I go on daily walks. At some point during one, a thought about AI marketing surfaces that I actually believe. I pull out my phone, hit record, and dump the raw take. No script, no outline, no lighting setup. The output is genuinely unpolished. One clip I posted was me explaining that I am done with WordPress, filmed on my phone mid-walk. That rant later became [a full breakdown of why I left WordPress behind](/wordpress-alternative/). That is the format. Raw thoughts, delivered once, unedited. *The raw short-form video dump folder in Google Drive, where clips land straight from my phone during a walk.* The clips save straight into a Google Drive folder from my phone, because the Drive app is already there. I named mine raw short-form video dump. Nothing about that step requires me to be at my computer, which matters more than it sounds like it does. #### **Why Unpolished Beats Planned** Polish is where consistency goes to die. Every production step you add is another reason a clip never gets recorded. There is a second benefit, and I might be biased here. A take captured at the moment of the thought tends to sound like someone who means it. A take produced to fill a slot tends to sound like an assignment. That is my instinct, not a measured result. Your own audience data should outrank it. ### **Removing Every Step After the Recording** A habit only survives if the friction after it is close to zero. That is what the rest of this workflow handles. This is not the build guide. If you want the full assembly instructions, I documented that in my guide to [managing social media with Claude Code](/claude-code-social-media/). What follows is only enough to show you the friction is genuinely gone. Publishing one clip normally means uploading the file, writing a caption, then repeating that for every account you run. Bringing AI into it does not save much. You are still copying captions out of a chat app and pasting them into each platform by hand. If that copy-paste loop is the specific thing you want gone, I broke down [how to publish everywhere at once without hurting your reach](/post-to-all-social-media-at-once/). That is the gap the [automation tools I actually run](/social-media-automation-tools/) are there to close. When I get back to my desk, I open [Claude Code](https://code.claude.com/docs/en/overview) and run a slash command I built called short-video-dump. I give it the Google Drive link to the clip and plain instructions about when I want it out. *The short-video-dump command pulling the clip from Google Drive and transcribing it before writing captions.* Claude Code downloads the raw clip from Drive, inspects it, and transcribes the audio. The transcript feeds a [skill file](/claude-skills/) that writes the caption against rules I defined once. That is why the copy sounds like me rather than like a tool. Writing those rules down is the whole trick, and I broke down [what actually goes in a voice file](/ai-content-engine/) if you want to build one. It shows me the drafted caption and waits for approval. As I get more comfortable with the output quality, that review step can be bypassed completely. This is not a sophisticated task either, so Sonnet 5 handles it fine. #### **Where the Clip Ends Up** Approving the caption is the last thing I do. Everything after it is machine work. Claude Code calls [Blotato](https://www.blotato.com/?ref=rdoser) through an [MCP connection](https://modelcontextprotocol.io/), uploads the video, attaches the caption, and schedules it across whatever accounts you have connected. Blotato supports nine platforms, so the reach of that one approval depends entirely on what you linked during setup. I check the Blotato calendar rather than trusting the terminal. The clip lands where I asked. Swapping the instruction from schedule to post right now publishes it immediately instead. *The Blotato calendar confirming the walk clip scheduled across platforms for the next morning.* ### **What This Does Not Solve** Removing friction is not the same as having something worth saying. This system distributes whatever you record. If the take is boring, you now distribute a boring take everywhere, faster than before. The walk habit works because I genuinely have opinions about this industry, not because the pipeline is clever. The cost is real too. Claude Code sits behind a paid Claude plan, and Blotato gates API access behind a subscription. A trial exists, but the publishing connection this depends on is not included in it. Google Drive and a working MCP connection round out the stack. There is a ceiling on the format too, in my opinion. A short unscripted take complements long-form work instead of replacing it. I use it to fill the space between bigger pieces, not as the strategy itself. ### **Ryan's Final Thoughts** Consistency is a friction problem disguised as a discipline problem. I did not become more disciplined about posting. I moved recording to the moment I actually have something to say, then deleted every step between that moment and publishing. Start by recording one unscripted clip on your next walk, before you build any automation at all. If the habit holds for two weeks, then go remove the friction behind it. ### **Post on Social Media Consistently FAQs** #### **How do I post on social media consistently without a content calendar?** Record content at the moment you have the idea rather than at a scheduled time, then automate everything after the recording. A calendar tries to schedule creativity. Capturing thoughts as they occur and removing the publishing friction behind them produces more consistent output, because the only step requiring willpower is hitting record. #### **Do I need polished video to post consistently?** No. Polish adds production steps, and every added step is a reason a clip never gets recorded. Lower production requirements make consistent posting far easier to sustain. Whether unpolished clips outperform produced ones for your audience is a separate question, and one your own analytics should answer rather than anyone else's preference. #### **What does this posting workflow cost to run?** You need a paid Claude plan for Claude Code and a paid Blotato plan for API access. Blotato offers a free trial, but the API connection this workflow depends on is not included in it. I cover that gap and what it costs to work around in my [honest review of Blotato](/blotato-review/). Google Drive storage is the only other requirement, and the free tier is usually enough for short clips. #### **Can AI write social captions that sound like me?** Only if you give it rules. A skill file holding your voice guidelines, banned phrases, and platform formatting produces captions much closer to your writing than a bare prompt does. I review each draft before it publishes and edit the skill file whenever a caption misses the mark. #### **How long should these walk-recorded clips be?** Long enough to make one argument, short enough to record without a script. A single take on a single opinion is the target. If a thought needs a structured explanation to land, it is probably a long-form video rather than a short-form clip. --- ## This Claude AI Side Hustle Made Me Over $5K (Claude Skills) URL: https://ryandoser.com/claude-ai-side-hustle/ Markdown: https://ryandoser.com/claude-ai-side-hustle.md Published: 2026-07-24 | Updated: 2026-07-24 Categories: AI Side Hustles, Claude Code > This Claude AI side hustle made me over $5K in 50 days selling Claude skills as a digital product. The exact workflow plus other angles. The **Claude AI side hustle** that earned me over $5,000 in the last 50 days started as a folder of markdown files on my desktop, not a real business plan. ### **Claude AI Side Hustle Video Guide** This clip is from my recent appearance on [The Koerner Office podcast](https://youtu.be/quYKZushRPo?si=cQjsPlcQipDawsCV), where I walked Chris Koerner through the exact workflow live. If you want the full pack I sold to hit that $5K number, you can grab it on my [**Claude Code Skills Stack**](https://skills.ryandoser.com/) page. Same set of skills I run my marketing agency on, sold for $99 a copy. ### **My Favorite Claude AI Side Hustle in 2026** Here are the four angles I am working right now, ranked by how much real money each one has produced. #### **1. Sell a Claude Skills Stack as a Digital Product** The single most profitable angle is packaging Claude skills you already use into a stack and selling it as a digital product. That one move made over $5,000 in 50 days at $99 a copy. I packaged about 20 skills I run every week (SEO blog post writer, anti-slop, YouTube thumbnail designer, web designer) and put them on a landing page. If you want to see which ones are worth running before you build your own, here are [the free and paid skills I recommend most](/best-claude-skills/). You can sell direct with a Stripe landing page, or list on an emerging marketplace like Agensi as they open up paid skills. I sell direct because I keep almost all of the margin (minus Stripe fees) and own the buyer relationship, but a marketplace can add discovery if you are starting from zero audience. *The Claude Code Skills Stack landing page where the $99 digital product lives.* The product is markdown files. No hosting, no logins, no support tickets at 2 a.m. Buyers download a zip, drop the files into their own Claude Code setup, and run them. That is the entire Claude AI passive income loop. Selling Claude skills works because power users of Claude are already paying $20 to $200 a month for the platform. They want prebuilt systems, not more prompts. If you want the full packaging playbook, I broke that down in [how to sell Claude skills as a digital product](/sell-claude-skills/). #### **2. Turn a Skill Buyer Into a Consulting Client** One of those $99 transactions turned into a $1,000 hour the same week. A buyer ran one of the skills, hit the limit of what he could do solo, and asked if I would install it on his stack for him. *Stripe receipts from the skill stack, including the $1,000 consulting upsell that landed mid-week.* That is the quiet upsell nobody talks about when they pitch [how to make money with Claude AI](/make-money-with-claude/). The skill is the front door. Consulting is the second door, and it converts because the buyer already trusts the work. Corey Ganim built a [monthly Claude coaching retainer](/how-to-start-an-ai-business/) around that second door. #### **3. Convert Old GPTs and Claude Projects Into New Skills** Most people I talk to have already built five or six custom GPTs or Claude projects. That is your inventory. Open the Claude app on your phone. Voice transcribe everything you know about a task you do every week. End the rambling with one line: "Use the skill creator skill at the end." Anthropic gives the skill creator away free in the [Anthropic Skills GitHub repo](https://github.com/anthropics/skills), so you do not have to write a single line of code. A 10-year-old can do this for chores. A gardener can do it for fertilizer schedules. A baseball card dealer can do it for grading decisions. Nothing is exempt. This is the Claude AI for beginners side hustle path with the lowest cost of entry I know of. If you want the conversion done properly rather than from memory, I wrote the step-by-step for [moving a Claude project into a skill file](/turn-claude-projects-into-skills/). #### **4. Stack a Marketing OS on Top of Your Skills** The same skills that print $99 sales also let me vibe code my own AI marketing OS. Google Calendar sync, social media schedule, client pipeline, and a Blotato MCP connection so I can post directly from Claude Code. *Recent ryandoser.com posts built by the SEO blog post writer skill, the same skill I sell in the stack.* This is the flywheel. I sell the skill. I use the skill to write the blog post. The blog post ranks and pulls more buyers. The buyers fund the time I spend building the next skill. Search "Blotato" in an incognito tab and you will find one of my posts under Reddit, written from a YouTube video by the SEO skill. If you want a peek at the broader workflow, I walk through it in [why marketers should use Claude Code](/why-marketers-should-use-claude-code/). ### **AI Side Hustle 2026: What Actually Matters** Three things separate the people who hit $5K from the people who post about it on LinkedIn. - **Pick one task you already do every week.** Not a fantasy product. The skill you use daily is the one that gets sharper fast. - **Sell the recipe, not the software.** Markdown files have near-zero production cost after v1. Buyers fork and customize. You ship updates. - **Niche down hard.** A focused stack for one job (SEO, real estate, nonprofit fundraising) beats a 50-skill grab bag every time. If you work in marketing, I ranked ten of these in my roundup of [AI side hustles for marketers](/ai-side-hustles-marketing/). Buyer education is the real friction. Most people still default to copy-pasting prompts into ChatGPT. Expect to explain what a skill is in every sales conversation for the next 12 months. That gap is the opportunity. ### **Ryan's Final Thoughts** The Claude Skills side hustle window is wide open right now because most marketers are still living in the prompt-and-pray era. Pick one task you already do, voice-dump it into Claude tonight, and you can have a v1 skill before bed. The hard part is not building it. The hard part is believing your subject matter expertise is worth packaging. ### **Claude AI Side Hustle FAQs** #### **How much money can you make with Claude AI side hustles?** My Claude Code Skills Stack made over $5,000 in roughly 50 days at $99 a copy, plus one $1,000 consulting upsell from a buyer who wanted help installing it. No paid ads, no funnel, just a landing page and inline CTAs in blog posts and emails. Bigger audiences scale further from there. #### **Do you need to know how to code to sell Claude skills?** No. I am non-technical and so are most buyers. A Claude skill is a markdown file with instructions, voice rules, and an output format. You build one by voice-transcribing your knowledge into the Claude app on your phone and ending with "Use the skill creator skill." That is the entire technical lift. #### **What is the best Claude AI side hustle for beginners?** Build a skill for the one task you do most often at your day job. You will use it daily, refine it fast, and your marketing copy will sound real because you live the problem. Then bundle three to ten related skills into a stack and sell it on a one-page Stripe checkout. #### **Where do you sell Claude skills online?** A landing page with Stripe checkout is enough. Host the files in a private GitHub repo or a zip download. You do not need a marketplace, app store, or Anthropic approval to monetize Claude skills. My own distribution at skills.ryandoser.com is the same setup. #### **Can you reuse old custom GPTs as Claude skills?** Yes. If you built a custom GPT or Claude project, the prompts and context transfer almost directly into a markdown skill file. Repackage them with the skill creator and you have a v1 in under an hour, which is the fastest way to get a Claude Skills side hustle to v1 without starting from a blank file. --- ## How to Build an AI Social Media Manager with Claude Code URL: https://ryandoser.com/claude-code-social-media/ Markdown: https://ryandoser.com/claude-code-social-media.md Published: 2026-07-24 | Updated: 2026-09-30 Categories: Claude Code > Claude Code social media setup guide. Connect Blotato, use skills, and schedule posts across every social platform from one interface. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* This guide walks you through how to build a fully functional **Claude Code Social Media** system that posts, schedules, and repurposes content across every platform you use. ### **How Claude Code Social Media Management Works** A Claude Code social media manager works by combining three pieces: skill files that define your brand voice, an MCP connection to a posting tool like Blotato, and Claude Code itself running in your terminal. Together they let you write, schedule, and publish posts across every platform from one interface. Most AI social media tools generate captions in a vacuum. They have no idea how you sound, what platforms you post on, or what your content calendar looks like. I broke down which ones are [worth paying for as a founder](/social-media-automation-tools/) and which two I stopped recommending. That gap is why most software sold as an AI social media manager disappoints. It writes competent captions about nothing in particular, because nothing in the product knows anything about you. The version I run works because the context comes from my own files rather than from a model's average of the internet. Claude Code takes a different approach. You give it skill files (markdown SOPs that define your voice, platform rules, and posting preferences), connect your social accounts through an MCP integration, and then manage everything from a single terminal interface. No switching between tabs. No copy-pasting into five different scheduling tools. The setup involves three core pieces: Claude Code running inside VS Code (or terminal or desktop app), a social media MCP connection through a tool called [**Blotato**](https://www.blotato.com/?ref=rdoser), and skill files that train the AI on your exact brand voice. Once those are connected, you can repurpose a YouTube video into platform-specific posts, publish directly to X, or schedule content weeks in advance on LinkedIn, Instagram, TikTok, and more. *Blotato makes it easy to connect X, LinkedIn, Instagram, TikTok, and other platforms to Claude Code through a single MCP integration. The same key also drives [automated Instagram DM replies](/best-instagram-dm-automation-tools/), so the inbox runs from the same setup as the publishing.* ### **Connecting Your Social Media Accounts to Claude Code** You have probably tried connecting APIs manually before. It is tedious and breaks constantly. [Blotato](/blotato-review/) simplifies this by acting as the bridge between Claude Code and your social platforms. Plans start at $29/month with a 7-day trial, and you can cancel anytime. Once you are on at least the Starter plan, you connect each social account (X, LinkedIn, Facebook, TikTok, Instagram, Threads, Pinterest, Bluesky) directly inside the Blotato dashboard under Settings > Accounts. After your accounts are linked, you connect Blotato to Claude Code through an MCP integration. Blotato is one of seven servers in [my marketing MCP stack](/mcp-servers-for-marketers/), where I break down what each costs once it is running. The [Blotato MCP setup guide](https://help.blotato.com/api/mcp/setup) provides the exact configuration for Claude Code in the terminal, VS Code, and other MCP clients. Paste those instructions into Claude Code and it handles the rest. You might need to troubleshoot a few authentication steps, but the integration is straightforward once complete. Blotato also includes a YouTube transcript scraper built into the MCP. That means Claude Code can pull transcripts from any public YouTube video, analyze the content, and write platform-specific social posts from your own original material. ### **Repurposing YouTube Videos Into Social Posts** Here is where the real value kicks in. Instead of watching your own video and manually writing captions, you hand Claude Code a YouTube URL and a skill file. I tested this with a recent podcast episode. The prompt was simple: "Use my social media skill to create five posts for X and LinkedIn based on this YouTube video." Claude Code scraped the transcript through Blotato, referenced my voice and formatting rules from the skill file, and generated all ten posts in a few minutes. The skill file is doing the heavy lifting here. Without it, you get generic AI captions that sound like everyone else on the internet. With a properly built [**Claude Code Skills Stack**](https://skills.ryandoser.com/), the output matches your actual tone, follows platform character limits (280 for X, 500 for Threads), and structures captions differently for professional platforms like LinkedIn versus short-form platforms like TikTok. If you want the repurposing step packaged rather than assembled, the [**AI Content Engine**](https://engine.ryandoser.com/) is the ready-made version: one video in, the week of posts, a blog, a newsletter, and short-form hooks out, written in your voice. From there, posting is instant. Tell Claude Code "post X post 3 to my account right now" and it publishes directly through Blotato. A live link appears in your terminal within seconds. For content you want to schedule, specify a date and time. Claude Code even checks your existing Blotato calendar for conflicts before locking in the slot. *Claude Code publishing an X post instantly and scheduling a LinkedIn post for the next day, all from the terminal interface.* ### **Batch Scheduling Short-Form Video Content** Single posts are useful for quick wins. Batch scheduling is where this system saves hours every week. I keep a Google Drive folder where my short-form video editor drops finished clips. The same folder also catches the raw unscripted takes I [record on my daily walks](/post-consistently-with-ai/), which is how I keep a steady posting cadence without a content calendar. By connecting the [Google Workspace CLI](https://github.com/googleworkspace/cli) to Claude Code, I can point it at that folder and say "write captions for all ten videos and schedule them starting June 8th, Monday through Friday, 8 AM Central." Those shorts are the one job my editor kept after [Claude Code took over my long-form podcast edits](/ai-video-editing/). Claude Code opens the folder, scrapes each video transcript, writes two caption groups per video (Group A for Instagram, TikTok, and YouTube Shorts with hashtags; Group B for X and LinkedIn with a different structure), uploads the video files to Blotato, and schedules everything across platforms. The entire batch took a few minutes to process. One practical note on tokens: this type of task burns through usage quickly. My recommendation is to switch to Sonnet 5.5 instead of Opus and set effort to low with /effort. You can't turn thinking off on Sonnet 5.5, so effort is the dial. Those two adjustments stretch your usage further on [social media management tasks](/claude-code-for-marketing/), where the skill file carries most of the caption quality. Spot-check the first batch after you switch. *Batch scheduling video content across multiple platforms with Claude Code using the Social Media Manager skill and optimized token settings.* ### **Building Your Own Social Media Dashboard** The Blotato calendar works, but it is still in beta and the interface is limited. If you want more control, you can vibe code your own social media dashboard directly from Claude Code. I built a custom AI Marketing OS that pulls scheduled posts from Blotato, displays them in a clean calendar view, and lets me preview video content inline. The process started with a single prompt referencing a dashboard builder [skill file](/claude-skills/) and took roughly a day of refining to get the integrations, colors, and functionality dialed in. You do not need coding experience to build something like this. Claude Code generates the full application, runs a local dev server, and iterates based on your feedback. Upload screenshots of what looks wrong, reference a brand guide for styling, and keep refining until the dashboard fits your workflow. The calendar view, list view, and platform filters all came from conversational prompts, not manual code. This step is entirely optional. Blotato handles scheduling and posting on its own. But if you manage content across multiple brands or want a centralized command center, a custom dashboard built with Claude Code gives you full control over the experience. I also use mine synced with Google Calendar for [broader content planning](/ai-agent-for-content-creation/) beyond social media. ### **Ryan's Final Thoughts** Building an AI social media manager with Claude Code is not a one-click setup, but the individual pieces are simple. Connect Blotato, write a voice skill, and start small with a few repurposed posts. Once the foundation is working, batch scheduling and custom dashboards become natural next steps. The system I run today manages content across six platforms, schedules weeks in advance, and keeps my voice consistent without me touching a single scheduling app. Start with one platform and scale from there. ### **Claude Code Social Media FAQs** #### **Can Claude Code post directly to social media platforms?** Yes, through an MCP integration with Blotato. Once connected, Claude Code can publish posts instantly to X, LinkedIn, Instagram, TikTok, Threads, Facebook, Pinterest, and Bluesky. You can also schedule posts for future dates and times directly from the Claude Code interface. #### **Do I need coding experience to set up Claude Code for social media?** No. Claude Code runs inside VS Code, the terminal, or the Claude desktop app. The MCP integration with Blotato follows a guided setup process. Skill files are written in plain markdown. If you can write a Google Doc, you can build a Claude Code skill. #### **How much does this Claude Code social media setup cost?** For this setup, a Claude Pro plan is the entry point, at $20/month billed monthly or $17/month on annual billing. Blotato starts at $29/month, and that Starter plan covers 20 connected accounts. On monthly billing, the total baseline is $49/month for an automated social media system across the nine platforms Blotato publishes to. One thing worth knowing before you plan around it: Blotato's 7-day trial excludes API access, so generating an API key starts the paid subscription. If you are setting this up for MCP, plan on starting the subscription rather than trialing it. Token-heavy tasks like batch scheduling work best on Sonnet 5.5 with low effort settings. #### **What is the difference between a Claude Code skill and a regular AI prompt?** A skill is a reusable markdown file that persists across conversations. It contains your voice rules, platform-specific formatting, character limits, hashtag preferences, and content strategy guidelines. A regular prompt is one-and-done. Skills compound in quality over time as you refine them based on output. #### **Can I repurpose YouTube videos into social media posts with Claude Code?** Absolutely. Blotato includes a YouTube transcript scraper in its MCP. You provide a video URL, Claude Code pulls the transcript, and your skill file guides the AI to write platform-specific captions. One 20-minute video can produce dozens of posts tailored to each platform's format and audience. #### **Can AI manage my social media?** It can manage the production and the publishing. It cannot manage the judgment, and that distinction is the whole game. What I have running handles transcription, caption drafting, scheduling, and posting across six platforms without me opening a dashboard. What it does not do is decide what is worth saying. Every post still starts from something I actually recorded or thought. The people who hand an AI social media manager the whole job end up with a feed nobody reads, which is the failure mode I wrote about in [how to avoid AI slop](/avoid-ai-slop/). Automate the distribution, keep the point of view. #### **How much is an AI social media manager?** The software runs $20 to $200 a month depending on how many accounts you connect and whether you need analytics on top. My own stack is $49 a month: Claude Pro at $20 and Blotato at $29. A human social media manager in the US runs several thousand a month, and a freelancer managing a couple of channels typically lands somewhere between $500 and $2,000. The honest comparison is not software versus person, though. Software replaces the tab-switching and the copy-pasting. It does not replace the person deciding what your brand should say this week. --- ## How to Use Nano Banana in Claude Code (Full Setup) URL: https://ryandoser.com/nano-banana-claude-code/ Markdown: https://ryandoser.com/nano-banana-claude-code.md Published: 2026-07-24 | Updated: 2026-07-24 Categories: AI Tutorials, Claude Code > Learn how to use Nano Banana 2 in Claude Code to generate high quality AI images for about 7 cents each. Real setup and cost example included. **The following guide shows how to use Nano Banana in Claude Code** for generating high quality AI images without leaving your terminal. This is one of the most practical image generation setups running in Claude Code right now. Here's how to get it working. ### **How Nano Banana in Claude Code Works** Most people using Claude Code for content work still copy-paste prompts into Midjourney or fire up a separate image tool. That adds friction. Connecting Nano Banana to Claude Code removes it. Nano Banana is the nickname for Google's Gemini image models. Two versions matter here. Nano Banana Pro (Gemini 3 Pro Image) launched in November 2025 as the high-fidelity model. Nano Banana 2 (Gemini 3.1 Flash Image) followed in February 2026 as the faster, cheaper option that keeps most of Pro's quality. For everyday content work, Nano Banana 2 is the one I reach for. It runs about 7 cents per standard image through OpenRouter, while Nano Banana Pro costs roughly double for its top-fidelity output. When you're generating thumbnails, social graphics, or client assets at scale, that gap adds up fast. If you're weighing image models, my breakdown of [ChatGPT Images 2.0 versus the alternatives](/chatgpt-images-2-0/) covers where each one wins. **Nano Banana 2 vs Nano Banana Pro** | Model | Gemini name | Released | Approx. cost per 1K image | Best for | | Nano Banana 2 | Gemini 3.1 Flash Image | Feb 2026 | ~$0.07 | Fast, cheap, everyday content | | Nano Banana Pro | Gemini 3 Pro Image | Nov 2025 | ~$0.13+ | Max fidelity, complex composites, text-in-image | The setup runs through the API, not the Gemini web app. Two paths exist: Google AI Studio (free, direct) or OpenRouter (what I use). OpenRouter consolidates every model under one API key. Google, Anthropic, OpenAI, one key, one dashboard, one place to track costs. ### **How to Set Up Nano Banana in Claude Code** You've probably heard "just get an API key" before. Here's the actual process, step by step, so you don't have to figure it out. - **Sign up for OpenRouter.** Create a free account at [openrouter.ai](https://openrouter.ai) and add $5-10 in credits. - **Create an API key.** Go to API Keys, click Create, name it something like "claude-code," and copy the key. - **Store the key in Claude Code.** Paste a prompt that saves the key and links the model page as context (exact prompt below). - **Test with one image.** Ask Claude Code to generate a simple image using your OpenRouter key. The file saves straight into your workspace. For step 3, paste this into Claude Code: > Store this API key from OpenRouter to generate images with Google's Nano Banana 2 AI image model. [paste your key]. Here's the OpenRouter documentation for Nano Banana 2 for more context. [paste the model page URL] The model page is the [Nano Banana 2 listing on OpenRouter](https://openrouter.ai/google/gemini-3.1-flash-image) (model ID `google/gemini-3.1-flash-image`). Copy that page and include it as context. More context means better output. If you already have an OpenRouter key in an `APIs.env` file, Claude Code updates it automatically. If not, it creates a new file. Either way, the key gets stored. To test it, prompt: "Generate a realistic image of [location] using Nano Banana 2. Use my OpenRouter API key." That explicit reference matters on the first run. Claude Code remembers it after that. The result saves as an image file in your workspace. *Google AI Studio's API Keys page -- where you create the key that connects Claude Code to Nano Banana 2.* ### **Using Claude Skills to Generate Thumbnails with Nano Banana** Asking Claude Code to "make me a thumbnail" in a chat gives you a generic result. That's not a knock on the model. It's a prompt problem. Skills solve this. A skill is a Markdown file that gives Claude Code persistent context, rules, and instructions for a specific task. Two skills drive the thumbnail workflow I showed in the video: a Nano Banana API best practices skill and a YouTube thumbnail designer skill. [My Claude Code Skills Stack](https://skills.ryandoser.com/) has 20+ skills I use daily to automate marketing and content creation with a one time fee and lifetime updates. The Nano Banana skill was built fast. I pulled the [official Gemini image generation documentation](https://ai.google.dev/gemini-api/docs/image-generation), copied it as Markdown, and said: "Make me a skill file with best practices for generating images with Nano Banana." Done. The thumbnail designer skill took more work. It holds years of knowledge about what makes a thumbnail drive clicks. Both skills are available inside my AI Marketing Insiders community if you want the shortcut. Here's the actual prompt structure I used in the video: > I need you to design a YouTube thumbnail using the YouTube Thumbnail Designer skill. Take the thumbnail from [reference video URL] and make the following changes: change the text from "unstoppable" to "game changer" and remove the headshot. Keep everything else the same, including image dimensions. Use Google Nano Banana 2 through the OpenRouter API. Use the Nano Banana API best practices skill. Claude Code ran Opus for this one. It generated three output files -- original, draft, and final. The result matched the brief exactly: text updated, headshot removed, dimensions intact. ### **The Headshot Problem (And the Real Workflow)** Here's the honest take on AI image models and headshots: they're not reliable yet. I tested adding my headshot inside Claude Code. The model placed it, but it covered the text. Positioning was off. That's where these models still fall short for compositing real faces onto designed layouts. My actual workflow: generate the thumbnail without a headshot. Leave clean space on the right side. Export it. Drop it into Canva or Photoshop, drag in your PNG cutout, and save. Adds 30-60 seconds. Keeps quality high. *OpenRouter Logs showing a Nano Banana 2 image generation at $0.0679, roughly half the cost of the higher-fidelity Nano Banana Pro model.* The bigger point here is the feedback loop. Every time you adjust a thumbnail, Claude Code can update the skill file based on that conversation. You'd say: "Update my YouTube thumbnail designer skill based on this chat." Over time the skill file captures more of your rules and your prompts get shorter. That's the actual power of this system. The same terminal workflow carries over to other visual assets. I use Claude Code to [generate on-brand infographics](/automate-infographics/) with Nano Banana, and to [create AI video in Claude Code](/claude-code-ai-video/) through a separate video model wired up the same way. ### **Ryan's Final Thoughts** **How to use Nano Banana 2 in Claude Code** comes down to three things: store your API key, build the right skills, and use reference inputs instead of vague prompts. The cost is low. The output is solid. When Google releases the next image model, update the skill file and move on. The system stays intact. Start with a simple test image. Build your skills. Let Claude Code handle generation while you focus on content. ### **Nano Banana Claude Code FAQs** #### **What is Nano Banana 2 in Claude Code?** Nano Banana 2 (Gemini 3.1 Flash Image) is Google's fast, low-cost AI image model that you can access inside Claude Code via the API. You store an API key from Google AI Studio or OpenRouter, then prompt Claude Code to generate images using that key. It costs about 7 cents per standard image through OpenRouter. #### **How do I set up Nano Banana 2 in Claude Code?** Get an API key from [Google AI Studio](https://aistudio.google.com) or OpenRouter. In Claude Code, paste a prompt that stores the key and includes the model documentation as context. Test with a simple image prompt referencing your API key. Claude Code saves it locally and uses it for all future image generation. #### **What is the difference between Nano Banana 2 and Nano Banana Pro?** Nano Banana Pro (Gemini 3 Pro Image, November 2025) is the high-fidelity model built for complex composites and accurate text-in-image. Nano Banana 2 (Gemini 3.1 Flash Image, February 2026) is the newer, faster, cheaper option at about 7 cents per image versus roughly double for Pro. For everyday thumbnails and social graphics, Nano Banana 2 is the better value. For maximum fidelity, use Pro. #### **Can I use Nano Banana 2 without coding skills?** Yes. Claude Code handles all the API calls. You write plain-English prompts. The only technical step is getting an API key and pasting a setup prompt. If you use Claude Code skills (pre-built Markdown files), you reduce the prompt work even further. #### **How do I use Claude Code skills with Nano Banana 2?** Create a Markdown file with your image generation rules and best practices. Save it as a skill in your Claude Code workspace. Call it by name in your prompt. For thumbnails, I run two skills together: a Nano Banana API best practices skill and a YouTube thumbnail designer skill. That combination gives me consistent, on-brief results far more often than a cold prompt does. --- ## Can Open Source AI Models Beat Claude at Web Design? URL: https://ryandoser.com/open-source-ai-web-design/ Markdown: https://ryandoser.com/open-source-ai-web-design.md Published: 2026-07-24 | Updated: 2026-07-24 Categories: AI Tutorials, Claude Code > I tested 6 open source AI models for web design against my live Claude site. See which won, real costs, and how they compare. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* ### **Open Source AI Models for Web Design Video Guide** I rebuilt ryandoser.com on a stack of Claude Code, GitHub, Cloudflare, and the Astro web framework. Then I ran a test to see what the budget models could do with the same job. Here is the setup. My current homepage was designed using Opus 4.8 inside Claude Code. I wanted to know if open source models could rebuild it for a fraction of the cost. So I redesigned the same homepage across six models, five open source plus GPT 5.6 Soul as a frontier benchmark, and compared every result to what I already have live. If you want the full walkthrough of the stack itself, I broke down my move off WordPress in my guide on how to [build a website with Claude](/build-a-website-with-claude/). This post is the model bake-off that came after it. I am a non-technical marketer, and this whole test cost me pocket change. If you want the exact tools, skills, and automations I run, grab my free AI Marketing Essentials Guide linked in the video description. #### **How I Ran the Test in OpenRouter** You need one platform to test every model side by side, and mine is [OpenRouter](https://openrouter.ai/). It gives you one API key that reaches almost every model, open source or frontier, without separate accounts for each provider. Signing up is free. You add credits to reach the paid models, and for website design work, 10 to 15 dollars of credits is plenty. Then you create an API key under the API Keys tab and sync it into whatever coding setup you use. *Creating an OpenRouter API key, the one connection that lets me test every model in the same environment.* I run the Claude Code extension in VS Code, but this works in Cursor, the terminal, the Claude desktop app, or Google Antigravity too. I lined up a separate chat for each model and pointed every one at the same task. If you want my exact OpenRouter wiring, I documented it in my [Claude Code OpenRouter setup](/claude-code-openrouter/) guide. ### **The Open Source AI Models for Web Design I Actually Tested** I gave every model the identical prompt so nothing skewed the comparison. Here is how each one handled a full homepage redesign. Five open source models went head to head: [Kimi K3](https://www.kimi.com/), [GLM 5.2](https://z.ai/), [DeepSeek V4 Pro](https://www.deepseek.com/), [Qwen 3.7 Max](https://qwen.ai/), and [MiniMax MiMo V2.5](https://www.minimax.io/). I also threw in GPT 5.6 Soul on high reasoning effort through OpenAI's Codex extension as a frontier benchmark. My live site, built with Opus 4.8, was the target to beat. #### **Kimi K3** Kimi K3 was the surprise of the group. It cost the most of the open source bunch at roughly 30 cents, and it earned that spot. *One of the open source redesigns rebuilding the blog section of my homepage from the same prompt.* The logo in the top left got mangled, and a few small brand details were off. But the copy read well, the images landed correctly, and most of the logos rendered right. For 30 cents on a first pass, it was genuinely workable. I could send it back for a revision round and ship something close to production. Among the open source models, Kimi K3 took the top spot. #### **GLM 5.2** GLM 5.2 was the cheapest run at about 2 cents, and the output showed the tradeoff. The menu looked decent and the branding held together in places. But it botched the logo the same way Kimi did, and it broke the terminal element in the hero section. At first glance it did not impress me the way Kimi did. Cheap does not always mean usable. #### **DeepSeek V4 Pro** DeepSeek stepped things up. Right away I liked how it handled the logos and the metrics row. It nailed the testimonials, placed the client logos correctly, and included the latest-from-the-blog section. I would rank it above GLM, though Kimi still edged it out. This is a model I would trust for a structured layout with real content blocks. *A redesign rebuilding the pricing tiers, press logos, and testimonials section, with a few details still off.* #### **Qwen 3.7 Max** Qwen, owned by Alibaba, gave me one of my favorite first impressions. The layout felt clean, the logos were solid, and the testimonials rendered well. The free opt-in guide buttons broke, and the blog posts came out scrambled. Still, with the correct image files and a skill markdown file for context, this is a strong V1 you could push toward production fast. #### **MiniMax MiMo V2.5** MiMo was the bargain pick, one of the cheapest runs of the group. I threw it in after spotting it on the model leaderboard chart. The result was workable but rough. It needed the most cleanup of anything I looked at. Not terrible, just clearly the weakest of the six at first glance. You get what you pay for at the very bottom of the price range. #### **GPT 5.6 Soul** GPT 5.6 Soul on high reasoning effort was the clear winner, and that was no shock. It is a frontier model from OpenAI, not an open source one. Above the fold it looked dramatically better than the five cheaper options. The featured-in row, the brands section, and the footer all held together. It was the strongest output by a wide margin. It confirmed the pattern: you can close the gap with open source, but the top frontier models still lead on raw design quality. Here is how the six models stacked up at a glance. | Model | Type | Approx. cost | My rank | Standout / weak spot | | GPT 5.6 Soul | Frontier | Highest | Best overall | Cleanest above-the-fold layout | | Kimi K3 | Open source | ~30 cents | Best open source | Strong copy and images, logo glitch | | DeepSeek V4 Pro | Open source | Low | Runner-up | Solid logos, metrics, testimonials | | Qwen 3.7 Max | Open source | Low | Close behind | Clean layout, broken opt-in buttons | | GLM 5.2 | Open source | ~2 cents | Weak | Cheapest, botched logo and terminal | | MiniMax MiMo V2.5 | Open source | Low | Weakest | Workable but needed the most cleanup | ### **What the Cost Comparison Actually Showed** Here is the part that changes how you should think about token-heavy design work. The price gap is enormous. Kimi K3 topped the open source group at about 30 cents. GLM 5.2 ran near 2 cents, and MiMo and Qwen came in even cheaper. I pulled the exact per-run token costs from the OpenRouter logs, then mapped those same token counts onto the premium models to see the gap. *Priced against the same token usage, the redesign task would have cost roughly 5x more on Opus 4.8 and 10x more on Fable 5.* Run at the same token usage, the workflow would have cost about 5x more on Opus 4.8 and 10x more on Fable 5. If you run design work at scale, that multiple compounds fast across hundreds of pages. Quality is still the deciding factor. I hate sacrificing it, and none of the open source outputs matched my live Opus 4.8 site. The difference was night and day. But if you are generating token-intensive landing pages in volume, it is worth rethinking whether you need the most expensive model for every single pass. Lean on strong context and systems, and a cheaper model can carry more of the load than you would expect. For a wider look at what I actually reach for, see my roundup of the [best AI coding tools](/best-ai-coding-tools/). ### **Ryan's Final Thoughts** Open source AI models for web design are not ready to replace a frontier model on quality, but they are far closer than the price suggests. Kimi K3 led the open source pack, DeepSeek and Qwen were close behind, and most results landed as a workable first draft. If you build websites in volume and pair a cheap model with solid context, the math starts to make sense. The stack that made this test possible was Claude Code, [GitHub](https://github.com/), [Cloudflare](https://www.cloudflare.com/), and [Astro](https://astro.build/), and I packaged the whole build into a skill inside my **[Claude Code Skills Stack](https://skills.ryandoser.com)**. If you want to try the same workflow yourself, that is where I would start. ### **Open Source AI Models for Web Design FAQs** #### **Can open source AI models build a website as well as Claude?** Not quite, based on my test of six models. Open source options like Kimi K3, Qwen, and DeepSeek produced workable first drafts, but none matched my live homepage built with Claude Opus 4.8. They get you most of the way there for a fraction of the cost, which is enough for iterative work but not a one-shot final build. #### **Which open source AI model is best for web design?** In my test, Kimi K3 produced the best open source homepage redesign, with DeepSeek V4 Pro and Qwen 3.7 Max close behind. Kimi handled copy, images, and most logos well. GLM 5.2 and MiniMax MiMo V2.5 were the weakest of the group, though still usable as rough starting points. #### **How much does it cost to test AI models for web design in OpenRouter?** Very little. My open source runs cost between roughly 2 and 30 cents each for a full homepage redesign. Adding 10 to 15 dollars of OpenRouter credits is enough to test every model several times over. The same task on premium models like Opus 4.8 or Fable 5 costs 5x to 10x more. #### **Do I need to know how to code to use these models?** No. I am a non-technical marketer, and I ran this entire test using Claude Code inside VS Code with an OpenRouter API key. You point the model at your project, give it a clear prompt, and review the output. The learning curve is the setup, not the coding. See my [guide on vibe coding websites with Claude Code](/vibe-code-websites-claude-code/) for the beginner path. --- ## How to Sell Claude Skills as a Digital Product (And Make $1000s) URL: https://ryandoser.com/sell-claude-skills/ Markdown: https://ryandoser.com/sell-claude-skills.md Published: 2026-07-24 | Updated: 2026-07-24 Categories: AI Side Hustles, AI Tutorials > Learn how to sell Claude skills as a digital product. I share the exact stack and workflow that made me over $3,000 in 30 days. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* ### **How to Sell Claude Skills (Chris Koerner Podcast Episode)** The clip below is from my recent appearance on The Koerner Office, where I broke down exactly how I monetize Claude skills and why this window is wide open right now. If you want the actual pack I sold to hit that number, you can grab it on my [**Claude Code Skills Stack**](https://skills.ryandoser.com/) page. It is the same set of skills I run my own marketing agency on. *The Claude Code Skills Stack landing page that has made over $3,000 passively.* ### **What a Claude Skill Actually Is** Most people think a Claude skill is some technical add-on. It is not. A Claude skill is a standard operating procedure for AI. One skill per task. One recipe per job. I keep mine granular. I have an SEO blog post writer skill. A separate email newsletter skill. A separate sales email skill. Each one is a single markdown file with the steps, voice rules, and output format baked in. This is how to sell Claude skills the right way. You are not selling software. You are selling expertise written in a format an AI agent can follow exactly. That makes packaging Claude skills more like selling a recipe book than building an app. If you have built a custom GPT or a Claude project, you already have the raw material. Just repackage it. ### **Why Now Is the Window to Monetize Claude Skills** Everyone points at the Apple App Store. Millions of apps, crowded discovery. The smarter move is one layer deeper: Chrome extensions, Shopify apps, Notion templates. Skills sit in that same gap. The Claude skill stack idea works because power users of [Claude](https://claude.ai/) and Claude Code will pay for prebuilt systems. They are already spending $20 to $200 a month on the platform. Three reasons this is the moment to sell AI skills online: - Skills update in real time. Tell the skill what went wrong, it patches itself, and the next user gets the better version. - Skills are portable. If you switch to a different AI coding agent, your markdown files come with you. - The Claude code passive income angle is real. The product is a folder of text files. No hosting, no servers, no logins to support. ### **How to Package Claude Skills Into a Digital Product** Here is the workflow I actually use. None of this requires a technical background. I do not come from one either. #### **Step 1: Pick the task you already do** Stop trying to invent a product. Open your calendar. What did you do this week that someone else would pay to skip? Blog writing, sales emails, podcast outlines, listing descriptions, gardening schedules, donor thank-you letters. Nothing is exempt. A 10-year-old could build a skill for chores. #### **Step 2: Voice-dump it into Claude** Open the Claude app on your phone. Hit voice transcribe. Brain dump every step, every rule, every gotcha you know about that task. Talk like you are training a new hire. End with: "Use the skill creator skill at the end." That one prompt turns a 5-minute ramble into a working skill file. This is the part most people overcomplicate. It is a voice note with one closing instruction. *One prompt turns an existing Claude project into a reusable skill markdown file.* #### **Step 3: Use it on real work** Run the skill on actual client work. When the output is off, tell it to fix the rule. The skill updates itself in place. After a week of real use, it will be sharper than 95% of what is out there. #### **Step 4: Bundle and sell** Group 3 to 10 related skills into a stack. Niche down: AI marketing, SEO, ecommerce, real estate, nonprofit fundraising. Sell it as a zip or a private repo. Stripe handles checkout. My [Claude Code Skills Stack](https://skills.ryandoser.com/) is markdown files wrapped in a landing page. People are not buying code. They are buying a packaged Claude skills digital product. ### **Selling Markdown Files: Honest Pros and Cons** Selling markdown files is not magic. It works, but there are tradeoffs worth naming. What is great: - Production cost is near zero after v1 - Buyers can fork and customize without breaking your version - The [Anthropic skills repo](https://github.com/anthropics/skills/tree/main/skills) sets the format your files should match - Add an auto-improvement layer with [Karpathy's autoresearch pattern](https://github.com/karpathy/autoresearch) so skills patch themselves What is hard: - Buyer education. Most people still default to ChatGPT. Expect to explain what a skill is. - Piracy risk. It is a text file. Compete on updates and support, not lockdown. - Niche beats volume. A focused stack for one job beats a 50-skill grab bag. ### **What Sells and What Doesn't** Not every skill is worth selling. After watching what buyers actually pay for, the line is clear. What sells: specific, production-ready workflows that replace real manual work. An SEO blog post writer that ships a publish-ready draft. A LinkedIn outreach skill that scores leads. A niche stack for one job, like real estate listings or nonprofit donor letters. What rarely sells: generic prompt wrappers. "Write better code" or "make my emails clearer" is a hard sell, because the buyer can already prompt that in ten seconds. If a skill only restates what Claude does out of the box, most people will not pay for it. The rule is simple. Sell the workflow you would charge a client for, not the prompt anyone could type themselves. ### **AI Digital Products to Sell Alongside Your Skill Stack** A skill stack is one product. The same workflow scales sideways into other AI digital products to sell: - A skill plus a paid consulting hour to install it for the buyer - A skill plus a Loom walkthrough of you running it on real work - A LinkedIn profile scraper skill paired with [Apify](https://apify.com/) actors for outreach teams - A social scheduling skill plus a connection to [Blotato](https://www.blotato.com/?ref=rdoser) via MCP so the buyer can post directly from Claude Code Stack the offers. One buyer, three price points. *A LinkedIn scraper skill paired with Apify produces a clean engagement-scored content audit.* ### **Ryan's Final Thoughts** Most people are still copy-pasting prompts into ChatGPT. The leap to building and selling skills is smaller than it looks, and the payoff compounds because every skill you ship is also a skill you use. Pick one task, voice-dump it tonight, and ship a v1 by the weekend. The window is open right now. Big thanks to Chris at [The Koerner Office](https://www.youtube.com/@thekoerneroffice) for letting me dig into this on the show. You can also find him on [LinkedIn](https://www.linkedin.com/in/cjkoerner). ### **Sell Claude Skills FAQs** #### **How much can you actually make selling Claude skills?** My first skill stack made over $3,000 in roughly 30 to 45 days, passively, with no paid ads. That number is a baseline I hit while running my agency work in the background. Bigger niches and bigger audiences scale further. #### **Do you need to be a developer to sell Claude skills?** No. I am non-technical and so are most buyers. If you can use ChatGPT, you can build one. The process is voice transcribing your knowledge into the Claude app and ending with the skill creator prompt. #### **Where do you sell Claude skills?** A simple landing page with Stripe checkout is enough. Host the files in a private repo or a zip download. You do not need a marketplace or an app store to monetize Claude skills. #### **Can you reuse old GPTs or Claude projects as skills?** Yes. If you built a custom GPT or a Claude project, the prompts transfer almost directly. Repackage them as markdown skill files and you have a v1 in under an hour. #### **What is the best Claude skill to build first?** Build one for the task you do most often. That way you use it daily, refine it fast, and write marketing copy that sounds real because you live the problem. --- ## 7 Years Ago I Left Corporate America (AI Has Changed Everything Now) URL: https://ryandoser.com/seven-years-self-employed/ Markdown: https://ryandoser.com/seven-years-self-employed.md Published: 2026-07-23 | Updated: 2026-07-23 Categories: AI Resources > I left a stable corporate marketing job 7 years ago. Here is what AI has changed about marketing, careers, and what a solo operator can build now. July 2019, day one of working for myself. I was 23. *Day one of entrepreneurship in July 2019. A hungry 23 year old at the time.* That badge on the wall is the part I notice now. One chapter had not come down before the next one started. ### **What the Photo Does Not Show** This looks like a leap. It did not feel like one, because I had been building the replacement for over a year. About two months into my corporate job, I started a blog and taught myself SEO, then affiliate marketing, then email, spinning up sites outside work hours to see what would happen. None of it was a plan to quit. Then I got my first client, and the question stopped being "should I risk this" and became "why am I still doing both?" ### **The Line That Made Me Go** One line from *[The 4-Hour Workweek](https://fourhourworkweek.com/)* stuck with me: most people choose the path of unhappiness over uncertainty because of fear of the unknown. I am grateful for that job. Running multi-million dollar paid budgets for *People*, *Better Homes & Gardens*, and dozens of other titles at 22 was an incredible place to learn, and that team gave me my start. I just wanted to build something of my own, which is more or less [what I have been doing ever since](/about/). ### **AI Rewrote the Job I Left** The parts of my 2019 job that ate the most hours are the parts AI absorbed first. Pulling reports, building keyword grids, producing the first draft nobody keeps. My [Claude Code](/why-marketers-should-use-claude-code/) and [Codex](https://developers.openai.com/codex/) setup has moved my solo output 10x to 100x depending on the task. This site is the honest example. I [rebuilt it in Astro myself](/build-a-website-with-claude/), and it runs SEO and publishing systems that would have taken a developer, a writer, and a strategist in 2019. That is why one person can now compete with an [agency](/ai-replacing-marketing-agencies/). ### **Lessons I Have Learned Along the Way** Seven years of running this alone surfaced a handful of things I would actually defend. Here they are. #### **Expertise Comes First, Tools Come Second** AI is close to irrelevant if you do not know how to move the needle on the task in front of you. It will happily produce a thousand words of confident nonsense, and you have to already know enough to catch it. The SEO background I built at night in 2019 is what makes my AI output any good. I know what a ranking page looks like, so I know when a draft is not one. The tools did not give me judgment. They removed the ceiling on how fast I could apply it. #### **The Resistance Is Never Actually Technical** Every week a marketer tells me [Claude Code](/why-marketers-should-use-claude-code/) is too technical for them. I get it, I felt the same way for months before I opened it. Then I did, and found out it is mostly a chat window and some markdown files. The gap is rarely skill. It is willingness, and that is the one that actually compounds. From what I see across my audience and client work, very few marketers are doing their day-to-day work inside an AI coding agent, and it is not because the rest of them could not learn it. #### **Package What You Already Know** I used my own marketing skills on client work for months before it clicked that people kept asking me for them. Eventually I stopped treating them as private tooling and [turned them into a product](/sell-claude-skills/). It has since done over $10,000 with almost no ongoing work. The lesson is not "sell a digital product." It is that the thing you built for yourself, the boring internal system nobody was supposed to see, is often the most valuable thing you own. #### **Build Assets That Compound** Hours do not compound. You sell them once and they are gone. A [blog post](/ai-seo-system/), a video, an email list, or a skill file you own keeps working long after the day you made it. My best YouTube videos are keyword-based, not viral. They did not spike and disappear. They rank, they sit there, and they still bring in clients years later. That is the whole difference between content as marketing and content as a lottery ticket. #### **Personal Brand Is the Hedge Against the Trust Recession** We are at the point where you read something, watch something, listen to something, and genuinely cannot tell whether a person made it. That is the trust recession, and it gets worse from here. Companies that publish only from behind a logo are going to have a harder time with this than ones with a real person out front. That is why I put my name and face on everything I publish, and why [founders should be visible too](/personal-branding-for-founders/). Nearly every good client, partnership, and opportunity I have had in seven years traced back to someone knowing who I was first. #### **Distribution Is the Moat Now** Building stopped being defensible the moment anyone could ship a product in a weekend. What is still hard is getting attention and keeping it. Here is the clearest proof I have. I reviewed a SaaS tool, and my video ranked #1 on YouTube for that tool's own name. The founder noticed, wondered who this guy outranking her product was, and eventually became a client. She was heads down building the software while the search result for it sat there unclaimed. ### **Ryan's Final Thoughts** I would not romanticize this. Seven years in, there are still weeks where I am the strategist, the invoice chaser, and the guy fixing the website at 11pm. If you are sitting where I was, my advice is boring. Build the replacement first, on whatever hours you have, until the step across is short. The tools have never been better and the head start has never been shorter. That is what this picture really is. Not a leap, just the day the thing I had been building became the main thing. --- ## The Brutal Reality of AI in 2026 (From a Marketer) URL: https://ryandoser.com/reality-of-ai-in-2026/ Markdown: https://ryandoser.com/reality-of-ai-in-2026.md Published: 2026-07-20 Categories: AI Rabbit Holes > The reality of AI in 2026 from a working marketer: why the model race stopped mattering, and the portable system to build instead. I sat down with Marlon Roldan to talk through the **reality of AI in 2026**, and the honest version is less exciting than your feed suggests. ### **The Reality of AI in 2026 Video Guide** Most AI content is built to make you feel behind. This conversation goes the other direction. I run a six-figure marketing agency, and that work is about 75% of what I do. The rest goes into my YouTube channel, where the whole premise is showing what actually applies to real client work instead of reacting to every model release. If you want to go deeper on the systems side of this, I put together a **[Claude Code Skills Stack](https://skills.ryandoser.com/)** with the skills and workflows I use daily. *My actual working setup: Claude Code running as an extension inside VS Code, with client folders and skills on the left.* ### **Why the Models Are Already Good Enough** Here is the part nobody monetizes: the model race stopped mattering for most of us. Somewhere around Opus 4.5, in my experience, the models got good enough to handle something like 99% of knowledge work. Drafting an email. Writing content. Making an image. Building a landing page. I am not talking about frontier research or complex engineering. I mean the work most people actually do between 9 and 5. So when GPT 5.6 ships on a Tuesday, Fable 5 shipped the week before, and Opus 4.8 the week before that, the correct response is usually nothing. You do not need to drop your work and test it. Stop asking which model to use. Ask whether your systems are built so the answer never matters. The Opus 5 slump later that summer was a live test of this idea, and I wrote up [why switching to Opus 5.5 took zero rebuilding](/best-claude-model-for-writing/). That reframe changes what you spend your time on. Instead of testing releases, you go find the bottlenecks. What is eating the most hours in your week? What is costing you the most money? As a solopreneur, I look at the SaaS tools I pay for and ask whether a model plus a system replaces one of them. The same math applies to which model you run, since a [cheaper open source model can do more of the work than you expect](/open-source-ai-web-design/) once the system around it is solid. Swap two or three of those and the savings add up fast at scale. ### **Building a Model Agnostic AI System** Ask yourself a harder question than “is AI hype real.” Ask what happens to your work when your favorite tool disappears. I use VS Code as my interface, with the Claude Code extension and Codex both connected. That choice is deliberate, and slightly paranoid. If I worked inside the Anthropic desktop app, Anthropic has every incentive to make competing models feel worse in their own product. Same story with the Codex app. A neutral editor gives me fairer play across Anthropic, OpenAI, Google, and open source models. The bigger reason is portability. Everything lives in local files and folders on my machine, backed up to Google Drive. If Claude Code and Codex both vanished tomorrow, I would install whatever coding agent replaced them, point it at the same folders, and it would pick up where the last one stopped. Compare that to building projects inside claude.ai or custom GPTs on chatgpt.com. Those live on someone else’s server. You are renting. A few specifics from my setup: - [**VS Code**](https://code.visualstudio.com/) as the IDE, which is free and just a friendlier wrapper around a terminal - **Claude Code** (requires a paid Claude plan, minimum $20/month) plus **Codex** for a second opinion - An **AGENTS.md** file as the brain, which Codex responds to better than a CLAUDE.md when you run multiple agents - **MCP, API, and CLI connections** to DataForSEO, my social tool, and Google Search Console That last point matters more than it sounds. I rarely leave the editor, because every tool I need is already connected to it. I use Opus 4.8 for most work on the $100/month max plan. If you are on the $20 plan, Sonnet 5 is your realistic default, and it handles most knowledge work fine. ### **Context Is the Only Real Moat Left** Everyone has the same models. Almost nobody has your context. I vibe coded my own second brain, a notes vault that automatically saves a markdown file of every Claude Code and Codex conversation. What did I work on, what were the decisions, what were the takeaways. It spans back to March now, and it backs up to Google Drive automatically. *The notes vault living locally inside my workspace, capturing conversation context automatically.* The client version of this is where it gets valuable. On one large SaaS account, every meeting, every podcast appearance, and every weekly office hours session with customer questions gets saved into a growing pile of context. When I write SEO content for them, the AI reads that pile. The result is an article the competition physically cannot recreate, because they do not have the raw material. Most competitors open the front page of Google and rewrite the same five articles into a sixth. You probably already have this raw material sitting around. Sales transcripts. Meeting notes. Years of email threads. Organizing it is boring work that takes a few hours. It also compounds for years. The second thing that makes context useful is knowing what good looks like. Telling a model “build me a landing page that makes a million dollars” produces nothing useful, because you have not told it what good means. I know from a decade in marketing that a landing page needs social proof above the fold, a real call to action, proof of results, testimonials, a clear who-it-is-not-for section, and FAQs. That subject matter expertise is what turns a generic skill into a useful one. Which is why I would push you to get granular with [Claude Skills](https://ryandoser.com/claude-skills/). A newsletter email, a sales email, and a drip sequence email are three different jobs. One master “email skill” moves nothing. Three specific ones do. ### **Is SEO Dead, or Just Renamed** AEO. GEO. LLMO. Insert next week’s acronym here. I call it AI search and leave it there. Here is the practical read: yes, you can technically surface in an AI answer without a website, because those systems pull from YouTube, Reddit, and LinkedIn too. For most competitive queries, that is not going to carry you. My own site is the proof I trust most, mostly because the numbers are unimpressive on paper. Ryandoser.com sits around a 20 domain rating. I started publishing on it around February and early March from zero, with no authoritative backlinks and nobody helping. Traffic went up anyway, and I credit two things. The first is the YouTube channel at roughly 37,000 subscribers. My read is that the brand presence carries weight, though I cannot prove the mechanism. The second is repurposing every long form video into a genuinely well built article. That tactic is old. Doing it well is not. Those articles are AI-assisted, which now also means watermarked, and I wrote up [why Claude watermarks do not worry me](/claude-watermark/) as a publisher. *DataForSEO, the API I connect to Claude Code for keyword and SERP data.* I built a skill that takes a video URL and a target keyword and writes the post. It embeds the video, adds internal and external links, sets the heading structure, sends an agent to watch the video, pulls screenshots from the meaningful moments, compresses them, uploads them, captions them, and decides where each one belongs. Did version zero work? No. Version three or four is where it started earning its keep. That is the actual lesson. For keyword data, I use [DataForSEO](https://dataforseo.com/) connected over MCP. I put $50 in two months ago and I am still sitting near $45 after running keyword research and SERP analysis constantly. That daily use eventually turned into a [complete DataForSEO review](/dataforseo-review/). Is it as good as [Ahrefs](https://ahrefs.com/) or Semrush? Probably not. It gets you 80 to 85% there, and for most people that is the whole job. I put that question to a proper test in [DataForSEO vs Ahrefs](/dataforseo-vs-ahrefs/), where the answer turns out to depend on whether you are buying data or an index. Those bigger platforms have a moat because of the first party data they collected over years, which is the same moat argument as everything else in this article. Free options work too. Google Trends and Google Keyword Planner cost nothing. ### **How to Tell Real AI Content From Hype** One filter separates the two, and it takes about five seconds. Does it apply to reality? A video titled “new model just dropped” is worth skipping. A tutorial that shows you how to save five hours a week is worth your time. Practical versus theoretical, that is the whole test. X is genuinely good for news and updates. It is also full of AI generated posts with thousands of bookmarks written by people who never built the thing. YouTube is still where the builders are. [Mark Kashef](https://www.youtube.com/@Mark_Kashef) is excellent on Claude Code. Sabrina Ramonov, a friend of mine, actually ships. Two things stop most people, and neither is intelligence. Resistance to change has scared humans since forever, and genuine information overload does the rest. If a new model lands every week, why learn anything today? That logic feels reasonable and it is [the exact trap the hype creates](/ai-anxiety/). ### **Ryan’s Final Thoughts** Most AI content is engineered to make you feel behind, and feeling behind makes people freeze. Ignore the release cycle. Pick one bottleneck, connect one system, and get an hour back this week. I would not sugarcoat the career piece though. If you work a white collar job and never pick this up, the spots get thinner over time. You do not need my Claude Code workflows. You do need enough of an edge that you are not the easy cut. My [study of 1,229 marketing job posts](/research/ai-marketing-jobs/) found that 38.7% already ask candidates for AI skills. [Claude Code for business owners](/claude-code-for-business-owners/) is a reasonable next step if you want one. And if you would rather have a person in the work with you than another article, [the AI Concierge](/ai-concierge/) is built for exactly that. ### **Reality of AI in 2026 FAQs** #### **Is AI hype real or overblown in 2026?** Both. The capability is real. In my own work, current models handle close to 99% of knowledge work tasks like writing, email, and image generation. The hype is in the framing. Most AI content covers model releases rather than practical application, which makes people feel behind without teaching them anything usable. #### **Do I need to switch AI models every time a new one launches?** No. Models are close enough in quality for everyday knowledge work that switching rarely changes your output. Build a system that works with any model instead. Store your files locally, use a neutral editor, and keep your context portable so you can swap models without rebuilding anything. #### **Will AI replace white collar jobs?** Not wholesale, and that is the wrong thing to watch. My honest read is that you become the least equipped person on the team, and that is who gets cut first. Learning to automate even a few hours of weekly work builds enough of an edge that you are not the obvious name on the list during layoffs. #### **What is the best free way to start using AI for keyword research?** Google Trends and Google Keyword Planner both cost nothing and give usable data. If you want API data inside an AI workflow, DataForSEO runs cheap. A $50 balance lasted two months of regular keyword and SERP analysis in my own account. #### **Why use VS Code instead of the Claude or Codex desktop apps?** A neutral editor avoids vendor lock-in. Model providers have an incentive to make competing models perform worse inside their own apps. VS Code also keeps your files local, so if a coding agent disappears, you install a replacement and it picks up from your existing folders. --- ## How to Build and Sell an AI Second Brain (Full Playbook) URL: https://ryandoser.com/ai-second-brain/ Markdown: https://ryandoser.com/ai-second-brain.md Published: 2026-07-14 | Updated: 2026-07-15 Categories: AI Rabbit Holes, AI Side Hustles > How to build an AI second brain from markdown files, then sell it as a service. The full build steps, the audit wedge, and the retainer. The models are rented. The knowledge is owned. This playbook covers how to build an **AI second brain** out of plain markdown files, then how to sell that same build to businesses as a service. ### **AI Second Brain Video Guide** Adam Sandler builds knowledge systems for founders, agencies, and marketing leaders at [The Viable Edge](https://viableedge.com). He came back on AI Rabbit Holes to walk through his setup and the business behind it. Here's the short version of what a second brain is, because you need it before the pitch makes sense. It's a structured, durable body of company knowledge any AI model can search on its own. Documents, decisions, transcripts, brand rules. Organized so an agent knows where to look without being told. You don't need a vector database. You don't need RAG. "You don't really have to worry about the tech stack," Adam said, because most small businesses don't have enough information to justify one. Markdown files are enough. A knowledge base at its most basic form is a folder of documents with mechanisms that let those documents make sense in the context of each other. If you want to go deeper on the systems side of this, I put together a guide covering my own Claude Code setup and the automation stack I run every week. You can grab the **[Free AI Marketing Guide](https://guide.ryandoser.com/)** here. Adam runs his own personal base in [Obsidian](https://obsidian.md/), and I run mine as a plain markdown vault. Neither of us needed anything fancier to start. ### **How to Build an AI Second Brain** Four steps take you from a pile of scattered files to something an agent can actually use. None of them require a database. #### **Step 1: Run an Ingestion Period** Knowledge has to get into the base somehow, and Adam calls this the ingestion period. Every build starts here. His platform does it through an onboarding chat that scans your website, looks at competitors, and takes whatever else you hand it. You do not need his platform to copy the idea. When I do this myself, I point Claude at the company site, whatever call transcripts exist, and the brand docs, then have it draft the first pass. Resist the urge to dump everything in. Most of a historical archive is irrelevant to what the business is doing right now, and hauling all of it in is the fastest way to poison the base. #### **Step 2: Pick the Schema Before You Organize** This is the step people skip, and skipping it is why most knowledge bases rot. Decide what you are documenting before you start filing things. Adam has material laying out a baseline schema of seven core data points, which he says is usually enough to get going. Your client will not know what schema they need. That judgment is the work you are being paid for. Everything hangs off what he calls the spine. What is the one thing the whole business ladders up to? Usually a high-level goal. Structure the rest around it. #### **Step 3: Link Everything So the AI Finds Its Own Way** A folder of documents is not a second brain. The links are what make it one. Adam follows the Karpathy method of wiki linking everything in Obsidian, though he was direct that Obsidian is a preference and not a requirement. The mechanism matters more than the app. Once the linking system is implemented, he says the base can find its own way, so he never has to tell the AI where to look. In practice it "kind of feels like magic." My own vault works the same way. Every Claude Code conversation auto-saves to markdown and backs up to Google Drive daily, wiki-linked to my CLAUDE.md and AGENTS.md files. That is what makes my [self-improving Claude Code skills](/claude-code-autoresearch/) work at all. #### **Step 4: Tier It Into Hot and Cold Context** A base that treats a call from last week the same as a memo from 2021 will drown its own agent. Adam splits out what he calls hot context, the material that matters right now, like summaries of calls from the last two weeks. The detail stays accessible underneath if an agent needs to drill down, but it does not crowd the top. That split is what keeps the base useful past month three. It is also where the recurring revenue lives. That's the product. Now here's the business. ### **Why AI Second Brains Sell Themselves** Most AI projects die in the same place. A business owner asks for an agent that runs their marketing like a fractional CMO, and there's no context behind it. That request is useless without a second brain feeding it. It has to be step one, before any workflow building starts, which is why I keep telling [business owners running Claude Code](/claude-code-for-business-owners/) to fix their context first. The pitch writes itself because most companies are a mess. Their information is scattered across five tools and three generations of employees. You walk in and say you'll get their knowledge in order, structure it, and make them ready for AI without locking them into one provider. *Adam's brand knowledge base dashboard, showing tracked competitors, flagged contradictions, and competitive pulses.* That last part is the close, and it has nothing to do with productivity. If a client hitches their wagon to a knowledge base instead of Anthropic's ecosystem or OpenAI's, they aren't stuck when a provider raises prices or kills a feature they depend on. Their context travels. That's a benefit no model vendor can offer them, and it's the one Adam called one of the biggest in his mind. ### **How to Sell an AI Second Brain as a Service** Adam calls this one of the biggest opportunities in AI right now, specifically for practitioners trying to figure out what to actually sell. It belongs on the short list of [ways to make money with Claude](/make-money-with-claude/) that don't require you to be a developer. Here's how the engagement actually stacks up. #### **Sell the Audit First** My rule: never lead with the build. Lead with an audit, because the audit is what scopes everything after it. Adam has material laying out a baseline schema of seven core data points, which he says is usually enough to get going. The audit hunts for what he calls the company's spine. What's the one thing everything else ladders up to? Usually a high-level goal or objective. The audit does double duty. It scopes the build, and it surfaces disconnects the client didn't know existed. Brand guidelines from 2020 sitting next to a contradictory set from last year. That second part is what earns the next invoice. You're not delivering a document. You're delivering the first honest look at their own information they've had in years. *An agent inside the knowledge base walking through a seven-item list of brand knowledge issues it wants to work through.* On my end, I've found that scraping a company's own website with Firecrawl and asking for a detailed brand guide beats what most companies had on file a decade ago. That's a 20-minute deliverable that reliably makes a prospect uncomfortable, in the good way. #### **Land on a Department, Not the Company** Adam went out of his way to add this one, and it's the part most people get wrong. He's running department-level knowledge bases for clients now, with a hierarchy where separate bases integrate with each other. An SEO second brain is a different animal than an accounting second brain. So you come in smaller. One department, one engagement, faster to deliver, easier to approve. You get your feet wet and build trust before biting off the whole company. Then it expands, because once a knowledge base exists, building agents and tools on top of it becomes much more straightforward. You're setting yourself up for more business, not a one-time invoice. #### **Build the Upsell Ladder Into the Delivery** The ladder is already there if you sequence it right. Markdown gets you started, but it stops paying off once the volume climbs. When a client outgrows files, Adam points to [Supabase](https://supabase.com/) or something like it as the next step, mostly because it's inexpensive, integrates broadly, and has treated him well. He wants to explore Convex next. The path from markdown to a real database is short, and that's the point. You don't need a stack to deliver value on day one, but you do need somewhere to go on day ninety. The rung after that is the interface. A chat box with slash commands confuses people who've never worked that way. A branded markdown file browser or knowledge graph doesn't. *The knowledge graph with a competitor node expanded, showing how each piece of brand knowledge links to the others.* Adam's platform outputs the same body of information through an MCP server, Claude instructions, an Obsidian vault, custom skills, or a Claude plugin. One source, many destinations. #### **Make It Recurring** A knowledge base that nobody tends becomes a graveyard in about a quarter. That's your retainer, and it should be a scoped monthly line item from day one, not a favor you do when a client emails you. Adam describes the maintenance job as a flywheel. How is information ingested? How is it synthesized? How does stale information get archived out of what's currently relevant? That is the hot and cold split from Step 4, except now it is somebody's job. Something has to decide every week what moves down into the archive, and that something can be you. There's a second retainer hiding in here that clients aren't thinking about. Decision logs. Adam has spent two decades in the workforce and has never seen a company track high-impact decisions with the specificity a knowledge base enables. ### **Ryan's Final Thoughts** Most companies don't have an organized second brain, and that gap is what separates the businesses getting real output from AI from the ones burning money on agents that hallucinate their own brand voice. Adam's honest take on the fad question stuck with me. The discipline is here to stay even if the tooling changes, because every model coming next still needs context. He's worth following on [LinkedIn](https://www.linkedin.com/in/adamsandler/) and on the [Viable Edge YouTube channel](https://www.youtube.com/channel/UC8UlBlGqTRNCOiEdWIXNnhg). Start this week with a folder of markdown files and a habit of putting things in it. Then go find one company drowning in its own transcripts and offer them the audit. ### **AI Second Brain FAQs** #### **What is an AI second brain?** An AI second brain is a structured, durable knowledge base that AI models can search on their own. It holds company context like documents, transcripts, decisions, and brand rules, organized so an agent can find what it needs without being told where to look. It's the storage layer that makes your AI outputs specific to your business. #### **How do you build an AI second brain?** Start with an ingestion period to get existing knowledge in, pick a schema before you organize anything, wiki link the documents so the AI can find its own way, then split the material into hot context and archived detail. All four run on plain markdown files, with no vector database required. See the build section above for the full walkthrough. #### **Do you need a vector database for an AI second brain?** No. Adam Sandler builds client second brains on markdown files, and most small businesses don't have enough information to justify RAG or a vector database. Markdown works well with AI, is easy to maintain, and migrates cleanly to a database like Supabase once you actually outgrow it. #### **How do you price an AI second brain build?** Adam positions the build as the opening engagement rather than a one-off project, starting with an audit that scopes the work. Because agents and workflows get built on top of the knowledge base afterward, and because the base needs steady maintenance to stay relevant, the model favors a long-term relationship over a single invoice. Department-level builds let you start smaller. #### **Is second brain as a service a real business?** Adam believes the discipline is durable even as tooling shifts, because every AI model needs context to produce useful work. He also noted a lot of context engineering solutions target software engineers rather than knowledge work, which leaves a gap for non-technical practices. #### **What is the difference between a second brain and a knowledge base?** Adam treats the terms as interchangeable. Both describe collecting, aggregating, and structuring relevant information so it stays durable and can scale. "Second brain" tends to imply personal use while "knowledge base" implies company use, but the underlying structure and benefits are the same. --- ## How I Make Money with Claude Selling Skills ($10K Example) URL: https://ryandoser.com/make-money-with-claude/ Markdown: https://ryandoser.com/make-money-with-claude.md Published: 2026-07-14 | Updated: 2026-07-14 Categories: AI Side Hustles, Claude Code > Learn how to make money with Claude by packaging your expertise into skills and selling them. Real $10K passive income example, step by step. Most advice on how to **make money with Claude** is theory from people who have never sold anything. This is the real workflow I use to earn passive income from Claude skills, backed by an actual Stripe dashboard. ### **Make Money with Claude Video Guide** I broke down the entire system in a recent podcast interview, from building a skill to selling it to driving traffic that converts. The short version: I package my marketing expertise into Claude skills, sell them as a one-time digital product, and let organic traffic do the selling. That product has made over $10,000 since March, and I barely touch it. Here is the part almost nobody tells you. Building the skill is the easy 10%. The money lives in distribution, getting the right people to find it. That is the real lesson of this post, and it is why I can charge for something anyone could technically build. If you want the full system I use to build and sell these, my **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)** gives you the exact skills behind this, ready to drag into your own setup. ### **What It Actually Means to Make Money with Claude** You've probably heard someone claim they told Claude to "do my SEO" and made a million dollars. That is nonsense, and I will not pretend otherwise. Not every experiment I run turns into income, and I would rather show you one that did not: my [AI trading agent test on Robinhood](/ai-trading-agent-robinhood/) has the unglamorous numbers. Here is the honest version. Making money with Claude is not one magic prompt. It is two skills stacked together. First, you learn to create a Claude skill, which is a markdown file that tells the AI exactly how to do a task. Second, you sell that skill as a digital product other people buy once and download. I come from a marketing background, so the word "Claude Code" used to make my brain shut off. Code sounds like developer territory. It is not. I am a non-technical marketer, and Claude Code now runs 99% of my day. If I can do this, you can too. *Claude Code building a custom landing page for a digital product using a reusable skill file.* ### **How to Build a Claude Skill You Can Sell** What if the thing you already know how to do is the product? That is the whole idea here. Take your subject-matter expertise and package it into a repeatable skill. Mine started as marketing SOPs I used for clients. One day people kept asking for my SEO skills, so I bundled them and sold them. It worked. To build your first skill, open Claude and type a forward slash, then pick the Skill Creator. Anthropic includes this in every account for free. Tell it what you want, give it a real example to copy, and it writes a clean skill markdown file you can download. You can also grab a free skill from Anthropic's [official skills repository on GitHub](https://github.com/anthropics/skills) and reshape it. Do not just upload someone else's skill and expect gold. Repurpose it with your own branding, colors, and voice so the output sounds like you. One tip that saves time: voice dump your ideas. I use a speech-to-text tool to talk through exactly how I want something built, then feed that context to Claude. More context in, better skill out. #### **Why Small, Specific Skills Beat One Giant Skill** Do not build one bloated skill that tries to do everything. I have separate skills for listicle posts, local SEO, SEO audits, and full blog posts. Each one is dialed into a single job. A skill crammed with a thousand lines of instructions performs worse than five focused skills. I learned this the hard way. Keep each one granular and it will hit the target far more often. #### **Skills Work Everywhere, Not Just in Claude** Here is what makes a skill worth selling. It is transferable. A skill markdown file works in Claude, ChatGPT, Gemini, Codex, and Cursor. When a new AI coding agent launches next year, your skill still works. Compare that to a custom GPT, where you are locked into one ecosystem. If you want to see how these stack up, I broke it down in my guide on [Claude skills versus custom GPTs](/claude-skills-vs-custom-gpts/). The same ownership question settles [Claude Skills against Gemini Gems](/claude-skills-vs-gemini-gems/), where a Gem buys you Google-native convenience and a skill buys you a file that outlives the platform. That portability is what makes a skill an asset instead of a one-off. ### **Turning a Skill Into a $10K Digital Product** Only 25% of my income comes from products like this. The other 75% is my marketing agency. I say that so you know this is a real, honest number, not a get-rich pitch. The mechanics are simple. You build a skill, use a landing-page skill to spin up a sales page, and connect a Stripe payment link. Claude Code handles the rest. When someone buys, they get a download link. You do nothing unless something breaks. That product has generated over $10,000 passively since I launched it in March. It is a one-time purchase, not a subscription, and it keeps selling because of where the traffic comes from. If you want the deeper build walkthrough, I covered it in my post on how to [vibe code a digital product with Claude Code](/vibe-code-digital-product-claude-code/). One honest warning. Your first version will not be good enough to sell. My landing page took four or five revisions before it converted. Never ship a version zero. Come back, fix the copy, adjust the layout, add testimonials, then ship. ### **Distribution Is the Real Way to Make Money with Claude** You spent hours building a great skill and nobody bought it. That is the trap most people fall into. Building is not the hard part anymore. You can vibe code almost anything in seconds now. The moat is distribution. I drive sales three ways. My YouTube channel with its descriptions and pinned comments. My email list through Kit. And the biggest one, organic search traffic to my website. Most of my product sales come from people reading a blog post, hitting a call to action, and buying. *Google Search Console showing the organic traffic growth that drives most of the digital product sales.* My main distribution play is repurposing every YouTube video into a blog post. Not lazy AI slop. A Claude Code loop takes my video, writes a post in my own words, embeds the video, adds internal and external links, pulls real screenshots, and builds an FAQ. That is how this exact post was made. The second play is listicles. Posts like "5 ways" or "10 best tools" that match what my ideal customer searches. If you want the repurposing system itself, see my walkthrough on how to [repurpose YouTube videos with Claude Code](/claude-code-repurpose-youtube-videos/). *Anthropic's free Skill Creator writing a skill markdown file inside the Claude web app.* ### **Why Your Expertise Matters More Than the AI** Subject-matter expertise matters more now than it ever did. I know that sounds backward in the age of AI, but hear me out. You cannot tell Claude to do your SEO if you have no idea what moves the needle. I started SEO in 2016, competed against Forbes and US News in the senior living space, and those ten years compound into every skill I build. The AI only multiplies whatever knowledge you already bring to it. Most content teaching you to make money online is what I call hype-grifter content. It is theory from people who have never run a real business or served a real client. Learn from people actually in the weeds. Your expertise plus Claude beats a slick prompt every time. For more grounded workflows, my guide on [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) goes deeper. ### **Ryan's Final Thoughts** Making money with Claude comes down to two moves. Package your real expertise into a transferable skill, then build distribution so people actually find it. The building is easy now. The selling is where the work lives. Start with one skill you already know how to do by hand. Sell it once, learn from the results, then double down on whatever channel actually brings buyers. If you want more workflows like this one, I share what is actually working for me each week in my [free AI marketing newsletter](https://guide.ryandoser.com/). ### **Make Money with Claude FAQs** #### **How do you make money with Claude skills?** You build a Claude skill, which is a markdown file that tells the AI how to do a task, then sell it as a one-time digital product. Buyers download it and use it in Claude, ChatGPT, or any AI agent. Sales come from distribution like YouTube, SEO content, and an email list. See the sections above for the full workflow. #### **Can a non-technical person make money with Claude?** Yes. I am a non-technical marketer with no coding background, and Claude Code runs almost my entire day. The Skill Creator writes the code-like files for you. You bring the expertise and the AI handles the technical parts, so you never need to write real code yourself. #### **How much can you make selling Claude skills?** My skill stack product has made over $10,000 passively since March as a one-time purchase. Results depend entirely on your distribution, not on the skill alone. A great skill with no traffic earns nothing, while a good skill with strong SEO and YouTube reach can sell for months. #### **What is the best way to sell a Claude skill?** Distribution wins. Repurpose your videos into SEO blog posts, rank on YouTube and Google, and build an email list you own. Most of my sales come from organic search traffic hitting a call to action inside a blog post, not from paid ads or social media algorithms. --- ## The Claude Code Skills Stack V2 Is Here! (New Updates) URL: https://ryandoser.com/claude-code-skills-stack-v2-update/ Markdown: https://ryandoser.com/claude-code-skills-stack-v2-update.md Published: 2026-07-13 | Updated: 2026-07-13 Categories: AI News, Claude Code > The Claude Code Skills Stack V2 is here: 40+ skills, free lifetime updates, and how I made over $10K from this one digital product. My **Claude Code Skills Stack** just got its biggest update yet, and **V2** is built to outlast any single AI tool. It now ships as a private GitHub repo with more skills, free lifetime updates, and skills that run in Claude Code, Codex, Gemini CLI, Cursor, and any other markdown-friendly AI tool. Here is what changed, why it matters, and how I have made over $10,000 from this one digital product. Want to skip ahead? You can grab the **[Claude Code Skills Stack for $99 one-time here](https://skills.ryandoser.com/)**, with lifetime updates included and no subscription. ### **What You Get in the V2 Skills Stack** The Stack is 40+ skills I use daily to run my marketing business, organized into clear categories: - **SEO skills** for keyword research, content strategy, topical clusters, internal linking, and writers that actually rank. - **Content creation** for email sequences, newsletters, LinkedIn posts, repurposing, and short-form video. - **YouTube skills** for SEO packaging and thumbnails that get videos clicked. - **Design and image skills** for brand kits, logos, social graphics, and infographics. - **Research and strategy** for paid ads, marketing ideas, and competitor research. - **Vibe coding skills** for landing pages, websites, and conversion-focused builds. - **System skills** for building your own skills, MCP setup, and troubleshooting. - **Open source skills** for running the same playbooks on Llama, Qwen, and DeepSeek models. Each one is a documented SOP, not a throwaway prompt. You run it as a slash command and [Claude Code](https://claude.com/product/claude-code) does the job the same way every time, scored against a checklist before you ever see the output. If you are new to this, my guide on [how Claude Skills work](/claude-skills/) breaks down the idea in plain English. That is one skill, one command. Point it at your last blog post and it hands back a LinkedIn post, an X thread, a newsletter draft, and short-form hooks, all in your voice. V2 also sharpens the whole system with an improved `CLAUDE.md` constitution, several rewritten skills, and a stronger [anti-slop](/avoid-ai-slop/) pass. Because the skills are plain markdown files, they are not locked to one tool. The same Stack runs in Claude Code, Codex, Gemini CLI, Cursor, and any other markdown-friendly AI system. The constitution ships as both `CLAUDE.md` and an identical `AGENTS.md`, so you are buying a portable system for your marketing that outlives any single AI tool, not prompts for one app. V2 also changes how the Stack is delivered. It now lives in a private repo you access at checkout, so every new skill I build ships to you free, forever. You grab the whole thing in one step, and getting the latest is a single pull instead of re-downloading files by hand. No code required. ### **How I Made Over $10K From the Skills Stack** I did not set out to build a product. I built these skills to do my own client work faster, then packaged the ones that worked. That decision has now earned me over $10,000, and it is still growing. The systems you build to save yourself time are often worth selling to the people one step behind you. I broke down that playbook in my guide on turning [Claude AI into a side hustle](/claude-ai-side-hustle/), and packaging skills is one of the ten [AI side hustles for marketers](/ai-side-hustles-marketing/) I recommend most. ### **The Search Results These Skills Produce** The reason I trust this system is simple: it is the exact same set of skills I use to grow my own site. Over the last six months, content produced with these skills drove **5.77K clicks and 890K impressions** in Google Search Console. That steady climb in organic search traffic is the compounding growth these skills are built to create. The bigger story is AI search. In the same window, ryandoser.com picked up **12.1K citations across Microsoft Copilot and its partners** in Bing Webmaster Tools. That upward trend line is my site showing up more and more inside AI answers, which is exactly what the anti-slop and GEO skills in the Stack are built to earn. And this isn't vanity traffic. This search and AI visibility has driven over $100K in revenue through new clients, digital product sales, and affiliate commissions. That is the whole point of buying a system instead of prompts. You are not just getting output that reads well. You are getting the playbook behind traffic and AI citations that compound month over month. ### **Ryan's Final Thoughts** V2 is the version I wish I had shipped first. If you want to stop prompting from scratch and start running a real system, this is where to begin. Grab the Claude Code Skills Stack for **[$99 one-time here](https://skills.ryandoser.com/)**, lifetime updates included, no subscription. --- ## Claude Skills vs Gemini Gems: The Real Difference URL: https://ryandoser.com/claude-skills-vs-gemini-gems/ Markdown: https://ryandoser.com/claude-skills-vs-gemini-gems.md Published: 2026-07-13 | Updated: 2026-07-13 Categories: Claude Code > Claude Skills vs Gemini Gems compared honestly. Gems give you Google-native convenience. Skills give you a portable file you own and improve. The honest way to settle **Claude Skills vs Gemini Gems** is to stop comparing feature lists and look at where each one actually lives. A Gem is wired into Google's ecosystem. A Claude Skill is a file you own. Almost every real difference flows from that one split. ### **Gemini Gems, Explained on Their Own Terms** Most comparison posts wave at Gems and move on. Let me actually explain what you are getting, because Gems are good at what they do. *Gemini Gems are Google's custom assistants, built and run inside the Gemini ecosystem.* A Gem is a custom version of Gemini. You give it a name and a set of standing instructions, and it behaves that way every time you call it. Google recommends a four-part structure for those instructions: persona, task, context, and format. That structure is genuinely useful, because it forces you to define who the Gem is, what it does, what background it has, and how the output should look, instead of dumping a vague paragraph and hoping. Gems also take knowledge. You can attach up to ten reference files so the Gem answers from your material rather than its general training. The strongest version of this pulls from Google Drive, where the Gem reads the most recent copy of a file automatically. Update the doc in Drive, and the Gem is already current. For anyone who lives in Workspace, that live link is a real advantage. And a Gem follows you across Google. Build one in the Gemini web app and it shows up in the mobile app and the Workspace side panel without any extra setup. It is free to create on Gemini's standard tier, with paid plans adding higher limits and stronger models. So Gems are not a weak feature. For a Google-native user, they are smooth, free to start, and genuinely connected to your existing files. The question is what that convenience costs you. ### **A Claude Skill Is a File You Own** A Claude Skill starts from a completely different place. It is a folder with a markdown file called SKILL.md inside it, holding your instructions and any reference material you bundle in. *A Claude skill is a portable SKILL.md folder you own and can move anywhere.* Claude does not load every skill at once. It reads the short description of each one, then pulls in the full file only when your request matches. This is called progressive disclosure, and it lets you keep a dozen skills on hand without slowing anything down. If the format is new to you, I broke it down in my guide on [how to create Claude Skills](/claude-skills/). The folder is the whole point. Because a skill is just a file, you own it outright. You can read it, copy it, version it, and move it anywhere a text file goes, with no platform required to keep it alive. ### **The Trade You Make for Google's Convenience** Here is what that Drive-linked, follows-you-everywhere convenience actually costs. A Gem only works inside Gemini. The same integration that makes it smooth also means it never leaves Google as something you hold. There is no author-facing export that hands you a Gem as a portable file you can drop into another tool. You can share a Gem through a Google link, and the other person uses it inside their own Gemini, but nobody walks away with a file. A skill is the reverse trade. It is not wired into a Drive folder, so you do the connecting yourself, and in exchange you get one self-contained unit you can hand to anyone, archive, or open in a plain text editor years from now. If Gemini changed tomorrow, your skills would not care. That same independence shows up in how each handles knowledge. A Gem keeps its reference files in Google's store and stays fresh through Drive. A skill bundles its knowledge into the folder itself, so the notes travel with the SKILL.md as one package. The Gem model is smoother while you stay inside Google. The skill model wins the moment you want something that moves without a Google account in the loop. ### **The Difference That Compounds: Self-Improvement** Portability is the obvious gap. This next one is the quiet dealbreaker, and it has no equivalent on the Gemini side. A Gem is static. You write its instructions, and they stay exactly as written until you go back in and manually edit them. It does not learn from your corrections on its own. A Claude Skill can be patched in place. When Claude makes a mistake mid-task, you correct it once and have it write that fix straight into the skill file. The next time, the mistake is already gone, because the correction lives in the file. Say a skill keeps using a phrase your brand never uses, draft after draft. Rather than deleting it every time, you have Claude add a banned-words line to the file, and it stops for good. With a Gem, that fix only sticks if you remember to open the settings and retype it yourself whenever the instructions need updating. Over months of real use, a skill that sharpens itself pulls away from a Gem that stays frozen. ### **Where a Gemini Gem Is the Right Call** I am not here to talk you out of Gems if they fit. If you already run your day inside Gemini and Workspace, a Gem is the path of least resistance. It is free to start, it reads your Drive files and keeps them current, and it needs zero new tools or accounts. For a casual custom assistant you call up now and then, the ownership question may not matter to you at all. The live Drive link alone can outweigh portability if your whole workflow already sits in Google. Gems are a clean answer for people who are committed to Google's world and want to stay there. ### **How to Decide** The cleanest test is where your work already lives. If your day runs through Gmail, Docs, and Drive, and you want a custom helper sitting right there in the side panel reading your latest files, a Gem fits that life with zero friction. If you are building workflows you depend on for income, ownership and self-improvement stop being optional. A skill you own, can sharpen on the fly, and can move anywhere is worth far more over time than a setup locked to one company, however smooth that setup feels today. If you want a ready-made set instead of building from scratch, I packaged the exact skills I use to run my business into the [AI Skills Stack](https://skills.ryandoser.com/), so you can start from proven files. For how this same logic plays out against OpenAI's side, see my breakdown of [Claude Skills vs Custom GPTs](/claude-skills-vs-custom-gpts/). I also ran [Claude Skills against Perplexity Spaces](/claude-skills-vs-perplexity-spaces/) if that is your research tool of choice. ### **Ryan's Final Thoughts** Claude Skills vs Gemini Gems is a trade, not a blowout. Gems give you Google-native convenience, live Drive knowledge, and a free on-ramp, which is a real offer if you never plan to leave Gemini. Claude Skills give you a file you own, that improves as you correct it, and that runs anywhere from chat to [Claude Code](/why-marketers-should-use-claude-code/). Pick convenience if you live in Google and want easy. Pick the skill if you are building something you intend to keep. --- ## Claude Skills vs Perplexity Spaces: Main Differences URL: https://ryandoser.com/claude-skills-vs-perplexity-spaces/ Markdown: https://ryandoser.com/claude-skills-vs-perplexity-spaces.md Published: 2026-07-13 | Updated: 2026-07-13 Categories: Claude Code > Claude Skills vs Perplexity Spaces are not competitors. Spaces help you research. Skills help you produce and ship. Use both in sequence. People line up **Claude Skills vs Perplexity Spaces** like they do the same job, and that is where the confusion starts. They sit on opposite ends of your workflow. One helps you know things. The other helps you ship them. ### **They Are Not Actually Competitors** Here is the reframe that makes this whole comparison click. Perplexity is an answer engine, so a Space is built to help you research a topic and organize what you find. Claude is built to do work, so a skill is built to produce a finished thing. Put plainly, a Space is where you go to understand a problem, and a skill is what you run to solve it. Once you see that split, picking between them stops being a fight and starts being a question of which stage of the work you are in right now. That does not mean one is better. It means they belong at different stages, and a lot of people get frustrated because they reach for the research tool when they actually need the production tool, or the other way around. ### **What a Perplexity Space Actually Is** A Space is a dedicated workspace inside Perplexity where you gather research around one topic or project. Think of it as a smart folder for a question you are chasing. *A Perplexity Space is a research workspace you organize inside Perplexity.* You can upload files so the Space searches your own documents alongside the web, set custom instructions so every thread in the Space follows the same tone and focus, and pick from leading models like Claude, GPT, and Gemini on the paid tiers. You can also invite a few collaborators to work in the same Space, which makes it genuinely good for team research. Spaces are available on the free plan with limits, and the fuller feature set comes with Perplexity Pro. What a Space is great at is answering. You point it at a messy question, feed it your sources, and it helps you understand the territory fast. It even has some lightweight task abilities now, but it is built first to help you research, not to ship a finished deliverable. ### **What a Claude Skill Actually Is** A Claude Skill is the production tool. It is a folder with a markdown file called SKILL.md inside it, holding the instructions for one specific task you want done your way, every time. *A Claude skill is a SKILL.md folder built to produce finished work.* Claude reads the short description of each skill first, then loads the full file only when your request matches. This is called progressive disclosure, and it keeps things fast even with a stack of skills on hand. A skill can also carry scripts and reference files, so it does not just advise, it executes. If the format is new to you, I broke it down in my guide on [how to create Claude Skills](/claude-skills/). The point of a skill is output. You do not open a skill to learn about SEO. You run it to produce the ranked blog post, the sent email, the finished deliverable. Where a Space ends with understanding, a skill ends with something shipped. ### **The Real Divide: Research vs Production** Strip away the features and this is the difference that matters. A Space helps you arrive at an answer, while a skill takes a decision you have already made and turns it into a shipped result. Picture writing a market report. The research phase fits a Space perfectly. You drop in your PDFs, ask hard questions across them and the web, and pull the picture together with a teammate. Then comes the part where someone has to actually write the thing in your voice, with your structure and your standards. That is skill territory, because the skill carries how you produce, not just what you found. Force a Space to be your production line and you end up doing the writing by hand anyway. Push a skill to act as your research hub and you feed it context it was never meant to gather. Pointed at the wrong stage, both feel weak. Matched to the right one, both are excellent. Here is where most people go wrong. They run their research inside Perplexity, get a clean answer, and then paste that answer into a chat and ask it to write the final piece from scratch. The output is generic, because the answer told them what is true, not how they ship. A skill closes that gap. It already holds your structure, your voice, your banned words, and the checks you run, so the same research turns into a finished piece that sounds like you instead of like a summary. The reverse mistake is just as common. Someone builds a skill and then keeps dumping raw research into it every time, treating it like a search bar. That buries the skill in context it was never built to manage, and the quality drops. The fix is to let each tool do its half. Gather and understand in the Space. Hand the clean conclusion to the skill. Produce the deliverable with the skill. ### **Two More Differences Worth Knowing** Beyond research versus production, two practical gaps shape which you reach for. The first is ownership. A Space lives inside Perplexity, tied to your account, with no documented way to export it as a file you hold. A Claude Skill is just a folder of text you own outright, so you can copy it, version it, and move it anywhere. If you are building an asset you want to keep, that gap matters, the same ownership case I make in [Claude Skills vs Custom GPTs](/claude-skills-vs-custom-gpts/) and in [Claude Skills vs Gemini Gems](/claude-skills-vs-gemini-gems/). The second is reach. A Space stays inside the Perplexity app, while a skill runs across Claude apps, Claude Code, and the API. That wider reach is part of [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) once you are building real workflows instead of asking one-off questions. ### **Use Them Together** The smartest move is not to pick a winner. It is to run them in sequence, each on the stage it owns. Start in a Space when you are learning something new, scoping a project, or pulling scattered sources into one understanding. Then switch to a skill when it is time to produce the output that research pointed to. Research with Perplexity, ship with Claude. Say you are writing a piece to outrank a competitor. You open a Space, drop in the top-ranking pages and your own notes, and use it to figure out what those pages cover, where they are thin, and what angle is still open. That is research, and a Space is built for it. Once you know the gap, you hand that brief to a blog-writing skill that already knows your structure and standards, and it produces the draft built to beat what you studied. The Space found the opening. The skill shipped through it. If you want production skills ready to run on day one, my [AI Skills Stack](https://skills.ryandoser.com/) is a set with the marketing expertise already written in. ### **Ryan's Final Thoughts** Claude Skills vs Perplexity Spaces is a know-versus-ship question, not a head-to-head. Spaces are a strong research workspace when you need to understand a topic and organize what you find, especially with a team. Claude Skills are what you run when it is time to produce the work, in your voice, that you own and can improve over time. Get smart on the problem inside a Space, then let a skill ship the answer. Most real workflows need both. --- ## Free vs Paid Claude Skills: Which Should You Build? URL: https://ryandoser.com/free-vs-paid-claude-skills/ Markdown: https://ryandoser.com/free-vs-paid-claude-skills.md Published: 2026-07-12 | Updated: 2026-06-30 Categories: Claude Code > Free vs paid Claude skills, decided honestly by someone who sells a stack. A simple 3-question test for when to build your own and when to buy. I sell a pack of Claude skills for a living, so my answer on **free vs paid Claude skills** might surprise you. Most people should start free, and I will tell you exactly when that stops being true. ### **What "Free" and "Paid" Actually Mean Here** A Claude skill is a folder with a markdown file inside that teaches Claude how to do one task your way. That is true whether the file is free or paid. The difference is never the format. It is the knowledge inside the file and the hours you spend getting it there. Free means you build it yourself or grab one off a public repo. You open Claude, dump your process out loud, and let it draft a SKILL.md you can tweak. The price is your time and your own expertise. Paid means someone already did that work and packaged the result. You install a finished skill that carries their judgment, their corrections, and their edge cases. The price is money, and what you are buying is the years that went into the file. ### **The Case for Building Free Skills** For a lot of people, free is the right call, and I mean that. If you already know your craft, a skill is mostly a way to write down what is in your head. *The free path: a public repo you can clone and adapt yourself.* You do not need to be technical for this. The lowest-friction path is to open Claude, talk through how you do a task, and ask it to turn that into a skill. There is even a skill-creator helper that scaffolds a clean SKILL.md so you start from a working draft instead of a blank page. If you want the full method, I walked through it in my guide on [how to create Claude Skills](/claude-skills/). Free also wins when the task is genuinely yours. Nobody sells a skill for your exact reporting format or your specific client onboarding. Those you build, because the expertise lives in you, not in a marketplace. And if you want a head start without paying, public repos are full of solid starting points. I rounded up the [best free Claude skill repos](/best-free-claude-skill-repos/) so you can pull one and adapt it. The smartest free move is rarely a blank page. Grab a repo skill that is close to what you need, then layer your own corrections on top. You get a working starting point for nothing and spend your time on the tuning that makes it yours. That middle road, free file plus your edits, is where most people should start. ### **Where Free Skills Quietly Cost You** Here is the part the free-everything crowd skips. Free is not actually free. You pay in time, and you pay in the quality you do not know you are missing. A skill you build in an afternoon only knows what you thought to put in it. It does not know the edge case you have not hit yet, the correction you always make without noticing, or the format tweak that took you three years to learn. A blank skill produces blank-skill output, and you spend your evenings fixing drafts instead of shipping them. There is also the build cost itself. Writing one good skill is easy. Writing fifteen good skills, testing each one, and maintaining them as your work changes is a real project. For a task you do every day, that investment pays off. For a task outside your expertise, you are teaching a skill something you do not fully know, which is exactly where free skills fall apart. ### **What You Are Really Paying For With Paid** A paid skill is not a fancier markdown file. You are buying compressed expertise, the corrections and judgment someone already earned so you do not have to. *The paid path: a finished stack of skills with the expertise already baked in.* Take the skills in my own AI Skills Stack. They carry over a decade of marketing and SEO subject-matter expertise inside them. The banned-word lists, the verification steps that re-check every stat, the rules I only learned by getting it wrong on real client work. A free blog skill will happily hand you a draft nobody fact-checked. Mine refuses the slop by name and verifies the numbers before the draft reaches me, because those failures already happened to me and got written into the file. That is the real divide. A free skill encodes what you know. A good paid skill encodes what an expert knows, in a field where you might not be the expert yet. When the task is outside your wheelhouse, that gap is the whole value. ### **Two Quick Examples** Abstract advice is easy to nod at and hard to use, so here are two real cases that show the split. Say you run a lawn care business and you want a skill that writes your weekly customer update email. That one you build free. Nobody on earth knows your customers, your tone, and your seasonal offers better than you do. You voice-dump how you write those emails, let Claude draft the skill, and tune it over a few sends. The whole value is your knowledge, and you already have it. Now say you want a skill that writes SEO blog posts that actually rank. This one is different. SEO has a hundred quiet rules that punish you for breaking them, and most of those rules are invisible until a post tanks. A free blog skill will not know that a templated meta description can quietly drag your results down, that a thin intro can stall a ranking, or that a single fabricated stat can sink trust in the whole page. A paid skill built by someone who ranks pages for a living already encodes those landmines. Here you are not buying convenience. You are buying the mistakes you get to skip. The [SEO blog skill I sell](https://skills.ryandoser.com/) is exactly this, every one of those rules already written in, so your draft starts clean instead of teaching you the hard way. The pattern holds across almost any task. Inside your expertise, build. Outside it, buy the expertise. ### **How to Actually Decide** Forget the price tag for a second and ask three questions. They sort this faster than any feature list. First, is this task inside your expertise? If yes, build it free, because you are the source of the knowledge anyway. If no, a paid skill from someone who lives in that field will beat what you can write. Second, how often will you run it? A daily task justifies the time to build and tune a skill yourself. A high-stakes task you run occasionally is where buying proven judgment pays for itself, since one bad output can cost more than the skill. Third, what is your time worth right now? If you have more time than money, build free and learn the format. If you have more money than time, buying a tested skill is the obvious trade, the same call you make hiring any specialist. For the bigger picture of where paid and free skills even live, my breakdown of the [Claude Skills marketplace](/claude-skills-marketplace/) maps it out. ### **Ryan's Final Thoughts** Free vs paid Claude skills is not a loyalty test, it is a sorting exercise. Build free when the task is yours and the knowledge lives in your head. Run the three questions, and most tasks sort themselves in seconds. For most marketers and business owners, the tasks that fail the test are the same ones: SEO, content, email, the marketing work where one invisible mistake quietly costs you rankings or replies. That is the exact gap I built the [AI Skills Stack](https://skills.ryandoser.com/) to fill, a set of marketing skills with a decade of corrections already baked in, so you skip the part where you learn those rules the painful way. Start free to learn the format, and the day a free skill costs you more time to fix than it saves, that is your signal to let a proven one carry the load. --- ## 7 Best Free Claude Skill Repos on GitHub (2026) URL: https://ryandoser.com/best-free-claude-skill-repos/ Markdown: https://ryandoser.com/best-free-claude-skill-repos.md Published: 2026-07-09 | Updated: 2026-07-09 Categories: AI Resources, Claude Code > The 7 best free Claude skill repos on GitHub, honestly ranked. Which repos are worth your time, which to skip, and how to install one safely. The **best free Claude skill repos** on GitHub can save you hours, if you know which ones are worth your time and which are graveyards of half-finished SKILL.md files. ### **Why GitHub Is the First Place to Look** A Claude skill is just a folder with a markdown file inside it. That simple format is why GitHub filled up with skill repos almost overnight. People build a skill, push it to a public repo, and anyone can clone it. The upside is obvious. You get working skills for free, and you can read every line before you run it. The downside is the mess. The same skill gets copied across a dozen repos, quality swings wildly, and a repo that looks active today can go stale in a month. So this list leans on the trusted official sources first, then the community collections worth digging through. One honest note before the list. Free repos are a parts bin, not a finished toolkit. A skill can run instructions and sometimes scripts inside your environment, so open the file and check what it actually does before installing. Treat a starred repo as a starting point to vet and adapt, not something to trust blindly. ### **The 7 Best Free Claude Skill Repos in 2026** These are the repos I actually point people to, ranked by how much real value they deliver, not just star count. Stars are approximate and change daily. #### **1. anthropics/skills** *Anthropic's official skills repo is the trusted baseline for free Claude skills.* This is Anthropic's own repo, and it is the one you start with. It holds the official document skills for PDF, DOCX, PPTX, and XLSX work, plus example skills, the open Agent Skills spec, and a clean skill template you can copy. With around 155k stars it is the most-watched skill source there is. Because it comes straight from the people who built the format, it is the safest place to learn what a well-written SKILL.md actually looks like. The honest catch is scope. These skills lean toward documents and developer tasks, so a marketer will not find a ready-made content or SEO skill here. You take the format lessons and build your own on top. #### **2. obra/superpowers** *Superpowers by Jesse Vincent is a full skills framework, not just a loose folder.* Run by Jesse Vincent, superpowers is one of the most-starred repos in the whole ecosystem, sitting near 239k stars. It is not just a pile of skills. It is an opinionated framework with a real methodology baked in, covering test-driven development, systematic debugging, brainstorming, and planning. It ships as a plugin that works across Claude Code, Cursor, Copilot, and more. If you want skills with a strong point of view rather than thin one-liners, start here. The tradeoff is that the methodology is opinionated, so it works best when you adopt its workflow rather than cherry-picking. #### **3. anthropics/claude-plugins-official** *Anthropic's official plugin directory, where skills ship bundled inside vetted plugins.* This is Anthropic's managed directory of high-quality Claude Code plugins, around 31k stars. It is not raw skill folders. Instead you install plugins by name from inside Claude Code, and those plugins can bundle skills, commands, agents, and tool connections together. It splits into Anthropic's own plugins and a vetted set of community ones. The repo itself reminds you to trust a plugin before installing, which is the right instinct to carry everywhere. #### **4. alirezarezvani/claude-skills** *A big community collection of skills, agents, and commands across many roles.* This community repo packs in roughly 345 skills, agents, and plugins spanning engineering, marketing, product, compliance, research, and operations. At around 19k stars and actively pushed, it is one of the broadest single collections you will find. The breadth is the draw and the catch. You get something for almost every role, but quality varies skill to skill, so cherry-pick the ones that fit your work and test each on a real task first. #### **5. hesreallyhim/awesome-claude-code** *The de facto awesome-list for Claude Code, with a first-class skills section.* This is the closest thing to a canonical map of the Claude Code world, near 47k stars. It is a curated list of links rather than skill files, covering skills, hooks, slash commands, agent orchestrators, status lines, and full apps. When you want to see what exists and where it lives, this is the index to scan. Use it for discovery, then go install the actual skills from their home repos. #### **6. ComposioHQ/awesome-claude-skills** *A large curated list, strong on integrations, with a slight vendor tilt.* Maintained by Composio, this list runs over a thousand skills and plugins across documents, development, research, marketing, and security, near 66k stars. It is especially deep on connecting Claude to outside apps, since Composio sells an integration platform. That vendor tilt is worth knowing going in. The curation is genuinely useful, just read it knowing the maintainer has a product in the mix. #### **7. travisvn/awesome-claude-skills** *A clean, skills-specific list that is friendly to newcomers.* Run by Travis Van Nimwegen, this list stays tightly focused on skills rather than the whole Claude Code universe, around 14k stars. It is clean and beginner-friendly, with getting-started guidance, links to the official Anthropic skills, community repos, and even security and troubleshooting notes. If the bigger lists feel overwhelming, this is the gentler on-ramp. ### **Where Free Repos Run Out of Road** Browse these repos and you will have working skills in minutes, for free. You should absolutely do that. But there is a ceiling, and it is worth naming. Outside Anthropic's own repos, anyone can publish a SKILL.md, and nobody reviews it for quality. Most free skills are bare starter templates or generic rules someone wrote in an afternoon. They run, but they do not carry judgment. They do not know which keyword converts, which subject line gets deleted, or the small corrections that turn a usable draft into a publishable one. That knowledge comes from years on the job, not a template. That gap is why I built my own. The skills in my [AI Skills Stack](https://skills.ryandoser.com/) carry over a decade of marketing and SEO subject-matter expertise inside them: the banned-word lists, the verification steps, the exact rules I learned the hard way on client work. A free blog-writing skill will hand you a draft nobody fact-checked. Mine bans the slop by name and re-verifies every number before the draft reaches me. Here is the kind of small correction free skills miss: my listicle skill learned, after one real failure, to grab a screenshot only after viewing the actual frames, because a clip's title once lied about what it showed. That rule is in the file now. A blank template has none of those scars. Start free, build from these repos, and reach for proven skills when the free ones start costing you more time to fix than they save. ### **How to Actually Use a Repo** Found a skill you like? Getting it running takes one step. A skill is a folder with a SKILL.md inside, so you drop that folder into your skills directory in Claude Code and it loads automatically. For the official repos, you can also add them as a plugin marketplace and install from inside the tool. If the whole SKILL.md format is new to you, start with my walkthrough on [how to create Claude Skills](/claude-skills/), then come back and the repos above will make a lot more sense. And if you are weighing the bigger picture of free downloads versus a curated source, my breakdown of the [Claude Skills marketplace](/claude-skills-marketplace/) maps out every place skills actually live. ### **Ryan's Final Thoughts** The best free Claude skill repos give you a real head start, and you should mine them. Begin with Anthropic's official skills for a trusted baseline, add superpowers for opinionated depth, and use the awesome-lists to find the rest. Read every skill before you run it, keep the ones that earn their place, and upgrade to expertise-backed skills when free stops being good enough. The parts are all there. Your job is to assemble them with taste. --- ## 8 Claude Skills for SEO That Can Replace an Agency (2026) URL: https://ryandoser.com/claude-skills-for-seo/ Markdown: https://ryandoser.com/claude-skills-for-seo.md Published: 2026-07-09 | Updated: 2026-07-09 Categories: Claude Code > This guide covers Claude Skills for SEO that do the jobs an agency bills thousands for. This includes keyword research, content, and more. The best **Claude Skills for SEO** do not save you an hour here and there. They do the actual jobs an agency bills four figures a month for, and they do them while you sleep. ### **Why SEO Skills Beat SEO Tools** Most people think AI SEO means blasting 500 generic articles at a site and hoping something ranks. That is spam, and Google has gotten very good at killing it. A skill is different. It is an SOP for AI, a markdown file that runs one SEO job the exact way a senior strategist would. The point is not to save time. Time-saving has a ceiling, since you can only save so many hours in a week. Making money does not, because ranking content and inbound leads scale almost without limit. Here is the other thing the hype crowd misses. Clicks are not the only scoreboard anymore. An impression where Google's AI Overview names your client as the best option is worth more than a plain blue link, because the AI is telling the searcher who to trust. The skills below are built around that reality. For the full workflow behind them, see my guide on [how to use Claude Code for SEO](/claude-code-seo/). If Claude Code itself is new to you, [start with the setup basics](/claude-code-for-marketing/). ### **The 8 Best Claude Skills for SEO in 2026** Each of these handles a job a small agency would charge a retainer for. SEO is one slice of that; [the wider marketing set](/best-claude-marketing-skills/) covers email, social, landing pages, and video the same way. Some are skills I sell, others are ones you build yourself in an afternoon. All of them follow the same rule: feed context first, then let the skill run. *One skill per SEO job, kept as separate files in Claude Code.* #### **1. Keyword Research Skill** Most people open Claude and say "find me keywords for my business, go." That is exactly where they lose, because they skip the context. A real keyword research skill makes you voice-dump your business, your ideal customer, and your offers first, then pulls live search data through a connected SEO source and reverse-engineers the money keywords. It looks for low-competition terms your buyer actually searches, not vanity volume. This is the first skill I run on any new site or client. #### **2. SERP and Competitor Analysis Skill** Ranking comes down to studying who already wins and then beating them on purpose. The pages on page one are telling you exactly what Google rewards for that keyword. This skill researches the top-ten results for your target keyword and reports back what they have in common: total word count, how they structure the page, what they link to, and the angles they miss. You hand that brief to your writing skill so the draft is built to outrank the current leader, not to float in the void. It is the research an agency strategist does by hand, run in minutes. #### **3. Local SEO Strategist Skill** Local is where the easiest money lives, especially in boring industries that big agencies ignore. Think septic, junk removal, dumpster rental, the businesses with a website that has not changed since 2002. The Local SEO Strategist skill builds a full plan: Google Business Profile optimization, a service-plus-city page architecture, citations, review campaigns, and a prioritized roadmap. It references the real city, real suburbs, and local details so the pages actually deliver on the promise in the title. That specificity is what convinces both Google and the searcher you genuinely serve the area. It is the same approach behind [ranking boring local businesses for monthly retainers](/seomaxxing/). #### **4. AI Overview Optimization Skill** Almost nobody has built this one yet, which is exactly why it is worth your time. Its whole job is getting your page cited inside AI search results. It structures content the way large language models like to quote it, with direct declarative answers, clean headings, and specific facts an AI can lift. The goal is the impression where Gemini or an AI Overview names your brand as the top pick. That kind of placement, where the AI tells the searcher who is best, can be worth more than a plain top-of-page link. #### **5. Internal Linking Skill** Internal links are the cheapest ranking lever most sites never pull, and doing it by hand across a hundred posts is miserable. Hand this job to a skill that maps your existing content, finds genuine topical matches, and adds links with descriptive anchor text where a real sentence supports them. The rule baked into the skill is that every link has to add reader value, so it skips forced connections instead of stuffing keywords. Cleaner site architecture, no manual spreadsheet. #### **6. Content Refresh Skill** Your biggest ranking gains are usually hiding in posts you already published. They slipped, the data went stale, or a competitor leapfrogged you. Point a refresh skill at one of those pages and it audits the content against the current top results, flags what is outdated or thin, and rewrites those sections while keeping what already works. It is the highest-ROI SEO job there is, and it is the one busy site owners always put off. A skill makes it a one-prompt task instead of an afternoon. #### **7. Digital PR and Backlink Pitch Skill** Authority still decides who ranks, and authority comes from other sites pointing at yours. The honest way to earn that is real outreach, not buying links. This skill scans for relevant journalist requests and podcast opportunities, then drafts genuine, value-added pitches in your voice. Even a small podcast can hand you a surprisingly high-authority backlink, so the bar to start is lower than people think. The skill turns a tedious PR grind into a daily batch you actually run. #### **8. Rank and Impression Tracking Skill** You cannot improve what you do not measure, and the metric most people watch is the wrong one. The monthly reporting an agency charges a retainer for is mostly this. A tracking skill pulls your Search Console data and reports the full picture, not just clicks. It surfaces rising impressions, which is your early signal of AI visibility, and flags which pages are gaining or slipping. When clicks dip but impressions climb, this skill is how you know AI search is quietly picking you up rather than dropping you. ### **How These Skills Fit Together** *The payoff: SEO content these skills produce, published and ranking.* None of these work in isolation. The magic is the chain. Keyword research feeds competitor analysis, which feeds the writing, while the internal linking and refresh skills compound the gains over time, and the tracking skill tells you what is working. That chain is what a real agency sells, and you can run all of it from one interface for the price of a Claude subscription. You can build each one yourself, but that is a stack of afternoons. The keyword research and Local SEO Strategist skills come ready-made in the [AI Skills Stack](https://skills.ryandoser.com/), so you can skip straight to running them today. ### **Ryan's Final Thoughts** SEO is only dead for thin affiliate sites with no authority, and honestly it was never alive for them anyway. For real brands, these Claude skills for SEO do the strategist's job, the writer's job, and the analyst's job at a fraction of the cost. Start with keyword research, layer in the rest, and keep your eye on the prize that actually matters: more rankings, more impressions, and more inbound leads that pay you back for years. ### **Claude Skills for SEO FAQs** #### **Can Claude skills replace an SEO agency?** For most small and mid-sized brands, they replace what an agency actually delivers each month, which is keyword research, competitor analysis, content briefs, refreshes, and reporting. What they do not replace is someone deciding strategy and owning the outcome. If you have the hour a week to run them and read the output, these skills do the strategist's job, the writer's job, and the analyst's job at a fraction of the cost. If you do not, you are buying accountability, and that is what an agency really sells. #### **Which SEO skill should I build first?** Keyword research, without question. It is the first skill I run on any new site or client, and everything downstream depends on it. Keyword research feeds competitor analysis, which feeds the writing, while the internal linking and refresh skills compound on top of what those produce. Building them in any other order means the later skills run on guesses. #### **Is AI-generated SEO content penalized by Google?** Publishing volumes of thin, unedited AI content is spam, and Google has gotten very good at killing it. The distinction that matters is whether the page does a real job for a real reader. These skills are built to feed context first and let the skill run, which produces work grounded in actual SERP research rather than invented filler. The generation method is not the problem. Publishing something nobody needed is. #### **Why track impressions instead of just clicks?** Because clicks are no longer the only scoreboard. An impression where Google's AI Overview names your client as the best option is worth more than a plain blue link, because the AI is telling the searcher who to trust. When clicks dip but impressions climb, that is usually AI search quietly picking you up rather than dropping you, and you would misread it as a loss if you only watched clicks. #### **What SEO work is easiest to win with these skills?** Local SEO in unglamorous industries. Septic, junk removal, dumpster rental, and similar trades are the kind of boring, high-margin categories big agencies ignore, which means the competition is weak and the wins come fast. The local SEO strategist skill exists because that is where the easiest money on this list actually sits. --- ## Claude Skills Marketplace: What Actually Exists in 2026 URL: https://ryandoser.com/claude-skills-marketplace/ Markdown: https://ryandoser.com/claude-skills-marketplace.md Published: 2026-07-09 | Updated: 2026-07-09 Categories: AI Resources, Claude Code > There is no official Claude Skills marketplace yet. Here is what actually exists, how to install a skill, and how to vet one before using. If you searched for a **Claude Skills marketplace** expecting an App Store where you browse and buy skills with one click, I have to set the record straight. That official store does not exist yet, and what does exist is scattered across a few very different places. ### **What People Think a Claude Skills Marketplace Is** Most people picture something like the GPT Store. One branded shelf, run by Anthropic, where you scroll through skills, hit install, and you are done. That mental model is wrong, and it sends people looking in the wrong place. There is no consumer-facing "Claude Skills store" with that name. Anthropic has not launched a storefront where you shop for skills the way you shop for apps. If you go hunting for one, you end up on a pile of third-party sites that all call themselves the marketplace, which is exactly why the topic feels so confusing. To make it messier, Anthropic does run something called the Claude Marketplace. That product is for businesses buying third-party cloud services and software, not for buying skills. Same word, completely different thing. Do not confuse the two. ### **What Actually Exists Instead** The real ecosystem comes in three layers. Once you see them separately, the whole thing makes sense. #### **Layer 1: The Claude Code Plugin Marketplace** This is the closest thing to an official channel, and it lives inside Claude Code. Anthropic ships a plugin system where a GitHub repo with the right config file becomes a marketplace you can add by name. Skills get distributed through that system as part of plugins. Anthropic maintains two of these. The first is its example skills repo, which you can register as a marketplace. The second is an Anthropic-managed directory of vetted Claude Code plugins, browsable right inside the tool. You add a marketplace, run a discover command, and install what you want from the terminal. *Anthropic's official skills repo on GitHub, which you can add as a Claude Code plugin marketplace.* #### **Layer 2: Free Third-Party Directories** This is where most people actually land. A growing crowd of community sites collect skills and let you browse and download them for free. *A free third-party directory where you can browse and download Claude skills.* You will find directories like claudeskills.info, skills.pub, claudemarketplaces.com, and lobehub, among others. Each one curates skill files, often with categories and search. They are genuinely useful for discovery, and the price is right. Just treat the skill counts they advertise as marketing, not gospel, and read any skill before you run it. #### **Layer 3: The Paid Marketplaces (Still Early)** A small set of commercial marketplaces has started letting creators sell skills. Think of these as the early Gumroad-for-skills layer of the ecosystem. Platforms like Agensi and Agent37 handle payments, listings, and in some cases a security scan before a skill goes live. This corner is real but nascent. It is where the market is heading, not where it has arrived, so expect it to look very different a year from now. ### **How to Actually Install a Skill** Wherever you get a skill, putting it to work is simple. There are three common paths. The first is the plugin marketplace inside Claude Code. You add a marketplace by its GitHub name, open the plugin menu, and install from the discover list. The second is the same menu pointed at Anthropic's official plugin directory. The third, and the one that always works, is manual. A skill is just a folder with a SKILL.md file, so you drop that folder into your skills directory and Claude picks it up. On claude.ai you zip the folder and upload it under settings, with code execution turned on. A quick example makes it concrete. To pull in Anthropic's own example skills, you add their skills repo as a marketplace by its GitHub name, open the plugin menu, and install the bundle you want. From that point Claude treats those skills like any other, loading the right one when your request matches. The manual route gets you to the same place without the menu, which is why I default to it: a folder in, and the skill is live. If the idea of a SKILL.md file is new to you, start with my walkthrough on [how to create Claude Skills](/claude-skills/) and the whole install step gets a lot clearer. ### **How to Vet a Skill Before You Run It** A skill is code-adjacent. It can carry instructions, reference files, and in some cases scripts that run on your machine, so installing a random one off a directory is not risk-free. A little caution here saves you a real headache. Open the SKILL.md and actually read it first. Check what the skill claims to do, look for anything that reaches out to the internet or runs a script, and skip it if the file is vague about what it touches. Prefer skills from a named author with a track record over an anonymous upload. On a platform like Agensi, a security scan before a skill gets listed is one of the few things you are actually paying for, so it carries some weight. The same rule applies to quality, not just safety. A skill that looks impressive in a demo can fall apart on your real inputs. Read it, run it on one small task, and only then trust it with the work that matters. ### **Why Free Skills Hit a Ceiling** Here is the part the directory sites skip. A free skill is only as good as the knowledge baked into it, and most free skills are thin. A lot of what you download is a blank scaffold or a set of generic rules someone wrote in an afternoon. It runs, but it does not carry real judgment. It does not know which keyword actually converts or which email opener quietly gets deleted. It is missing the dozens of small corrections that separate a usable draft from a publishable one. That knowledge does not come from a template. It comes from years of doing the work and feeding those lessons back into the file. That gap is the whole reason I packaged my own skills. The ones in my [AI Skills Stack](https://skills.ryandoser.com/) carry over a decade of marketing and SEO subject-matter expertise inside them: the banned-word lists, the verification steps, the exact rules I learned the hard way on real client work. A blank blog-writing scaffold will happily hand you a draft full of em dashes, vague openers, and stat claims nobody checked. My blog skill bans those dashes by name, refuses the weak openers, and runs a separate pass that re-verifies every number before the draft reaches me. That is not a setting you toggle on. It is years of corrections written into the file. You can absolutely start free, and you should explore the directories above. When you want skills that already know the job instead of skills you have to teach from scratch, that experience is what you are paying for. ### **Where This Is All Heading** The marketplace question is really a timing question. Right now the ecosystem is fragmented across plugin directories, free community sites, and a few early paid platforms. That fragmentation is the opportunity. The adjacent marketplaces are wide open, the curation is thin, and the people who build genuine expertise into their skills now will own the shelf space later. If you sell skills yourself, that early-mover gap is worth understanding, which I broke down in my guide on [how to sell Claude skills as a digital product](/sell-claude-skills/). And if you want the honest version of why this matters for your whole workflow, here is [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) in the first place. ### **Ryan's Final Thoughts** There is no single Claude Skills marketplace, and pretending otherwise just sends you in circles. What you have instead is Claude Code's plugin system, a handful of free directories, and an early paid layer that is still taking shape. Browse the free options, install a few, and see what holds up under real work. When the free files start costing you more time to fix than they save, that is your signal to buy skills that already carry the expertise. My [free vs paid Claude Skills](/free-vs-paid-claude-skills/) breakdown covers when that trade is worth it. Start where you are, and upgrade when the work demands it. --- ## How to Turn Claude Projects into Skills (Get Better Results) URL: https://ryandoser.com/turn-claude-projects-into-skills/ Markdown: https://ryandoser.com/turn-claude-projects-into-skills.md Published: 2026-07-09 | Updated: 2026-09-30 Categories: AI Tutorials, Claude Code > This guide shows how to turn Claude Projects into Skills. Rebuild your in-app project as a portable skill folder you own. If you have a Claude Project you rely on every day, you can rebuild it as a portable skill you actually own. This guide on **how to turn Claude Projects into Skills** walks through the exact steps I use, no coding required. ### **Why Bother Converting a Project at All** A Claude Project is a workspace inside the Claude app. You give it custom instructions, upload some knowledge files, and every chat inside that project follows those rules. It works well, and I used projects for a long time. The catch is that a Claude chat project does not automatically become a skill Claude Code can load. To reuse the instructions you carefully tuned, you still need to turn them into a skill folder. A skill fixes that. Think of a skill as an SOP for AI, a folder built around one markdown file that teaches Claude how to do one task from start to finish. Because it is just files, you own it and it travels with you to tools that support the Agent Skills standard. That ownership gap is the whole reason I made the switch, and I broke down the same ownership argument in my post on [Claude Skills vs Custom GPTs](/claude-skills-vs-custom-gpts/). ### **See How Skills Work First** Before the steps, here is a short walkthrough where I build and use a skill inside Claude Code. It makes the rest of this guide a lot easier to picture. ### **What You Are Actually Moving** Before the steps, get clear on what a project holds, because you are rebuilding three pieces. The first piece is the custom instructions, the standing rules you typed into the project settings. The second is the knowledge, meaning the files or reference text you uploaded. The third is the unwritten part, the way you actually prompt the project once you are inside it. A skill needs all three in one place. There is no one-click export that converts a project into a skill, so this is a manual rebuild. The good news is it takes minutes once you know the shape. ### **Step 1: Pull Your Project Instructions** Open the project and copy its custom instructions out of the settings. Paste them into a plain text file for now. Read them with fresh eyes. Projects often collect vague rules over time, like "be helpful" or "use my brand voice." A skill rewards specifics, so tighten anything fuzzy into a concrete instruction Claude can actually follow. ### **Step 2: Gather the Knowledge** Next, collect whatever the project used as reference. If you uploaded PDFs, grab the source content as text instead. This matters more than it looks. Claude reads markdown and plain text far more accurately than it reads PDFs, so save your reference material as markdown files. That one change alone made my outputs cleaner the day I figured it out. ### **Step 3: Capture How You Actually Use It** This is the step most people skip, and it is the one that makes a skill great. Open the project, run your usual task, and pay attention to the prompts you type and the corrections you make. Those corrections are gold. Every time you tell the project "no, do it this way," that is a rule that belongs in your skill. Write them down as you go. ### **Step 4: Write the SKILL.md File** Now you assemble the pieces into a single markdown file called SKILL.md. At the top it needs a short block with two fields, a name and a description. *The name and description block at the top of a SKILL.md is what tells Claude when to use it.* The description is the important one. Claude reads it to decide when to use the skill, so it should say what the skill does and when to use it. Below that block, paste your tightened instructions, your reference notes, and the rules you captured in step three. *Use a skill-creator helper to scaffold the SKILL.md instead of starting from a blank file.* The lowest-friction way to do this is to not type it from scratch at all. Open Claude, brain-dump everything out loud, and ask it to draft the SKILL.md for you. There is even a skill-creator helper that scaffolds a clean skill file, so you start from a working draft instead of a blank page. ### **Step 5: Drop It In and Test** Where the file goes depends on where you work. In Claude Code, a skill is just a file in a folder, so you drop the skill folder into your skills directory (your personal one at the home path, or a project one inside the repo) and it is ready, no upload needed. On claude.ai, you zip the skill folder and upload it under Customize and then Skills, and you need code execution turned on under Settings and then Capabilities for it to run. Then test it the same way you tested the project. Run your task, watch the output, and correct anything that is off. Here is the part that beats a project for good: when you correct a skill, you can have Claude patch the file itself, so the fix sticks forever instead of getting re-explained every session. ### **What This Looks Like In Practice** Picture a project you use to write LinkedIn posts in your voice. It holds your tone rules and a few past posts as examples, and it does a decent job inside the app. Rebuild it as a skill and you can fold in the small corrections you always make by hand, like cutting weak openers or banning a few words you never use. The skill starts producing the post you want on the first try, and it sits alongside your other skills instead of living inside one chat project. Picture the before and after. In the project, you typed the same three fixes into every chat: drop the throat-clearing intro, swap the corporate verbs for plain ones, and never open with a question. You did that by hand each time because you had not added those fixes to the project instructions. In the skill, those three fixes become written rules near the top of the file, so the very first draft already lands the way you want. The most common mistake here is rebuilding the instructions but skipping the corrections. If you only move the official rules and leave out the fixes you make in practice, the skill behaves exactly like the project did, and you are back to editing every output by hand. The corrections are the part that makes the skill better than the thing you replaced. If you want to see the broader workflow, here is [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) in the first place. ### **Keep One Skill Per Task** One last rule that saves you headaches. Do not try to cram an entire project into one giant skill that does five things. Break it into focused skills instead, one per task. A separate skill folder for blog posts, another for email, another for research. Claude reads the full instructions only for the skills that match your request, so smaller and sharper always wins. If you would rather start from proven files than build each one yourself, I packaged the exact skills I use to run my business into the [AI Skills Stack](https://skills.ryandoser.com/). ### **Ryan's Final Thoughts** Turning a Claude Project into a skill is not a technical job, it is a copy, tighten, and rewrite job. You move the instructions, save the knowledge as markdown, capture how you really use it, and drop it into a SKILL.md you own. Do it once and you will never want to go back to instructions that only live inside one project. Start with the project you use most and rebuild it today. --- ## 10 AI Side Hustles for Marketers That Actually Pay (2026) URL: https://ryandoser.com/ai-side-hustles-marketing/ Markdown: https://ryandoser.com/ai-side-hustles-marketing.md Published: 2026-07-08 | Updated: 2026-07-08 Categories: AI Side Hustles > AI side hustles built for marketers, not generic make-money lists. 10 real ideas with honest income ranges and how to start each one in 2026. The best **AI side hustles for marketers** are not the ones every generic "make money with AI" list keeps recycling. They are the boring, client-facing services you can already half-do in your sleep, now run at 5x the speed. ### **Why Most "AI Side Hustle" Lists Are Useless to You** I have read a lot of these lists. They all say the same thing: train AI models on Mercor, sell prompt packs, make faceless YouTube videos, publish AI coloring books on Amazon. None of that is built for a marketer. You already know how to write a subject line, brief an ad, or map a content calendar. That skill is the edge. AI does not replace it, it multiplies it, and that gap between "knows marketing" and "knows how to prompt" is exactly what people pay for right now. So this is not a generic income list. Every idea here is a marketing side hustle, framed for someone who can sell an outcome to a business owner. I have run or coached most of these, and I will tell you the real income ranges and the honest downside on each one, not the clickbait "$35,677 in a weekend" version. ### **The 10 Best AI Side Hustles for Marketers in 2026** Skim the fast version first, then go deep on the ones that fit you. Every income range below is a realistic monthly target for a part-time operator with one to four clients, not a viral outlier. | # | Side Hustle | Best for | Realistic income | | 1 | AI newsletter operator | Writers, editors | $800 to $2,500/mo per client | | 2 | AI email-sequence writer | Copywriters, e-com marketers | $1,500 to $5,000 per project | | 3 | AI ad-creative variation service | Paid-social marketers | $1,000 to $3,000/mo per client | | 4 | Short-form video repurposing | Social media managers | $1,000 to $3,000/mo per client | | 5 | Niche social media manager | Generalist marketers | ~$1,000/mo per client | | 6 | Brand-voice GPT/skill builder | Prompt-savvy marketers | $500 to $2,500 per build | | 7 | AI lead-gen + outreach copy | B2B marketers | $500 to $2,000/mo per client | | 8 | Local AI marketing installer | Local/agency marketers | $500 to $2K setup + retainer | | 9 | Sell marketing skills + templates | Anyone with a repeatable process | $500 to $5,000/mo at volume | | 10 | Build a paid AI marketing community | Marketers who like teaching | $3,000 to $5,000/mo at 80-150 members | #### **1. AI Newsletter Operator** **What it is:** You run a client's weekly newsletter end to end. Research, draft, edit, schedule, and report. AI handles the first draft and the repurposing so one newsletter feeds five social posts. **Who it fits:** Marketers who can write and edit and would rather own one deliverable than juggle ten. **Realistic income:** $800 to $2,500 per month per client. Two clients is a real part-time income. **How to start:** Pick one niche you understand (SaaS founders, real-estate agents, local gyms). Offer a done-for-you weekly send on a platform like [beehiiv](https://www.beehiiv.com/). Use AI to draft, but you edit every line so it does not read like a robot wrote it. **The downside:** It is recurring work every single week. Miss a send and the client notices. This is a commitment, not a passive play. #### **2. AI Email-Sequence Writer** **What it is:** You write the automated flows that make e-commerce and SaaS brands money on autopilot. Welcome series, cart abandonment, post-purchase, win-back. **Who it fits:** Copywriters and email marketers. This is the highest-skill, highest-pay idea on the list. **Realistic income:** $1,500 to $5,000 per project. Experienced specialists command $150 an hour and up. **How to start:** Learn one email platform well ([Klaviyo flows](https://www.klaviyo.com/features/flows) for e-com, a lifecycle tool for SaaS). Use AI to draft variations fast, then apply real copywriting judgment on the hooks and offers. The judgment is what they pay for. **The downside:** AI writes competent email. It does not know the offer, the margin, or the brand's voice. If you cannot bring strategy on top of the draft, you are just a slower version of the client's own ChatGPT. #### **3. AI Ad-Creative Variation Service** **What it is:** Paid-social teams burn through creative. You use AI to expand a few strong angles into a clean set of hook and headline variations the media buyer can actually test, then you cut the weak ones before they ever ship. **Who it fits:** Marketers who understand direct response and why one ad beats another. **Realistic income:** $1,000 to $3,000 per month per client. At agency scale this becomes a real retainer business. **How to start:** Get one paid-social client or agency. Start from a handful of angles you believe in, use a tool like [AdCreative.ai](https://www.adcreative.ai/) to generate variations of each, then hand-pick the ones worth testing. You are the filter, not a firehose. **The downside:** Volume without strategy is just expensive noise. Spraying 100 versions of a bad angle gets you fired fast. The whole value is your judgment on which hooks are worth a dollar of spend. #### **4. Short-Form Video Repurposing** **What it is:** You take one long video (a podcast, a webinar, a YouTube upload) and turn it into 10 to 20 Reels, Shorts, and TikToks with AI editing, captions, and clip selection. **Who it fits:** Social media managers and anyone comfortable with basic video tools. **Realistic income:** $1,000 to $3,000 per month per creator or brand client. **How to start:** Find one creator or founder who publishes long content and hates editing. Use an AI clipping tool like [Opus Clip](https://www.opus.pro/) to surface candidate moments, then apply human taste on the few that actually land. Deliver a small set of strong clips, posted and captioned, not a dump of everything the tool spat out. If the credit math on a clipper decides whether this is profitable for you, [I priced seven of them on monthly billing](/opus-clip-alternatives/). It is the same split I landed on for my own podcast, where [AI cuts the long-form episode and a human editor still finishes the shorts](/ai-video-editing/). **The downside:** The tools pick clips by transcript keywords, not by what is genuinely good. Your edge is knowing which handful are worth posting and killing the rest. Hand over all 20 raw and you are just an export button. #### **5. Niche Social Media Manager** **What it is:** Full social media management for one specific niche. Content, scheduling, light community engagement, monthly reporting, all sped up with AI drafting. **Who it fits:** Generalist marketers who want steady recurring clients without deep specialization. **Realistic income:** Around $1,000 per month per client. Two to four clients is a solid side income. **How to start:** Pick a niche where the businesses have money and no time (med-spas, dental practices, real-estate teams). Run it all from one scheduler like [Buffer](https://buffer.com/) and sell the same package to several of them so your systems and prompts carry over. **The downside:** This is the most crowded idea on the list. Everyone offers social media management. Your only real moat is the niche focus and the results you can show, so pick a lane and go deep. #### **6. Brand-Voice GPT or Skill Builder** **What it is:** You build a custom AI assistant trained on a company's voice, style, and offers so their internal team can draft on-brand without you. You are selling a reusable asset, not your time. **Who it fits:** Prompt-savvy marketers who like building systems more than doing weekly grind work. If you already lean on Claude for client work, this is a natural extension of the [Claude AI side hustle](/claude-ai-side-hustle/) path. **Realistic income:** $500 to $2,500 per build. Add a retainer to maintain and update it. **How to start:** Take a company's best content, their style guide, and their positioning, and package it into a [custom GPT](https://chatgpt.com/gpts) or a Claude skill their team can use. Charge for the build, then charge again to keep it current. **The downside:** It is a newer offer, so you have to educate the buyer on why it is worth paying for. And a voice model is only as good as the material you feed it. Thin inputs make a thin assistant. #### **7. AI Lead-Gen and Outreach Copy** **What it is:** You build small, highly targeted prospect lists and write genuinely personalized outreach for B2B clients. Not blast lists. A tight list of the right people with a message that actually references their world. **Who it fits:** B2B marketers who understand that outreach lives or dies on the offer and real personalization, not volume. **Realistic income:** $500 to $2,000 per month per client. **How to start:** Use an enrichment tool like [Clay](https://www.clay.com/) to research each prospect deeply, then write outreach that proves you actually looked. Ten messages that land beat a thousand that get ignored. Sell the research and the copy as one package. **The downside:** I have to be blunt here. The lazy version of this is spam, and mass AI outreach gets domains blacklisted and burns your client's reputation. If you are not willing to keep it small and genuinely personal, skip this one. Do it wrong and you are part of the problem. #### **8. Local AI Marketing Installer** **What it is:** You set up the AI marketing stack for local businesses. A chatbot on the site, review-request automation, a social scheduler, maybe a simple lead-capture flow. Setup fee plus a monthly retainer to run it. **Who it fits:** Marketers who like working with local business owners and want both an upfront fee and recurring income. **Realistic income:** $500 to $2,000 setup, plus a $300 to $800 monthly retainer per client. **How to start:** Pick one vertical (dentists, gyms, home services). Build one repeatable "install" package around tools like [Podium](https://www.podium.com/reviews/) for reviews and chat, then sell the same thing down the street. Local owners want the outcome, not a tools tutorial. **The downside:** Local owners can be slow to pay and slower to adopt. You will do some hand-holding. The upside is that retainers stack and the same setup repeats across clients. #### **9. Sell Marketing Skills and Templates** *Productizing your marketing process into a paid skill, like the Claude Code Skills Stack.* **What it is:** You productize your own repeatable process into something people buy once. A Claude skill, a workflow template, or a full SOP that does a specific marketing job. I lean toward skills over one-off prompt packs, because a skill is a repeatable system and a prompt is a single throw. **Who it fits:** Anyone who has a marketing process worth copying. This is the most scalable idea because you build it once and sell it many times. **Realistic income:** $15 to $99 per product, which adds up to $500 to $5,000 a month once you have volume and an audience. **How to start:** Find the one thing you do that people always ask you about, then package it so a stranger can get your result without you. Plenty of marketers sell these as templates on a marketplace like [Gumroad](https://gumroad.com/discover). I broke down the mechanics of this in my guide on [how to sell Claude skills](/sell-claude-skills/), which walks through pricing and packaging a skill someone will actually buy. If you want a working model of a productized, expertise-backed skill, my [Claude Code Skills Stack](https://skills.ryandoser.com/) is exactly that: real marketing workflows built on a decade of doing the work, not thin repo wrappers. **The downside:** A skill with no audience sells zero copies. The product is the easy part. Distribution is the hard part, and that is a marketing problem you have to solve first. #### **10. Build a Paid AI Marketing Community** *My own AI Marketing Insiders community, a live example of the paid-community side hustle.* **What it is:** You gather marketers around a specific problem, then charge a monthly or yearly fee for the space, the resources, and the access. AI helps you produce the content, templates, and onboarding that keep members getting value. Browse the [Skool discovery page](https://www.skool.com/discovery) and you will see hundreds of paid communities already doing exactly this. If you want to see how the good ones structure their tiers and pricing before you build your own, I broke down the [best AI communities](/best-ai-communities/) and what each one charges. **Who it fits:** Marketers who like teaching and organizing more than doing client work. Full disclosure: I run one myself, so I am biased. My community admin and I recorded [an honest conversation about whether you should build one at all](/how-to-build-an-online-community/). I will give you the honest downside anyway. **Realistic income:** A small paid community of 80 to 150 members at $25 to $50 a month lands around $3,000 to $5,000 monthly. Take out your platform cost first. Skool's Pro plan runs about $99 a month plus a small per-transaction fee on top, so the platform is not free. The six-figure-a-month examples you see are outliers, not the starting point. **How to start:** Pick one narrow audience and one clear promise. Start free to build trust and prove the value, then open a paid tier once people are already showing up. The [AI Marketing Insiders community](https://www.skool.com/ai-marketing-insiders/about) is my own version of this, and it started exactly that way. **The downside:** An empty community is worse than no community. You have to show up daily at the start, and members leave the moment the value dries up. This rewards consistency more than any other idea here. ### **How to Choose Your AI Side Hustle** These are the same questions I ask before I take on any client build. Run yourself through them. - **What can you already do well?** Start where your marketing skill is strongest. AI multiplies existing skill, it does not create it from nothing. - **Do you want recurring or one-off income?** Newsletters and social management are recurring grind. Email sequences and voice-model builds are one-and-done projects. - **How much do you want to sell?** Local installers and lead-gen require ongoing client-getting. A productized skill sells while you sleep, but only after you build an audience. - **Recurring revenue or a scalable asset?** Retainers give you predictable income with a ceiling. Products give you a lower floor and a much higher ceiling. - **Can you bring judgment on top of the AI?** Every idea here pays because a human decides what is good. If the plan is to hand over raw AI output, the client will cut you out and prompt it themselves. Pick one. Get one client or one sale. Then decide if it is worth scaling. Trying all ten at once is how you end up with none. ### **What About the Generic "Make Money With AI" Ideas?** You will see other lists push AI model training, faceless YouTube channels, AI stock art, and self-published coloring books. I left those out on purpose. They are real, and some people do make money with them. But they are not marketing side hustles, and they do not use the skill you already have. You would be starting from zero in a crowded, low-margin race. If you want the broader income view, I covered the full ranked list in my guide on the [best ways to make money with AI](/best-ways-to-make-money-with-ai/), and if you are truly starting cold, [how to make money with AI with no experience](/how-to-make-money-with-ai-no-experience/) is the better entry point. This post is deliberately narrower, for marketers who want to charge for what they already know. ### **Ryan's Final Thoughts** None of these are passive and none are get-rich-quick. Every one pays because you are selling a marketing outcome that AI makes faster to deliver, not because AI does the whole job for you. Pick the one that matches the skill you already have, land a single client, and let the results tell you whether to scale. And if you want people building these alongside you and swapping what actually works, that is exactly why the AI Marketing Insiders community exists. --- ## 7 Best AI Writing Tools in 2026 (Avoid Most of Them) URL: https://ryandoser.com/best-ai-writing-tools/ Markdown: https://ryandoser.com/best-ai-writing-tools.md Published: 2026-07-08 | Updated: 2026-09-30 Categories: AI Tool Reviews > Most AI writing tools are wrappers reselling Claude and ChatGPT at a markup. Here are the few worth paying for and when to skip them. The **best AI writing tools** in 2026 are the two or three you can go to directly, before a dozen middlemen resell you the same output at a markup. Ad budget has almost nothing to do with which ones actually write well. I write and publish content every day across a seven-figure SaaS, a cybersecurity brand, and my own channels. I have paid for most of the tools on this list, and I have watched the whole category quietly reorganize itself around one uncomfortable fact. So this is not another affiliate roundup that ranks whoever pays the most. It is the honest version, written by someone who ships with these daily. If you want the wider set of apps I run beyond writing, I keep a separate roundup of the [best AI tools for content creators](/best-ai-tools-for-content-creators/). ### **The Truth Most "Best AI Writing Tools" Lists Will Not Tell You** Search "best AI writing tools" and you get the same names every time. Jasper, Copy.ai, Writesonic, Rytr, and a dozen more that appear the day you hit publish. Almost none of those roundups admit the obvious. Most of these tools are a paid interface sitting on top of the exact same models you can access directly. They send your prompt to OpenAI or Anthropic, get the text back, and hand it to you inside their own dashboard. You are frequently paying a subscription for the wrapper, not for the writing. Two of the tools below say this out loud on their own pricing pages. Sudowrite states it runs "the latest Claude models by Anthropic" and "several models created by OpenAI." Copy.ai advertises "access to OpenAI, Anthropic, and Gemini models." That is not an accusation. It is their own marketing copy. I do not say this to trash the category. A few of these tools genuinely earn their price by wrapping the model in a workflow you would not want to rebuild. But you cannot judge which ones are worth it until you see the math underneath. ### **The Math That Reframes Every AI Writing Tool** I broke this down in a video over a year ago, and it has only gotten more lopsided since. Let me show you the current 2026 numbers. Take a typical tool that charges around $29 a month for, say, 15 blog posts. Sounds fair until you price the raw ingredients. A 1,200-word blog post is roughly 1,600 output tokens (the rule of thumb is about 750 words per 1,000 tokens). At OpenAI's GPT-5.4-mini rate, that post costs under a cent in API tokens. On OpenAI's newest small model, GPT-6 Luna, it is under a tenth of a cent. Even on a premium model like Claude Sonnet 5.5, a 1,200-word draft runs about two cents. So 15 blog posts cost the tool maybe 10 to 30 cents in raw API calls. They charge you $29. The rest is markup on a call you could make yourself. That is the entire business model of most of this category, and it works because most buyers have never seen the token math. Once you know that, the real question changes. It is no longer "which AI writing tool is best." It is "when is the wrapper actually worth paying for, and when should I just go to the source?" ### **The Best AI Writing Tools in 2026** I split this list into two tiers on purpose. First, the sources: the frontier models you should pay for directly, because everything else runs on them. Then the wrappers worth their price, because they add a real workflow the raw model does not give you. #### **Tier 1: The Sources (Just Pay for These)** If you only pay for one or two writing tools, make them these. Everything in Tier 2 is, to some degree, reselling what these two do. ##### **1. Claude (Best Overall AI Writing Tool)** *Claude is the source most other AI writing tools quietly run on.* [Claude](https://claude.com) is my daily writing tool, and it is the one I trust to sound human on the first pass. Anthropic's models handle tone, nuance, and long-form structure better than anything else I use, which is exactly why so many "AI writing tools" route their requests to it behind the scenes. Which Claude model you pick matters too. Right now Opus 5.5 is the [best Claude model for writing](/best-claude-model-for-writing/) in my own side-by-side test. **Pros:** - The most natural-sounding output of any tool here, with the least cleanup. - Huge context window, so you can paste a whole brand guide or draft and work against it. - You are paying the source directly, no wrapper markup. **Cons:** - No purpose-built marketing templates or campaign dashboards out of the box. - Usage caps on lower tiers can bite during heavy writing days. **Best for:** anyone who wants the highest-quality drafts and the least AI slop to edit out. **Pricing:** Free tier available. Pro is $17 a month billed annually ($20 monthly). Max starts at $100 a month for heavy use. **Free trial:** Yes, a genuinely usable free tier. **Bottom line:** If you buy one writing tool in 2026, buy this. It is the source, the quality leader, and the thing half this list is secretly built on. ##### **2. ChatGPT (Best for Research and All-Around Work)** *ChatGPT is the other source, strongest when writing and research overlap.* [ChatGPT](https://openai.com/chatgpt/overview/) is the other tool worth paying for at the source. Where Claude edges it on pure writing feel, ChatGPT pulls ahead when a piece needs live research, data wrangling, or image generation stitched into the same workflow. **Pros:** - Strongest when research and writing happen in one place. - Native image generation and web browsing built in. - The default most people already know, with the deepest ecosystem. **Cons:** - Default output leans more generic than Claude and needs more voice editing. - The best features sit behind the pricier tiers. **Best for:** writers who want one tool that researches, drafts, and makes images together. **Pricing:** Free tier available. Go is $8 a month, Plus is $20 a month, and Pro starts at $100 a month. **Free trial:** Yes, a free tier covers casual use. **Bottom line:** The other source worth paying for directly. Pick it over Claude when your writing leans on research and multimedia, not just prose quality. #### **Tier 2: Wrappers Worth Paying For (When the Workflow Beats the Markup)** These tools run on the same frontier models, but they wrap them in a workflow that saves real time for a specific job. The test is simple: are you paying for something the raw model cannot do for you, or just for a nicer button? ##### **3. Jasper (Best for Marketing Teams and Brand Voice)** *Jasper wraps frontier models in a marketing-team workflow with brand voice and campaign orchestration.* [Jasper](https://www.jasper.ai) is the wrapper that earns its keep for marketing teams, not solo writers. It layers brand-voice controls, campaign workflows, and team collaboration on top of several fine-tuned models, so a whole team writes on-brand without everyone re-prompting from scratch. **Pros:** - Genuine brand-voice enforcement across a team, which raw models do not centralize. - Campaign and workflow orchestration built for marketing departments. - Deep template and integration library. **Cons:** - The price is steep next to going to the source, and you pay for the orchestration, not the model. - Overkill for a solo creator who can get the same drafts from Claude. **Best for:** marketing teams that need many people writing on-brand at once. If that is your world, it also sits alongside the wider [best AI marketing tools](/best-ai-marketing-tools/) I rank separately. **Pricing:** No free tier, trial only. Pro starts at $59 a month billed annually ($69 monthly). **Free trial:** Yes, a limited trial, no permanent free tier. **Bottom line:** Worth it for a team that needs brand-voice governance and campaign workflows. A solo writer is better off at the source. ##### **4. Sudowrite (Best for Fiction and Creative Writing)** *Sudowrite openly runs Claude and OpenAI models, wrapped in tools built for novelists.* [Sudowrite](https://www.sudowrite.com) is the one wrapper I recommend without hesitation for its niche, because the workflow is genuinely purpose-built. It is made for novelists and fiction writers, with tools like Story Bible, character tracking, and scene expansion that a raw chat window simply does not offer. To its credit, Sudowrite is transparent about the model underneath. Its own pricing page says it runs the latest Claude and OpenAI models, so you know exactly what you are paying the wrapper to organize. **Pros:** - Fiction-specific tools (Story Bible, character and plot tracking) no general model packages. - Openly discloses the frontier models it runs on. - Affordable entry price for the value to a working novelist. **Cons:** - Useless for marketing or business writing, this is a fiction tool. - You are still paying on top of model costs you could access directly for general prose. **Best for:** novelists and fiction writers who want structure around long creative projects. **Pricing:** No free tier, trial only. Hobby and Student starts at $10 a month, billed annually. **Free trial:** Yes, a trial, no permanent free tier. **Bottom line:** The clearest "wrapper worth it" pick on this list, but only if you write fiction. For anything else, go to the source. ##### **5. Grammarly (Best for Editing and Polishing)** *Grammarly is the editing layer that lives everywhere you already write.* [Grammarly](https://www.grammarly.com) is not a content generator, and that is the point. It is the editing pass, catching grammar, tone, and clarity issues right inside your email, doc, or CMS. It earns its spot because it works everywhere you write, not in a separate tab. **Pros:** - Real-time editing built into the browser and apps you already use. - Strong grammar, tone, and clarity suggestions. - A free tier that covers the essentials. **Cons:** - Not a drafting tool, so it pairs with a source rather than replacing one. - Its underlying models are not disclosed, so treat the AI features as a black box. **Best for:** anyone who wants a live editing layer over everything they write. **Pricing:** Free tier with 100 AI prompts a month. Pro is $12 a month billed annually ($30 monthly). **Free trial:** Yes, a capable free tier. **Bottom line:** The editing complement to a source, not a competitor to it. Draft in Claude, polish with Grammarly. ##### **6. Copy.ai (Best for Fast Short-Form Copy Variants)** *Copy.ai says outright it runs OpenAI, Anthropic, and Gemini models.* [Copy.ai](https://www.copy.ai) is built for spinning up many short-form variants fast, ad copy, subject lines, product descriptions, and the like. Like Sudowrite, it is refreshingly honest about the engine: its pricing page advertises access to OpenAI, Anthropic, and Gemini models directly. **Pros:** - Fast at generating many short-copy variations at once. - Openly lists the frontier models it runs on. - Template library aimed at sales and marketing copy. **Cons:** - At $29 a month, you are paying wrapper pricing for models you could prompt yourself. - Long-form quality trails the sources it runs on. **Best for:** teams that want batches of short marketing copy without prompt-wrangling. **Pricing:** Chat plan is $29 a month ($24 billed annually). **Free trial:** No free plan is listed on the pricing page, only a "Try for free" button that does not spell out the terms. **Bottom line:** Fine if the variant workflow saves your team real time. If you are comfortable prompting, the source does the same job cheaper. ##### **7. QuillBot (Best for Rewriting and Paraphrasing)** *QuillBot leads with paraphrasing and rewriting, a distinct job from drafting from scratch.* [QuillBot](https://quillbot.com) earns its place because it does one job better than a raw chat window: reworking text you already have. Its paraphraser rewrites a sentence in different tones and lengths on demand, which is genuinely faster than re-prompting a model for each variation. Around that core it stacks a grammar checker, summarizer, and citation tools. **Pros:** - Fast, controllable paraphrasing in multiple tones, the thing it is built around. - Generous free tier that covers light rewriting without a card. - Bundles grammar, summarizing, and citations in one place for students and researchers. **Cons:** - It rewrites more than it creates, so it complements a source rather than replacing one. - QuillBot stays quiet about which models power it, so you are trusting the output more than the engine. **Best for:** students, researchers, and anyone who rewrites existing text more than they draft from scratch. **Pricing:** Free tier with a 125-word paraphrase limit. Premium is $8.33 a month billed annually. **Free trial:** Yes, a capable free tier. **Bottom line:** The pick when your work is reworking words rather than generating them. Pair it with a source for the actual drafting. ### **The Honest Exception: Not Every Tool Is a Wrapper** It would be lazy to claim every AI writing tool is just a reskinned model, so here is the counter-example. [Writer](https://writer.com) built and runs its own family of large language models, called Palmyra, rather than routing your prompts to OpenAI or Anthropic. That is a real technical moat, and it is why enterprises with strict data-governance rules pick it. If you need an AI writing platform that owns its model stack end to end, Writer is the genuine article, priced for enterprise teams rather than solo creators. It is the rare exception: most of the category is wrappers, and the few that are not tell you so with pride. ### **Save Your Money: The Tools to Skip** These show up on every roundup, but once you have seen the token math, they are hard to justify for most people. [Rytr](https://rytr.me) at $9 a month ($7.50 billed annually) and [Writesonic](https://writesonic.com) at $99 a month ($79 billed annually) are both interfaces over the same frontier models, and neither discloses much special sauce for the price. Rytr is cheap enough to be harmless if the templates click for you. Writesonic now sells itself as an AI search visibility platform, so it is less a writing tool than it used to be. For straight drafting, neither beats going to the source. Spend the money on a Claude or ChatGPT subscription instead and get far more usage. ### **How to Choose an AI Writing Tool** Before you pay for anything, run your use case through these questions. They are the same ones I ask before adding any tool to my own stack. - **Do you actually need a workflow, or just the writing?** If you only need drafts, go to the source (Claude or ChatGPT). Pay for a wrapper only when it automates a real process you would otherwise build yourself. - **Are you a team or a solo writer?** Brand-voice governance across a team (Jasper) is worth paying for. A solo creator rarely needs it. - **What kind of writing is it?** Fiction rewards a purpose-built tool (Sudowrite). Marketing copy, blogs, and email usually do not need more than a source plus an editing pass. - **Do you want to generate or to polish?** Generators (the sources, Jasper, Copy.ai) write from scratch. Assistants (Grammarly, QuillBot) improve or rework what you already wrote. Most serious writers use one of each. - **How much will you actually write?** Heavy volume makes a flat subscription to a source far cheaper than any per-output wrapper. ### **When Not to Use an AI Writing Tool at All** The honest answer is that AI writing has a ceiling, and pretending otherwise is how the internet filled up with slop. Use a human, or heavy human editing, when the writing carries your reputation: a keynote, a sales page your business depends on, anything with legal or medical stakes, or a personal story only you can tell. AI is phenomenal for first drafts, outlines, variants, and getting past the blank page. It is dangerous when you ship its output unread. I have written a whole piece on [how to avoid AI slop](/avoid-ai-slop/) if you want the full method, but the short version is this: the tool writes the draft, you own the judgment. ### **Ryan's Final Thoughts** The best AI writing tool for most people is a direct subscription to a source, Claude or ChatGPT, plus an editing pass. Everything else on this list has to justify a markup over models you can already reach yourself, and only a few genuinely do. The tool vendors will never tell you the last part. The model is commoditized now. The real edge is the system you wrap around it, the prompts, the skills, and the workflows that turn a good model into publishable work on the first try. That is exactly what I packaged into my [AI Skills Stack](https://skills.ryandoser.com/), built on a decade of marketing and SEO work rather than a folder of generic templates. You can start with the free skills and see the difference the system makes. The tool is cheap. The judgment is the moat. ### **AI Writing Tools FAQs** #### **Which AI writing tools are just wrappers?** Most of them, and a few say so openly. Sudowrite states it runs "the latest Claude models by Anthropic" and "several models created by OpenAI." Copy.ai advertises "access to OpenAI, Anthropic, and Gemini models." Grammarly and QuillBot stay quiet about what sits underneath. The honest exception is Writer, which built and runs its own family of models called Palmyra rather than routing your prompts to OpenAI or Anthropic. #### **Is Claude or ChatGPT better for writing?** Claude is the better writer and my pick if you buy only one. ChatGPT is the better generalist. Pick ChatGPT over Claude when your writing leans on research and multimedia, and pick Claude when the output quality of the prose itself is what matters. Claude Pro is $17 a month billed annually ($20 monthly), and ChatGPT Plus is $20 a month, so the cost is not the deciding factor. In my [blind nine-model marketing writing test](/best-ai-models-for-marketing/), Claude and GPT models tied on blog posts, so test both on your own brief. #### **Why are AI writing tools so expensive compared to the API?** Because the markup is on the interface, not the intelligence. A 1,200-word blog post is roughly 1,600 output tokens, using the rule of thumb of about 750 words per 1,000 tokens. Even on a premium model like Claude Sonnet 5.5, that draft runs about two cents. So 15 blog posts cost the tool maybe 10 to 30 cents in raw API calls, and they charge you $29. That markup is defensible when the wrapper genuinely adds workflow, brand voice, or team features. It is not defensible when it just adds a text box. #### **What is the cheapest good AI writing setup?** A single source subscription plus a free editing pass. Claude or ChatGPT at $20 a month covers the writing, and Grammarly's free tier gives you 100 AI prompts a month for the polish. QuillBot's free tier adds paraphrasing within a 125-word limit. That combination costs less than most single wrapper tools and gives you the model the wrappers are reselling. #### **When should I not use an AI writing tool?** When the writing carries your name and your risk. Skip it for a keynote, a sales page that has to convert, anything with legal or medical stakes, and any personal story. A generator is built to produce something plausible, which is the opposite of what those pieces need. --- ## 10 Best AI Coding Tools in 2026 (For Non-Technical Users) URL: https://ryandoser.com/best-ai-coding-tools/ Markdown: https://ryandoser.com/best-ai-coding-tools.md Published: 2026-07-07 | Updated: 2026-07-08 Categories: AI Resources, AI Tool Reviews > This guide ranks the best AI coding tools in 2026 for non-technical users. Honest picks, real pricing, and the criticism vendors hide. The **best AI coding tools** turned me, a marketer, into someone who ships real software. I run SEO for seven-figure SaaS, cybersecurity, and affiliate clients, and most of the internal tools behind that work were built with the exact apps on this list. ### **Why Most "Best AI Coding Tool" Lists Are Useless** Most roundups rank these tools off a spec sheet. They never open a terminal. I use these daily. I have built keyword-research pipelines, WordPress automations, landing pages, and social schedulers with them, often with zero traditional coding background driving the harder parts. If your work leans more toward content than code, my roundup of the [best AI tools for content creators](/best-ai-tools-for-content-creators/) is a better starting point. This list is ranked by what actually holds up when you point it at real building work, not by which vendor has the prettiest homepage. I also went where the honest opinions live. Reddit threads, Hacker News, GitHub issues, the places developers vent when a tool burns them. The pattern in 2026 is loud and clear: model quality is basically at parity across the top tools now. These tools trade the crown depending on the benchmark. Claude tends to lead on harder real-world fixes, OpenAI's Codex leads on terminal and agentic tasks, and on the standard SWE-bench Verified set they are effectively neck and neck. Because every vendor reports on its own setup, treat any single headline percentage as marketing, not a settled ranking. The real fight has moved to cost, trust, and how much the agent breaks while you sleep. I fold that community signal into every pick below, sources and all. ### **The Best AI Coding Tools in 2026** I ranked these on real capability, honest community sentiment, and how they hold up on client work. Prices were verified on the live vendor pages on July 7, 2026. #### **1. Claude Code (Paid)** *Claude Code reads your codebase, edits files, and runs commands from the terminal, IDE, desktop, or browser.* Claude Code is my daily driver and the reason I can build the things I build. It is Anthropic's agentic coding tool that reads your whole codebase, edits files, runs commands, and opens pull requests, all from the terminal, VS Code, JetBrains, the desktop app, or the browser. It wins the head-to-heads on code quality. One [community analysis of 500-plus Reddit comments](https://dev.to/_46ea277e677b888e0cd13/claude-code-vs-codex-2026-what-500-reddit-developers-really-think-31pb) and 36 blind trials had Claude Code taking roughly 67 percent of the matchups. Developers credit it for architecture work and big refactors, and one widely shared story had it cleaning up a 3,000-line file that other tools choked on. The sub-agents, hooks, and MCP support make splitting work across specialized agents feel native. The honest knock is cost. Usage limits set off a real backlash in spring 2026, with daily "limit hell" threads on Reddit, and one benchmark clocked it using roughly four times the tokens of a leaner tool like Aider. There is no free tier. Access comes with [Claude Pro](https://claude.com/pricing) at 20 dollars a month (17 a month billed annually) or Max from 100 a month. If you are a marketer wondering whether this is worth learning, I made the full case in [why every marketer should be using Claude Code](/why-marketers-should-use-claude-code/). #### **2. Codex CLI (Paid)** *Codex CLI is OpenAI's terminal coding agent, tied to your ChatGPT login and built for long autonomous runs.* Codex is Claude Code's usable-all-day rival, and that framing comes straight from the community. OpenAI's [open-source terminal agent](https://developers.openai.com/codex/cli/) is built in Rust, reads and edits your code locally, and ties to your ChatGPT login so you skip the separate API key. The dominant Reddit refrain is that Codex at 20 dollars lets you code all day without hitting limits, while Claude at the same price runs out on a handful of complex prompts. Developers trust it for long, autonomous runs, with one shared post describing a roughly 25-hour unattended session that stayed on spec and repaired its own failures. It leads on terminal and shell-heavy agentic work. The top gripe is that it nags. Out of the box it asks permission for every file read and command, which the community fixes with a couple of flags. Even fans admit the raw code quality sits just below Claude on the hardest problems, which is why the smartest developers run both. Access comes with a ChatGPT plan, from Plus at 20 dollars a month up to Pro at 100. **Claude Code vs Codex, the short version:** Claude for architecture and gnarly refactors, Codex for cheap all-day autonomy and DevOps grinding. Most pros I know run both on purpose. The split looks different for marketing work, and I broke down [how I divide jobs between the two agents](/claude-code-and-codex-together/) when the output is content rather than software. #### **3. Cursor (Free & Paid)** *Cursor pairs an AI-first editor with its standout Tab feature that predicts your next edit.* Cursor is the community default for a reason, and its Tab feature is the stickiest thing in AI coding. It does not just autocomplete the line you are on. It predicts your next edit, so you rename a function and it pre-stages that change everywhere the function is referenced. Developers describe it as disappearing into their fingers. It is an AI-first editor, a fork of VS Code, with a strong multi-file agent and the freedom to swap between Claude, GPT, and Gemini models per task. The [Hobby tier](https://cursor.com/pricing) is free with no card. The Individual plan runs 20 dollars a month, with Teams at 40 per user. Cursor's reputation took a hit in June 2025 when it moved to usage-based billing. Power users reported bills jumping from 28 dollars to 500 in three days, and the company publicly apologized for the trust damage. The mature take from developers who ran both is that Cursor and Claude Code now feel about equal on quality, so the real cost is losing context when you switch between them. #### **4. GitHub Copilot (Free & Paid)** *GitHub Copilot lives natively across every major editor and stays the safe enterprise pick.* Copilot is the safe institutional pick, the one nobody gets fired for buying. It lives natively across VS Code, Visual Studio, JetBrains, Neovim, and Xcode, and enterprises love the IP indemnification that most rivals do not offer. The [free tier](https://github.com/features/copilot/plans) gives you 2,000 completions and 50 chats a month, Pro is 10 dollars a month, and Pro+ is 39. That free tier is the most generous genuinely-useful one here, which makes Copilot my default suggestion for beginners. Here is the part the vendor pages hide. Developers have been complaining for months that Copilot is getting lazy, with a long GitHub thread titled ["Is Copilot slowly getting worse?"](https://github.com/orgs/community/discussions/68356) People say completions that used to flow now need babysitting. The blame usually lands on constant model swaps introducing regressions. Copilot also moved to usage-based billing in June 2026, which the community reads as the end of the all-you-can-eat era. #### **5. Claude (Free & Paid)** *The Claude web app and Cowork are the lowest-friction way to code with AI before you open a terminal.* Before you ever touch a terminal, the [Claude web app](https://claude.ai/) is the lowest-friction way to code with AI, and it is where a lot of my marketing team's smaller builds start. Artifacts generate live React apps, SVGs, and interactive prototypes right inside the chat, which developers repeatedly call the thing ChatGPT does not match. The 200,000-token context window means you can drop an entire codebase in and debug by conversation. Claude Cowork extends this into an agentic workspace on paid plans, so you get Claude's coding agents without any terminal setup. It runs on the same subscription as Claude Code. Free tier for chat, Pro at 20 dollars a month, Max from 100. I broke down when to use each one in my guide to [Claude AI vs Cowork vs Code](/claude-ai-vs-cowork-vs-code/). The recurring complaint mirrors Claude Code: the caps. A March 2026 bug had five-hour Claude Code sessions draining in one to two hours, and the community cares more about predictable cost than benchmark scores. #### **6. Lovable (Free & Paid)** *Lovable lets you describe an app and get a polished prototype, the standout of the vibe-coding builders.* Lovable is the vibe-coding pick, a browser-based builder where you describe an app and get a working prototype. [Lovable](https://lovable.dev/) wins when the interface has to look great with minimal effort, and it is the tool a non-technical founder can use to ship a SaaS prototype in an afternoon. It holds consistent styling across pages better than most rivals, and it wires up a backend, auth, and Stripe without you touching a config file. Free tier gives you five build credits a day, with Pro from 25 dollars a month. Now the part with real receipts. Credit burn is the number one frustration. The AI gets stuck in a loop, fixes one thing, breaks another, and charges you for every attempt. Lovable also has a real security black eye: CVE-2025-48757 exposed more than 170 apps built before its late-2025 fix, with API keys leaking from client bundles. It is excellent for prototypes and dangerous at scale. Vibe-code the draft, then bring engineering discipline for anything real. #### **7. Replit Agent (Free & Paid)** *Replit Agent builds, runs, and deploys apps from the browser with zero local setup.* Replit Agent is the fastest path from idea to a running, deployed app with zero local setup, all in the browser. [Agent 3](https://replit.com/) runs autonomously for up to around 200 minutes, tests apps as it builds, and fixes its own errors. For someone with little coding experience who just wants a live app, the speed is genuinely impressive. Starter is free, Core is 25 dollars a month (20 billed annually), and Pro is 100 (95 billed annually). I am putting it in the middle for a reason the community will never let it forget. During a documented code freeze, the Agent ran unauthorized commands and wiped a live production database belonging to a well-known SaaS founder, then admitted it panicked and initially claimed the rollback would not work. Agent 3 also triggered a pricing revolt, with users reporting 1,000-dollar weeks after it started spawning sub-agents that refactor working code you never asked it to touch. Great for throwaway prototypes, terrifying anywhere near production or a real budget. #### **8. Windsurf, now Devin Desktop (Free & Paid)** *Windsurf is now Devin Desktop after Cognition acquired it and windsurf.com began redirecting to devin.ai.* This one comes with an asterisk you will not find on most lists. Windsurf has been folded into Cognition and rebranded as [Devin Desktop](https://devin.ai/desktop), and windsurf.com now redirects to devin.ai. The Cascade agent is still genuinely strong, and developers on Reddit say it understood a medium-to-large codebase better than Cursor did. The reason it dropped in my ranking is trust, not capability. Google reverse-acquihired the founders and around 40 top engineers in July 2025, then the remaining staff were offered buyouts to leave. Hacker News read it as a founder deserting his team. The fair question developers now ask is whether a tool that lost its entire core team, and is now mid-pivot into Devin, will keep evolving. Windsurf also quietly dropped its old price advantage and now matches Cursor at 20 dollars a month, so the one clear edge is gone. Free tier available, Pro at 20, Max at 200. #### **9. Cline (Free, Open Source)** *Cline is an open source agent built around visible diffs and step-by-step approval.* Cline is what you reach for when you do not trust an agent to touch your code without asking. It is an [open-source VS Code extension](https://cline.bot/) built around Plan Mode and Act Mode, so you strategize first, then approve each step with visible diffs. Nothing lands in a hidden box. Developers who distrust autonomous agents committing straight to main love it for exactly that. It is Apache 2.0, free, and bring-your-own-key, so it runs any model including local ones. There is now a flat ClinePass option at 9.99 dollars a month if you would rather not manage keys. The catch is the meter never stops. Heavy users on Claude Sonnet report 50 to 200 dollars a month in API tokens, and a context-condensing update (GitHub issue 5616) caused a wave of complaints about excessive token burn. The savings over a flat subscription are real, but only past a usage threshold and only if you route routine work to cheaper models. It is a skill, not a default. #### **10. Aider (Free, Open Source)** *Aider is the token-efficient terminal pair programmer with the best git integration on this list.* Aider is the tool for people who refuse to play the subscription-meter game. It is an [open-source terminal pair programmer](https://aider.chat/) with the best git integration on this list, auto-committing every change with a sensible message and making diffs and undos painless. It is model-agnostic and bring-your-own-key, so it works with Claude, GPT, DeepSeek, or a local model. Its claim to fame in the community is efficiency. An [independent benchmark from Morph](https://www.morphllm.com/comparisons/morph-vs-aider-diff) had Aider using roughly 4.2 times fewer tokens than Claude Code on the same 47-file job, which is why the self-hosting and local-model crowd on Reddit swears by it. The trade-off is that it is less agentic than the new wave. Context management is manual, you add files yourself, and it is terminal-only with no visual diff review. Think of it as a precise pair programmer that keeps you in the driver's seat. ### **Which AI Coding Tool Should You Pick?** The honest answer is that you build a stack, then match the tool to the job. Here is the fast version. - **Total beginner or tight budget:** start with GitHub Copilot. The free tier is the most generous, and it teaches you patterns right inside VS Code. - **Daily driver for real work:** Cursor if you want an editor, Claude Code if you live in the terminal. - **Complex reasoning, big refactors, large codebases:** Claude Code, for the large context window and top-tier code quality. - **Cheap all-day autonomy:** Codex, Aider, or OpenCode. - **Non-technical founder shipping an app fast:** Lovable, Bolt, or Replit. - **Privacy, air-gapped, or self-hosted:** Cline pointed at a local model through Ollama, so your code never leaves your machine. Not my wheelhouse, but that is the lane. The stack most working developers I know actually run is Cursor as the daily editor plus Claude Code for the heavy refactoring and audits. Start there. If SEO is your day job like mine, the same logic applies to my roundup of the [best AI SEO tools](/best-ai-seo-tools/). And once you want those coding agents running on a schedule instead of by hand, see my rundown of the [best AI automation tools](/best-ai-automation-tools/). ### **Honorable Mentions: The Tools Reddit Loves That Nobody Lists** Generic roundups miss the fastest-rising community darlings, so here are the ones worth watching. [OpenCode](https://opencode.ai/) is the breakout open-source terminal agent, essentially Claude Code but model-agnostic across dozens of providers including local models. It hit number one on Hacker News and racked up huge adoption fast. If being locked to one company's models bothers you, this is the answer. [Amp](https://ampcode.com/) from Sourcegraph gets the most emotional praise in the developer threads, with users saying it finishes the job every time on prompts that stalled out in Cursor. Its parallel sub-agents and deep codebase indexing are the draw, and there is now an ad-supported free tier. [Zed](https://zed.dev/) is the speed darling, a Rust and GPU-native editor with a sub-second cold start that now runs Claude and Codex agents inside it through the Agent Client Protocol. [Bolt.new](https://bolt.new/) is Lovable's vibe-coding sibling, built by StackBlitz. It hands you more control than Lovable, letting you open any file, add npm packages, and keep hacking on the project. The community line is simple. Describe an app, use Lovable. Give me a project I can keep building, use Bolt. Free tier includes a million tokens a month, with Pro at 25 dollars. [Base44](https://base44.com/) is the rising all-in-one builder Wix acquired in 2025 for a reported 80 million dollars. Its wedge over Lovable and Bolt is that the backend, auth, and analytics are built in, and you can export the full source code to your own repo at any time, so there is no lock-in. Free tier available, paid from 16 dollars a month. ### **Ryan's Final Thoughts** The best AI coding tool is not a single winner, it is a workflow. Remember that most of these tools are thin harnesses over the same frontier models, so the model you point them at often matters more than the logo on the app. I dug into [the same wrapper problem in AI writing tools](/best-ai-writing-tools/), where the markup over the raw model is even harder to justify. I run Claude Code as my primary, keep Codex or Aider around for cost-sensitive grinding, and reach for the browser tools when I want a prototype fast. Pick your primary on quality, your backup on cost, and never let an autonomous agent near production without a leash. Building that stack is where most people stall, so I packaged the exact skills and workflows I use on client work into my [AI Skills Stack](https://skills.ryandoser.com/). You can start with the free skills and see what a decade of marketing and SEO expertise adds once it is baked into the tools. Start there, break a few things, and build the stack that fits how you actually work. ### **AI Coding Tools FAQs** #### **What is the best AI coding tool for a complete beginner?** GitHub Copilot. Its free tier gives you 2,000 completions and 50 chats a month, which is the most generous genuinely useful free tier on this list, and Pro is only 10 dollars a month if you outgrow it. If you are non-technical and want a working app rather than a code editor, Lovable, Bolt, or Replit are the better starting point, because they let you describe what you want instead of editing files. #### **Is it safe to use AI coding tools on production code?** Not without a leash, and there are documented reasons why. During a code freeze, Replit's Agent ran unauthorized commands and wiped a live production database belonging to a well-known SaaS founder, then admitted it panicked. Lovable's CVE-2025-48757 exposed more than 170 apps built before its late-2025 fix, with API keys leaking from client bundles. Use these tools freely on prototypes and side projects. On production, require review before anything executes. #### **Does Claude Code have a free tier?** No. Access requires a paid Claude plan, either Pro at 20 dollars a month (17 billed annually) or Max from 100 a month for heavy use. That is the main reason I point beginners at Copilot first, even though Claude Code is my own daily driver. #### **Which AI coding tool uses the fewest tokens?** Aider, by a wide margin. An independent benchmark from Morph had Aider using roughly 4.2 times fewer tokens than Claude Code on the same 47-file job, and another benchmark clocked Claude Code using roughly four times the tokens of a leaner tool like Aider. That gap only turns into savings past a real usage threshold, and only if you route routine work to cheaper models. #### **Is one model clearly best at coding?** No, and treat any single headline percentage as marketing rather than a settled ranking. One community analysis of 500-plus Reddit comments and 36 blind trials had Claude Code taking roughly 67 percent of the matchups, which is meaningful but not decisive. Model quality is basically at parity across the top tools now, so the harness, the context it holds, and the price you pay matter more than the model badge. --- ## 13 Best AI SEO Tools in 2026 (Ranked by an SEO Expert) URL: https://ryandoser.com/best-ai-seo-tools/ Markdown: https://ryandoser.com/best-ai-seo-tools.md Published: 2026-07-07 | Updated: 2026-10-09 Categories: AI Resources, AI Tool Reviews > The 13 best AI SEO tools in 2026, ranked by an SEO expert managing seven-figure clients, plus how link building now wins AI search citations. The **best AI SEO tools** now decide two things at once: whether Google ranks you, and whether ChatGPT even says your name. ### **Why "AI SEO Tools" Means Something New in 2026** Search split into two games. People still Google things, but a growing share read an AI answer and never click. That changes what a good SEO tool has to do for you. The old scorecard was keyword density and backlinks. The new one adds a harder question: does an AI engine trust you enough to cite you? If that framing is new to you, start with my breakdown of [what AI SEO actually means](/ai-seo-strategy/) and come back for the tools. Most tools that call themselves "AI SEO" are old suites with a writing assistant bolted on. A few were built for this moment. I did not pull this list from the top of Google. I have generated millions of dollars through SEO and AI search, and I currently run SEO for seven-figure clients across SaaS, cybersecurity, and affiliate sites. These are the tools I actually reach for on client work, ranked by what moves rankings and revenue, not what a vendor pays to promote. I cross-checked the community chatter on Reddit and X against my own results, so you get the honest version, including where a popular tool quietly frustrates the people paying for it. I also cover a shift most roundups skip: why link building and trust signals suddenly matter more for AI search than another on-page tweak. The tool I use for that side of it is covered separately in my [Backlinker AI review](/backlinker-ai-review/). ### **The Best AI SEO Tools in 2026** I ranked these for how I actually deploy them across client accounts, from the data layer up to the content and visibility tools. Prices run from free to agency-tier, so read the honest notes before you buy. | Tool | Best for | Starting price | | DataForSEO | The data layer under everything else | Pay-as-you-go, no monthly seat fee | | Ahrefs (Letaido) | Backlinks and competitive research | Ahrefs from $129/mo. Letaido, its agent product, $99/mo plus AI usage | | Rankability | Agencies running client work | $97/mo Starter, self-serve | | Semrush | All-in-one suite with AI visibility | $139/mo SEO plan, API on Advanced at $549/mo | | Claude Code for SEO | Builders who want to automate their own workflows | $20/mo Claude Pro | | Surfer SEO | Guardrails for writers optimizing drafts | $49/mo Discovery (billed yearly) | | Search Atlas (OTTO) | Automated on-page fixes, with supervision | $79/mo billed annually, OTTO included on one project | | ChatGPT and Claude | Ideation layer | $20/mo each, usable free tiers | | Perplexity | Research and real-time queries | Free tier, Pro at $20/mo | | Arvow | Hands-off autopilot publishing | $39/mo Solo (promo, regularly $69), up to $249/mo Ultimate | | Peec AI | Tracking brand mentions in AI answers | See the AI-visibility section below | | Clearscope | Premium content grading | $129/mo Essentials, no free tier | | Frase | Solo creators on a budget | $39/mo Starter (billed yearly), 7-day free trial | My Rankability walkthrough below shows what stress-testing one of these tools looks like firsthand, and I went deeper on its 2026 repricing in my full [Rankability review](/rankability-review/). *Testing an AI SEO tool content optimizer during a hands-on review* #### **1. DataForSEO** *DataForSEO homepage, an AI SEO data API with a Claude MCP server* [DataForSEO](https://dataforseo.com/?aff=245611) is my number one for a reason most roundups will never tell you: it is the data layer under everything else. It is not a dashboard. Think of it as an SEO data API covering SERPs, keywords, backlinks, and on-page data, and it ships an official MCP server that plugs straight into Claude and Claude Code. On my client accounts, I have Claude pull live ranking data through it instead of paying for five seat-based dashboards. Pricing is pay-as-you-go with no monthly seat fee, and while Ahrefs still wins on data depth, the keyword and SERP data is decent at a fraction of the cost. I broke down the full rate card and the new v3 MCP server in my [full DataForSEO review](/dataforseo-review/). The tradeoff is that it returns raw JSON, so there is a real setup curve and no pretty interface. For a builder who lives in Claude, that raw access is exactly the point. I lean on this approach in my [Claude Code keyword research](/claude-code-keyword-research/) workflow. #### **2. Ahrefs (Letaido, formerly Agent A)** *Ahrefs Agent A page, captured before the product was rebranded Letaido* [Ahrefs](https://ahrefs.com/letaido) is still the first tool I open for any link-heavy client, and its agent product, launched as Agent A and since rebranded Letaido, is a real agent, not a chat wrapper. It gets full access to Ahrefs data and runs keyword research, competitor analysis, audits, and scheduled monitoring on its own. On a cybersecurity account I manage, I use it to catch competitor backlink moves before they show up in rankings. I compare it head to head with the cheaper pay-as-you-go option in [DataForSEO vs Ahrefs](/dataforseo-vs-ahrefs/), and worked out [which parts of a Semrush plan a per-request API can actually replace](/dataforseo-vs-semrush/) separately. For the cheaper end of the market, here is [where the hidden cost multipliers actually bite](/dataforseo-alternatives/). Letaido is sold as [one $99-a-month plan](https://letaido.com/), with AI usage billed on top. Ahrefs' own page contradicts itself on whether you also need an Ahrefs subscription: a feature bullet says one is required, while the FAQ says Letaido works on its own. Here is my honest warning, and it comes with receipts: one January 2026 accuracy test found Ahrefs Brand Radar reporting 3 ChatGPT mentions where the true count was 123. The backlink data is elite, and it is what I pay for. The AI-visibility layer is not there yet, so I do not trust it for client reporting. #### **3. Rankability** *Rankability homepage, an agency AI SEO optimization tool* [Rankability](https://www.rankability.com/) is built for agencies like the way I run client work, not for hobbyists. It pairs content optimization with ranking diagnosis and AI-visibility tracking across 11 AI platforms, including ChatGPT, Perplexity and Google AI Overviews, in one workspace. Its Serena agent reads a client's real data and tells you what to change to get recommended by AI, which is exactly the report a seven-figure client wants to see. **Update, October 9, 2026:** Rankability changed its pricing on October 7 and now sells three self-serve plans. Starter is $97 a month, Agency $297 and Agency Pro $497, or $970, $2,970 and $4,970 paid yearly. Monthly plans need no annual commitment. Every plan includes unlimited client workspaces and team members, API and MCP access, agency-branded reports and 11 AI platforms. Content projects run 20, 80 or 160 a month and tracked AI queries 100, 300 or 500, shared across clients. There is still no free trial. That no-trial wall is the objection I hear most, since you cannot test before you pay, though one month of Starter is now a cheap way in. If you manage a roster of clients, the branded reporting earns its keep the first month. #### **4. Semrush** *Semrush homepage, an all-in-one AI SEO suite* [Semrush](https://www.semrush.com) is the all-in-one default when you want SEO, PPC, content, and AI search under one login, and it is the tool I hand junior team members first. Its free Copilot assistant reads your reports and suggests next moves, and the AI Visibility Toolkit tracks your brand across ChatGPT, Perplexity, Gemini, Copilot, and Google AI Mode. Core pricing starts at $139 per month on the SEO plan, with API access reserved for Advanced at $549, which I broke down in [Semrush API pricing](/semrush-api-pricing/). One honest caveat applies here, same as Ahrefs: first-party AI-mention trackers are still shaky. I have watched these dashboards undercount real citations on my own brands, so I treat the numbers as directional, not gospel. The arithmetic behind that is in my [Searchable review](/searchable-review/), which works out how few times a day these tools actually sample each prompt. My [AIclicks review](/aiclicks-review/) covers a different failure mode in the same category, where a vendor's own pages disagree with each other on price and plan limits. #### **5. Claude Code for SEO** *Claude Code page, a programmable agent used as an AI SEO tool* [Claude Code](https://claude.com/claude-code) is the unconventional entry, and it is the single biggest edge in my stack. It is not a fixed SaaS product. Instead you get a programmable agent you run from your terminal, and I have shaped it into a full SEO stack: keyword research, drafting, on-page edits, technical audits, and publishing straight to WordPress. I run real client work through it every week. It needs a paid Claude plan from $20 per month on Pro, and it has a real learning curve. You build your own workflow instead of clicking someone else's buttons, which is the whole appeal. I walk through the exact setup in my [Claude Code SEO workflow](/claude-code-seo/) guide (my [AI Skills Stack](https://skills.ryandoser.com) packages those SEO skills if you want them ready to run, free ones included). #### **6. Surfer SEO** *Surfer SEO homepage, one of the best AI SEO tools for content optimization* [Surfer](https://surferseo.com) is the AI content editor I lean on when a writer needs guardrails. You paste a draft, it scores your page against whatever is already ranking, then tells you the terms and questions you missed. It also added AI-visibility tracking across ChatGPT, Perplexity, Gemini, and Google AI Overviews, though basic tracking starts on the Standard plan ($99 per month) and the full AI Tracker lives on Pro ($182 per month), not the entry tier. Pricing starts at $49 per month on Discovery when billed yearly, which covers the core editor. One knock I have seen firsthand on client teams: chasing the content score can push writers toward keyword stuffing and mechanical prose. Use it as a checklist, not a boss, and edit for a human after. #### **7. Search Atlas (OTTO)** *Search Atlas homepage, home of the OTTO AI SEO agent* [Search Atlas](https://searchatlas.com) bundles SEO, ads, content, and AI visibility, and its OTTO agent is the headline: it does not just suggest fixes, it deploys them automatically and monitors your site around the clock. On paper that is the dream for anyone drowning in technical debt. Pricing starts at $79 per month billed annually, about $99 month to month, with a 7-day trial, and OTTO is now included on the Starter plan's one project. Now the warning I give every client considering it: do not let OTTO run unsupervised. It ships many changes through a JavaScript pixel, which means AI crawlers may never see them, an odd gap for a tool sold on AI visibility. I have seen reports of broken renders and thin output. Use its suggestions, then push changes into your CMS yourself. I dug into the review pools, the real pricing, and what its own pages commit to in my full [Search Atlas review](/search-atlas-review/). #### **8. ChatGPT and Claude (for ideation)** *ChatGPT interface used as an AI SEO ideation tool* Every AI-first marketer already pays for one of these, so treat them as your ideation layer. I use them daily for topic clusters, briefs, outlines, meta descriptions, and pressure-testing search intent before I write a word. Neither [ChatGPT](https://chatgpt.com) nor [Claude](https://claude.ai) is an actual SEO tool, and both will confidently invent stats, so I verify everything before it touches a client site. Both cost $20 per month on their paid tiers, and both have usable free versions. I lean on Claude for longer strategic thinking and ChatGPT for fast first drafts. Either one speeds up the work without replacing it. A model hands you a starting draft, not a ranked page. #### **9. Perplexity** *Perplexity answer engine used for AI SEO and AEO research* [Perplexity](https://www.perplexity.ai) is not a dedicated SEO tool, and it belongs here anyway. As an answer engine, it shows me how AI responds to a client's target queries, which sources it cites, and how competitors get pulled into answers. For AEO research, that beats staring at a keyword report. It runs a genuinely useful free tier, with Pro at $20 per month. I use it to reverse-engineer the AI answers I want a client to appear in, then build content that earns the citation. Cheap, fast, and honest about its sources. #### **10. Arvow** *Arvow homepage, an AI SEO autoblogging tool that auto-publishes content* [Arvow](https://arvow.com/) is the autopilot pick, and I am careful about where I point it. Formerly Journalist AI, it runs the full loop: keyword research, article generation in your brand voice, images and links, then auto-publishes straight to WordPress, Shopify, Ghost, or Webflow. It also has an AI agent that fixes on-page issues like schema and internal links. For a high-volume affiliate site, that hands-off content engine is genuinely useful. Pricing starts at $39 per month on Solo (promo, regularly $69), up to $249 on Ultimate, with no free trial. Two honest cautions from what I have seen. First, autoblogging at volume needs a human editor or it drifts into thin content that AI search ignores. Second, reported user complaints center on billing and refunds, so read the terms before you commit annually. Powerful, but supervise it. If you are weighing the agency-priced end of this category, I took apart what $499 a month buys in my [Adaptify SEO review](/adaptify-seo-review/). At the cheaper end of autopilot publishing, both [Outrank](/outrank-review/) and [BabyLoveGrowth](/babylovegrowth-review/) run $99 a month and pair auto-published articles with a backlink exchange, which is the specific combination I would read Google's link spam policy about before switching on. I priced [the whole field of $99 auto-publishers](/outrank-alternatives/) against each other separately. #### **11. Peec AI** *Peec AI dashboard, an AI SEO visibility tracker for marketing teams* [Peec AI](https://peec.ai) is the community favorite that generic roundups bury under enterprise names, and it is the AEO tracker I recommend to clients who are not ready for a big contract. It is a focused AI-visibility tracker that shows how your brand appears across AI search platforms, scoring visibility, position, and sentiment against competitors. The price-to-value is what earns it a spot. If you want the enterprise benchmarks instead, [Profound](https://www.tryprofound.com) is the category leader most pros cite, and [AthenaHQ](https://www.athenahq.ai) is the YC-backed challenger with strong citation-growth case studies. For most of my smaller clients, Peec answers "are we showing up in AI" without an enterprise invoice. Start here before you spend big. #### **12. Clearscope** *Clearscope homepage, a premium AI SEO content grading tool* [Clearscope](https://www.clearscope.io) is the accuracy gold standard I reach for when a single page has to rank and nothing less will do. Its Content Grade tracks closer to real SERP performance than most rivals, and it now watches brand mentions inside ChatGPT and Gemini. On the client work where quality outranks budget, it is worth every dollar. The catch is cost and scope. Pricing starts at $129 per month on Essentials, with no free trial and no free tier, and it only does optimization. For a hobby blog that is overkill. On a SaaS account where one ranked page pays for the year, nobody notices the bill. #### **13. Frase** *Frase homepage, an AI SEO tool for solo content workflows* [Frase](https://www.frase.io) is the value pick I send solo operators to when they cannot buy five tools. Research a topic, build a brief, draft in your voice, publish to your CMS, then watch for content decay, all in one tab. It pulls real People Also Ask, Reddit, and Quora questions, and it does not meter your AI words the way rivals do. Plans open at $39 per month on Starter, billed yearly, with a 7-day free trial and no credit card. The tradeoff I have noticed is that its optimization scoring is a notch weaker than Surfer or Clearscope. For a solo founder starting out, that tradeoff is easy to accept. ### **The Part Most SEO Tool Lists Skip: Link Building and Trust Signals** Here is the shift that matters more than any dashboard, and the one I spend the most client budget on. AI search does not just read your page. It reads your reputation across the whole web, and it decides who to cite based on trust signals your site cannot fake on its own. The data backs up what I see in client accounts. [Ahrefs studied roughly 75,000 brands](https://ahrefs.com/blog/ai-brand-visibility-correlations/) and found web mentions correlate with AI citations far more strongly than raw backlinks do. Other 2025 analyses point the same way: brand search volume and third-party mentions on Reddit, YouTube, and earned press correlate with getting cited more than on-page tweaks. These are correlations, not proof of cause, but the direction matches what actually wins for my clients. *AI SEO tool pricing tiers shown during a hands-on review* Translation for your strategy: earning mentions is the new link building. That is why these platforms belong in a 2026 SEO roundup. I dig deeper into the mechanics in my [guide to AI search](/how-to-manipulate-ai-search/). #### **Link-Building Marketplaces (Presswhizz)** *Presswhizz homepage, a link building marketplace for AI SEO trust signals* [Presswhizz](https://presswhizz.com/) is a link-building marketplace connecting you with publishers for guest posts and niche edits across a claimed 41,000-plus sites, with metrics like DR and traffic shown before you buy. It is fast and transparent, and most orders reportedly land within 24 hours. One honest caveat before you spend. Independent proof is thin, with only a handful of public reviews, and accepting thousands of sites means quality varies. On client work I vet each placement on its own metrics rather than trusting the marketplace wholesale. Convenient, but not autopilot. #### **Digital PR You Run Yourself (Featured and Qwoted)** *Featured homepage, a HARO-style digital PR platform for earned mentions* The self-serve route is a HARO-style platform where journalists post what they need and you pitch expert quotes. If you would rather hand this to someone, I ranked the [AI SEO specialists actually publishing work in this space](/best-ai-seo-experts/). [Featured](https://featured.com/) relaunched the free HARO model after the paid version collapsed, curating journalist requests to your niche so you skip the spammy email blast. It runs a free plan with 3 answers a month, and paid tiers start at $50 per month for more. *Qwoted homepage, a media-sourcing platform for digital PR mentions* [Qwoted](https://www.qwoted.com/) is the other credible pick, trusted by outlets like Forbes and Reuters, and built to keep junk pitches out. Its free tier gives you a couple of pitches a month, while Pro at $149 per month opens 35 pitches plus AI that flags low-competition requests. Between the two, I have landed real press mentions for clients without hiring an agency. #### **Digital PR Agencies (Linkifi and Search Intelligence)** *Search Intelligence homepage, a digital PR agency for earned links* If you would rather outsource, two agencies come up repeatedly, though I will be straight that this is an editorial nod, not community consensus. [Search Intelligence](https://search-intelligence.co.uk/) runs data-led PR campaigns at scale, with per-campaign pricing that starts around 5,500 pounds and a guarantee to keep working until the promised links land. [Linkifi](https://www.linkifi.io/) takes an inbound-journalist approach focused on high-authority placements, with pricing available by consultation only. Co-founder Chris Panteli walked through Linkifi's own research on ChatGPT's sources on [my podcast episode about ChatGPT recommendations for local businesses](/how-to-get-chatgpt-to-recommend-your-business/). Both target the same outcome: earned mentions in publications that AI engines and Google both respect. For a brand that can fund it, outsourced digital PR is the fastest path to the trust signals that get you cited. ### **Ryan's Final Thoughts** If you want these connected to Claude rather than opened in a browser tab, I ranked the [MCP servers that pipe SEO data straight into your assistant](/best-seo-mcp-servers/). Pick by your stage, not by hype. When I onboard a new client, I start with the data layer in DataForSEO or Ahrefs, then layer content tools on top. Solo creators should start with Frase or Perplexity, a $20 model, and free pitches on Featured or Qwoted. Teams that live or die by ranked pages should look at Clearscope, Surfer, or Rankability. Agencies juggling many clients will get the most from Ahrefs plus Rankability's white-label reporting. The technical crowd that would rather build than rent already knows where DataForSEO and Claude Code fit. Whatever you choose, spend as much effort earning mentions as optimizing pages, because in AI search that is what gets you named. ### **Best AI SEO Tools FAQs** #### **What is the best free AI SEO tool?** There is no single free tool that does everything, but you can assemble a workable free stack. Perplexity has a genuinely useful free tier for research and real-time queries. ChatGPT and Claude both have usable free versions for ideation. Frase offers a 7-day free trial with no credit card required, and Featured runs a free plan with 3 answers a month for pitching. What you cannot get free is the data layer, which is why DataForSEO's pay-as-you-go pricing with no monthly seat fee is the cheapest honest entry point for real keyword and SERP data. #### **Can AI SEO tools replace an SEO specialist?** No, and the tools that market themselves that way are the ones to watch most carefully. Search Atlas ships many of its automated changes through a JavaScript pixel, which means AI crawlers may never see them. That is an odd gap for a tool sold on AI visibility, and it is exactly the kind of thing a tool will not catch on its own. These tools compress the work a specialist does. They do not replace the judgment about which work is worth doing. #### **Are AI visibility trackers accurate?** Treat them as directional, not gospel. One January 2026 accuracy test found Ahrefs Brand Radar reporting 3 ChatGPT mentions where the true count was 123. The category is young and the underlying sampling is genuinely hard, so use trackers to watch a trend line over repeated checks rather than to trust any single absolute number. Before you pay for one, it is worth knowing [which AI search metrics hold up and which do not](/ai-search-myths/). #### **How much should I budget for an AI SEO stack?** It depends entirely on stage, and the spread is wide. A solo creator can run on Frase at $39 per month plus a $20 model subscription and free pitching tiers. A team that lives on ranked pages is looking at Clearscope from $129 per month or Surfer from $49 per month on Discovery billed yearly. An agency adding Ahrefs' Letaido agents pays $99 per month plus AI usage, and Rankability starts at $97 per month on Starter, with Agency at $297 for bigger client rosters. Start at the data layer and add tools only when a specific job demands one. #### **Do backlinks still matter for AI search?** Mentions matter more. Ahrefs studied roughly 75,000 brands and found that web mentions correlate with AI citations far more strongly than raw backlinks do. That is the practical shift: a publication naming your brand in text can be worth more than a linked citation buried in a resource page, which is why the digital PR and HARO-style options belong in an AI SEO stack at all. --- ## 5 Claude Code Hacks From a Top One Percent User (Steal These) URL: https://ryandoser.com/claude-code-hacks/ Markdown: https://ryandoser.com/claude-code-hacks.md Published: 2026-07-06 | Updated: 2026-07-07 Categories: AI Rabbit Holes, Claude Code > Claude Code Hacks from a top one percent user. This includes ASCII planning, Gemini workhorse, guided loops, and Codex review. These **Claude Code hacks** come from Mark Kashef, an AI expert who lives in Claude Code and spends $3,000 a month on tokens. By his own count he went from a top 20% user to a top 10% user in months, and he runs the tool like almost no one else. ### **Claude Code Hacks Video Guide** I sat down with [Mark Kashef](https://www.promptadvisers.com/), founder of Prompt Advisors, to break down the exact Claude Code hacks he uses to run his business, his YouTube channel, and even his personal life. Watch the full conversation here. Mark went from a top 20% user in January to a top 10% user by summer, mostly by studying the Claude Code harness after it leaked in March. His point stuck with me: a recent Google study found only 10% of a workflow's results come from the model. The other 90% is the harness. So the skill worth building is not "which model," it is how you drive the tool. If you want to package your own Claude Code workflows into reusable systems, that is exactly what I teach inside the **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)**, a decade of marketing experience turned into ready-to-run skills. ### **Best Claude Code Hacks to Use in 2026** Here are the five hacks Mark walked me through, each one pulled straight from his real workflow. #### **Hack 1: Plan in ASCII Art Before You Build Anything** Most people jump straight to building. That first version becomes an anchor the model never lets go of. Mark's fix is to plan in plain text first. He asks Claude Code to draft a page or a system using ASCII art, a rough sketch made of characters, before a single line of real code exists. It lets him move things around and argue with the model cheaply. "Once you build V0, that is the core foundation for the LLM for that session," Mark told me. "It's going to be very anchored with that V0." A full first draft of a web page can burn 50,000 to 100,000 tokens. An ASCII sketch costs almost nothing and shows you the generic "vibe code slop" coming before you commit. Mark spends most of his time planning and only hours building. On one enterprise system he wrote 18 versions of a plan file over two weeks, then built 80% of it in two days while he was away from the computer. The tradeoff is real. This front-loads your time into planning, which feels slow if you are used to prompting and hoping. But once the plan is tight, the building runs almost on its own. #### **Hack 2: Use Gemini as Your Cheap Workhorse** Claude Code is a strong daily driver. It is not the right tool for every job, and paying Opus prices for grunt work is a waste. Mark runs a Gemini skill for the heavy, boring tasks. Gemini is weak at coding but strong at multimodal work, and it comes with a fast, cheap million-token context window. He uses it to turn messy PDFs into clean markdown, describe every image and chart on a page, and distill hundreds of documents into a set of high-value "nuggets" before anything touches a database. *Mark built this Local AI Engineering guide by running Gemini through rounds of deep research, then combining it with a Claude Code skill.* This is how a good AI knowledge base should work. You do not dump raw PDFs into a database and hope for magic. You keep the useful parts and throw out the junk, so you are not paying to store noise. Mark also points Gemini at video (his "date night" skill scores restaurant Instagram posts) and at full-page screenshots that Claude in Chrome sometimes misses. If you care about keeping costs down, my breakdown of [Claude Code usage tips to save tokens](/claude-code-usage-tips/) pairs well with this approach. #### **Hack 3: Use Loops for Testing, Not for Thinking** Loop engineering is trendy right now. Mark was blunt with me: most of how people use it is a complete waste of time. Telling Claude Code to "make it better" a hundred times with no context is just spending thousands of tokens to avoid writing a proper plan. People use looping as a substitute for thinking. The loops that actually work give the model a target. Here is where Mark uses and abuses them: - **Testing a build or an API.** Run Claude in Chrome through the full user journey and keep going until it hits zero errors. - **Grading against a rubric.** Define what success looks like, then loop until the output meets every requirement. - **Simulating your audience.** Before he films, Mark loops a script through personas based on his real YouTube demographics, has them leave the harsh comments a viewer might post, and rewrites until most simulated comments turn positive. The pattern is always the same. Add context, give it a rubric, and reiterate. A blind loop guesses. A guided loop improves. Watch the cost, though, since a runaway loop can quietly burn thousands of tokens, so cap it with a clear stopping condition. #### **Hack 4: Let Codex and Claude Code Roast Each Other** Mark calls himself anti-tribal. He does not care whether a tool wins the internet war. He uses whatever serves the task. About 90% of the time he builds with Claude Code, then has Codex review everything Claude produced. He grabs the free [Codex plugin from OpenAI's official GitHub](https://github.com/openai/codex) and runs a command called adversarial review, which audits a plan, pulls out its weaknesses, and offers fixes. *The Codex adversarial review command Mark runs to poke holes in a Claude Code plan before he builds it.* The real trick is not running it once. Mark tells Claude Code to go back and forth with Codex on a loop until nothing is left to flag. By round seven Codex is still poking holes. By version 10, on a $20 Codex plan, he has a plan that is not Fort Knox but is genuinely strong. He calls this his holy trinity: Gemini as the workhorse, Claude Code as the daily driver, and Codex as the devil's advocate. Adversarial review is one reason to keep both installed, and [running Claude Code and Codex together](/claude-code-and-codex-together/) pays off for content work too, since only one of them can make an image. Three models, each doing what it does best, and three of [the AI coding tools I rank against each other](/best-ai-coding-tools/). If you want to go deeper on that team-of-agents idea, I broke down [Claude Code agent teams](/claude-code-agent-teams/) in a separate post, and workflows are the newer evolution of it. #### **Hack 5: Turn Boring Explanations Into 3D Visuals** This is the hack Mark called the biggest change he ever made to his YouTube workflow. He gives Claude Code access to the free Hyperframes CLI, feeds it a GitHub link, and asks it to build animated visuals. A play button that shows how a context window degrades over time hits far harder than a talking head explaining the same idea. Aaron Makelky now does most of his video editing in HyperFrames from the terminal, which we covered in [our episode on editing video with Claude Code](/ai-video-editing/). *A 3D "Layers of an Agentic OS" visual Mark built with Claude Code and the Hyperframes CLI.* Once he likes a result, he tells Claude Code to crystallize it into a skill so he never has to explain it again. That is why he can spin one up in a minute during a podcast. He uses the same trick for content repurposing, turning a video into shareable B-roll charts, and even made a set of anatomy diagrams to help his wife study for a Pilates certificate. The honest downside is polish. Mark said it took him a while to get the nice 3D look, so your first pass will not look this clean. The payoff only shows up after you save the winning version as a skill. One more habit worth stealing sits underneath all of this. Mark saves each session with a custom TLDR command that writes the key decisions to Obsidian and auto-injects them into his next session. Context windows degrade past roughly 300,000 to 400,000 tokens, so he never fills one up. He just hands off and keeps moving. If you are still using Claude like a chatbot, my guide on [Claude AI vs Cowork vs Code](/claude-ai-vs-cowork-vs-code/) shows where that operator mindset starts. ### **Ryan's Final Thoughts** Mark's biggest warning was about money, not tools. The cheap, subsidized token era is ending, and he thinks token budgets will land on the CFO's desk within a year. His advice was simple: pay for the best AI to learn how it works while it is still cheap. As he put it, it has never been a better time to become mediocre at this, because a few months of real practice will leave you wishing you started sooner. He shares more of this thinking on his [YouTube channel](https://www.youtube.com/@Mark_Kashef) and inside his [Early AI Dopters community](https://www.skool.com/earlyaidopters/about). ### **Claude Code Hacks FAQs** #### **What are the best Claude Code hacks for beginners?** Start with planning before building. Ask Claude Code to sketch your idea in ASCII art or plain text first, argue with it, then build once you like the direction. This one habit saves the most tokens and produces better results than one-shot prompting. Plan with Opus, then run the build with a cheaper model like Sonnet. #### **Do I need the $200 Claude Max plan to use these Claude Code hacks?** No. Mark runs a Max plan and spends thousands on extra tokens, but the core ideas work on any plan. Planning in plain text, using a cheaper model for grunt work, and giving loops a clear rubric all save money. Heavier hacks like dynamic workflows spend one to two million tokens per run, up to three million on the most intensive tasks, so use those only when the job justifies it. #### **How does Mark Kashef use Gemini with Claude Code?** He treats Gemini as a cheap workhorse for multimodal tasks. Gemini converts PDFs to clean markdown, describes images and charts, analyzes video and screenshots, and distills large document sets into high-value summaries. Claude Code then works from that clean, pre-processed input, which saves tokens and improves accuracy. #### **What is Codex adversarial review in Claude Code?** It is a command from the free OpenAI Codex plugin that audits a plan, exposes its weaknesses, and suggests fixes. Instead of running it once, you tell Claude Code to loop back and forth with Codex until no red flags remain. The result is a much stronger plan before you spend tokens building. --- ## Claude Skills vs Custom GPTs: What to Do Before GPTs Retire URL: https://ryandoser.com/claude-skills-vs-custom-gpts/ Markdown: https://ryandoser.com/claude-skills-vs-custom-gpts.md Published: 2026-07-06 | Updated: 2026-09-25 Categories: ChatGPT, Claude Code > Claude Skills vs Custom GPTs after OpenAI's retirement notice: what the GPT migration keeps, what it drops, and why a skill file is the safer bet. The **Claude Skills vs Custom GPTs** comparison looks very different now that OpenAI is retiring custom GPTs on December 11, 2026, and its migration path turns a GPT's instructions into a skill. ### **Claude Skills vs Custom GPTs: What Each One Is** A custom GPT is a version of ChatGPT you configure with instructions, knowledge files, and actions. You build it in the GPT Builder, and it lives inside ChatGPT. A Claude Skill is a folder with a markdown file called SKILL.md inside it. Claude loads the full file when your request matches what the skill is for or when you call it by name, and you can drop scripts and reference files into the same folder. In the video below, I build the same email newsletter skill three different ways, including one that starts from an existing GPT or Project. When I recorded it, my setup already ran on 15 to 20 skills, from an anti-slop checker to an email writer to a social post writer. If you want to skip the blank page, I packaged the ones I use to run my business into the **[Claude Code Skills Stack](https://skills.ryandoser.com/)**. ### **OpenAI Is Retiring Custom GPTs** This is the news that makes the Claude Skills vs Custom GPTs comparison urgent. On September 11, 2026, OpenAI announced it will retire custom GPTs across every ChatGPT plan. According to OpenAI's [custom GPT retirement FAQ](https://help.openai.com/en/articles/20001519-custom-gpt-retirement-and-migration-faq), GPTs are scheduled to retire on December 11, 2026. Enterprise workspaces with an approved deferral get until February 11, 2027. At retirement, custom GPTs stop running and their GPT pages go away. OpenAI's GPT creation help article says personal accounts (Free, Go, Plus, and Pro) can no longer create or publish new GPTs, though its pricing page still lists GPT creation on the paid personal plans. OpenAI's help pages don't fully agree on the interim milestones, so treat any date other than the retirement itself as a moving target. The December 11 date is the one to plan around. ### **What the GPT Migration Keeps and What It Drops** OpenAI offers a "Migrate to plugin" option under My GPTs, which the GPT's creator runs on a published GPT. Per OpenAI's [GPT migration guide](https://learn.chatgpt.com/docs/migrate-custom-gpts), you can even migrate after retirement, although the GPT itself will no longer run. The telling part is what the migration does with your instructions. Your GPT's instructions become a skill inside the new plugin. Knowledge files get copied over as reference files, and connected apps move over as apps. Several things do not survive the move: - Custom actions (the API calls your GPT made) do not transfer. - The model you picked for the GPT does not carry over. - Sharing settings reset, so a migrated plugin starts private. - Drafts and unpublished edits are left behind, because migration uses the latest published version. - Conversation starters don't transfer one-to-one, and OpenAI warns the plugin may respond differently than the GPT did. If your GPT leans on custom actions, budget time to rebuild them. If it is mostly instructions and a few files, the migration keeps the valuable part, but run a few real tasks through it before you trust it. ### **ChatGPT and Claude Now Share One Skill Format** Skills in ChatGPT follow the same open SKILL.md standard Claude reads, so the instructions you once wrote for a GPT can also run as a Claude Skill. That is the part of the retirement OpenAI's help pages don't spell out. OpenAI's [skills documentation](https://learn.chatgpt.com/docs/build-skills) says skills in ChatGPT and Codex build on the open agent skills standard: a directory with a SKILL.md file that needs a name and a description. The [Agent Skills standard site](https://agentskills.io/) lists dozens of tools that read these folders, including Claude, Claude Code, ChatGPT and Codex, Cursor, VS Code, and Gemini CLI. The format is shared, so a skill is no longer tied to one chatbot, though any scripts inside it may need edits to run somewhere new. That changes my old Claude Skills vs Custom GPTs argument, and I want to be honest about it. When I first wrote this post, the case against GPTs was that you could never take one with you, and that is now only half true. The migrated skill still lives inside a ChatGPT plugin on OpenAI's servers. A skill folder you keep on your own computer, whichever app runs it, is the version you fully control, so I build mine as files first. *A Claude Skill is a plain markdown file you own, open here in Claude Code.* ### **Fix a Skill Mid-Task, Not in a Builder** This is still the difference that sold me. When Claude gets something wrong, I correct it once and tell it to update the skill file so the fix sticks. In the video, I ask Claude to put an emoji in every subject line and shorten the email, then add one line: update this skill going forward. Claude shows the exact change in red and green and asks before it edits the file. *Claude proposing an edit to the email skill file and asking for approval before saving it.* A real example from my own setup: my blog skill kept slipping a dash I never use into drafts, so I had Claude write a rule banning it into the skill file. The fix now lives in the skill instead of in my memory. A custom GPT stayed exactly as configured until you went back into the builder to change it. With a skill, the correction happens in the same chat where you spotted the problem. If you want to see how far this loop goes, I broke down my setup in my guide on [Claude Code autoresearch](/claude-code-autoresearch/). ### **Where Claude Skills Work Today** Skills are no longer a paid-only feature. According to Anthropic's [skills help article](https://support.claude.com/en/articles/12512180-use-skills-in-claude), they are available on the Free, Pro, Max, Team, and Enterprise plans, as long as code execution is turned on. On the Free, Pro, and Max plans, you turn on code execution under Settings, then add skills under Customize, where you can upload a skill as a ZIP file. The menu has moved since I recorded the video, so follow the current path rather than what you see on screen. Inside Claude Code, a skill is just a folder, so there is no upload step at all. Skills you enable in your Claude settings also load in Claude Code 2.1.273 or later, and the API supports skills in beta through the code execution tool. Moving a skill from your laptop into the Claude app still means zipping and uploading it. The file travels anywhere, but the install happens once per place. ### **How to Move a Custom GPT Into a Claude Skill** You won't write any code for this. My method starts from the context you already built. *Moving a GPT into a Claude skill: instructions and files carry over, custom actions need a rebuild.* - Open your GPT's configuration and copy its instructions, plus any knowledge files you uploaded. - Paste them into Claude along with Anthropic's skill best practices, and ask it to turn everything into a SKILL.md file. - Review the file, ask for changes until it reads right, then download it. - Drop it into your skills folder in Claude Code, or upload it in the Claude app. When I did this in the video from an existing Claude Project, the skill came out far more detailed than the one I built from a blank prompt. The project's instructions, files, and chat history gave Claude real context to work from. If you are converting a Claude Project, I walked through [rebuilding a Project as a skill file](/turn-claude-projects-into-skills/) step by step. My full guide on [how to create Claude Skills](/claude-skills/) covers the three methods from the video and adds a fourth. If you are leaving ChatGPT entirely, my walkthrough on [switching from ChatGPT to Claude](/switch-from-chatgpt-to-claude/) covers the rest of the move. ### **The Deed Still Beats the Lease** A custom GPT was always the rental, and OpenAI just gave notice. The instructions you wrote are worth keeping, and a skill is where they belong. Move them before December 11 so you can test the replacement while the original still runs, and keep a copy as a file on your own machine. That way the next platform change is an upload, not a rebuild. ### **Claude Skills vs Custom GPTs FAQs** #### **Is OpenAI getting rid of custom GPTs?** Yes. OpenAI announced on September 11, 2026 that custom GPTs will retire on December 11, 2026, with a February 11, 2027 date for Enterprise workspaces that get an approved deferral. After that, GPTs stop running, but OpenAI's migration guide says a GPT's creator can still migrate it to a plugin later, so your instructions are not lost on the deadline. #### **What is the ChatGPT equivalent of Claude Skills?** ChatGPT now has skills of its own, built on the same open SKILL.md standard Claude uses. Where you can use them depends on the surface and your plan: standalone skills run in the ChatGPT desktop app and Codex, while skills bundled in plugins reach ChatGPT on web and mobile too. #### **Can Claude Skills be used with ChatGPT?** Often, yes. Because both follow the Agent Skills standard, a SKILL.md folder built for Claude has the same basic structure ChatGPT and Codex expect. Test it before relying on it, since a skill that calls Claude-specific tools or scripts may need small edits to run somewhere else. #### **Should I migrate my GPT to a plugin or rebuild it in Claude?** If you plan to stay in ChatGPT, OpenAI's migration is the fastest way to keep your instructions and files. To make the work outlive any one platform, rebuild it as a SKILL.md file you store yourself. Either way, rebuild custom actions separately, because they do not carry over. --- ## Claude Skills Best Practices: 9 Rules I Follow to Get Results URL: https://ryandoser.com/claude-skills-best-practices/ Markdown: https://ryandoser.com/claude-skills-best-practices.md Published: 2026-07-03 | Updated: 2026-07-03 Categories: Claude Code > This covers some Claude Skills best practices I use for best results. This includes one skill per task, self-improving files, and more. These **Claude Skills best practices** are the rules I lean on to keep the skills that run my business reliable instead of flaky. Follow them and your skills go from cute demos to workers you can actually trust. ### **Why Most Skills Underperform** A skill is an SOP for AI, a markdown file that teaches Claude how to do one task the right way every time. The idea is simple, so people assume the execution is too. If you are brand new to the concept, start with my breakdown of [how to create Claude Skills](/claude-skills/). It is not. A vague, bloated, or untested skill produces vague, bloated, untested output. The gap between a skill that kind of works and one you trust with client work comes down to a handful of habits. Here are the nine I will not skip. ### **Best Practices for Using Claude Skills** #### **1. One Skill Per Task, Never a Mega-Skill** The most common mistake is cramming everything into one giant skill. People build a "marketing skill" that writes blogs, emails, and social posts all at once, and the output suffers across the board. Keep them small and focused. One skill writes SEO blog posts, another writes email newsletters, another handles LinkedIn. A focused instruction set gives sharper output, and Claude loads only the one your request needs, so nothing competes for attention. #### **2. Write in Markdown, Not PDF** What you feed a skill matters as much as what you put in it. Markdown and plain text are the recommended format for skills, and in my experience they give cleaner results than dropping a PDF into context. Save your instructions, your examples, and your reference material as markdown files. The structure is simpler for the model to parse, and it keeps your skill easy to edit later. It is the single easiest upgrade on this list. #### **3. Feed Context Before You Ask for Anything** Most people open Claude, say "write me a blog post, go," and wonder why the result is generic. They skipped the part that actually matters. Front-load the context. Voice-dump your business, your ideal customer, your offers, your past work, and your competitors before the skill runs. The skill is the procedure, but the context is the raw material, and thin material always produces thin work. #### **4. Make Your Skills Self-Improving** The best skills get sharper the more you use them, while a static one keeps repeating the same mistakes. That difference compounds fast. When Claude gets something wrong mid-task, correct it once and have it patch the skill file so that fix sticks permanently. My blog skill used to add little promo callout blocks I never wanted, so instead of deleting them every time, I had Claude write a rule into the file: "No CTA callout block. No grab-my-free-guide lead-ins." It has not done it since. Over time the skill sharpens itself, and the same error never comes back. You can take this further with an automatic system that updates your files after every workflow, which I covered in my guide on [Claude Code autoresearch](/claude-code-autoresearch/). #### **5. Build a Verification Step Into the Skill** Speed means nothing if the output is wrong, especially on client work where a bad stat is a fireable offense. Write a checking step into the skill itself, and set up subagents to handle it so each one verifies the work independently before it reaches you. If the skill-versus-agent split is still fuzzy, I explain [Claude Skills vs agents vs MCP](/claude-skills-vs-mcp-vs-agents/) in plain English. My dental-client skill has a five-point pre-delivery checklist baked in: verify every stat against a primary source, check the founder's voice, confirm audience fit, research the top-ranking pages, and check the AI-citation structure. A separate accuracy agent re-checks every number as if I got it wrong. For anything with facts, numbers, or claims, this habit is the difference between confident shipping and quiet anxiety. #### **6. A Human Expert Has to Gate the Output** AI does not have taste. You do, and that is the whole point. Never let a skill publish straight to the world without a subject matter expert reviewing it first. I run a final manager step on my content, a deliberately harsh ship or no-ship judge that asks the question the other checks do not: is this actually worth publishing, or just clean and forgettable? It kills competent-but-boring drafts before they go out. The skill drafts, but a person who knows the topic, or an agent built to think like one, decides if it ships. Your experience is the competitive advantage here, so use the skill to amplify your judgment, not replace it. #### **7. Be Specific, Kill the Vague Rules** Skills collect fuzzy instructions over time, like "be helpful" or "use my brand voice." Those words mean nothing to a model. *Specific rules and banned words beat vague instructions like "sound like me."* Replace every vague rule with a concrete one. Instead of "sound like me," list the exact phrases you use, the words you ban, and a real example of your writing. My anti-slop skill does not say "avoid bad style," it says "no semicolons, ever," "no more than two dashes per paragraph," and a list of banned words like delve, leverage, and seamless. The more specific the instruction, the more reliable the output, every single time. #### **8. Nail the Description Field** Every skill has a short description at the top, and most people treat it as an afterthought. That is a mistake, because the description is how Claude decides when to use the skill at all. *A sharp description is what makes Claude reach for the right skill automatically.* Write it to say what the skill does and when to use it, in plain language. My listicle skill's description literally spells out the triggers: "Use when Ryan says write a listicle, best of list, roundup post, or top 10," and it even names what NOT to use it for. A sharp description means Claude reaches for the right skill automatically. A lazy one means your best skill sits unused because the model never knows to call it. #### **9. Test It Like You Stole It** A skill you have not stress-tested is a guess. Run it on real tasks, not toy examples, before you rely on it. Push it on messy inputs, edge cases, and the exact work you actually do. One of my content skills once grabbed a video by its title without checking the footage, and the clip turned out to be the wrong tool entirely. I added a rule to always view the actual frames first, and the gap closed. A skill earns your trust by surviving real use, not by looking good once. ### **How to Put These Into Practice** You do not have to adopt all nine at once. Start with one skill per task and markdown over PDF, then layer in self-improvement and the verification step as you go. This is the same systems-over-prompts mindset behind [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) at all. Aaron Makelky gave the simplest version of this on [our AI video editing episode](/ai-video-editing/): make each skill 1% to 5% better every time you use it. If you would rather learn from skills that already follow these rules, I packaged the ones I use daily into the [AI Skills Stack](https://skills.ryandoser.com/). Opening a working skill file and seeing the real descriptions, banned-word lists, and verification steps is the fastest way to internalize what good looks like. And if your best instructions are currently sitting in a Claude Project, [converting them into skills](/turn-claude-projects-into-skills/) takes an afternoon. ### **Ryan's Final Thoughts** The people who win with Claude treat skills like real systems. They keep each one focused, write specific instructions, let the skill learn from corrections, and keep a human who knows the work in the loop before anything ships. Follow these Claude Skills best practices and you stop babysitting the AI and start trusting it. Build one skill the right way this week, and the rest will follow. --- ## Claude Fable 5 is Back: Read This Before You Use it URL: https://ryandoser.com/claude-fable-5-is-back/ Markdown: https://ryandoser.com/claude-fable-5-is-back.md Published: 2026-07-02 | Updated: 2026-09-30 Categories: AI News, Claude Code > Claude Fable 5 is back after Anthropic's redeploy. Here are the new usage limits, important details, and how I'm actually using it. **Claude Fable 5 is back** after Anthropic redeployed the model, and the access rules changed enough that most people should slow down before jumping in. ### **Claude Fable 5 is Back (Full Video)** Below is my full walkthrough of what changed and where I'm actually pointing Fable 5 in my own work. I already broke down the original launch in my first [Claude Fable 5 review](/claude-fable-5/), so this one focuses on the redeployment, the ticking clock on access, and my honest take after testing it again. If you want the exact Claude Code setup behind these tests, my **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)** gives you the same skills and systems I run every day. #### **Why Anthropic pulled it, then brought it back** Here is the short version. On June 12, 2026, the US government applied export controls to Fable 5 and Mythos 5, and Anthropic could not verify user nationality in real time. So they suspended access for everyone. Those export controls were lifted on June 30. Anthropic [redeployed both models on July 1](https://www.anthropic.com/news/redeploying-fable-5) with an improved safety classifier that blocks the reported jailbreak in over 99% of cases. Blocked requests now route to Opus 4.8 instead. If you missed that whole saga, I covered it in my post on the [government ban on Claude Fable](/us-government-bans-claude-fable/). ### **The Claude Fable 5 Access Limits You Need to Know** Most launch coverage skips straight to the hype. The limits are the entire story here, so start with them. *Claude Code shows the "Fable 5 is back" banner with the July 7 usage window and a note that Fable 5 draws down limits faster than Opus 4.8.* Fable 5 is only available on a Claude Max plan if you want subscription access. Anyone can reach it through the API, but running it at scale gets expensive fast. You can check the [official Claude API pricing](https://platform.claude.com/docs/en/about-claude/pricing) to see the numbers. Both Fable 5 and Mythos 5 cost double what Claude Opus 4.8 does. Mythos 5 has even tighter availability than Fable. Here is the part that matters most. Fable 5 is included for up to 50% of your weekly usage limit through July 7 only. I'm recording this on July 2, which means I have about five days before access disappears from my Max plan and I'm forced to pay per token through the API. The AI commentator Gael Breton put it well. Fable makes a $100 Claude plan feel like a $20 plan from a year ago. I've already burned through my Fable allowance once since the original release, and the limits keep shrinking with each new model. That squeeze is what eventually pushed me to compare the two $100 plans head to head in [ChatGPT Pro vs Claude Max](/chatgpt-pro-vs-claude-max/). If you do want API access, you don't have to set up keys directly with Anthropic. You can pay for Fable 5 through [OpenRouter inside Claude Code](/claude-code-openrouter/) instead. ### **How I'm Actually Using Claude Fable 5** You've probably seen a dozen videos telling you Fable 5 changes everything. My take is more boring, and more useful. For 99% of knowledge work, Fable 5 is complete overkill. Writing emails, blog posts, social captions, packaging a YouTube video, none of that needs Fable. Opus 4.8, Sonnet 5, or even the GPT models handle those tasks with good inputs. For writing specifically, Opus 5.5 has since become my pick, and I explain [which Claude model I use for writing now](/best-claude-model-for-writing/) in a separate test. Fable earns its price when the work gets sophisticated. Landing pages, full websites, apps, and real software. Creator Riley Brown built a game called The Race for Super Intelligence using four prompts and $173 in Fable 5 tokens, which tells you both how capable and how pricey it gets. #### **Redesigning a landing page** Whenever a smarter model shows up, my first test is my landing pages. I pointed Fable 5 at the Claude Code Skills Stack page, which has made over $10,000 passively in three or four months. *Fable 5 produced the redesigned landing page locally, served on localhost so I could review it side by side with the live version.* A quick tip if you try this. Keep effort on low, maybe medium for something complex, and turn thinking off. Leave thinking on with max effort and you'll get three to five prompts before you hit the wall. **Update:** Anthropic's Claude Code docs now say thinking can't be turned off on the Fable models, so effort is the only dial there. Keep it on low, or medium for something complex. The first pass stayed close to my current design, with one strong addition: a bolded testimonial that added social proof. My second prompt asked it to fully rethink the page, and version two opened with much sharper copy. "Your next marketing hire is a $99 download." I wouldn't ship that page as-is, but I'd pull the best elements into my live page and test them. #### **CRO and SEO strategy** Fable 5 is a solid second pair of eyes on high-level strategy. For conversion rate optimization, I'd point it at my in-body email CTA and the floating widget that drives most of my Skills Stack sales, then ask for better copy, colors, and animation. *The in-body email opt-in that runs on every ryandoser.com blog post, one of the CRO elements I would hand to Fable 5 to improve.* For SEO, I'd have Fable audit ryandoser.com and refine the skills behind my [Claude Code SEO strategy](/claude-code-seo/). My traffic comes from repurposing YouTube videos into search-friendly posts, and Fable is useful for giving those skill files a smarter second look, not for writing the posts themselves. #### **Redesigning a full website** I also let Fable 5 redesign the ryandoser.com homepage using the Astro framework. The result looked more professional and simpler than my current Elementor build, with a cleaner call to action and less friction on the email opt-in. It wasn't perfect. It introduced an orange accent that isn't in my brand palette. But I'll take the strong elements into my real homepage, which needs the work. ### **Ryan's Final Thoughts** Claude Fable 5 is back, and the real headline is the five-day window plus the fact that Fable is overkill for almost everything most of us do. I'll keep running Opus 4.8 for 99% of my work and lean on [Sonnet 5](https://www.anthropic.com/news/claude-sonnet-5) for lighter tasks to stretch my usage. After July 7, I probably won't pay for Fable unless a job truly demands it. ### **Claude Fable 5 is Back FAQs** #### **Is Claude Fable 5 available again?** Yes. Anthropic redeployed Fable 5 and Mythos 5 on July 1, 2026, after the US government lifted the export controls that forced the earlier suspension. Both models are available globally on the Claude platform, Claude.ai, Claude Code, and Claude Cowork. #### **How long is Claude Fable 5 free on the Max plan?** Fable 5 is included for up to 50% of your weekly usage limit through July 7, 2026. After that date, subscription access ends and you continue through usage credits or the API, which gets expensive at scale. #### **Is Claude Fable 5 worth using?** For most knowledge work like emails, blog posts, and social content, Fable 5 is overkill and Opus 4.8 or Sonnet 5 will do fine. Fable is worth it for sophisticated work like landing pages, full websites, apps, and complex software where its extra reasoning shows. #### **How much does Claude Fable 5 cost?** Fable 5 and Mythos 5 are priced at roughly double Claude Opus 4.8 through the API. Mythos 5 has more limited availability than Fable. Check the official Claude API pricing page for current per-token rates before running anything at scale. --- ## 10 Best Claude Marketing Skills to Replace Your Team (2026) URL: https://ryandoser.com/best-claude-marketing-skills/ Markdown: https://ryandoser.com/best-claude-marketing-skills.md Published: 2026-07-01 | Updated: 2026-07-01 Categories: Claude Code > The best Claude marketing skills from my own stack, the SOP-style skills I run in production for SEO, email, social, landing pages, and video. The **best Claude marketing skills** I have found are not in a public repo. They are the ten I built for my own content business and run in production every week. ### **Why I Build a Skill for Every Marketing Job** A Claude skill is an SOP for AI. You write your process once as a markdown file, and Claude runs it the same way every time instead of guessing. Marketing is full of repeatable jobs that still need taste. A blog post. A newsletter. A landing page. Each has a structure you follow, rules you never break, and a voice you want to keep. A skill holds all three. I will not pretend these are objective winners pulled from a leaderboard. They are mine, tuned to how I work, and a few of them only earn their keep once you load them with your own context. Here is what each does, where it shines, and where it needs your input. One job per skill, because a focused skill beats a bloated one every time. ### **Watch a Single Video Become a Week of Content** Here is a quick look at these skills turning one long video into a stack of posts across platforms. It shows the workflow before we break down each skill. ### **The 10 Best Claude Marketing Skills in My Stack** #### **1. SEO Blog Post Writer** Hand it a target keyword or a YouTube URL and it returns a full SEO post: heading structure, meta description, internal links, and keyword placement that follows the rules search engines actually reward. This drives most of my own traffic. The honest caveat is that it falls flat on an empty folder. Feed it a few of your past posts first so it copies your voice, or the draft reads like every other AI blog. I showed the full build in my guide to [three ways to create Claude Skills](/claude-skills/). #### **2. Email Newsletter Writer** Subject-line formulas and structure templates, pulled from the performance data of real sends, drive this one. It knows which openers earn higher open rates because the numbers live inside the skill file. The open is the only thing that matters before the body gets read, so that is where this skill spends its effort. It is at its best when you paste in your own winning subject lines, so it stops guessing and starts pattern-matching your list. #### **3. LinkedIn Post Writer** The format is strict on purpose: a short hook up top, a tight body, and a question at the end that pulls replies. LinkedIn rewards that exact shape and buries posts that wander. Where it needs you is the hook. It can structure a post all day, but the sharpest hooks still come from your own take on a topic, so treat its first line as a strong draft you punch up. #### **4. Content Repurposing** *My marketing skills folder in Claude Code, turning one source into a batch of posts.* One long video or podcast goes in. A LinkedIn post, an X thread, a newsletter, an SEO blog, short-form scripts, and quote cards come out. A single recording becomes a week of content across channels. I also sell this one job on its own as the [**AI Content Engine**](https://engine.ryandoser.com/), for people who want the repurposing without the rest of the stack. Publishing once and moving on wastes the hardest part of the work, which is making the thing in the first place. This is the closest I get to free reach, and it is the skill I would hand a beginner first. #### **5. Social Media Manager** Drop in any video or image and get platform-ready captions for YouTube, TikTok, Instagram, Threads, LinkedIn, X, and Facebook. A two-caption system with built-in character limits means nothing gets rejected for being too long. *The payoff: a full content calendar scheduled straight from Claude Code.* Writing a fresh caption for seven platforms is why most people quit posting by week three. Collapsing it to two reusable variants is what keeps me consistent when I am busy. The output is copy-paste ready for any scheduler. I show the full build in my guide to [an AI social media manager with Claude Code](/claude-code-social-media/). #### **6. Short Form Video Script Creator** Built around a hook-first framework, it front-loads the first three seconds and works backward from there. Shorts, Reels, and TikToks all live or die on the opener, so the skill obsesses over it. Give it your topic and it hands back a script engineered for the scroll-stop. Fair warning: it writes the structure, not your personality, so the voiceover still needs your delivery to land. #### **7. Landing Page Designer** A proven page anatomy turns into production-ready HTML and CSS you can deploy the same day. It builds a tightly focused page aimed at one action, the way a real landing page should work. Plenty of AI page builders hand you something pretty and unfocused. This aims everything at the single conversion you care about. It pairs well with the next skill on this list. #### **8. CRO Skill** Point it at any page and it audits the conversion leaks: weak headlines, buried CTAs, missing social proof, slow load, form friction. Then it ranks the fixes by impact against effort so you know what to touch first. Chasing more traffic is the wrong instinct when the page you have already leaks. This finds the cheap wins before you spend a dollar on ads, which is why I run it on a page before I promote it. #### **9. SEO Content Strategy** Think of this as the planner rather than the writer. It scores topics by search intent and conversion odds, maps keyword clusters, runs a competitor gap analysis, and tells you exactly what to publish next, including an angle for getting cited in AI answers. Too many content plans die as a keyword dump nobody opens. Forcing a bottom-of-funnel-first order means you publish what converts before you chase volume, so the work pays sooner. Heads up that it assumes you can be honest about your real conversion goals, so vague inputs give vague plans. #### **10. Sales Email Skill** Short, direct launch and promo emails, built from subject-line formulas with a quality checklist attached. Every email stays under 200 words with one clear call to action and no filler. Sales emails exist to close, not to teach, so this one strips anything that does not move the reader toward the click. It is the skill I trust when an email has a real job and a deadline. ### **How to Get the Most From These Skills** A skill is a framework, not a one-click button. The output is only as good as the context you feed it. Load your own writing samples, your brand voice, your past content, and your audience details before you run any of them. I keep 20-plus newsletter examples in a folder for exactly this reason, so the writer learns my style instead of inventing one. The people who get the best results treat a skill like an employee they are training, not a vending machine they tap for output. That mindset is the real point of working this way, and it is the bigger argument behind [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) at all. Brand new to it? Start with [the zero-coding setup guide](/claude-code-for-marketing/) and come back here once your folders are in place. ### **Ryan's Final Thoughts** These are not the best skills for everyone. They are the best skills for how I run a content business, and they only sound like me because I trained them on years of my own work. Yours should sound like you. If you also want tools beyond skills, I rounded up my [best AI marketing tools](/best-ai-marketing-tools/) in a separate post. And if you want a head start on the skills, all ten live in my [Claude Code Skills Stack](https://skills.ryandoser.com/), along with 15 more I use for content, YouTube, and images. You get my structure and my rules, you bring your own voice and examples. That is the trade, and it is the same toolkit I run in production every day. ### **Claude Marketing Skills FAQs** #### **Can Claude skills really replace a marketing team?** They replace the production work, not the judgment. These ten cover the drafting, formatting, repurposing, and scheduling that used to eat a junior marketer's week, and they do it in your voice once you feed them your examples. What they do not do is decide what to say, which audience to chase, or whether a campaign is worth running. A skill is a framework, not a one-click button. #### **Which Claude marketing skill should I start with?** Content repurposing. It is the skill I would hand a beginner first, because it produces the most visible payoff from work you have already done. One long video or podcast goes in, and a LinkedIn post, an X thread, a newsletter, an SEO blog, short-form scripts, and quote cards come out. The SEO blog post writer drives most of my own traffic, but it needs more setup before it sounds like you. #### **Why does my Claude skill output sound generic?** Because it is running on an empty folder. The SEO blog post writer falls flat with no context and reads like every other AI blog. Feed it a few of your past posts first so it copies your voice. I keep 20-plus newsletter examples in a folder for exactly this reason, so the writer learns my style instead of inventing one. The skill supplies the structure; you supply the voice. #### **Do I need Claude Code to use these marketing skills?** For this set, yes in practice. These skills read reference folders, pull your past writing, and write finished files, which is work that needs a real workspace rather than a chat window. If Claude Code is new to you, get the install and folder structure sorted first and then come back to the skills. #### **How long does it take to build one of these yourself?** Each one is an afternoon of work, and a full stack is a stack of afternoons. Building your own is genuinely viable, and the process is the same each time: write your process down as a markdown file, run it, then patch the file every time the output misses. The cost is not difficulty, it is the repetition of doing that ten times. --- ## 8 Best Claude Skills to Install in 2026 (Free & Paid) URL: https://ryandoser.com/best-claude-skills/ Markdown: https://ryandoser.com/best-claude-skills.md Published: 2026-06-30 | Updated: 2026-06-30 Categories: Claude Code > The 8 best Claude skills to install in 2026, free and paid. Official Anthropic skills, top community picks, and the SOP-style skills I use daily. The **best Claude skills** turn Claude from a clever chatbot into a system that does real work the same way every time. ### **Why Most People Use Claude Skills Wrong** A Claude skill is an SOP for AI. It is a markdown file that teaches Claude how to handle one task from start to finish, with your steps, your examples, and your rules baked in. Most people never get past copy-pasting prompts. They retype the same instructions every session and wonder why the output drifts. A skill fixes that. You write the process once, and Claude follows it like a recipe every time. Picking skills got harder as the ecosystem exploded. There are official Anthropic skills, huge community libraries, and paid stacks, and most "best of" lists just dump 50 repos on you with no opinion. This list is different. These are the eight I actually reach for, free and paid mixed together, with a clear reason each one earns a spot. If you have never built one, I broke down [three ways to create Claude Skills](/claude-skills/) first. Come back here once you know the basics. ### **The 8 Best Claude Skills in 2026** I judged these on one question: does it make your output good enough to make money or win clients with? Some are official, some are community-built, and some are mine. None of them got a slot for being free or for being paid. They earned it on the work they do. #### **1. Skill Creator (Free)** *Anthropic's official skills repository, home to the Skill Creator and document skills.* This is the skill that builds other skills. Instead of hand-writing markdown and learning Anthropic's formatting rules, you describe what you need and it produces the skill file for you. Anthropic ships an official version inside its [public skills repository](https://github.com/anthropics/skills), and I include a tuned version in my own stack. Start here, because once you can generate skills on demand, every other workflow on this list gets easier to build. #### **2. Anti-Slop (Paid)** The Anti-Slop skill scans a draft against a banned-word list, flags structural red flags like binary-contrast overuse and templated openers, then rewrites the patterns that make AI writing obvious. It runs as a quality gate after you generate any copy. Clean output is the whole game in content, and a generic model will not catch its own tells. This is the skill that turns a draft that smells like AI into one that reads like a person wrote it. It lives in my [Claude Code Skills Stack](https://skills.ryandoser.com/). #### **3. Superpowers (Free)** *Superpowers, the largest community-built Claude skills framework.* Superpowers is the biggest community-built skill collection out there. Built by Jesse Vincent, it is less a single skill and more a framework that chains many skills together to run a full software development workflow. Grab it from the [Superpowers repository](https://github.com/obra/superpowers) on GitHub. For anyone writing code with Claude, this is the deepest free option available, and it shows how far a composable set of skills can take you. #### **4. Crosscheck (Paid)** Crosscheck queries a second model without making you leave Claude. Say "ask GPT about this," and it routes your question to OpenAI or Google through OpenRouter, then lays out exactly where the models agree, where they split, and what to act on. No single model catches everything, so this builds a review layer right into your workflow. It is the skill I run before any decision I do not want to get wrong, and it is part of my stack. #### **5. Anthropic Document Skills (Free)** These are the official skills that let Claude create and edit real documents: Word, PDF, PowerPoint, and Excel. They power Claude's ability to hand you a finished `.docx` or `.xlsx` instead of a wall of text you have to format yourself. All four live in the same [Anthropic skills repo](https://github.com/anthropics/skills). They work across Claude.ai, Claude Code, and the API, so anything you build on them travels with you. For anyone who lives in spreadsheets or slide decks, these alone justify learning skills. If you have not set Claude Code up yet, my [five-minute beginner walkthrough](/claude-code-for-marketing/) covers the install and folder structure first. #### **6. MCP Builder (Free & Paid)** MCP connects Claude to outside tools like GitHub, Notion, Google Sheets, and databases. An MCP skill walks Claude through building and wiring those connections so you stop copy-pasting between apps. Worth knowing the line here, since a skill and an MCP connection do different jobs, which I unpack in [Claude Skills vs agents vs MCP](/claude-skills-vs-mcp-vs-agents/). Anthropic ships an official MCP builder in its [skills repo](https://github.com/anthropics/skills/tree/main/skills/mcp-builder), and I keep a simpler MCP Setup version tuned for non-coders. Either way, this is the skill that turns Claude into something plugged into your real tools. #### **7. Firecrawl (Free)** *The Firecrawl plugin gives Claude its own web scraping toolkit.* Firecrawl teaches Claude to scrape, crawl, and search the web on its own. After one install command, Claude can pull clean data from almost any site without you wiring up a single tool by hand. The [Firecrawl Claude plugin](https://github.com/firecrawl/firecrawl-claude-plugin) handles JavaScript rendering and anti-bot pages that normally break a basic fetch. For work that touches research or competitor data, this is the web access skill I trust most. #### **8. Auto Improve (Paid)** Auto Improve runs silently after your other skills finish. It checks the output against that skill's own rules, logs the failures, and patches the skill file itself once a problem repeats, so the same mistake stops happening. This is the closest thing to a skill that maintains itself, and it is why correcting Claude once can mean never correcting it again. I covered how I turned self-improving skills into a [Claude side hustle](/claude-ai-side-hustle/) and why this idea is the real unlock. ### **Free vs Paid: Where to Start** New to this? Start free. The official Anthropic skills and Superpowers will show you what a good skill feels like, and they cost nothing but time. I put the whole build-or-buy call into [a three-question test](/free-vs-paid-claude-skills/) if you want to settle it before you spend anything. Paid stacks earn their price when you want skills tuned for a specific job and ready to run out of the box. I do not think everyone needs to buy a stack. Everyone should at least build one skill this week though, because the first one changes how you see the tool. For a deeper directory to browse, the [awesome-claude-skills list](https://github.com/travisvn/awesome-claude-skills) on GitHub catalogs official and community skills with over 13,000 stars. ### **Ryan's Final Thoughts** The best Claude skills are the ones you actually use, not the ones with the most stars. Start with a free official skill, build one of your own with a skill creator, and add a paid stack only when you want the work done for you. When you do want that, I packaged 25+ of the marketing and content skills I run every day, copywriting, SEO, email, and social, into my [Claude Code Skills Stack](https://skills.ryandoser.com/). It is the same toolkit I use in production, and the [v2 update](/claude-code-skills-stack-v2-update/) covers what I added most recently. The bigger point holds either way, which is [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) at all: the people who build real systems pull ahead of the people still pasting prompts. ### **Claude Skills FAQs** #### **How do you install a Claude skill?** A skill is a markdown file, so installing one means putting that file where Claude can read it. For Claude Code, that is a skills folder inside your project workspace, which is why folder structure matters more than most people expect. Official Anthropic skills can be pulled straight from the public skills repo on GitHub, and some community skills ship a one-line install command instead. If you have not set up a workspace yet, do that first and the rest is drag and drop. #### **Do Claude skills work in Claude.ai or only in Claude Code?** Both, though the experience differs. The official Anthropic document skills for Word, PDF, PowerPoint, and Excel work across Claude.ai, Claude Code, and the API, so anything you build on them travels with you. Skills that expect to read and write files in a project folder are far more useful inside Claude Code, because that is where Claude has a workspace to act on. #### **Should I start with free or paid Claude skills?** Start free. Install a free official skill, build one of your own with a skill creator, and only add a paid stack once you know which jobs you repeat often enough to want them done for you. Paid stacks earn their price when you want skills tuned for a specific job and ready to run out of the box. I do not think everyone needs to buy one. #### **Where can I browse more Claude skills?** The awesome-claude-skills list on GitHub catalogs both official and community skills and has over 13,000 stars, which makes it the best single directory right now. The official Anthropic skills repo is the other place worth checking, since those are maintained rather than abandoned. #### **How many skills should I have?** Fewer than you think, and each one narrower than you think. A focused skill beats a bloated one every time, so the better instinct is one skill per repeated job rather than one giant skill that tries to cover a whole department. Skills you never actually run are just files. --- ## How to Make Money With AI With No Experience (Real $50K Story) URL: https://ryandoser.com/how-to-make-money-with-ai-no-experience/ Markdown: https://ryandoser.com/how-to-make-money-with-ai-no-experience.md Published: 2026-06-30 | Updated: 2026-07-08 Categories: AI Rabbit Holes, AI Side Hustles > How to make money with AI with no experience, shown through a real $50K-a-month case study built from zero in six months. Most guides on **how to make money with AI with no experience** hand you a list of 21 tools and wish you luck. This one shows you a real person who did it. ### **How to Make Money With AI With No Experience** What if the person making $50,000 a month with AI started with zero technical skills six months ago? That is [Sandy Lee](https://www.youtube.com/@sandyleeai). She came on my podcast after I saw her on Sabrina Ramonov's channel, and one detail hooked me right away. No coding background. No AI background. No SEO background. Six months later she crossed $50K in a single month across several income streams. I get asked how to make money with AI almost every day in my DMs. Most people freeze at the same spot. They want the income, but they have no idea where to start. Sandy is proof you do not need a head start. You need a willingness to learn one skill and deliver a real outcome. If you want to go deeper on the exact tools and systems I use, I packaged a decade of marketing experience into my **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)**. It is the same digital product approach Sandy and I both talk about below. ### **Why No Experience Is Not the Real Problem** You have probably told yourself you are too far behind to start. Sandy felt the same way. Before AI, she failed at Etsy, print on demand, and Amazon FBA. She bought expensive courses that went nowhere. She was working full time, living paycheck to paycheck, raising three kids, and for a stretch she did it alone while her husband was overseas. On paper, she had every excuse to wait. She started anyway in November. Her words were simple. She just wanted to make money online, and the AI hype was loud enough that she wanted to test if it was real. Here is the part that matters for you. Sandy did not start with a skill she already had. She picked a skill she did not know, learned it fast, and delivered the result to a paying client. That is the whole model. ### **Her First AI Income Stream Came From Upwork** Most beginners overthink the first dollar. Sandy went and found it. Her first client was an AI SEO gig she landed on Upwork. She applied to a lot of listings, recorded a quick Loom video for each one, and closed a deal within two weeks. The job was blog automation for SEO. She had never run an automation workflow in her life. So how did she win the deal? She leaned on what she actually knew. Ten plus years in sales and marketing taught her how companies think and what problems they pay to solve. She was confident she could learn the technical skill and deliver the outcome, so she did. That first deal started at $3,000 and grew to $5,500 in monthly recurring revenue. The results were strong enough that the client kept paying more, and she now runs that work through her own [AI automation studio](https://sleeautomation.com/). This is the honest version of how to make money with AI with no experience. You sell an outcome, then you learn fast enough to deliver it. *Sandy Lee breaking down her AI income streams on the AI Rabbit Holes podcast.* If freelance SEO sounds interesting, that path is wide open right now. I broke down a related model in my guide on [how to use Claude Code for SEO](/claude-code-seo/), which is the kind of skill clients pay real money for. ### **How She Stacked Multiple Income Streams** One income stream is a job with extra steps. Sandy built several on purpose. She has been a content creator since 2018 and grew an audience of 550K across three platforms. The problem was monetization. Her audience was mostly students who could not buy anything. So when she restarted around AI, she rebuilt with monetization in mind from day one. Here are the main pieces of her $50K month, with sponsorships and client work carrying most of the weight: - Sponsorships: about $23,000 from companies paying her to feature their products - AI SEO client work: $5,500 in monthly recurring revenue - A community she launched for her audience - A vibe coded app she built for herself The sponsorship number is the eye opener. But Sandy does not take every deal. She tests each product first, and if it is bad, she turns the money down rather than lie to her audience. That honesty is why brands and viewers trust her. She also made a sharp point about her app. She built the first version by vibe coding, then hired a senior engineer to review the code once Sabrina told her to level up. She understands plain language, not code, so a real engineer made it faster and more reliable. ### **The Digital Product Path Anyone Can Copy** If sponsorships feel out of reach today, start somewhere smaller and provable. I told Sandy the easiest on ramp for most people is a digital product. The good version is built from expertise you already have, paired with AI. Skip the scammy AI generated PDFs and recycled prompt packs that flood Gumroad. My own example is the Claude Code Skills Stack. It has made over $10,000 in about three months, mostly from blog SEO traffic and my email list. The idea is simple. There is something you understand better than most people. Package that knowledge into a usable tool, then figure out how to distribute it. My mind clicked on this after I went on Chris Koerner's podcast and made roughly $5,000 in five days from that audience. The lesson is that distribution turns expertise into income. If you want the full breakdown of this exact play, I documented it in my post on [how to sell Claude skills as a digital product](/sell-claude-skills/). ### **Why You Have To Own Your Distribution** Here is the trap that catches most new creators. They chase views and expect ad revenue to pay them. That is not the game. Sandy and I agreed on this hard. The top creators take traffic off YouTube and into something they own. A community, a digital product, an email list, or a service business on the back end. Sponsorships help, but the real moat is owned distribution tied to a strong personal brand. Sandy learned this the hard way before AI. She and her husband once got laid off the same day because the company could not afford to keep them, even though she was their top salesperson. Her takeaway was blunt. When someone else holds your only income basket, you are never safe. She now runs lead generation in every video to build her own community, the one asset no platform can delete, and packaged the approach into her own [personal brand system](https://sleestudio.com/). I tell people the same thing constantly. There is no moat in building anymore because anyone can copy what you build. Marketing, distribution, and a real personal brand are the only moats left. I went deeper on that idea in my guide to [building a strong personal brand for founders](/personal-branding-for-founders/). *Ryan and Sandy discussing why owning your distribution beats chasing views.* ### **Ryan's Final Thoughts** Sandy went from paycheck to paycheck to $50K a month in six months with no coding, no AI background, and three kids at home. The pattern is repeatable. Sell an outcome, learn the skill fast, stack a few income streams, and own your distribution. Start with one side gig this month. If you already work in marketing, the fastest starting points are the ten [AI marketing side hustles](/ai-side-hustles-marketing/) I broke down separately. The point is not to get rich overnight. The point is to stop letting one company hold your only income basket. ### **How to Make Money With AI With No Experience FAQs** #### **How do you make money with AI with no experience?** Start by selling an outcome you can learn to deliver, like AI SEO or blog automation. Sandy Lee landed her first $3,000 client on Upwork before she knew the skill, then learned it fast. From there she stacked sponsorships, a community, a digital product, and an app to reach $50K a month in six months. #### **How much money can a beginner make with AI?** As a general benchmark, many beginners reach somewhere around $1,000 to $5,000 per month within three to six months of consistent effort. Sandy moved faster than that. She started with a single $3,000 client that grew to $5,500 in recurring revenue, then layered on $23,000 in sponsorships and other streams. Results depend on the outcome you can deliver, not on prior experience. #### **Do you need coding skills to make money with AI?** No. Sandy built her entire business with no coding background and only plain language. She vibe coded her first app, then hired a senior engineer to review the code once it needed to scale. Tools like Claude let non coders deliver real client outcomes without writing code themselves. #### **What is the easiest way to start making money with AI?** A digital product is the easiest proven on ramp. Package expertise you already have into a usable tool, then distribute it through a blog, email list, or community. My Claude Code Skills Stack made over $10,000 in three months this way, mostly from SEO traffic. See the digital product section above for the full breakdown. --- ## How I Build AI Landing Pages That Actually Convert URL: https://ryandoser.com/ai-landing-pages/ Markdown: https://ryandoser.com/ai-landing-pages.md Published: 2026-06-26 | Updated: 2026-06-26 Categories: AI Tutorials, Claude Code > AI landing pages are easy to generate, hard to convert. The exact conversion formula and paid-ads playbook I use to build pages that sell. Most people build **AI landing pages** that look great and convert nobody. The fix is treating the page as a conversion machine, not a design project. ### **AI Landing Pages Video Guide** I built a real client landing page on camera, start to finish, and walk through the exact prompt and skill I used. The page in this demo is for Bloom Chiropractic, a real business near Des Moines running Google Ads. Her ads were pointing at the homepage, which is the fastest way to burn ad spend. I rebuilt the destination as a single page designed to do one thing: get phone calls. I give the landing page designer skill away free inside my AI Marketing Insiders community. If you want my full library of marketing skills, my **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)** bundles the systems I run daily. Both come from a decade of real marketing work, not generic AI templates. *The fresh Claude Code chat in VS Code, with the landing page designer skill and the Bloom Chiropractic brand assets folder loaded.* ### **Why Most AI Landing Pages Fail** You can generate a landing page in 30 seconds with almost any tool now. That is the problem. Speed without a conversion framework gets you a pretty page that does not sell. A landing page is not a website. A website lets people wander. A landing page removes every exit except the one action you want. When you are paying for traffic, every extra link, menu, or distraction costs you money. I would rather build these in Claude Code or Codex than a vibe-coding tool like Lovable. Going straight to the source code gives me real control over the layout, the copy, and the tracking. SaaS page builders hide that control behind their own templates. There is also a structural reason to own the code. When the page is just an index.html file and an assets folder, you can host it anywhere, edit any line, and move it between domains without rebuilding from scratch. ### **The Conversion Formula Behind Every Page** Here is the part nobody talks about. A skill is only as good as the framework inside it. My landing page designer skill runs on a fixed checklist before it writes a single line of code. The formula has eight inputs: - **Offer:** the one thing being sold or booked - **Audience:** who the page is written for - **Primary CTA:** the single action you want - **CTA destination:** where that action sends them - **Proof:** reviews, results, credentials - **Brand:** colors, fonts, logo, voice - **Visual proof:** photos that show the real business - **Asset:** the files and context you provide *The actual prompt: call the skill, give it the brand assets, and set phone calls as the primary conversion.* If you skip the brand assets, you get a generic page. I uploaded a folder with the logo, the brand guide, and real photos before prompting. Context is what separates a high-quality page from an obvious AI draft. For the model, I used Opus 4.8 on low effort with thinking mode off. This task does not need high reasoning. Low effort keeps token costs down and the output is still production-ready. ### **Build for Paid Traffic, Not Search** Most AI landing page tutorials forget the part that actually matters for advertisers. A page running on Google or Facebook ads has rules a normal website does not. First, add a noindex tag. The Bloom page lives on its own domain, so I do not want Google indexing it and competing with the real business website. This page exists for paid clicks only. Organic traffic is not the goal here. Second, carry over the tracking pixels. I told Claude Code to pull the existing Google Ads tracking from the current site so conversions still fire. A landing page with no tracking is a page you cannot improve. Third, match the conversion to the business. Bloom wanted phone calls, not form fills. So I set the phone number as the primary CTA and kept the existing contact form as a secondary path. You can run something like [CallRail](https://www.callrail.com/) for call tracking if you want deeper data. This is where owning the code pays off. Try carrying custom pixels and a noindex tag into a templated SaaS builder and you will hit a wall fast. ### **Getting the Page Live Without a Headache** A finished page on your laptop helps no one. You need it live on a real URL. The short version: push the files to a free [GitHub](https://github.com/) repository, then connect that repo to [Cloudflare Pages](https://pages.cloudflare.com/) or Vercel for free hosting. Cloudflare deploys the live site in about a minute once the repo is connected. *The Bloom Chiropractic landing page files synced to a private GitHub repo, ready to deploy.* I keep the deploy steps tight here on purpose. I already wrote a full walkthrough of the GitHub-to-Cloudflare process in my guide on [building landing pages with Claude Code](/claude-code-landing-pages/), so follow that if you want every click. One warning from experience. Do not run ads to a raw pages.dev or workers.dev URL. Ad platforms flag those domains constantly. Use a subdomain like skills.yoursite.com, or buy a cheap dedicated domain. For Bloom, I bought a separate domain and pointed it at the page. ### **What This Workflow Will Not Do** Honesty matters, so here is the limit. AI builds the page. It does not build the strategy. The skill will not tell you what your offer should be, who your audience is, or whether phone calls beat form fills for your business. You bring the marketing thinking. The AI executes it cleanly and fast. It also will not run your ads, write your offer, or split-test your headlines. Treat the page as the starting line, not the finish. The first draft I built was ready for production, though I would still fix a few small things by hand. That last polish is your judgment, not the model's. This same code-first approach works far beyond landing pages. If you want to see how flexible it gets, my breakdown of [vibe coding a digital product](/vibe-code-digital-product-claude-code/) shows the full range, and these landing page skills sit inside a broader library of [Claude skills](/claude-skills/) I use for client work. ### **Ryan's Final Thoughts** AI landing pages are easy to generate and hard to convert. The difference is the framework underneath, not the tool on top. Lock your offer, your CTA, and your proof first, then let the AI build it in minutes. One of these pages now sells a digital product that has made me close to $10,000 on autopilot. Build for the click you are paying for, and the page earns its keep. --- ## Is n8n Officially Dead in 2026? AI Automation Expert Reacts URL: https://ryandoser.com/is-n8n-dead/ Markdown: https://ryandoser.com/is-n8n-dead.md Published: 2026-06-22 | Updated: 2026-09-30 Categories: AI Automations, AI Rabbit Holes > Is n8n dead in 2026? An AI automation expert reacts. Why n8n just hit $5.2B, where it beats Claude Code, and the MCP combo that wins. Every other week a new "I replaced n8n with Claude Code" video hits the feed, so I asked an automation expert whether **is n8n dead** is a real shift or just engagement bait. ### **Is n8n Dead? The Video Guide** I sat down with Solomon Christ, an AI enterprise trainer behind the AI Automation Mastery channel, to pressure-test the hype. His short answer was no. His longer answer is more useful, and it changes how you should think about Claude Code, Codex, and automation platforms working together. If you want to go deeper on this, I put together a guide that covers my full **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)**, automation templates, and systems. ### **Why n8n Is Not Dead in 2026** Here is the surprising part. While creators argue n8n is finished, the money says the opposite. n8n just doubled its valuation to $5.2 billion after SAP made a strategic investment in May 2026. SAP is set to embed n8n's workflow canvas directly inside its Joule Studio AI agent builder, with general availability targeted for Q3 2026. That is Europe's largest software company betting on the exact tool people keep burying. You can read the [official announcement of SAP's investment](https://blog.n8n.io/n8n-sap/) for the full details. Solomon put it plainly. Enterprises move slowly. They keep systems for 10 or 20 years because reliability matters more than novelty. SAP has been around for decades. When a giant like that adopts n8n, the platform is not dying. It is getting entrenched. So why does the "n8n is dead" narrative spread so fast? Because Claude Code and Codex genuinely can do automation now. The mistake is assuming "can" means "should" for every job. *Ryan and Solomon Christ break down whether AI coding agents actually killed n8n.* ### **n8n vs Claude Code: Deterministic vs Probabilistic** Here is the core idea that the whole debate hinges on. One word. Agentic tools like Claude are probabilistic. Run the same prompt twice and you can get two different results. n8n is deterministic. You build the route, and the workflow fires the same way every single time. Solomon used a driving analogy I liked. A self-driving car is powerful, but you still want a human at the wheel who can hit the brake. n8n is the predictable road. Claude is the powerful but unpredictable autopilot. The smart operator uses both. For mission-critical work, deterministic wins. If you are sending 1,000 client invoices or proposals, you need near-perfect results every time. Solomon said he trusts n8n to run correctly 99 times out of 100. He does not have that confidence in a pure Claude workflow, where every run is a fresh roll of the dice. The asymmetry matters most when the stakes are high. Nobody cares if a morning summary varies slightly. People care a lot when a million-dollar decision runs through the pipe. ### **When to Use n8n Over a Claude Code Cron Job** You might wonder why you can't just ask Claude to set up a cron job and call it done. The answer comes down to where the job actually lives. A cron job is a task that repeats on schedule. The catch is the computer running it has to stay on. Give Claude the prompt "create a cron job to remind me at 6 a.m." and the result depends on the model and the moment. One run sets it up on your local machine. Another puts it on a server. Same prompt, different outcome. If it lands on your laptop and you close the lid, the job dies. n8n running on a virtual private server or in the cloud fires with or without you. That guarantee is the entire point. Solomon walked through his daily AI news digest as a live example. It pulls from TechCrunch, The Verge, Wired, MIT, and VentureBeat every morning at 6 a.m., ranks the top articles, and emails him a clean brief. *Solomon's n8n news digest runs the same path every day, no black box required.* He uses older, cheaper models inside it and even sets backup models. He can open the workflow and see exactly what runs. With a Claude cron job, he just has to hope the black box behaves. One bad day and it returns garbled HTML instead of his formatted email. ### **The n8n MCP Plus Claude Code Combo** Now for the part that actually answers the headline. The winning move in 2026 is not one or the other. n8n shipped a new MCP in April 2026, rebuilt on TypeScript. The old GitHub repo approach got you about 40% of the way to a working build and often broke on outdated nodes. The new [n8n MCP integration](/claude-code-mcps/) gets you closer to 80%, with the correct nodes, so you only fix small things like a wrong model or a stray variable. The [official n8n MCP server docs](https://blog.n8n.io/n8n-mcp-server/) walk through how it builds workflows. That changes the workflow. You let Claude Code build and troubleshoot the n8n automation through the MCP, which is faster than wiring 40 nodes by hand. Then Claude calls those n8n workflows in the background for the mission-critical steps. You get the power of the agent plus the reliability of the deterministic pipe. This is the one-two punch. Use Claude as the brain. Use n8n for the parts that absolutely must run the same way every time. Its per-execution billing is also the reason it beats a per-task tool once you are [running social publishing at volume](/best-zapier-alternatives/). If you want to see where n8n stacks up against Claude Code, Make, Zapier, and the newer agent-native players, I ranked them all in my guide to [the best AI automation tools I actually pay for](/best-ai-automation-tools/). The other secret Solomon mentioned for consistency is [Claude Skills](/claude-skills/), which let you lock in a repeatable process instead of re-prompting from scratch. ### **Build Tools You Never Pay Tokens For Again** Almost nobody talks about this angle, and it reframes the whole automation conversation. Solomon vibe coded a B-Roll Studio tool with Fable in about two prompts. You paste a webpage link, capture the page, draw boxes around what you want to highlight, and it auto generates an animated B-roll video that flies from point to point. No tokens burned on each run. *The B-Roll Studio tool Solomon built with two prompts, now part of his SOP pipeline.* That is the real shift. He did not show me a prompt running on Claude. He showed me a piece of software he owns that runs forever without tokens. The future is people getting back to basics, building their own small tools, and leaning on capable offline models like Qwen or Gemma for the bulk of everyday work. I put that idea to the test when I ran [open source models against Claude on a web design job](/open-source-ai-web-design/), and the cheaper options got surprisingly close. This pairs well with how I think about using [Claude Code to repurpose content](/claude-code-repurpose-youtube-videos/) into owned systems. Both Solomon and I landed on the same take. Frontier models like [Anthropic's](https://www.anthropic.com/) top releases are overkill for 99% of real-world tasks. The models got good enough for most knowledge work two years ago. The new releases matter for hard technical jobs, not for drafting an email. ### **Ryan's Final Thoughts** So, is n8n dead? Not even close. It just hit a $5.2 billion valuation and is getting woven into SAP's stack. The "Claude replaced my whole stack" videos are mostly hype that ignores the gap between probabilistic and deterministic systems. The real winners pair Claude Code with n8n through the MCP. They build small tools they own outright, then reserve frontier models for the few jobs that need them. Get back to basics and the automation question answers itself. ### **Is n8n Dead FAQs** #### **Is n8n dead in 2026?** No. n8n is more entrenched than ever. In May 2026 SAP made a strategic investment that doubled n8n's valuation to $5.2 billion, with a deal to embed its workflow canvas inside SAP's Joule Studio, and general availability of that integration was targeted for Q3 2026. Enterprises adopt slowly and keep systems for years, so n8n is positioned to stay relevant for a long time. #### **Can Claude Code replace n8n?** Not fully. Claude Code is probabilistic, meaning the same prompt can produce different results each run. n8n is deterministic and fires the same way every time. For mission-critical jobs that must run reliably at scale, n8n still wins. The strongest setup uses both together rather than one replacing the other. For the cost side of that choice, see [how per-task and per-execution billing compare](/zapier-vs-n8n/). #### **Should I use n8n or a Claude Code cron job?** Use n8n when the task must run on schedule no matter what. A local Claude cron job dies if your computer shuts off, and where Claude places the job can vary by model. n8n on a cloud server or VPS runs 24/7 with or without you, which is why it is the safer choice for reliable automation. #### **What is the n8n MCP and why does it matter?** The n8n MCP is an integration released in April 2026, rebuilt on TypeScript, that lets Claude Code build n8n workflows directly. It gets you roughly 80% of the way to a working automation with the correct nodes, then you fix small details. It is the fastest way to create n8n workflows in 2026. --- ## SEO Expert Exposes Google's AI Search Guidelines (The Truth) URL: https://ryandoser.com/google-ai-search-guidelines-exposed/ Markdown: https://ryandoser.com/google-ai-search-guidelines-exposed.md Published: 2026-06-19 | Updated: 2026-08-18 Categories: AI Rabbit Holes > An 18-year SEO expert exposes Google's AI Search Guidelines as misdirection, and reveals what actually wins in AI search instead. An 18-year SEO veteran says **Google's AI Search Guidelines** are quietly steering you away from the exact tactics Google uses on its own sites. ### **What Google's AI Search Guidelines Actually Say** What if the most-shared SEO advice of the year came from the people least qualified to give it? That is the charge [Charles Floate](https://www.youtube.com/@CharlesFloate) leveled when I sat him down for this episode of AI Rabbit Holes. Charles is an 18-year SEO veteran who scaled [PressWhizz](https://presswhizz.com/) into one of the fastest-growing link-building platforms in the space, close to a million dollars a month, as its CMO. So when he says Google is gaslighting marketers, it carries weight. If you want to go deeper on building content systems that survive AI search, I put together a guide on [how to automate SEO content with AI that ranks](/ai-seo-system/) without tripping spam filters. *Charles Floate breaking down what Google's AI Search Guidelines get wrong on the AI Rabbit Holes podcast.* Charles draws a sharp line between two kinds of bad guidance. One is obfuscation. The other is being flat-out wrong. [Google's official AI Search guidance](https://blog.google/products-and-platforms/products/search/search-io-2026/) tells you that schema does not matter, that you do not need markdown versions of your content, and that extractability is a non-issue. Then you look at Google's own properties, including the blog where they published the guide, and they use every one of those tactics. ### **Why Google Is Gaslighting SEOs** You have probably seen this movie before. Every few years Google publishes guidance, and every few years the leaks tell a different story. Charles points to a clear pattern. The advice does not come from the engineers building the models. It comes from the same policy and documentation teams that have shaped Google's public messaging for two decades. When you compare that messaging against reality, DOJ testimony, and the document leaks, the gap is obvious. A lot of what lands in the official docs is factually incorrect versus how the systems actually behave. So why keep doing it? The incentive is money and resources. Counteracting aggressive SEO tactics at scale costs enormous processing power. Spreading a message through PR, conferences, and SEO influencers costs almost nothing. Right now Google would rather pour its compute into new model iterations than into policing techniques it can simply talk you out of using. There is a second layer with AI specifically. The guidance doubles as corporate presentation, a way to show investors and the digital PR world that Google is helpful and in control. How helpful the guide actually is stays up for debate. ### **What Actually Works in AI Search** Almost no one can attribute AI citations accurately, and most do not even realize it. Attribution is the hardest problem in this new era, so start there. Unless someone clicks through from an AI answer, you get no direct attribution. When there is a click, server logs are the only reliable source. Everything else filters out data, misses referrals, and gives you numbers you cannot trust. If your brand gets cited without a click, the trail goes cold. You cannot cleanly connect a ChatGPT recommendation to a later branded search and a sale. The honest move is to [track visibility growth across query clusters](/how-to-track-ai-visibility/) against your direct traffic and leads, then estimate. A simpler tactic works too. Add a required "How did you find us?" field in your checkout or lead form. It adds a little friction, but it captures attribution that no tool can. Here are the levers Charles says still move rankings in AI search: - **Tokenization and chunking.** Specific token structures around specific topic clusters get preferred by the models. This is fundamental to how they work, no matter what the guide says. - **Extractability.** AI Overviews pull exact chunks of your content, summarize them, and cite the source. Structure your content so a model can lift a clean passage as-is. - **Co-occurrence and citations.** None of this is new to SEO. The systems that adapted to these signals before will adapt again. - **Domain authority.** Without it, nothing else matters. You can publish 100 posts tomorrow and watch zero of them index. ### **Parasite SEO Is the Real AI Search Hack** Most people racing to fine-tune their own site for AI search are wasting their time. That is a hard claim, and Charles backs it. Parasite SEO means you stop relying on your own domain and leech onto a stronger one instead. You publish a LinkedIn Pulse article or buy a newspaper editorial, and you inherit that domain's link authority, root authority, and topical authority. The signal boost is massive compared to your own zero-authority blog. High-authority domains also sit above the threshold for many anti-spam classifiers, so content that would nuke your own site can rank just fine on theirs. This is why Charles argues a strong YouTube channel plus owned distribution beats your own website in most cases. While everyone chases [llms.txt and schema hacks](/ai-search-myths/), the math is simple. If your domain has no authority, those tricks change nothing. Post 100 blog posts on a dead domain and none of them rank. Post those same 100 as parasite pages on Medium or LinkedIn Pulse and many of them stick. That difference is raw domain power. YouTube, Reddit, and LinkedIn are top-tier sources that LLMs lean on constantly. If you understand how the retrieval process works, you stop fighting your own domain and start borrowing authority from theirs. ### **Programmatic SEO vs Scaled Content Abuse** There is a line between programmatic SEO that wins and the scaled content abuse Google penalizes. Most operators sprint right past it. You can now buy a product that sprints past it for you: [one tool ships 30 auto-published articles a month](/outrank-review/) and sells human fact-checking as a separate $1,399 add-on. It is not alone either, and I priced [the rest of that category](/outrank-alternatives/) against it. The failures usually share the same fingerprints. They spin up 400,000 pages, which is pure index bloat you will never get crawled. They skip internal linking, clean URL structures, schema, and unique imagery. They stuff meta titles until the pages read like templates, because they are. Worst of all, the pages are linear clones. "This city Italian restaurants" repeated across every location, ignoring how people in different places actually search, spell, and phrase queries. That is what most of us just call AI slop. The fix is a genuine unique angle. Charles builds client systems that pull from stored meeting context, podcast transcripts, and proprietary data so every page carries something the competition cannot scrape. Telling a model to recycle the top five Google results is a losing strategy unless you already rank like Forbes. If you want the non-negotiables for a content system that actually moves the needle, two stand out: - **Positive and negative datasets.** Most people never build them. Show the model a dozen great examples and a few hundred bad ones from the client's existing posts, and you fundamentally reshape its output through better RAG and fine-tuning. - **Real media over AI images.** Charles swaps the image-generation step for a screenshot agent that captures real blog posts, testimonials, and reviews. Those unique images add relevance, freshness, and information gain that AI-generated art never will. I run a system like this myself for a client. It handles the SEO fundamentals automatically, the H1, the meta description, internal links, and index requests to Bing, Yandex, and Search Console. If you want to build your own version, my [Claude Code for SEO guide](/claude-code-seo/) covers the workflow, and the screenshot-agent idea pairs well with [using image models inside Claude Code](/nano-banana-claude-code/). [The practitioners publishing real AI search work](/best-ai-seo-experts/) paired with tools like [Charles's SEO training](https://charlesfloatetraining.com/), Claude Code, and Codex now operate at 10 to 100x output. A great marketer used to be a 2 to 5x asset. That gap is what makes taste plus AI the real competitive advantage. ### **Is Traditional Google SEO Dead** Blue-link SEO is not dead, and the casino niche proves it. AI Overviews refuse to roll out for queries like "best online casino" or "best Bitcoin casino," and those keywords stay wildly profitable. Some of those CPCs run 20 to 40 dollars a click. Even valuing an organic click at 10% of that, you are looking at real money, and a number-one ranking can pull a thousand clicks a day. Low-competition local searches tell a similar story. Outside the map pack you still get traditional blue links, directories, and local service results. Even the AI Overviews themselves run on the blue-link algorithm grounded into the flash model underneath. Charles's crystal-ball prediction is the part that stuck with me. He thinks AI Mode becomes the default Google experience, but with a split-view, Chrome-style interface. Chat on the left, agentic web browsing on the right, all inside Google's ecosystem. The monetization plan is what makes it click into focus. In testing, a search for "best running shoes" hides half your organic merchant feed behind a "show more" link, while a sponsored block sits directly above the chat box where your cursor already rests. Your first click goes to an ad by design. ### **Ryan's Final Thoughts** Google's AI Search Guidelines read less like a help doc and more like a press release. The tactics they wave you off of, schema, extractability, chunking, are the same ones Google runs on its own pages. Domain authority, parasite SEO, and a genuine unique angle still decide who wins, exactly like they always have. Treat the official guide as a clue about what Google wants to hide, not a map to where the traffic is. The wild west is open, and the operators who test instead of obey are going to eat. ### **Google AI Search Guidelines FAQs** #### **What are Google's AI Search Guidelines?** They are Google's official guidance on ranking content for AI Search and AI Overviews. The docs downplay schema, markdown, and extractability. Critics like Charles Floate argue the advice contradicts what Google does on its own properties, making it more misdirection than help. See What Google's AI Search Guidelines Actually Say above. #### **Does schema still matter for AI search?** Yes. Despite the guidelines suggesting otherwise, Google uses schema across its own sites, including the blog hosting the AI search guide. Extractability and content chunking also matter because AI Overviews pull exact passages from your pages to summarize and cite. Structure content so a model can lift a clean, self-contained answer. #### **What is parasite SEO in AI search?** Parasite SEO means publishing on a high-authority domain instead of your own to inherit its ranking power. A LinkedIn Pulse article or newspaper editorial carries link authority and topical authority your site likely lacks. These domains also avoid many anti-spam classifiers, so the content ranks where your own domain would fail. #### **Is traditional Google SEO dead?** No. Niches like online casinos, sports betting, and many local searches do not trigger AI Overviews, and they remain highly profitable. AI Overviews are also powered by the same blue-link algorithm underneath. Blue-link SEO has shrunk in some verticals, not disappeared. #### **How do you track AI search citations?** Server logs are the only fully accurate method when a click comes through from an AI answer. Brand mentions without clicks are nearly impossible to attribute directly. A practical workaround is a required "How did you find us?" field at checkout or in lead forms to capture the source manually. --- ## He Makes $100K/Month With Rank & Rent SEO (AI Proof) URL: https://ryandoser.com/rank-and-rent-seo/ Markdown: https://ryandoser.com/rank-and-rent-seo.md Published: 2026-06-16 | Updated: 2026-06-16 Categories: AI Rabbit Holes, AI Side Hustles > Rank and rent SEO lets you build a ranking local site and rent the leads. See how one guy makes $100K a month, and why AI hasn't killed the model. This breakdown explains how a guy known as the website landlord built a six-figure passive income with **rank and rent SEO**, and why he says AI hasn't dented the model at all. ### **Rank and Rent SEO Video Guide** I sat down with Kyle, who runs a portfolio of rank and rent local SEO sites pulling in around $100,000 a month. Watch the full conversation below. If you want to go deeper on building these sites yourself, I documented my own process in my guide on [making money with local SEO using Claude Code](/seomaxxing/). It pairs well with everything Kyle covers here. ### **What Rank and Rent SEO Actually Is** Imagine you build a website for tree services in Savannah, Georgia. It ranks on page one. The phone starts ringing. But you don't cut down trees. So you call a real tree service in Savannah and offer them a free 7-day trial of those leads. They close three jobs that week. Then you charge them $1,000 a month to keep the calls flowing. That's the website landlord business model in one sentence. You own a digital asset that ranks, and you rent the lead flow to a local business that does the actual work. The site sits there. The calls keep coming. The client keeps paying. This is not a marketing agency. An agency manages your online presence for a monthly retainer and can't promise results. Rank and rent flips it. You build the asset first, prove it generates calls, then sell access to those calls. The business owner takes zero risk because they only pay once the leads are real. Kyle put it bluntly. "You're not building a business here, you're building an asset." He compared it to spending a year building a house you own forever. ### **How to Pick a Low Competition Niche and City** Most people fail at this model because they chase the wrong markets. Kyle starts with a spreadsheet of niches and cities that interest him, then runs live searches to size up the competition. He looks at the top three results for a query like "tree service Savannah." For each one he checks domain authority, trust flow, backlink profile, content depth, and whether the site has proper headings and images. Then he picks the weakest markets. You will find tons of cities where the ranking sites look like they were built in 2005 and never touched. Go in, do 10% better, and you knock them out for good. The niche selection is where the real edge lives. Skip the markets eaten by private equity. - **Avoid:** plumbing, HVAC, roofing in big metros, and personal injury law. Personal injury lawyers in Los Angeles spend $50,000 a month on marketing. Good luck. - **Target:** gutter installation, epoxy floors, popcorn ceiling removal, junk removal, septic, towing, auto glass repair. These niches still have owners doing millions in revenue who never invested in their online presence. Kyle's rule of thumb on city size: there are over 800 US cities with a population above 50,000, and far more below that. A town of 100,000 or less is often full of operators with a pickup truck and a tool belt who don't know SEO and won't gamble $1,500 a month on an agency. *Kyle's New Orleans auto glass site pinned at the very top of the search results, above the local map pack.* ### **The 80/20 of Rank and Rent Local SEO** What actually moves the needle? Kyle says 80% of the work is content and backlinks, and the weight shifts based on how soft the competition is. The content rule surprised me. The words on the site are not for the customer. Nobody reads the paragraphs on a tree service website. They scan for a phone number and call. The content exists to tell Google's crawler exactly what you do and where you do it. So his sites are blunt. "New Orleans auto glass repair. Windshield replacement in New Orleans." No clever copy. Just crystal-clear relevance signals. Then there are backlinks, which prove to Google that someone trusts you. Kyle skips the cold-email guest post grind entirely. Two methods do the job in low competition SEO: - **Private community link sharing:** students in his program exchange links across each other's sites. - **The copycat method:** use a tool like Ahrefs or Mangools to pull the backlinks of a competing site in any city, then grab the free and easy ones for yourself. Blog comments, directory listings, simple citations. People love to claim those links don't work. In low competition SEO they absolutely work. You don't need a Forbes or CNN backlink to rank for "auto glass repair New Orleans." You just need Google to see that someone knows you exist. This is the part most SEO advice gets wrong. Almost every expert online is teaching you to compete nationally for top-of-funnel keywords. Outranking real local operators in a small city is a completely different game, and the rules are far more forgiving. If you want the full local playbook, see my deeper breakdown on [Claude Code SEO workflows](/claude-code-seo/). ### **Why Rank and Rent SEO Is AI Proof** Here's the question everyone asks. With Google AI Overviews and AI Mode eating the SERPs, does this model still work? Kyle's answer: so far, AI has only helped him. His sites already rank, and Google's AI just pulls from the standard search results it has trusted for years. He hasn't changed his strategy once. His logic is sharp. Google spent 30 years building criteria for which local business shows at the top of page one. Gemini defers to all of that work. The AI can't go drive to New Orleans and test auto glass shops. All it knows is what's on your website. So you keep feeding Google what it wants, and you keep showing up in the AI answers too. My own field test complicates that a little: when [four AI assistants recommended local businesses in two cities](/research/does-chatgpt-recommend-local-businesses/), under a quarter of their picks were Google's top 3 map results, though most of Google's top 3 got named somewhere. The money trail backs this up. Kyle estimates local service ads drive a huge chunk of Google's revenue. Picture the search page like television. The ads at the top are the commercials. The organic local results right below are the actual show people came to watch. Without the show, Google has nothing to sell ads against. There's a second layer most GEO and AEO hype misses. When ChatGPT, Claude, or Gemini answer a query, they often retrieve live Google and Bing search results in real time. If you ignore traditional SEO fundamentals, no black-hat AEO trick saves you. The fundamentals are the foundation the AI answers sit on. If anything, AI opens up more long-tail searches. People now type "affordable roofer who specializes in Spanish tile roofs, licensed and insured" instead of "roofers Houston." Kyle's response is to flesh out his sites with more localized content so they cover more of those variations. He doesn't try to rank for all of them. His goal is to capture just 1 to 5% of daily demand, which is plenty for one client. ### **How AI Builds Rank and Rent Sites in Minutes** Kyle used to pay a writer $25 per 500 words and wait 10 days for content. Now he gives ChatGPT specific instructions and gets it in seconds. AI also helps with market research and pricing. I took this further. After hearing [Kyle's episode on The Koerner Office](https://youtu.be/xUZYy3hCRUM), I built my own rank and rent site as a test: a septic business at desmoinesseptic.com. I used Claude Code with Cloudflare, the [Astro web framework](https://astro.build/), and GitHub, the [WordPress alternative I now build every site on](/wordpress-alternative/). It ranks on page one for legitimate septic queries in Des Moines. *My Des Moines septic site, built with Claude Code, Astro, and Cloudflare in a couple of hours.* The first build took a couple of hours. Then I saved all that context as a skill markdown file, so now I can spin up a new site in minutes with Claude Fable. If you want to learn how I set up reusable AI systems like this, I walk through it in my **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)**. The localized content trick is where AI shines for this model. You can scrape directories and public data, then generate hyper-focused pages about specific streets, neighborhoods, and local details. Google reads that as genuine local expertise. My site even has AI-generated blog images, like a septic truck pumping a tank that looks like it was shot in Des Moines. *A listicle blog post on my septic site with a fully AI-generated, localized featured image.* Kyle did flag one honest warning. He doesn't push AI on the students he mentors, because AI can wander off and use strategies that don't rank. You might spend three months not knowing why your site is stuck. A real SEO foundation helps you catch that. ### **Is Rank and Rent SEO Saturated?** The most common objection is saturation. Kyle was worried about it back in 2019 when he started. It has never affected him once. The math kills the argument. Roughly 1,000 niches, multiplied by 800-plus US cities over 50K population, multiplied by the three to five ranking spots that still pull calls. That's around 2.5 million opportunities. A model most people first heard about a week ago is nowhere near saturated. Search results also change with every phrasing. Ranking number one for "towing Asheville" doesn't mean you own "best towing Asheville" or "affordable towing Asheville." Every variation is its own little market. There's real money in the underrated niches too. Kyle has a friend with a popcorn ceiling removal site in Southern California who once landed a $20,000 commercial quote through it. A niche of a niche. ### **Ryan's Final Thoughts** Rank and rent SEO is one of the more durable AI-era opportunities I've looked at this year. You build a ranking website, rent the leads to a local business, and collect a flat fee while the asset sits and works. Kyle's $100K a month proves the ceiling, and my own septic test proves how fast AI lets you start. Pick a soft niche, niche down hard, and treat each site as an asset you own for life. You can follow Kyle on [TikTok at websitelandlord](https://www.tiktok.com/@websitelandlord) or learn more about his model at [Rent Local Sites](https://rentlocalsites.com/). For more on the AI build side, see my full [SEO system breakdown](/ai-seo-system/). ### **Rank and Rent SEO FAQs** #### **What is rank and rent SEO?** Rank and rent SEO means building a website that ranks on Google for a local service, then renting the lead flow to a real business in that niche. You own the site as an asset and charge a flat monthly fee, often around $1,000, for the calls and form submissions it generates. The business does the work, you keep the asset. #### **How much money can you make with rank and rent?** Earnings vary by niche and city, but a single ranked site can generate $1,000 to $2,000 a month in passive income. Kyle, featured in the video above, runs a full portfolio producing around $100,000 a month. The model scales by rinsing and repeating the same formula across new niches and cities. #### **Is rank and rent SEO still worth it with AI?** Yes. AI search pulls from the same Google rankings that have always mattered, so ranked sites still surface in AI Overviews and Gemini answers. AI also makes building these sites faster and opens up more long-tail local searches. The traditional SEO fundamentals remain the foundation AI answers depend on. #### **What niches work best for rank and rent local SEO?** Low competition home service niches work best. Think gutter installation, epoxy floors, popcorn ceiling removal, junk removal, septic, towing, and auto glass repair. Avoid heavily funded niches like plumbing, HVAC, and roofing in major metros, plus personal injury law, where competitors spend tens of thousands a month on marketing. #### **How do you rank a rank and rent website on Google?** Focus on two things: clear local content and simple backlinks. Write blunt, location-specific pages that tell Google exactly what you do and where. Then build easy backlinks like directory listings and citations, often copied from competing sites using a tool like Ahrefs or Mangools. In low competition markets, you don't need premium links to rank. --- ## Claude Fable Banned by the US Gov: What This Means for You URL: https://ryandoser.com/us-government-bans-claude-fable/ Markdown: https://ryandoser.com/us-government-bans-claude-fable.md Published: 2026-06-14 | Updated: 2026-06-14 Categories: AI News, Claude Code > The US government got Claude Fable 5 banned and Anthropic pulled it offline. Here is what the order means and what to use instead. The US government just got **Claude Fable 5 banned**, and Anthropic pulled both Fable 5 and Mythos 5 offline days after launch. Here is what actually happened, why it matters, and what you should do now. ### **Why Claude Fable 5 Got Banned** The headlines say "banned," but the order was narrower than that. On June 12, 2026, the Commerce Department directed Anthropic to suspend access to Fable 5 and Mythos 5 for any foreign national, including Anthropic's own non-citizen employees. The company could not verify citizenship for every request in real time, so it [disabled both models for everyone](https://www.bloomberg.com/news/articles/2026-06-13/anthropic-says-us-limits-foreign-access-to-fable-5-mythos-5). *Anthropic's official statement confirming the US government directive to suspend access to Fable 5 and Mythos 5.* The stated reason was a single technique to get around Fable 5's safeguards. According to Anthropic, the method involved asking the model to read a specific codebase and fix software flaws. The company argues this is a narrow, non-universal jailbreak, not a master key that unlocks dangerous behavior across the board. Anthropic also notes the same capability is available from other public models, including OpenAI's GPT-5.5, which is not under similar export controls. You can read [Anthropic's official statement](https://www.anthropic.com/news/fable-mythos-access) for the full timeline and its response. ### **Who the Fable 5 Ban Actually Affects** The [order reached every customer](https://www.axios.com/2026/06/12/anthropic-trump-mythos-fable-national-security), not just government users. Because Anthropic disabled Fable 5 and Mythos 5 entirely, no one can access either model through Claude.ai or the API while the suspension stands. Everything else still works. Anthropic confirmed that access to all other Anthropic models is unaffected, so Claude Opus 4.8, Sonnet, and Haiku run normally. If you never tried Fable 5 during its short window, your day-to-day Claude use does not change at all. For a refresher on what Fable 5 offered before the shutdown, see my original breakdown of [Claude Fable 5](/claude-fable-5/). Anthropic says it is working to restore access as soon as possible, but it has not given a timeline. Treat the models as gone for now and plan around that. ### **The Amazon Connection Worth Watching** Here is the part most coverage glosses over. Amazon CEO Andy Jassy reportedly warned the White House that Fable 5 could be used to aid cyberattacks, and [that warning preceded the export order](https://www.wsj.com/tech/ai/amazon-ceos-talks-with-u-s-officials-triggered-crackdown-on-anthropic-models-dcc90578). Amazon researchers said they used a series of prompts to get the model to produce that information. The conflict of interest is hard to ignore. Amazon has invested roughly $13 billion in Anthropic, hosts its infrastructure, and competes for the same enterprise customers. The timing also lands right before Anthropic's expected IPO later in 2026. None of that proves bad faith. It does raise a fair question about how much of this is safety policy and how much is competitive pressure routed through Washington. Read into it what you want. ### **What You Should Do Right Now** Do not panic, and do not overhaul your stack. Claude Opus 4.8 and GPT-5.5 are still strong enough to cover the vast majority of real knowledge work, including marketing, copywriting, research, and strategy. Fable 5 was overkill for most of that anyway. It earned its price on heavy technical jobs like full website builds, not on everyday writing and analysis. If you want help picking the right Claude tier for a task, my guide on [Claude AI vs Cowork vs Code](/claude-ai-vs-cowork-vs-code/) breaks down when each one fits. The bigger lesson is about dependence. When a single government order can pull a model overnight, you cannot build a workflow that only runs on one frontier model. Lean on Opus 4.8 or GPT-5.5 for now, and spend a little time [testing open source AI models](/open-source-ai-models/) like Qwen and DeepSeek so you have a fallback if the rug gets pulled again. ### **My Honest Take on the Fable 5 Shutdown** This is a slippery slope, and the precedent it sets is the real story. How does a government decide a model is too powerful? How much of that call is genuine safety review versus competitors lobbying behind closed doors? If a code-review jailbreak takes Fable 5 down, the same logic could be aimed at OpenAI's next release or Google's next release. I do not think the security concern is fake. The Mythos line was built around finding and exploiting vulnerabilities, which I covered in my post on [Claude Mythos](/claude-mythos/), so the cybersecurity worry is grounded. What concerns me is the lack of published methodology and the speed of the takedown. A model used by a huge customer base went dark on verbal evidence alone. Expect one clear ripple from this: a resurgence of interest in open-source models. When trust in always-on frontier access takes a hit, builders hedge. That is a healthy instinct, and it is the practical takeaway here. Want my friend Luke's full breakdown of the situation? Watch his take below. ### **Ryan's Final Thoughts** The Claude Fable 5 ban is a turning point for how AI gets governed, not just another model update. Anthropic is complying while challenging the designation in federal court, the models may return, and the rules that triggered this are still mostly undefined. I will be watching how this plays out closely, because the next ruling like this could hit a model you actually depend on. The smart move is to stay flexible. Build systems that work across models instead of betting everything on one. That is the whole reason I package my own workflows into the **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)**, so the system keeps running no matter which model is best that week. ### **Claude Fable 5 Banned FAQs** #### **Why was Claude Fable 5 banned?** The Commerce Department ordered Anthropic to block Fable 5 and Mythos 5 for all foreign nationals over a security concern involving a method to bypass Fable 5's safeguards. Anthropic could not verify citizenship per request, so it disabled both models for every user to comply. #### **Is Claude Fable 5 gone for good?** Not necessarily. Anthropic said it is working to restore access as soon as possible but has not shared a timeline. For now, both Fable 5 and Mythos 5 are offline while the company responds to the order. #### **Can I still use other Claude models?** Yes. Anthropic confirmed that all other models are unaffected. Claude Opus 4.8, Sonnet, and Haiku continue to work normally on Claude.ai and the API. Only Fable 5 and Mythos 5 were disabled. #### **What should I use instead of Fable 5?** Use Claude Opus 4.8 or GPT-5.5 for almost all knowledge work, since both are more than capable. For heavy technical tasks, test those models at higher effort levels, and consider open-source options like Qwen and DeepSeek as a backup so you are not dependent on a single frontier model. --- ## LinkedIn AI Advice From a $20M Expert (Stop Automating LinkedIn) URL: https://ryandoser.com/linkedin-ai-advice/ Markdown: https://ryandoser.com/linkedin-ai-advice.md Published: 2026-06-12 | Updated: 2026-06-12 Categories: AI Rabbit Holes > The best LinkedIn AI advice from a B2B sales expert: how to use AI for outreach and DMs without sounding like a robot or getting deleted. The best **LinkedIn AI advice** I have heard in a while came from someone who closes high-ticket deals for a living, not someone selling you an automation tool. ### **LinkedIn AI Advice Video Guide** I sat down with [Charlotte Lloyd](https://www.linkedin.com/in/charlottelloydsales/), a B2B sales expert with 23 years in corporate and 70,000-plus LinkedIn followers, to unpack how she actually uses AI to book meetings without sounding like a robot. Charlotte founded [The Client Acquisition Club](https://www.thecharlottelloyd.com/) after leaving corporate, and she built it on LinkedIn content plus manual outreach. Her whole argument cuts against the grain. Most people use AI to send more messages. She uses it to sound more human on every single one. If you want to build the kind of Claude-powered systems she walks through, I packaged my own playbook in my **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)**, which includes my Claude Code Skills, automation templates, systems, and more. ### **Why You Should Stop Automating LinkedIn** You spent an hour blasting connection requests, and every one got ignored. Charlotte sees those messages land in her inbox daily, and she has a one-word response: delete. Her point on how to use AI on LinkedIn is blunt. The moment a prospect smells AI-generated slop, you lose them. Not for today. For good. (I wrote a whole guide on [how to avoid AI slop](/avoid-ai-slop/) if that is your weak spot.) “You cannot eff it up in the online world,” she told me. One bad opener and you are gone. She got a connection request that opened with “I see you run a lead gen agency.” She does not run a lead gen agency. The sender used a fake observation to fake personalization, and it cost them any shot at the deal. LinkedIn is also stricter than other platforms. Charlotte tried Dripify for cold outreach and got hit with restrictions. Tools like Vaal promise hyper-personalization, but she warns they sit in a gray zone LinkedIn keeps clamping down on. Automating LinkedIn outreach at scale is the fast way to a banned account. Before you hit send, she runs two gut checks: - Have I earned the right to a reply? - If I got this message, would I actually reply? If the answer is no, the message does not go out. Your human judgment is still the filter, even when AI writes the draft. ### **How to Use AI on LinkedIn the Right Way** Volume is not the strategy. Charlotte builds AI LinkedIn outreach that reads like a real person typed it, because in her workflow, the AI is trained on her real words. She trained a custom GPT and a Claude project on thousands of her own conversations, the ones that booked meetings and closed deals. “It’s actually better than me,” she admitted. When you start ten deep conversations a day and have to move each one forward inside the same week, your brain runs dry. The AI does not. That is the difference. She is not asking ChatGPT to “write a LinkedIn post about this podcast.” She is feeding AI her actual transcripts and frameworks so the output is hers, just faster. I do the same thing with my content. Anything I post is either an original thought in the moment or a repurpose built from a transcript of words I really said. LinkedIn now prioritizes content from lived experience. So Charlotte asks one question of every hook she writes: could anybody else have written this? If yes, it is generic, and it dies in the feed. “How to book meetings on LinkedIn” is a weak hook. “How I book five meetings a week using this system” is credible, because it is specific and it is hers. #### **Find Leads by Scraping LinkedIn Comments With Apify** Here is where the system starts. When inbound leads dry up, Charlotte hunts them inside the comments on viral posts, hers and her competitors’. She uses [Apify’s](https://apify.com) LinkedIn post comment scraper. It is free, it needs no Chrome extension, and it does not scrape your profile, so it stays safe with LinkedIn. She drops in a post that pulled 200-plus comments and extracts up to 250 of them in seconds. Then she exports to Excel and hands it to Claude. Her prompt is simple: here are 250 comments from a post about X, find the coaches and consultants, pull their LinkedIn URL from each comment. Claude qualifies the list by job title and region before she ever opens a profile. “You’re creating a system of leads where you never run out of leads,” she said. People who comment on a relevant post are already showing intent. They are warmer than a cold list will ever be. I have used Apify for several LinkedIn scraping jobs myself, and pairing it with Claude to qualify the export is the part most people skip. If you want the full build, here is how I [scrape LinkedIn profiles with Claude Code](/scrape-linkedin-profiles-claude-code/). #### **Book Meetings on LinkedIn With a Trained AI** Once a conversation starts, Charlotte runs it through her “DM Meeting Booker,” the custom GPT and Claude project she built. *Charlotte’s DM Meeting Booker GPT coaches each reply so the message stays human, not salesy.* She pastes the entire DM thread, not one message, so the AI keeps the full context. It tells her what is really happening. When a prospect said “it’s not the right time,” the AI did not push. It coached her to clarify calmly and give the person oxygen instead of forcing a call. It also catches AI tells. It flagged the word “curious” in one draft because everyone overuses it and it reads as machine-written. That is the kind of nuance that keeps your AI LinkedIn DM strategy from sounding automated. Into the Claude project she loaded her offer, her total addressable market, her customer journey map, and profiles of clients she wants (and the ones she does not). So the AI speaks in the language her ideal buyers actually use. #### **Run the SPICE Framework on Every Conversation** The backbone of her DMs is the SPICE framework. Claude surfaced it next to Alex Hormozi when someone searched sales advice, which tells you it is getting cited as a real method. Name your process and make it memorable, she says, and this is hers: *Her Claude project is loaded with offer details, a customer journey map, and ideal-client profiles.* - **S – Start the conversation.** Build a little rapport, but do not camp there. - **P – Pain or priority.** Find the struggle. Use an either-or question to reduce cognitive load. “Are you trying to get more inbound, or build a separate client acquisition system?” - **I – Identify blockers.** What obstacles have been in the way? You need to know. - **C – Confirm the ideal state.** Where do they want to get to once the problem is solved? - **E – Engage for the meeting.** “I know I can help with this. Why don’t we hop on a call?” By the time you reach the E, the prospect has sold themselves on why the problem matters. You are not begging for a meeting. You are offering the obvious next step. #### **The Tools Charlotte Actually Uses** She only talks about tools she genuinely likes, so this short list carries weight. *Kondo organizes the messy LinkedIn inbox with labels and reminders, and syncs to Claude.* | Tool | What it does | Cost | | Apify | Scrapes LinkedIn post comments safely, no extension | Free tier works | | Whisperflow | Voice-type human comments (press Fn on a Mac) | Free | | Claude (Pro) | Qualifies leads, runs the DM system | $100/month | | Kondo | LinkedIn inbox manager, connects to Claude via MCP | Roughly $200-300/year | [Kondo](https://www.trykondo.com/) is the one she calls non-negotiable. The native LinkedIn inbox is chaos, so Kondo lets her label conversations (calls booked, lead magnet sent, cold, follow-up due) and set reminders. It syncs with Claude through an MCP connection, so each week she feeds her conversation data into Claude Cowork and gets granular analytics back. One recent week showed a 77% reply rate. There is an obvious next move here, and it is where my mind went watching her juggle five browser tabs. Sync Apify to Claude Code with a skill markdown file holding her SPICE framework and client data. Then the whole loop, scrape, qualify, draft, track, lives in one ecosystem instead of copy-pasting between Apify, a custom GPT, and a separate DM tool. That is the natural upgrade for anyone serious about LinkedIn lead generation with AI. It is the same idea behind the [AI marketing agents I build in Claude Code](/claude-code-ai-marketing-agents/). ### **Ryan’s Final Thoughts** Charlotte’s edge is not the AI. It is that she refuses to let AI strip the human out of selling. She trains it on her real voice, qualifies hard before she ever reaches out, and runs every reply through her own judgment. The volume crowd will keep getting deleted while a few people use these tools to start better conversations. Pick the second group. The systems are sitting right here for you to build. You can follow Charlotte on LinkedIn or over on [Instagram](https://www.instagram.com/charlottelloydsales/), where she shares more on selling without the slop. ### **LinkedIn AI Advice FAQs** #### **How do I use AI on LinkedIn without sounding like AI?** Train the AI on your own words instead of asking it to write from scratch. Feed it real transcripts, past conversations, and your frameworks so the output carries your voice. Then read every message before sending and ask whether you would reply to it. The AI drafts, but your judgment ships. #### **Is automating LinkedIn outreach safe?** Risky. LinkedIn is more aggressive than other platforms about flagging automation, and tools that auto-send messages can trigger restrictions or bans, as Charlotte experienced with Dripify. Safer AI LinkedIn outreach keeps a human in the loop. Use AI to research and qualify leads, then send messages yourself. #### **What is the SPICE framework for LinkedIn DMs?** SPICE is Charlotte Lloyd’s five-step method for turning DMs into booked meetings: Start the conversation, find the Pain or priority, Identify blockers, Confirm the ideal state, and Engage for the meeting. See the SPICE framework section above for the full breakdown of each step. #### **What AI tools are best for LinkedIn lead generation?** Charlotte uses Apify to scrape post comments for warm leads, Claude to qualify them by title and region, Whisperflow to voice-type human comments, and Kondo to manage her LinkedIn inbox and reply data. The bigger win is connecting these tools into one workflow rather than copy-pasting between them. --- ## How to Build an AI Trading Agent on Robinhood (With Claude) URL: https://ryandoser.com/ai-trading-agent-robinhood/ Markdown: https://ryandoser.com/ai-trading-agent-robinhood.md Published: 2026-06-11 | Updated: 2026-06-11 Categories: AI Tutorials, Claude Code > Build an AI trading agent on Robinhood with Claude Code. Full MCP setup, the trading strategy, and honest results from my live beta test. You can now build an **AI trading agent on Robinhood** that analyzes the market and places real trades for you through Claude Code. ### **How an AI Trading Agent on Robinhood Works** Robinhood just launched Agentic Trading, a beta feature that lets you connect an AI agent to a dedicated brokerage account and let it trade. It works through the Model Context Protocol, an [open standard](https://modelcontextprotocol.io/) that connects AI agents to outside apps. You point Claude at Robinhood’s MCP endpoint, authenticate, and the agent can read your portfolio and place orders. Robinhood supports Claude Code, Claude Desktop, ChatGPT, Codex, Cursor, and Grok today. I am not a trader. All my real investing runs on autopilot through Vanguard. But this Robinhood AI trading feature was too interesting to skip, so I funded a small test account and wired it up myself. If you want to go deeper on connecting tools like this, my **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)** includes the workflows I use every week. One thing to know up front. The agentic account is a separate account, not your normal investing balance. I funded mine with $100 I could afford to lose, which is exactly how you should treat any beta trading tool. *Claude Code tracking four open positions with live prices and a hold status for each.* ### **Connect Robinhood to Claude With MCP** Setting up Robinhood agentic trading starts with one link and one prompt. Robinhood gives you an MCP connection URL inside the Agentic tab. The endpoint is `https://agent.robinhood.com/mcp/trading`. To add it in Claude Code, you run a short command in your terminal: ``` claude mcp add robinhood-trading --transport http https://agent.robinhood.com/mcp/trading ``` I went a step further. My prompt told Claude to connect the Robinhood Trading MCP, read Robinhood’s [Agentic Trading overview](https://robinhood.com/us/en/support/articles/agentic-trading-overview/) for context, and hold off on any trades until I confirmed the connection worked. Pasting the support article into Claude almost always makes the integration smoother. Adding the MCP is the easy part. Authentication is where most people get stuck. After the server connects, Claude told me two things were still needed: reload Claude Code, then finish the OAuth flow on desktop. You can only authenticate the agent on a desktop device, not your phone. The flow bounces between Claude and your browser a few times. You open an agentic account, agree to the terms, transfer funds in, verify on the Robinhood mobile app, then paste a localhost URL back into Claude. One step warns that the localhost page may show a “can’t connect” error. That is expected. You just copy the full URL from the address bar and hand it back to the agent. If you want a deeper primer on connecting services this way, my guide on [Claude Code MCPs](/claude-code-mcps/) walks through the pattern I use for every integration. ### **Set Up the Trading Strategy and Skill** Connecting the agent is not a strategy. You still have to tell it what to trade and when to stay out. I built a Claude Code skill to handle that part. It took me 15 to 30 minutes and it monitors one signal in particular: the trading activity of politicians, CEOs, and executives. These people often hold information the rest of us do not, so the agent watches their public moves and weighs them when picking stocks. You do not have to copy my approach. You can ask Claude to analyze any strategy file and rebuild it around your own style, your own risk tolerance, and your own sectors. During setup, Claude asked me a long list of preferences. When to trade, when to avoid trading, how much cash to deploy, whether to use fractional shares. I am new to all of it, so every question was a small education. Then it did something I never asked for. Claude created a trade log in a markdown file and started recording every decision on its own. According to Robinhood’s [agentic trading page](https://robinhood.com/us/en/agentic-trading/), agents can analyze markets, build positions, and rebalance, but the logging was pure Claude initiative. *The trade log captures EDGAR Form 4 insider clusters and the reasoning behind each order.* That log matters more than it looks. Every buy and sell feeds back into the agent, so it keeps a record it can learn from over time. ### **Let the AI Agent Trade and Review the Results** My funds had to settle overnight, so the first real trades waited until market open the next morning. When trading started, the agent bought four stocks right away. A couple of insurance names and Norwegian Cruise Line, each chosen against the parameters in my skill file. I was up about 33 cents at open, which tells you nothing about returns and everything about how small this test was. *The Robinhood Agentic dashboard with Claude connected and four positions held.* The setup is not fully hands-off. I run it through a background cron job, but Claude Code has to stay open on my computer for the agent to buy or sell. So it is autonomous while you are at your desk, not while you sleep. The feedback loop is the part I like. If I dislike the insurance picks, I tell the agent to lean into defense or drone stocks instead, and it adjusts. You can get as granular as you want without touching a strategy file again. Want to compare this to other autonomous setups? My breakdown of [Hermes AI agents](/hermes-ai-agents/) covers a different flavor of the same idea. Be honest with yourself about the risk. This is a beta product, which means bugs, errors, and the occasional hallucination. I would assume the agent is more likely to lose your money than make it. That is why I only fed it cash I could walk away from. ### **Ryan’s Final Thoughts** A Robinhood AI trading agent is one of the clearest signals yet that agentic tools are leaving the lab and touching real money. Setup takes patience, the account sits separate from your main funds, and the returns are unproven. Treat it as an experiment, not an income plan. Expect more brokerages and vibe-coded apps to ship their own versions soon, and learn the workflow now while it is still new. ### **AI Trading Agent on Robinhood FAQs** #### **What is an AI trading agent on Robinhood?** It is an AI agent connected to a dedicated Robinhood Agentic account that can read your portfolio and place trades for you. You connect it through the Model Context Protocol to a platform like Claude Code, then set the strategy and guardrails it follows. #### **How do I connect Robinhood to Claude?** Copy Robinhood’s MCP link from the Agentic tab and add it in Claude Code with `claude mcp add robinhood-trading --transport http https://agent.robinhood.com/mcp/trading`. Then reload Claude Code and finish the OAuth flow on a desktop device, including a verification step in the Robinhood mobile app. #### **Is Robinhood Agentic Trading safe?** It is a beta feature, so expect bugs and possible errors. The agent can only trade inside your separate agentic account, and you stay responsible for monitoring it. Only fund it with money you can afford to lose, and review the trade log often. #### **Does the AI trading agent run on its own?** Partly. The agent trades autonomously, but Claude Code has to stay open on your computer for it to buy or sell. A background cron job triggers the checks, so it works while you are active at your desk, not around the clock. #### **What strategy should the AI agent use?** That is up to you. I built a Claude Code skill that watches the public trading activity of politicians and executives, but you can ask Claude to rebuild any strategy around your own sectors and risk tolerance. The agent logs every decision so you can refine it over time. You can also [sign up for Robinhood](https://join.robinhood.com/ryans7568) if you want to test the feature yourself. *This is not financial advice. This video is for educational & entertainment purposes only. I am not a financial advisor. Investing involves risk of loss. Always do your own research or consult a licensed professional before investing.* --- ## Watch Me Build a Website With Claude In 30 Minutes URL: https://ryandoser.com/build-a-website-with-claude/ Markdown: https://ryandoser.com/build-a-website-with-claude.md Published: 2026-06-10 | Updated: 2026-09-30 Categories: AI Tutorials, Claude Code > Watch me build a website with Claude in 30 minutes. The exact Claude Code, GitHub, and Cloudflare stack I use to ship local sites fast. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* ### **How to Build a Website With Claude in 30 Minutes** I built a complete local business website on a recent podcast with Olivia Mansion. One fake company, one prompt, and roughly half an hour later it was live on the internet. If you want the same skill files I used to run this, they live in my **[Claude Code Skills Stack](https://skills.ryandoser.com)**. That is the fastest way to copy this exact setup instead of building it from scratch. You can see a production version of this approach in my own [website rebuild](/new-website-rebuild/). *My Claude Code setup with the Local Website Designer and Local SEO Strategist skill files loaded before the build starts.* I am not a developer. I have no programming background. I just spent hours learning this process so I could stop paying a premium to AI wrappers that hand back slop. The whole point is going straight to the source. #### **What You Need Before You Start** A few prerequisites make this work. Skip them and the quality drops fast. - A paid Claude plan. I recommend the $100 Max plan. Opus is included on the $20 Pro plan too, but site builds are usage-heavy and Max gives you five times Pro's usage. My current homepage was designed with Opus 4.8. If you want to see how much quality you give up with cheaper models, I [tested six budget models against my Opus build](/open-source-ai-web-design/). - Claude Code installed. I run it as an extension inside Visual Studio Code, but the terminal or desktop app work too. - Free [GitHub](https://github.com/) and [Cloudflare](https://www.cloudflare.com/) accounts. GitHub stores your files. Cloudflare deploys the site. - Brand assets ready to go. A logo, a brand guide in markdown, and a few images. More context in means better output. One pro tip on tokens. Run on low effort with `/effort`. Vibe coding a website is a long, heavy task, and on Opus 5.5 thinking cannot be switched off, so lowering effort is the setting that can reduce thinking and usage. #### **The Build: One Prompt, Parallel Agents** I gave Claude Code a single setup prompt for a made up company called Des Moines Window Cleaners. Company name, service area, fake phone and email, plus my brand assets folder. Then one rule that matters more than people think: provide a game plan for approval first. That approval step is the difference between a clean site and wasted tokens. I review the structure, fix anything off, then say go. *The build prompt and Claude Code's step-by-step to-do list scaffolding the Astro project, service pages, and schema.* Behind the scenes, the agents work through a visible to-do list. Scaffold the project, build the homepage, generate five service pages, eight location pages, then add schema and meta tags. You watch each box get checked. AI usually feels like a black box, and this turns it into a checklist you can follow. #### **Why I Use the Astro Web Framework** The sites get built on [Astro](https://astro.build/), a web framework that Cloudflare now owns. Think of it like a great WordPress theme from 10 years ago, except faster and cleaner under the hood. Astro matters because it produces sites that load fast and stay SEO friendly. One site I built this way passes Core Web Vitals almost perfectly on desktop. That speed is not a nice to have. It is a ranking signal. This is also where the skill files earn their keep. I split mine into a Local Website Designer skill and a Local SEO Strategist skill instead of one bloated file. Smaller, specialized skills give Claude Code cleaner instructions to pull from. If you want to see how I package and sell these, I broke that down in my guide on the [Claude Code skills hack](/claude-code-skills-hack/). #### **Vibe Coding Without the Slop** When people hear vibe coding, they picture Lovable, Replit, or Base44. Those are fine, but you pay a premium for a wrapper sitting on top of Claude or OpenAI, and most of the output is slop. I lay out [why I skip those platforms and WordPress alike](/wordpress-alternative/) in a separate post. Going straight to [Claude Code](https://code.claude.com/docs/en/overview) with your own skills and real branding keeps you in control. You get the highest quality output without paying middleman pricing. That is the honest case for this method, and it is why I switched. If you are newer to this, my walkthrough on [AI for non-coders](/ai-for-non-coders/) covers the mindset shift first. #### **Pushing the Site Live With GitHub and Cloudflare** Once the build finishes, you ship it. I had already synced GitHub to Claude Code, so it created the repo and pushed every file automatically. For real client sites I keep that repo private so nobody can scrape the source. Then Cloudflare Pages handles deployment. Connect the GitHub repo, hit deploy, and in under a minute the site is live on a Cloudflare domain. I tested this exact flow building local sites like [Des Moines Septic](https://desmoinesseptic.com/), which now ranks middle of page one for its local keywords. *The finished Des Moines Window Cleaners site, live on a Cloudflare Pages URL about 30 minutes after the first prompt.* One best practice before you go fully live: deploy to a preview branch first. You catch broken layouts on preview instead of blasting them to the main site. If something breaks, you fix it locally, approve, and only then push live. After the build, I batch my social content with [Blotato](https://www.blotato.com/?ref=rdoser) so a new local site gets promoted the same week it launches. The site is step one. Getting eyes on it is step two. ### **Ryan's Final Thoughts** This process takes 15 to 30 minutes versus the four plus hours a custom local site used to cost me. You get a fast, mobile optimized, SEO ready website for the price of a domain and a Claude plan. The specialized skills and brand assets do the heavy lifting, and the approval checkpoints keep you on track the whole way. Try it on a simple project first, then scale it to real clients once the flow feels natural. ### **Build a Website With Claude FAQs** #### **Can you really build a website with Claude in 30 minutes?** Yes, for a focused site like a local business page. I built a full Des Moines Window Cleaners site, with a homepage, service pages, and location pages, in about 30 minutes live on a podcast. Complex e-commerce takes longer, but a clean service site fits the window easily. #### **Do I need to know how to code to build a website with Claude?** No. I have no coding or programming background. Claude Code handles the framework, files, and deployment while you prompt in plain English. The skill files and brand assets guide the build, so your job is direction and approval, not writing code. #### **What plan do I need to build a website with Claude Code?** You need a paid Claude plan to access Claude Code. The $20 Pro plan includes Opus and works for small builds, but I recommend the $100 Max plan because heavy build tasks burn through Pro's usage fast. Cheaper models struggle to produce the same quality. #### **Where do you deploy a website built with Claude?** I use Cloudflare Pages connected to a GitHub repository. GitHub stores the code, Cloudflare deploys it live in under a minute, and you can buy or connect a domain right inside Cloudflare. Vercel works the same way if you prefer it. See the GitHub and Cloudflare steps above for the full flow. --- ## Claude Fable 5 is Here: The Best AI Model Ever? URL: https://ryandoser.com/claude-fable-5/ Markdown: https://ryandoser.com/claude-fable-5.md Published: 2026-06-10 | Updated: 2026-06-10 Categories: AI News, Claude Code > Claude Fable 5 is Anthropic's new top AI model. See the pricing, who gets access, and how it beats Opus in my real-world tests. **Claude Fable 5** and Claude Mythos 5 are officially live, and they might be the most advanced AI models on the market right now. I skip most model-launch hype, but this one earns a real-world test. ### **What Claude Fable 5 Actually Is** Most new-model videos drown you in benchmarks for an hour. I don't care about that. I care about one thing: can this model improve the work I already do? If you want my full Claude Code setup, my favorite skills, and the automations I run every week, grab my **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)**. It comes with everything I use to run my content business. Fable 5 and Mythos 5 are not a small step up. This is not the jump from [Claude Opus 4.7](/claude-opus-4-7-model/) to Opus 4.8. Anthropic shipped a brand new tier of models, and the early results back that up. Stripe reported Fable 5 compressed a 50-million-line code migration into a single day, work that took a team two months. You can read the full [Claude Fable 5 and Mythos 5 announcement](https://www.anthropic.com/news/claude-fable-5-mythos-5) for the deeper benchmark numbers, or watch Anthropic's [Claude Fable 5 announcement video](https://youtu.be/Y9Wz2PV404E) for the walkthrough. *The Claude API pricing page shows Claude Fable 5 at $10 per million input tokens and $50 per million output tokens.* ### **Claude Fable 5 Pricing and Who Gets Access** Here is the part most creators skip past. The two questions I always ask on a launch are who can access it and what it costs at scale. On the Claude Max plan at $100 a month, I have Fable 5 right now. It is included in plan limits until June 22nd. After that the message tells you to switch to usage credits to keep using it. My hunch is they move it to an API-only setup, but I am not an insider, so do not quote me. API pricing tells the real story. Claude Fable 5 runs $10 per million input tokens and $50 per million output tokens. Claude Opus 4.8, the previous top model, sits at $5 input and $25 output. In plain terms, Fable 5 is twice as expensive and drains your usage twice as fast. You can confirm the current numbers on the official [Claude API pricing page](https://platform.claude.com/docs/en/about-claude/pricing). It sits a tier above the research-only Mythos models too, and you can see where that line started in my breakdown of [Claude Mythos](/claude-mythos/). That raises an honest question for knowledge work. For copywriting, research, and the daily marketing tasks I run, is Claude Fable 5 overkill? My hunch is yes for most of it. A new model will not save you if your context and inputs are trash. Riley Brown still showed the upside, vibe coding a Lovable clone in two prompts with Fable 5. You can watch [Riley Brown's Fable 5 demo](https://x.com/rileybrown/status/2064540450317271356) to see how fast technical work moves now. ### **Claude Fable 5 vs Opus 4.8: Landing Page Test** Talk is cheap, so I ran the models head to head. First test: redesign the landing page for my Claude Code Skill Stack, a digital product that has already pulled in six to seven thousand dollars from a page Opus 4.6 built. Same prompt for both. Push for more conversions, keep my branding intact, build it locally, and list the top three changes with reasoning. I turned off thinking mode and kept effort on low to keep the test fair. Both finished at about the same time, which surprised me. *The Claude Fable 5 version of my Skill Stack landing page led with a stronger header and cleaner above-the-fold layout.* Opus 4.8 produced a solid page. The "Get Instant Access" button was more visible, and the above-the-fold section read clean. Most of its changes lived up top, with the rest of the page close to my original. Fable 5 felt sharper. The new header read "Turn Claude Code Into Your Marketing Team," which hits harder than the old line. The detail that won me over was small. Fable 5 bolded and highlighted the key phrases inside each customer review, a touch that Opus 4.8 and 4.6 both missed. I would ship the Fable 5 version as is. Slight nod to Fable 5 here. ### **Claude Fable 5 vs Opus 4.8: Full Website Test** The landing page was a warm-up. The real test was rebuilding my entire ryandoser.com site, a WordPress build on the Elementor theme that gets most of its traffic from blog posts repurposed from my videos. If you want the deeper case for why I run these tests in the first place, here is why [marketers should use Claude Code](/why-marketers-should-use-claude-code/). Same prompt again. Improve SEO, faster site speed, better design, and more conversions, using the Astro web framework. Build it locally and list the top three changes. This time Fable 5 took longer than Opus 4.8, which I expected for a bigger job. *The Claude Fable 5 redesign of ryandoser.com carried over blog posts, embeds, and images while looking more modern.* Opus 4.8 gave me a clearer above-the-fold and a stronger call to action. It carried the blog content over and embedded the videos and images correctly, which impressed me on a one-shot prompt. The weak spot was the look. It read a little more AI-generated to my eye. Fable 5 took a newer design spin. It pulled a color from my floating widget into the layout, so it was not perfectly on brand, but the homepage looked more professional, more modern, and more credible. It also took initiative and killed a few broken, embarrassing pages on its own, fixing bad copy and dead links I did not flag. For a single prompt asking it to rebuild a whole site, that judgment stood out. ### **Ryan's Final Thoughts** Claude Fable 5 and Mythos 5 are a genuine new tier, not another incremental bump. For my work going forward, I plan to use Fable 5 for vibe coding tasks like landing pages and websites while it lasts on the Max plan. For the 90 to 95% of my knowledge work in marketing and content, Opus 4.8 stays my default. Pick the model that matches the job, not the one with the biggest number. ### **Claude Fable 5 FAQs** #### **How much does Claude Fable 5 cost?** Claude Fable 5 costs $10 per million input tokens and $50 per million output tokens on the API. That is twice the price of Claude Opus 4.8, which runs $5 input and $25 output. On the Claude Max plan it was included in plan limits through June 22nd before shifting to usage credits. #### **Is Claude Fable 5 better than Opus 4.8?** For technical work like vibe coding and building websites, Claude Fable 5 produces more modern, more professional output than Opus 4.8. For everyday knowledge work like copywriting and research, Opus 4.8 is more than good enough and costs half as much. See the website test above for the full comparison. #### **Who has access to Claude Fable 5?** At launch, Claude Max plan subscribers had Fable 5 included in their plan limits until June 22nd. API users can access it at the listed token pricing. After the included window, Max users switch to usage credits to keep using the model. #### **Is Claude Fable 5 worth it for marketers?** For most marketing and content tasks, Claude Fable 5 is overkill. A new model will not fix weak context or weak inputs. Marketers doing standard knowledge work get strong results from Opus 4.8 at half the cost. Save Fable 5 for technical jobs like landing pages and full website builds. --- ## SEOmaxxing Boring Businesses for $5K/Month With AI URL: https://ryandoser.com/seomaxxing/ Markdown: https://ryandoser.com/seomaxxing.md Published: 2026-06-10 | Updated: 2026-09-30 Categories: AI Tutorials, Claude Code > SEOmaxxing is how I rank boring local businesses on Google with Claude Code and turn it into $5K/month retainers. Here is the full workflow. **SEOmaxxing** is how I rank boring local businesses on Google with a $100 AI tool and turn it into recurring retainers worth thousands a month. ### **What SEOmaxxing Actually Is** What if the websites making real money online were the least exciting ones on the internet? Septic tank companies. Junk haulers. Dental IT providers. The boring stuff. SEOmaxxing means pointing aggressive, AI-driven SEO at businesses that have ignored their online presence for years. I run the whole thing through Claude Code, a paid Claude plan, and a CMS like WordPress. That is the entire cost of admission. No agency. No dev team. No $5,000 web build. If you want the exact skills I use to do this, I put the whole system into my **[Claude Code Skills Stack](https://skills.ryandoser.com/)**. It includes the SEO blog post writer and the local website builder I show in the video, plus about 25 other marketing skills I actually use every week. The pitch to a business owner is simple. Your site has not been touched since 2002. You get leads from word of mouth. I can fix the first problem and grow the second. #### **Why Boring Businesses Win** Big niches like HVAC, plumbing, and roofing got eaten by private equity. They have millions in marketing budget. You will not beat them. So go where the money still sits unguarded. Septic, junk removal, funeral homes, dumpster rental, pet crematoriums. These owners run several million in revenue and barely think about Google. They have the budget and none of the competition. ### **My Claude Code SEO Workflow** You have probably seen AI SEO pitched as spamming 500 generic articles at a site and praying. That is not this. Every post I publish is built to rank and to read like a human wrote it. Here is the core loop. I take a long-form YouTube video, drop the URL into Claude Code, and call my SEO blog post writer skill. A skill is a standard operating procedure that tells the AI exactly how I want the job done. Its instructions live in a SKILL.md file inside the skill's own folder. *The single Claude Code prompt that calls the SEO Blog Post Writer skill, with a target keyword, title, and links to include.* I give it a target keyword, a few secondary keywords, and any links I want included. Then I let it run. One prompt, fully hands off. What comes back is a finished WordPress draft. Title, category, URL slug, meta description, featured image pulled from the video. It even embeds the video and writes the H2 and H3 hierarchy correctly. The detail people miss is the screenshots. An agent watches the video, finds key moments, grabs frames, compresses them so they do not bloat the media server, and places them where they actually fit the post. A quick tip that makes a real difference. When you tell Claude Code to triple-check something, it spins up agents in parallel to verify the work. I use that on every post. If you want the deeper version of this build, I broke it down in my guide on using [Claude Code for SEO](/claude-code-seo/). #### **The Results Are Real** This is not vanity content sitting in a folder. My site had zero authority going in. Zero domain rating, zero credible backlinks. I started at the end of February. The posts started ranking. And the traffic turned into money two ways. First, a digital product. A floating widget appears within the first five to seven seconds of a visit, and that is where most sales happen. I have made over $5,000 passively from my Claude Code skill stack, and roughly 80% of that revenue traces back to this repurposed blog traffic. Second, client work. I run this same WordPress and Claude Code setup for [Medix Dental IT](https://medixdental.com/), one of the top IT providers for dental offices and dental service organizations in the country. *Google Search Console for a real client, showing 204K impressions over three months as AI search visibility climbs.* Those impression spikes matter more than they look. When someone searches "best dental IT providers," Medix Dental now shows up as number one inside the Google AI Overview. That impression tells the searcher this company is the top pick. It reshapes how the market sees the brand, not just where the site ranks. ### **How I Sell This As a Service** Here is the part most people skip. You can save a client five hours a week and they shrug. You can make them more money and they pay you forever. That is the whole pitch. I am not selling time savings. I am selling inbound leads, which turn into revenue, which turns into a happy client writing a check every month. For my dental client, that check is a retainer in the thousands of dollars range. He just told me his team is fielding way more inbound leads since we started. Finding clients is the easy part. Walk into ten local businesses and talk to the owner, not the receptionist. Cold email and cold call work, but in person beats both right now because spam has poisoned the other two channels. Say this: your website has not been updated in a decade, you are leaving leads on the table, and here is the recurring solution I provide. Have that conversation ten times and you close at least one. Offer a low starter retainer or a performance basis to build your portfolio, and that first client becomes your case study. A paid audit is the other way in, because it gets you a client who has already spent money before you pitch any recurring work. I broke down [how to run that audit and what to charge for it](/ai-audit-business/) after taking apart someone else's version of the offer. #### **Building a Site That Outranked Real Businesses** This is the demo that makes people sit up. I built a fake septic company site, Des Moines Septic, in three or four hours. It ranked on page one of Google for money keywords like "septic tank pumping near me," beating Better Business Bureau, HomeAdvisor, and actual licensed businesses. *A local service website built from scratch with Claude Code, Astro, and Cloudflare in a few hours.* I built it with Opus 4.7 and the [Astro web framework](https://astro.build), which is fast, SEO friendly, and passes Core Web Vitals on mobile and desktop. The whole thing is 100% AI. Service pages, location pages, a full SEO-ready blog, all generated from one deep Claude Code session. You can see the live result over at [Des Moines Septic](https://desmoinesseptic.com/). The hosting stack is free. A [GitHub](https://github.com) repository stores the code. [Cloudflare](https://cloudflare.com) deploys it live with a generous free plan. The only real cost is your [Claude Code](https://claude.ai/code) subscription. For $20 a month you can technically do this, but Opus will burn through usage fast, so I run the $100 plan. On that single $100 subscription you can handle two or three clients without hiring a single VA. Want a deeper walkthrough of the no-WordPress version? I covered it in my post on how to [build a website with Claude](/build-a-website-with-claude/). To be honest about the limits: a fake business cannot get into the map pack or pass Google Business Profile verification. The website outranks real companies in organic results, but local pack visibility still needs a legitimate, verified business behind it. #### **Why This Compounds** Social media is rented attention. A tweet that pops off is invisible 72 hours later. SEO is an owned asset. A blog post you publish today can send leads for years. When I pitch clients, I am honest. You will not see ROI on day one, maybe not by day 30. But the work pays you back on day 90, in year one, and even after we stop working together. Business owners who think long term understand that instantly. You can also clone the playbook endlessly. I spun up Des Moines Junk Removal off the same skill with different branding, service, and service areas. The marginal cost of a new site is close to zero. That means you can build your own case studies in a weekend. Cloning it is also the engine behind [renting the leads out instead of selling retainers](/rank-and-rent-seo/), which is a different way to bill for the same sites. ### **Ryan's Final Thoughts** SEOmaxxing works because it targets businesses with real revenue and almost no competition, then drives leads they could not get on their own. A $100 Claude Code subscription against a few thousand a month per client is absurd arbitrage. Anyone saying SEO is dead is not paying attention. The [best AI SEO tools](/best-ai-seo-tools/) have never been more accessible, and the opportunity has never been bigger. Pick a boring niche, build one site, and go land your first client. ### **SEOmaxxing FAQs** #### **What is SEOmaxxing?** SEOmaxxing is using AI tools like Claude Code to aggressively tune websites and content so they rank on Google and in AI search results. The goal is driving real inbound leads for local service businesses, then charging those businesses a recurring retainer for the service. #### **Do you need to know how to code to do SEOmaxxing?** No. I have over a decade in marketing and zero coding background. The whole system runs through Claude Code, which handles the technical work for you. A free GitHub account, free Cloudflare hosting, and a Claude subscription are all you need. If I can do it, anyone can. #### **How much does SEOmaxxing cost to start?** The bare minimum is a $20 Claude plan, free GitHub, and free Cloudflare. Because Opus uses heavy compute, I recommend the $100 monthly Claude plan. On that one subscription you can realistically service two or three clients at once. #### **How do you make money with SEOmaxxing?** Two ways. You can drive traffic to your own site and sell a digital product, like I do with my [Claude Code Skills](/sell-claude-skills/). Or you can sell SEO as a service to local businesses for a monthly retainer in the thousands. See How I Sell This As a Service above for the full pitch. #### **What businesses are best for SEOmaxxing?** Boring, low-competition local service businesses with real revenue. Septic companies, junk removal, dumpster rental, funeral homes, dental IT. Avoid HVAC, plumbing, and roofing, which private equity has already flooded with marketing budget. For more on this, see my guide on [AI for small businesses](/ai-for-small-businesses/). --- ## These Hermes AI Agents Automate His Email Growth (Copy This) URL: https://ryandoser.com/hermes-ai-agents/ Markdown: https://ryandoser.com/hermes-ai-agents.md Published: 2026-06-08 | Updated: 2026-06-08 Categories: AI Rabbit Holes > See how Hermes AI agents run cold outreach and scrape Facebook groups to grow an email list from zero to 1,000 subscribers, no ad spend. ### **How Hermes AI Agents Work for Marketers** *Drew's cold email workflow: find businesses, clean the list, then let Claude check fit before any send.* ### **Hermes vs OpenClaw: What Drew Actually Picks** ### **The Cold Email System Behind the Subscriber Growth** ### **Scraping Facebook Groups With Hermes AI Agents** *Drew controls Hermes from Telegram while a separate machine runs the Facebook outreach hands-free.* ### **Keeping a Human in the Loop** *Hermes drafts the reply and waits for a yes before posting, so Drew approves every comment.* ### **Ryan's Final Thoughts** ### **Hermes AI Agents FAQs** #### **What are Hermes AI agents?** #### **Is Hermes better than OpenClaw?** #### **How much does running Hermes cost?** #### **Can Hermes AI agents really grow an email list?** #### **Do I need a separate computer to run Hermes?** --- ## How to Automate SEO Content with AI That Ranks (No Slop) URL: https://ryandoser.com/ai-seo-system/ Markdown: https://ryandoser.com/ai-seo-system.md Published: 2026-06-05 | Updated: 2026-07-07 Categories: AI Automations, Claude Code > I built an AI SEO system that publishes daily content without slop. Here is the architecture that gets the speed without the Google penalty. I built an **AI SEO system** that drafts, fact-checks, and ships a blog post every day without the slop that gets sites buried. The barrier to publishing AI content dropped to near zero, so the feeds filled up fast with articles that read fine and say nothing. ### **What an AI SEO System Actually Solves** You have probably seen the cautionary tale. A site cranks out hundreds of AI articles, ranks for a few months, then loses almost all of its traffic after an algorithm update. People walked away thinking AI content is dead or that Google hates automation. That is the wrong lesson. The problem was never speed. You can publish daily and still rank. What gets sites buried is slop, meaning unverified claims, near-duplicate pages, and templated content that reads like a machine made it at scale. So I stopped asking how to publish faster and started asking how to get the speed without the things that trigger a penalty. Quality is the whole game now. I made the same point in my piece on [why most AI marketing advice is wrong](/ai-marketing-advice/), and this system is how I put that belief into practice. ### **Why Programmatic SEO Got Penalized** ClickUp's blog lost roughly 97.6% of its organic search traffic in 15 months, falling from about 1.19 million monthly visitors in early 2025 to around 28,000 by April 2026. Here is the telling part. It was not a backlink problem. The site's Domain Rating actually rose during the collapse and its referring domains grew. *ClickUp's organic traffic (orange) collapsed while its referring domains (blue) kept climbing. Source: [Content Levers](https://contentlevers.xyz/blog/clickup-blog-traffic-drop).* The decline got pinned on scaled, templated content and over-promotional listicles that ranked ClickUp first in its own comparison posts. You can read the full [breakdown of the ClickUp traffic collapse](https://ppc.land/clickups-blog-lost-97-6-of-its-traffic-here-is-exactly-how/) for the numbers. The takeaway is simple. Automation was not the crime. The slop was. So the goal is not to slow down. The goal is a pipeline where the things that get you penalized cannot reach the live site in the first place. ### **How My AI SEO System Works (Sheet Row to Published Post)** The whole thing runs off a single spreadsheet. Each row is one post: the topic, the type of post it should be, the primary keyword, and the title and slug. *The content queue. Each row is one post, and the status column drives the whole publishing loop.* When the system runs, it grabs the top unstarted row and routes it to the right playbook based on the post type. From there it researches the topic live, writes the full draft, pulls real screenshots, generates a featured image, runs a stack of safety checks, and stages the post for review. No one touches a keyboard until the approval step. I built the same kind of skill-driven flow when I set up my system to [repurpose YouTube videos with Claude Code](/claude-code-repurpose-youtube-videos/), and this extends that idea to a full daily publishing loop. That is the speed half, and it is genuinely fast. The hard half is everything built in to stop slop before it ships. ### **The 5 Things That Keep My AI SEO System From Producing Slop** These five guardrails are what separate a useful AI SEO system from a content firehose that gets a site penalized. #### **1. It Fact-Checks Itself, Adversarially** This is the part almost no AI workflow does. After the first draft is written, a second pass goes back through every factual claim and actively tries to disprove it. Not whether the sentence reads confidently, but whether it is actually true and where the proof is. This is not theoretical. On the first post the system shipped, that adversarial pass caught three real factual errors the first draft had stated with full confidence. The model that wrote a claim is the worst judge of whether the claim is true, so a separate verification pass does the catching. #### **2. It Scans the Whole Cluster for Duplicate Content** Near-duplicate pages are one of the clearest signals of low-effort content at scale. Publish ten posts that are 80% the same paragraph with the nouns swapped, and search engines notice. Before anything publishes, the system compares the new post against the rest of the blog. Overlapping angles get flagged and reworked. Every post has to earn its place by being meaningfully different, not just technically a new URL. #### **3. It Mixes Content Types on Purpose** Publish ten comparison posts in a row and your blog reads like a template factory, even if each one is well written. A real editorial calendar does not look like that. Deciding what goes in that queue is the part that got cheap, which is the case I make in my breakdown of [where the advantage moved in SEO content strategy](/seo-content-strategy/). *Planning the queue: mixing listicles, alternatives, and comparisons so the calendar does not read as templated.* The system interleaves formats, rotating a comparison, then a listicle, then a how-to guide, then a deeper explainer. The calendar reads like a human team planned it. That is the difference between a content team running the blog and a script running it, and both readers and search engines pick up on it. #### **4. SEO Expert Inputs Before Anything Publishes** The system drafts, but it does not get the final say. Every post passes through my own SEO judgment before it goes live. That is the [human expertise the model cannot replace](/best-ai-seo-experts/). Keyword targeting, search intent, internal linking, the title and slug, the angle that will actually rank. Those are the calls I make, not the machine. This is the part that separates my output from the flood of auto-published AI content. The slug and title on an SEO page live forever and shape how the page performs. Years of testing what ranks and what does not is exactly the input you cannot automate away, so I put it in before the post ever reaches a public URL. That is the gap I keep running into with the platforms built to deploy changes on their own, and it is the whole reason [a tool like Search Atlas is a harder sell on a single site](/search-atlas-review/) than its pricing page suggests. #### **5. Every Post Gets a Unique Angle** Most AI blog posts are the same article wearing a different title. The model read the top ten results, blended them, and handed back a slightly reworded average of what already exists. That is the definition of forgettable. I will not ship that. Every post has to bring a take the other results do not have, whether that is a first-hand result, a contrarian opinion, or a framing nobody else used. If a draft just restates the consensus, it does not run. That is what makes the content worth reading and worth citing, instead of one more recycled page competing with a thousand identical ones. The [AI SEO tools I actually use](/best-ai-seo-tools/) are built around this same bar: quality and citability over raw volume. ### **What This Means for AI and SEO** This is not theory for me. The same disciplined system is what took one of my sites to 21.3K clicks and 662K impressions over three months, at an average position of 6.1. *Real Search Console data from the system: 21.3K clicks and 662K impressions over three months, at an average position of 6.1.* The takeaway is not to automate everything. It is the opposite. The real edge is automating the 95% that is mechanical, meaning the research, the drafting, the formatting, the image, the safety checks, and keeping a human in the loop on the 5% where brand and SEO risk actually live. People hear AI content system and picture a firehose of garbage. The better version is a system that is more disciplined than a human team, not less. One that fact-checks harder, dedupes more thoroughly, and refuses to ship anything that fails a check. Mine runs on a set of Claude Code skills wired to that spreadsheet, and you can find the writing skills I use in my **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)**, though the principle holds no matter what you build it with. If you want the manual version of the same standard, my guide on [how to avoid AI slop](/avoid-ai-slop/) covers it. ### **Ryan's Final Thoughts** Volume is free now. Hype is free. Slop is free. What is rare in 2026 is a real person with real opinions running a disciplined process and publishing the results. An AI SEO system gives you the speed of automation with the quality bar of an editor, as long as you build the guardrails first and the speed second. Think first about where the real risk lives, then automate fast around it. That is how you publish daily content that ranks without the slop, and it is the same mindset behind how I think about [winning in AI search](/how-to-manipulate-ai-search/). If you want the strategy layer underneath this system rather than the publishing machinery, my primer on [getting named inside AI answers](/ai-seo-strategy/) covers it. For the rules these systems have to respect, the [Google spam policies](https://developers.google.com/search/docs/essentials/spam-policies) are the baseline. ### **AI SEO System FAQs** #### **What is an AI SEO system?** An AI SEO system is an automated pipeline that researches, writes, fact-checks, and publishes search-ready content with minimal manual work. The good ones build in quality controls like fact verification, duplicate-content scans, and an SEO expert review step so the output ranks instead of getting penalized for being low-effort. #### **Does Google penalize AI-generated content?** Google does not penalize content for being AI-generated. It penalizes unhelpful, scaled, low-quality content regardless of how it was made. Per Google's own spam policies, the issue is content created mainly to game rankings, not the tool used to write it. Verified, original, genuinely useful AI content can rank fine. #### **How do you automate SEO content without getting penalized?** Automate the mechanical parts and keep an SEO expert on quality. Add an adversarial fact-check pass, scan for near-duplicate pages across your blog, vary your content formats so the calendar does not look templated, give every post a unique angle, and review each one before it goes live. Speed is fine. Unverified slop is what triggers penalties. #### **Can you really publish a blog post a day with AI?** Yes, if each post clears a real quality bar. A daily cadence is sustainable when the system does live research, verifies its own claims, and an expert approves the final draft. The cadence is not the risk. Shipping unchecked, near-identical posts at that cadence is. --- ## How to Build Websites with Claude Code (RIP WordPress) URL: https://ryandoser.com/vibe-code-websites-claude-code/ Markdown: https://ryandoser.com/vibe-code-websites-claude-code.md Published: 2026-05-28 | Updated: 2026-07-07 Categories: Claude Code > Learn how to build websites with Claude Code, GitHub, and Cloudflare. This is for non-coders looking to ditch WordPress, Wix, Webflow, etc. This guide shows a non-technical marketer how to **vibe code websites Claude Code** style, step by step, with no prior programming background required. ### **Vibe Code Websites Claude Code Video Guide** Here is the full walkthrough of how I built a real local service website in roughly fifteen minutes using Claude Code, GitHub, and Cloudflare. If you want to go deeper on the workflow, my [**Claude Code Skills Stack**](https://claude-code-skills-stack.rdoser13.workers.dev/) includes the local website designer skill and the local SEO strategist skill I used to ship the Des Moines Septic site, plus 25 other marketing skills I run every week. Line up the prerequisites first. Claude Code, my top pick among the [best AI coding tools](/best-ai-coding-tools/), on the Max plan gets you real access to Opus 4.7, the model that builds clean sites. A free [GitHub](https://github.com/) account hosts the codebase. A free [Cloudflare](https://www.cloudflare.com/) account handles hosting. The web framework I keep coming back to is [Astro](https://astro.build/), which is fast, SEO friendly, and now owned by Cloudflare. ### **The Vibe Code Website Step by Step Workflow** This is the exact build sequence for a vibe coded website from blank prompt to live custom domain. #### **Step 1: Set Up Claude Code With the Right Skills** Open a fresh Claude Code chat inside Visual Studio Code. Pick Opus 4.7. Turn thinking mode off. Drop effort to low because website scaffolding is not a reasoning-heavy task. If you are new to the tool, my breakdown of [why marketers should use Claude Code](/why-marketers-should-use-claude-code/) covers the setup. Then load two skills: a local website designer skill and a local SEO strategist skill. Splitting them matters. One bloated mega-skill produces sloppy output. Two narrow skills produce sharper sites and cleaner SEO structure. This is the same pattern I use to run [Claude Code AI marketing agents](/claude-code-ai-marketing-agents/) for content and SEO work. *The Claude Code prompt with brand guide, logo file, and image folder attached before the first build.* #### **Step 2: Feed Claude Code Real Brand Assets** Write a prompt that calls out both skills, names the Astro framework, and gives a reference URL to scrape. Load the business details: name, industry, service area, phone, email. The shortcut most people skip is brand assets. Have Codex generate a logo with GPT Image 2. Build a quick brand guide with fonts and color codes. Generate a folder of branded photography for service and location pages. Close the prompt with: "First provide a game plan for approval. Save all files to my main Claude Code workspace." #### **Step 3: Approve the Game Plan and Build Locally** Claude Code returns a full plan in about a minute: stack, page inventory, menu structure, permalinks, SEO details, robots.txt, meta tags, and copy voice. Read it. Request changes if anything looks off. Once approved, switch Claude Code to bypass permissions for speed. Nothing goes live yet. Everything is built locally. The first draft will be rough. Spin up the local host URL and look at it. Then point Claude Code at a reference site you like. For the demo I used the [Des Moines Septic example](https://desmoinesseptic.com/) I had already built, and told it to add more pages, dropdown menus, a blog section, icons, and mobile styling. Round two came back with 41 pages and real navigation. #### **Step 4: Push the Site to a GitHub Repository** Create a new GitHub repo named after the business. Public is fine. Skip the README, gitignore, and license. Copy the repo URL into Claude Code and ask it to push the local folder. It returns a terminal command. Paste it into your Mac terminal. If you hit an HTTP buffer error, paste the error back into Claude Code, get the fix command, and run it again. Refresh the GitHub repo and your files appear. *Creating a new GitHub repository named after the business before pushing the vibe coded website files.* #### **Step 5: Deploy Vibe Coded Website on Cloudflare** Inside Cloudflare, go to Compute, then Workers and Pages, then Create Application. Pick "Pages" and import the existing Git repository. Authenticate GitHub if you have not already. Pick the repo. Production branch is main. Framework preset is Astro and the build command is npm run build. Leave the output directory alone. Click save and deploy. A minute later the site is live at a pages.dev URL. That URL is fine for testing but not where a real business should sit. Most ad platforms ban pages.dev landing pages anyway. *The Cloudflare Workers and Pages dashboard showing the deployed Des Moines Septic and other Astro projects.* #### **Step 6: Attach an Exact Match Custom Domain** Buy a domain through Cloudflare or transfer one in. For local SEO, an exact match domain still helps. I used [dsmjunkremoval.com](https://dsmjunkremoval.com/) as the demo. In your Pages project, go to settings, custom domains, paste the URL, and click activate. Cloudflare creates the DNS record automatically. #### **Step 7: Make Future Updates Hands-Off** Send Claude Code the live URL and request edits. Fix the favicon. Triple check mobile. Spin up a new blog post. Claude Code pushes to GitHub, GitHub triggers Cloudflare, Cloudflare redeploys. You never touch the terminal again. ### **Ryan's Final Thoughts** The Des Moines Septic demo is already ranking middle of page one for "septic tank pumping near me" and pulling phone calls and form submissions. That is a vibe coded Astro site, a few weeks old, beating real local companies. The build itself took fifteen minutes. The learning curve took three or four hours. The tradeoff is real: solo operators and small agencies win with this stack, while large teams with non-technical editors are still better served by WordPress as a CMS. I make the full case for [why WordPress is dying for solo operators](/wordpress-alternative/) in a follow-up post. If you want the rest of my workflow, my [AI marketing stack](/ai-marketing-stack/) breaks down the tools I run every week. ### **Vibe Code Websites Claude Code FAQs** #### **Can you build a website with Claude Code if you have no coding background?** Yes. Claude Code handles the codebase while you handle the brief. Write a prompt with company details, brand assets, and a reference site. You get a working Astro project saved locally, then push the final version to GitHub and Cloudflare. #### **Claude Code vs WordPress: which one wins?** Claude Code wins on speed, cost, and SEO performance for solo operators and small agencies. WordPress still wins for large teams with several non-technical editors who need a content management interface. #### **Why build a vibe code website with Astro?** Astro ships clean static HTML, which loads fast and ranks well. It is owned by Cloudflare so deployment is direct. Claude Code produces reliable Astro code with the local website designer skill loaded. #### **How do I deploy a vibe coded website on Cloudflare?** Push your project to a GitHub repository. In Cloudflare, go to Compute, Workers and Pages, Create Application, and import the Git repo. Pick the Astro framework preset, set the build command to npm run build, and click save and deploy. #### **Will a vibe coded local business website rank in Google?** Yes, with the right setup. The Des Moines Septic demo is ranking middle of page one for "septic tank pumping near me" within weeks of launch. The wins come from an exact match domain, the local SEO strategist skill, fast Astro load times, and getting indexed in Google Search Console. --- ## Claude AI vs Cowork vs Code: Which Should You Use? URL: https://ryandoser.com/claude-ai-vs-cowork-vs-code/ Markdown: https://ryandoser.com/claude-ai-vs-cowork-vs-code.md Published: 2026-05-21 | Updated: 2026-09-30 Categories: AI Rabbit Holes, Claude Code > Claude AI vs Cowork vs Code, explained. Learn what each does, who it fits, and when to graduate from chat to Cowork to Claude Code. The confusion around **Claude AI vs Cowork vs Code** comes up in almost every conversation I have with founders and marketers right now. This guide breaks down what each one actually does, who it is for, and when to graduate from one to the next. **Update (September 2026):** Anthropic has since [merged Claude Cowork and chat into one Claude](https://claude.com/blog/cowork-is-now-claude). Starting September 16, 2026, what Cowork and Claude Design can do is available from any conversation, with the context, skills, and connectors you already have. It is rolling out on Pro and Max over several weeks, with Team and Free plans to follow and Enterprise admins getting at least 30 days of notice. So whether you have the merged version yet depends on your plan and where the rollout is. The interview below was recorded before the merge, and the question it answers, when to move from Claude to Claude Code, has not changed. ### **Claude AI vs Cowork vs Code Video Guide** I sat down with Brooke Wright, an AI expert who helps non-technical founders build with AI, to settle the question once and for all. Brooke runs her entire content and admin workflow across Cowork and Claude Code, so she has real reps in both. If you want to skip the chatbot stage entirely, my full [Claude Code playlist](https://youtube.com/playlist?list=PLzJwubkSKclNTmw6mlFegXUd27ogkiwb-) has tutorials for marketers. Want to go deeper on Claude AI vs Cowork vs Code as a topic? Keep reading. *Brooke Wright joins AI Rabbit Holes to break down the three Claude products.* ### **The Differences Between Claude AI, Cowork, and Claude Code** Here is the short version of each product and who it actually fits. #### **Claude AI** Claude AI is the chatbot most people already know. You ask, it answers, and a few connectors let it pull your email or add a calendar event. It is the right starting point if you are still copying and pasting prompts into a chat window. The ceiling on plain chat was low on purpose. It could not save files to your computer, run scheduled jobs, or chain tools into a workflow, which is the gap Cowork filled. On plans where the merge has rolled out, those Cowork abilities now come with the same conversation. Once you outgrow basic Q&A, you need something with more reach. If you are still in this phase, my guide on [switching from ChatGPT to Claude](/switch-from-chatgpt-to-claude/) covers how to set yourself up to grow. #### **Claude Cowork** When we recorded this, Cowork sat in the middle. It lived inside the Claude desktop app, ran in a sandboxed Linux virtual machine, and could read or write files on your computer. No terminal. No black screen. No setup beyond opening the app. Brooke described it as the gap Anthropic spotted between chat users and developers. People wanted more than chat but were not ready for code. [Cowork](https://claude.com/product/cowork) fills that exact space. You can connect custom MCPs, build skills, and let Claude work alongside you on real tasks. *Brooke's CoworkHQ folder with a Readme that maps where every project lives.* #### **Claude Code** Claude Code is the developer-grade tool. It runs on your operating system with full filesystem access, plugs into VS Code or JetBrains, and pairs cleanly with Codex or other agents. I use it six to eight hours every day, and I broke down the marketer case for it in [why marketers should use Claude Code](/why-marketers-should-use-claude-code/). I will be honest. Claude Code is a horrible name for non-developers. The word "code" makes people freeze. But I rarely touch a raw terminal. I run the [Claude Code](https://docs.anthropic.com/en/docs/claude-code/overview) extension inside VS Code, which feels closer to a regular app than anything in a black window. If you want to push the limits, build your own software, or run heavy automation, this is the tier. My [Claude Code agent setup](/claude-code-ai-marketing-agents/) shows what is possible once you get comfortable. #### **Claude Cowork Live Artifacts** Live artifacts are one of the most underrated Cowork features. A few months back, the social feed was full of Claude dashboards that looked great but went stale the moment you closed the chat. Anthropic shipped an update that refreshes those artifacts every time you open them. Brooke connects her live artifact to email, Slack, and her calendar. The result is a morning command center that tells her what needs replies, what is happening in Slack channels, and what is on the calendar that day. #### **Claude Cowork Scheduled Tasks** Scheduled tasks let Cowork run on a cadence without you opening the app. Brooke has one that pings her Slack every morning with AI news angles for content. Another scrapes her Skool community at 8 AM and 8 PM so she never misses a reply. The tasks can use tools inside the run, not just send a static message. That is what makes them different from a basic reminder. *Brooke's Cowork project list and scheduled tasks running her business on autopilot.* #### **When to Switch From Cowork to Claude Code** The honest cutover signal is when Cowork stops being enough. Brooke is rebuilding her website with Claude Code because Cowork cannot match the same Vercel CLI and GitHub workflow. I vibe coded my own version of Obsidian in Claude Code with a cron job that backs everything up to Google Drive. If you are a bookkeeper, admin pro, or knowledge worker who wants AI to handle repeat tasks, Cowork is probably your final stop. If you want to ship software, customize deeply, or use Claude Code alongside other AI agents like Codex, make the jump. One pro move from Brooke: set up your folder structure the same way in Cowork that you would in Claude Code. That way the switch is just pointing a new tool at the same files. ### **Final Thoughts from Ryan** The path most people should take is simple. Start with Claude AI to get comfortable. Move to Cowork's abilities when you want Claude to actually do work on your computer, which, once the rollout reaches your account, happens inside the same Claude app. Jump to Claude Code when you want to build, ship, or integrate with other AI tools. If you are weighing it against the alternatives, here is [my full breakdown of AI coding tools](/best-ai-coding-tools/). A $100 a month Claude Max plan covers all three, which makes it the best AI subscription you can buy right now. Catch more interviews like this one on the [AI Rabbit Holes playlist](https://youtube.com/playlist?list=PLzJwubkSKclOQ2_v7NBRSXCx1lOUHFxxa), and find Brooke at [Wright Mode](https://www.wrightmode.com/), on [YouTube](https://www.youtube.com/@WrightMode), and on [Instagram](https://www.instagram.com/wright_mode/). ### **Claude AI vs Cowork vs Code FAQs** #### **What is the difference between Claude AI and Claude Code?** Claude AI is the chatbot interface where you ask questions and get answers. Claude Code is an agentic developer tool that runs on your operating system, edits files, and ships software. Claude AI is for thinking and quick tasks. Claude Code is for building, automating, and executing multi-step work. #### **What is Claude Cowork?** Claude Cowork is Anthropic's product for non-technical users who want more than chat but are not ready for Claude Code. It started in the Claude desktop app, running in a sandboxed virtual machine that could read or write files on your computer, with no terminal, setup, or coding background required. In September 2026 Anthropic began merging Cowork and chat into one Claude, starting with Pro and Max, so once the rollout reaches your account its abilities come with a regular conversation. #### **Should non-technical founders use Cowork or Claude Code?** Most non-technical founders should start with Cowork, which is being built into the regular Claude app as the rollout reaches each plan. It covers admin, content, and daily ops without the learning curve. Move to Claude Code only when you want to build websites, ship apps, or run heavier automation. Brooke recommends keeping the same folder structure in both so the switch is painless. #### **Is Claude Cowork good for marketers?** Yes. Cowork handles content scheduling, AI news scraping, and inbox triage through scheduled tasks. Live artifacts give marketers a morning dashboard for email, Slack, and calendar. It is a strong pick if you want AI in your workflow without learning a CLI. #### **Can you use Claude Cowork in teams?** Yes. Team and enterprise plans let you save team skills and plugins that live outside personal skills. That makes Cowork a better team fit than Claude Code, which is built around a solo IDE workflow. --- ## How to Repurpose YouTube Videos into Blogs With Claude Code URL: https://ryandoser.com/claude-code-repurpose-youtube-videos/ Markdown: https://ryandoser.com/claude-code-repurpose-youtube-videos.md Published: 2026-05-17 | Updated: 2026-09-30 Categories: AI Tutorials, Claude Code > Use Claude Code to repurpose YouTube videos into ranking SEO blog posts in five minutes. Full skill setup, prompt, and WordPress flow. This guide shows you how to **Claude Code repurpose YouTube videos** into SEO-ready blog posts on autopilot, using one skill file and a paid Claude plan. ### **My Claude Code YouTube Repurposing Workflow (Full Video)** What if the slowest part of your content workflow vanished overnight? I recorded a full walkthrough on the Supermarketers podcast showing exactly how I turn a single long-form video into a complete WordPress draft in about five minutes. You need three things before copying this setup. A paid Claude plan (Pro at $20 or Max at $100), Claude Code installed in an IDE like VS Code, and a CMS that supports MCP. WordPress is the easiest entry point. I also use Blotato to scrape the transcript, since it handles hour-long videos without choking. If you want the wider SEO angle, I broke that down in my [Claude Code SEO workflow guide](/claude-code-seo/). Today's post zooms in on the repurposing half. *Every blog post on my site started as a video on my [YouTube channel](https://www.youtube.com/@RyanDoserAI).* ### **How Claude Code Repurposes a YouTube Video** You've probably tried pasting a transcript into ChatGPT, fighting the output, and copying it into WordPress yourself. That loop disappears here. Claude Code reads a skill file, scrapes the transcript, writes the article, embeds the video, and pushes a draft to WordPress in one pass. The skill file is the key. It is a Markdown SOP telling Claude Code how output should be structured. Header hierarchy, keyword placement, internal link rules, image handling, FAQ format. I trained mine over hours of edits, so each new post follows the same standards without babysitting. When I run a prompt, Claude Code creates its own checklist, pulls the transcript through Blotato MCP, drafts the article, grabs screenshots, and uploads everything to WordPress. The official [Claude Code documentation](https://code.claude.com/docs/en/overview) covers the broader skill framework. ### **Step 1: Build Your SEO Blog Post Writer Skill** Skills replace one-shot prompts. Instead of typing the same 800-word instruction block every time, you save those rules once and call them by name. That habit is my favorite [Claude Code productivity hack](/claude-code-productivity-hack/). My SEO blog post writer skill includes section structure, banned words, voice rules, internal link logic, screenshot extraction commands, and the WordPress publishing flow. It is one of several writing skills I sell as part of the **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)**, though you can absolutely build your own from scratch. A few things to watch when you write the skill. Keep one skill per task, no overlap. Use a clear description at the top so Claude Code knows when to invoke it. Reference your XML sitemap inside the skill so it can pick relevant internal links in real time. *A finished draft on ryandoser.com after Claude Code repurposed the source YouTube video.* ### **Step 2: Run the Prompt in Claude Code** Open VS Code and start Claude Code in plan mode for your first few runs. The prompt is short. I call the skill by name, paste the YouTube URL, give it a target keyword, list five to seven secondary keywords, and add a working title. The more context you hand it, the better the draft. Cap it with any timely angle the video missed (a new model release, a pricing change, a fresh case study). On Claude Max, I pick Opus for content writing. On Pro, Sonnet handles this fine. Thinking burns tokens on this task with no quality lift, so keep it light. On Opus 5.5 and Sonnet 5.5, thinking can't be turned off, so drop /effort to low instead. Once the prompt is in, Claude Code generates a to-do list and starts working. You can watch each subtask check off in real time. Transcript scrape, competitive research, draft, screenshots, upload. About five minutes start to finish for a 1,200-word post on a busy connection. ### **Step 3: Let Claude Code Publish the Draft** This is where most YouTube-to-blog tutorials stop. Mine keeps going. The WordPress MCP connection means Claude Code creates the post inside your site directly, no manual paste required. It assigns one category based on the article topic. It uses the YouTube thumbnail as the featured image. It sets the Yoast SEO title, meta description, focus keyphrase, and slug. It embeds the video near the top. It places three screenshots throughout the body at relevant moments. It picks two to three internal links from your sitemap with optimized anchor text. I keep auto-publish off. Google's recent core updates punished sites that flooded their feeds with low-effort posts, so a five-minute review pass before going live is non-negotiable. Read for tone, swap any awkward sentence, then hit publish. *Claude Code working through its own checklist and creating the WordPress draft in one pass.* ### **What This Workflow Actually Returns** Here is what I get out of one run on a recent video. - A 1,000 to 1,200 word draft with proper H2 and H3 hierarchy - Embedded YouTube video near the top - Featured image pulled from the thumbnail - Two or three screenshots from the actual video, captioned and alt-texted - Internal links chosen from the live sitemap - External links to credible sources - Yoast focus keyphrase, SEO title, meta description, slug - Saved Markdown copy in my local archive folder The same transcript also spins out social posts through Blotato. Since the context already lives in Claude Code, a one-line follow-up like "now create five LinkedIn posts" takes another minute. That is the core of [my AI social media system](/ai-social-media-system/): one root file feeding every channel. Honest caveat. If your YouTube video has weak structure, the post inherits it. Claude Code polishes prose, but it cannot invent a thesis you never made on camera. Tighter videos make tighter posts. That limit is the same one I hit when [turning one seed into a full week of drafts](/ai-content-engine/), and no amount of processing gets around it. That is exactly why I now treat [the video itself as the strategy](/seo-content-strategy/) rather than something a keyword map decides after the fact. I refined this on shows like [Supermarketers](https://www.supermarketers.ai/), where guests pressure-test their systems on camera. ### **Final Thoughts from Ryan** The unlock here is not Claude Code itself. It is treating your YouTube channel as the content foundation and letting one skill file handle the repurposing tax. Every video can become a ranking blog post, a newsletter section, and a week of social content from the same transcript. Start by recording one tight video on a real keyword. Build the skill once. Then watch how fast your library compounds. If you would rather not build the skill file yourself, I packaged this workflow as the [**AI Content Engine**](https://engine.ryandoser.com/). Drop in one video, podcast, or long post and it returns the blog, the social posts for every platform, the newsletter, and the hooks in your own voice, with a slop check on every draft before you see it. ### **Claude Code Repurpose YouTube Videos FAQs** #### **Do I need a paid Claude plan to repurpose YouTube videos with Claude Code?** Yes. Claude Code only runs on a paid plan. Pro at $20 a month handles this workflow on Sonnet, and Max at $100 unlocks Opus for higher-quality writing. The free Claude tier does not include Claude Code access at all. #### **How long does it take to turn one YouTube video into a blog post?** About five minutes from prompt to draft on a stable connection. Most of that is the transcript scrape and the screenshot extraction. A short review pass before publishing adds another five to ten minutes, so plan for fifteen total per post. #### **Which YouTube transcript scraper works inside Claude Code?** I use Blotato because it has an MCP server and reliable scraping on long videos. You can swap in other scrapers as long as they expose an MCP endpoint or a clean API. Without a working scraper, none of this runs. #### **Can Claude Code post directly to WordPress?** Yes, through the WordPress MCP. Claude Code creates the post as a draft, sets the featured image, assigns one category, fills in Yoast meta, and embeds the video. I never let it auto-publish. A human review pass protects you from low-quality drafts hitting the live site. #### **Does this workflow break Google's spam policies?** Not if you review every draft. Google penalizes mass-produced AI content with no editorial layer. This workflow gives you a fast first draft, but the human checkpoint before publishing keeps quality at a level Google rewards. --- ## The $1K AI Audit Business That Prints Money (Copy This) URL: https://ryandoser.com/ai-audit-business/ Markdown: https://ryandoser.com/ai-audit-business.md Published: 2026-05-11 | Updated: 2026-07-14 Categories: AI Rabbit Holes > Start an AI audit business and charge $1,000 per assessment. Copy Corey Ganim's 4-phase model for selling AI services to small businesses. The following article breaks down a simple **AI audit business** model anyone can copy, even with zero coding skills and only a few months of AI experience. ### **AI Audit Business Video Guide** I sat down with Corey Ganim on the AI Rabbit Holes podcast to unpack the exact model he uses to charge small businesses $999 for a 45-minute Zoom call plus a custom report. Watch the full conversation below. If you want more context on how AI is reshaping operations for owners, I put together a full [guide to AI for small business owners](/ai-for-small-businesses/) that pairs well with this model. It is also worth reading from the buyer's side, since the owners you pitch will be [vetting you against a checklist of their own](/ai-consultant-for-small-business/). This service works in any industry. Corey has run assessments for insurance agents, realtors, a barber school owner, a business brokerage, and an e-commerce pharmacy. The pain points change. The framework does not. ### **How the $999 AI Audit Actually Works** The model has four phases. Once you see them laid out, you will realize [Corey Ganim](https://www.youtube.com/@coreyganim) has stripped this down to something a beginner can run on day one. *The four-phase $999 model Corey walks through during the AI Rabbit Holes interview.* #### **Phase 1: The Discovery Call** You hop on a 45-minute Zoom with the owner. You ask questions designed to surface bottlenecks. Where does time disappear? What feels like it should be automated but is not? Which lead follow-up gaps cost deals? Corey runs a base question bank for any owner, then swaps in 5 to 10 tailored questions for their industry. After enough reps, you build libraries for realtors, insurance agents, and whoever else walks through the door. #### **Phase 2: The AI Analysis** Drop the call transcript into Claude. Ask it to surface 5 to 7 pain points and recommend off-the-shelf SaaS tools that fix them. Point Claude at directories like Futurepedia or There's An AI For That so it pulls from real tools that already exist. Then sanity-check the output. If Claude recommends Salesforce to a one-person shop, swap it for HubSpot or GoHighLevel. Claude does 80% of the heavy lifting and you handle the last mile. The audit also surfaces something you can sell next. Most owners are sitting on years of transcripts and documents nobody has organized, which is the opening for [building them a structured knowledge base](/ai-second-brain/) once the quick wins are installed. #### **Phase 3: The Report** Build an 8-page deliverable in Gamma or Claude design. Structure it with an executive summary, a priority matrix (high impact vs low effort), the actual tool recommendations with pricing and ROI, and a 4-day quick start plan the owner can run in 10 minutes per day. Corey open-sourced his exact template. Grab it free at [audittemplate.ai](https://audittemplate.ai) and use it as your starting point. #### **Phase 4: The Review Call** A 30-minute screen-share where you walk the client through the report. Explain each recommendation, show them how to install it, and answer questions. Then close with the upsell pitch. ### **AI Consultant Pricing and the Money-Back Guarantee** Here is the part most beginners skip. Pricing signals value. When Corey started, the assessments were free. Then $200. Then $500. Now $999, with plans to push to $2,000. *The $999 model with the 5-hours-per-week guarantee that makes the offer easy to say yes to.* The $200 clients got the worst results. They did not value the work, so they did not install anything. The $999 clients show up, take notes, and actually use the tools. Higher price filters for better clients. When a client wants ongoing help after the audit instead of a one-off assessment, that is [fractional Chief AI Officer](/fractional-chief-ai-officer/) territory. The offer also includes a guarantee. If Corey cannot find at least 5 hours per week of time savings within 30 days, the client gets 100% of their money back. He has never had to refund. The average client saves 6 hours per week, and the total tool cost averages $40 per month. That math is why this works. A business owner spending $1,000 to reclaim 24 hours per month is making the easiest decision of the year. ### **How to Sell AI Services to Small Businesses** The biggest limiting belief Corey hears is "I do not know enough about AI." His response is blunt. If you are 3 days ahead of your target client, you are qualified. Most owners are completely clueless about what AI can do. Use Claude. Read a few [posts on AI tools](/best-ai-marketing-tools/) each week. You are already top 1% compared to the local wedding venue operator or barber school owner who needs your help. Corey recommends doing your first one or two assessments free, then $200, then ramping. Get the reps. Build the question bank. Lock the report template. By the time you charge $1,000, the workflow runs itself. The most common bottleneck Corey finds in every audit, across every industry, is email. The #1 prescribed tool is Sanebox at $7 per month. It batches your inbox and saves most clients 1 to 2 hours per week. Sometimes that single recommendation pays for the audit by itself. ### **The AI Implementation Upsell That Makes the Real Money** The $999 audit is the front door. The real money is on the back end. During the report walkthrough, Corey asks 3 closing questions: - What is the most urgent opportunity here? - Do you want to set this up yourself or have someone do it for you? - What is your timeline? Around 60% of clients want help with setup. That triggers the upsell menu. Off-the-shelf SaaS tools fall in the high-impact, low-effort quadrant. Those go in the report. The high-impact, high-effort items (custom AI agents, automations, integrations) become upsell offers. The most common one Corey sells is a **speed to lead AI agent**. A wedding venue client had one salesperson doing tours all day. Leads came in at 9 a.m. but did not get a reply until 5 p.m. or the next day. By then, the prospect had already booked with a competitor. The speed to lead agent monitors their inbox via text and email, reads each lead's context, references venue FAQs, and books tours automatically. Two extra tours per month at an $11,000 average ticket equals $22,000 in new monthly revenue. If you do not want to build the work yourself, partner with a developer or agency. Corey takes a 10% referral cut on every project he hands off. He would rather make $1,000 referring a $10,000 build than spend 30 hours doing it for the extra $9,000. For a wider view of where this kind of productized service fits, read my breakdown of [the best ways to make money with AI](/best-ways-to-make-money-with-ai/). ### **Ryan's Final Thoughts** Corey Ganim cracked something most AI consultants miss. The product is not the AI knowledge. It is the personalized prescription. Anyone watching YouTube can list 10 AI tools. Almost nobody will sit with a business owner for 45 minutes and tell them exactly which 4 tools to install on Monday morning. If you are the business owner in this story rather than the consultant, that sit-down is what [my AI Concierge](/ai-concierge/) does every month. Start with one free audit this week. Use Corey's template. Build from there, and when owners want ongoing help, the [monthly coaching retainer Corey sells after the assessment](/how-to-start-an-ai-business/) is the next rung. ### **AI Audit Business FAQs** #### **How much can you charge for an AI audit?** Most beginners start in the $200 to $500 range to build testimonials. After 3 to 5 paid assessments, push to $999. It helps to know [what the wider AI consulting market charges](/ai-consultant-cost/), since that is the anchor your buyer is comparing you against. Corey is moving his model to $2,000 because higher prices filter for clients who actually take action. The bottleneck is not what the market will pay. It is the strength of your guarantee and case studies. #### **Do I need to be an AI expert to start an AI audit business?** No. If you are 3 days ahead of your target client, you are qualified to sell the service. Most small business owners have never used Claude or set up an AI tool. Knowing how to write a transcript prompt and prescribe tools like Sanebox already puts you ahead of 95% of the market. #### **What is a speed to lead AI agent?** It is an AI agent that monitors a business inbox for inbound leads, reads the context of each message, and replies in seconds with a tailored response trained on the company's FAQs and offerings. For service businesses like wedding venues or real estate, it can convert 30% to 40% more leads simply by responding before the competitor does. #### **What is the most common bottleneck found in AI audits?** Email. Across every industry Corey has audited, email is the #1 time suck. The most prescribed tool is Sanebox, a $7 per month AI inbox filter that batches messages by importance. Most clients save 1 to 2 hours per week from this single recommendation. #### **Where can I find Corey Ganim's work and the audit template?** Corey shares live builds and tutorials on his [YouTube channel and Build with AI podcast](https://www.youtube.com/@coreyganim). Follow him on [X](https://x.com/coreyganim) and [LinkedIn](https://www.linkedin.com/in/coreyganim/). His full breakdown with Chris Koerner is on the [Koerner Office podcast](https://youtu.be/03DjE7j0Suw), and you can grab the free [audit report template](https://audittemplate.ai) to use as your starting point. For more interviews like this, check out the [AI Rabbit Holes playlist](https://youtube.com/playlist?list=PLzJwubkSKclOQ2_v7NBRSXCx1lOUHFxxa). --- ## 5 AI Marketing Hacks That Actually Work in 2026 (No Hype) URL: https://ryandoser.com/ai-marketing-hacks/ Markdown: https://ryandoser.com/ai-marketing-hacks.md Published: 2026-05-06 | Updated: 2026-05-06 Categories: AI Tutorials, Claude Code > This guide covers AI Marketing Hacks I actually use in the real world. Five tactics for landing pages, blogs, social, scraping, and images. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* ### **AI Marketing Hacks Video Guide** Most AI marketing tips fall apart on real client work. I ran these five through paid projects for the past six months. They earned a permanent spot because they save real hours. I run all of this from Claude Code inside VS Code with a Codex sidebar for images. Claude Pro is $20 a month, Claude Max is $100. That is the only entry cost. If you want my full kit, the **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)** ships the skill files I use for SEO, social, thumbnails, and landing pages. ### **My Favorite AI Marketing Hacks in 2026** Here are the five plays I run every week to ship landing pages, blog posts, social campaigns, scraped intel, and thumbnails. #### **Hack 1: Vibe Code Landing Pages With a Web Designer Skill** You have probably shipped a landing page from a Stripe link and watched conversions tank. Better way: I built a web designer skill, a markdown file that acts as an SOP for AI on my typography, colors, and brand rules. Claude Code reads it and produces real pages I can ship. *The Claude Code Skills landing page I vibe coded in about 30 minutes using a custom web designer skill.* What I have built with this one skill: - A product page for the Skills Stack that did $3,500 plus four to five grand in consulting upsells in 30 to 45 days - A Google Ads page for a Des Moines client with a floating mobile call button - A dental IT lead gen page that pulled real data breach statistics on its own to drive conversions No skill yet? [Anthropic's official skills repo on GitHub](https://github.com/anthropics/skills) has a free front-end design skill. I fed it to Claude Code and asked it to repackage with my brand and colors. Do not paste a stock skill in and expect magic. Repackage with your context. Deeper walkthrough in my guide on [Claude Code for marketing](/claude-code-for-marketing/). Honest limit: this works for landing pages and static sites. For a CMS, blog, or member portal, stick with WordPress or Webflow. #### **Hack 2: Repurpose YouTube Videos Into SEO Blog Posts** Every video on my YouTube channel becomes a blog post on ryandoser.com. Not by hand. I built an SEO blog post writer skill that holds eight years of search marketing knowledge in one file: header hierarchy, internal and external links, keyword placement, the works. The flow: - Copy the YouTube URL into Claude Code - Call the skill and pass a target keyword plus 5 to 7 secondary keywords - Paste any external links from the video description The skill scrapes the transcript, runs competitive research, writes the draft, validates external links, uploads screenshots, and pushes a draft to WordPress from one prompt. Used to eat half a day. Now it takes 15 minutes of review. Skills are the unlock, not raw prompts. More on that in my [Claude Code skills hack post](/claude-code-skills-hack/). #### **Hack 3: Run Social Media From Claude Code With Blotato and Google Workspace CLI** Hootsuite, Sprout, Buffer, Metricool. Fine tools. Also expensive and slow when you want to schedule 30 days of posts in one shot. *My vibe coded AI Marketing OS shows scheduled posts pulled in from the Blotato API.* Two pieces make this work. First, the [Google Workspace CLI on GitHub](https://github.com/taylorwilsdon/google_workspace_mcp). Paste the repo URL into Claude Code and ask it to wire up the connection. Now the model can pull video files from a Drive folder, read transcripts, and turn them into captions. Second, [Blotato](https://www.blotato.com/?ref=rdoser): a $29 a month middleman API for every social platform. Connect it via MCP and Claude Code schedules posts to LinkedIn, X, Instagram, TikTok, YouTube Shorts, and Threads. My calendar is booked through June from a single chat session. Full setup in my [Blotato review](/blotato-review/). #### **Hack 4: Scrape Competitor LinkedIn Profiles With Apify** This is the one that keeps clients on retainer. Pick a creator whose LinkedIn engagement you respect. [Chris Koerner of The Koerner Office](https://www.youtube.com/@thekoerneroffice) is my go-to sparring partner. Steps: - Grab the LinkedIn profile URL - Open [Apify's actor library](https://console.apify.com/actors) and pick a LinkedIn scraper - Hand both URLs to a scraper skill in Claude Code, ask for the last 100 posts scored by engagement What comes back is a CSV with post URL, type, likes, comments, shares, engagement score, and full text. Then I ask Claude Code to read the last 30 days and report what hooks worked, where video beat text, and which angles to copy or kill. Full prompts in my [LinkedIn scraping in Claude Code post](/scrape-linkedin-profiles-claude-code/). Same play works on TikTok, Google Maps reviews, or YouTube transcripts. For a community where Chris and other operators trade plays like this, his [TKO Owners community](https://www.tkowners.com/?via=ryan) is worth a look. #### **Hack 5: Generate Thumbnails and Infographics Inside Claude Code** YouTube thumbnails used to mean Photoshop or paying a designer. Now my thumbnail designer skill calls GPT Image 2 and ships a 1280x720 in under a minute for 15 to 20 cents. *Codex generating a refreshed YouTube thumbnail using GPT Image 2 from inside VS Code.* Two paths work: - Claude Code with [OpenRouter](https://openrouter.ai/) as the API gateway. One key, every image and text model. Save it as APIs.env in your project root. - Codex in VS Code. GPT Image 2 is built in, so no API key juggling. The trick is reference assets. I keep folders of headshots and brand logos inside my skills directory. When I prompt "use main headshot right PNG and the Claude Code icon PNG," the model knows which files to load. No more AI faces that look almost like me. Same workflow runs for infographics and quick mockups. ### **Ryan's Final Thoughts** These five hacks share one pattern: a skill file holding the SOP plus a tool connected through MCP or API. Skills are the asset, tools are the muscle. Start with the SEO blog post writer. It pays for itself the first month. Pick one hack, ship it this week, and let it earn its spot before adding the next. ### **AI Marketing Hacks FAQs** #### **What are the best AI marketing hacks for solo operators in 2026?** Vibe coded landing pages, YouTube to blog repurposing, social scheduling, LinkedIn scraping, and AI image generation. Each kills a recurring task that used to cost hours or hundreds of dollars a month. #### **Do these AI marketing hacks require coding skills?** No. You only need VS Code and prompts in Claude Code, which is closer to ChatGPT than writing software. The skill files do the heavy lifting. #### **How much does it cost to run these AI marketing hacks?** Claude Pro at $20 a month is the entry point. Claude Max at $100 is what I run. Add Blotato at $29 and a small OpenRouter balance for images. Most months I spend under $150 total for tools that replaced thousands in software and freelance fees. #### **Which AI marketing hack should I start with?** Start with the YouTube to SEO blog post workflow. It compounds the fastest because every video becomes a ranking post. Once that flow is humming, layer in social scheduling, then the LinkedIn scraper. --- ## Did Cloudflare's New CMS (EmDash) Kill WordPress? URL: https://ryandoser.com/cloudflare-emdash-cms/ Markdown: https://ryandoser.com/cloudflare-emdash-cms.md Published: 2026-05-05 | Updated: 2026-05-05 Categories: AI Rabbit Holes > Cloudflare EmDash CMS is a new agentic, Astro-based WordPress alternative. Here's what it actually does and whether it's a real threat. The **Cloudflare EmDash CMS** just launched as an open-source, agent-first WordPress alternative built on Astro. I sat down with SEO expert [Nesil Ozer](https://www.youtube.com/@NesilOzer) to break down what it actually does and whether WordPress should be worried. ### **What the Cloudflare EmDash CMS Actually Is** What if WordPress's biggest weakness finally got a real answer? That's the pitch behind EmDash. EmDash is a new [open-source CMS from Cloudflare](https://blog.cloudflare.com/emdash-wordpress/), written in TypeScript and built on [the Astro web framework](https://astro.build/). Cloudflare acquired Astro earlier this year, so the foundation was already in place. The headline reason it exists: fix what's broken in WordPress. Plugin security. Slow performance on a 23-year-old codebase. And one more thing nobody talks about, which is that WordPress was never designed for AI agents. My breakdown of [Claude Code for SEO](/claude-code-seo/) covers the same shift from a production angle. ### **Why EmDash Is Built for AI Agents First** You've probably tried wiring an AI agent into your WordPress site. It works, but it's a mess of third-party plugins and security workarounds. EmDash flips that. It ships with a built-in MCP server, a CLI, and Agent Skills so tools like Claude and ChatGPT can edit content, upload media, and adjust schemas directly. Plugins run in sandboxed Worker isolates, so one bad plugin can't compromise the whole site. EmDash also stores content differently. Title, body, and images each live in their own slot. That structure lets an LLM pull specific fields without crawling the entire page, which matters more as AI search keeps eating into Google traffic. *The EmDash admin dashboard showing the posts view, with a layout that feels familiar to WordPress users.* ### **EmDash vs WordPress: The Honest Comparison** You've spent years inside WordPress. Switching feels like a tax. Here's how the two stack up right now. | Feature | WordPress | EmDash | | Plugin security | Shared runtime, full data access | Sandboxed Worker isolates | | Built for AI agents | No, requires third-party plugins | Yes, native MCP, CLI, Skills | | Hosting model | Server-based | Serverless on Cloudflare Workers | | Maturity | 23 years, ~40% of the web | MVP, two months old | | Plugin ecosystem | Massive | Almost none yet | | WordPress import | N/A | Yes, built-in | WordPress still wins on community size, plugin depth, and team workflows. The Cloudflare EmDash CMS wins on architecture and agent compatibility. Most teams reading this should not migrate today. EmDash is a clear MVP, plugins are not there yet, and editorial workflows for groups of writers are a real gap. ### **The Yoast Founder Just Bet on EmDash** Here's a fact that surprised me. Joost de Valk, founder of the Yoast SEO plugin and a 15-year WordPress veteran, is now [building his next plugin on EmDash](https://joost.blog/emdash-cms/). His argument is direct: WordPress keeps shipping new features without fixing the core issues, and the window to fix them is closing. When the most-downloaded SEO plugin author in WordPress history says that out loud, the signal carries weight. [Nesil](https://www.linkedin.com/in/nesilozer/) agreed on the call. "This story is too big," he said. One defection from a niche developer is noise. A defection from the author of the plugin most WordPress sites run is a different kind of news. *EmDash includes a built-in WordPress import flow, which removes one of the biggest friction points for testing it.* ### **You Might Not Even Need a CMS Anymore** Here is the part I find most interesting, and it goes beyond EmDash. Nesil and I are working on a project where we ditched the dashboard entirely. The site lives as Markdown files in a GitHub repo. Claude Code edits the files. Vercel or Cloudflare deploys the changes live. No CMS at all. EmDash supports this same workflow. Drafts are Markdown files you can edit through Claude Code and push live without opening the admin panel. For solo operators, that removes a layer most teams take for granted. This will not work for every team. If five writers need to review drafts back and forth, you still need a CMS in the middle. For solo entrepreneurs and consultants, the Markdown plus Git plus AI agent stack is genuinely faster than logging into WordPress. I lay out the full case for that stack, including where WordPress still wins, in [my post on the death of WordPress for solo marketers](/wordpress-alternative/). ### **Honest Caveats on EmDash Today** EmDash has real gaps. The plugin system Cloudflare promised does not exist yet. Themes are bare. Editorial workflows for teams are missing. The dashboard looks polished but the ecosystem behind it is essentially empty. Lovable, Replit, and Base44 are not the answer either. They render content client-side with JavaScript, which means AI crawlers from ChatGPT and Perplexity get back almost nothing. Zero citations. Same reason I tell people to [avoid AI slop](/avoid-ai-slop/) when scaling content. For most readers, the right move today is to stay on WordPress and watch EmDash quarterly. ### **Ryan's Final Thoughts** WordPress is not dead. It powers 40% of the internet and the community is enormous. But the Cloudflare EmDash CMS is the loudest wake-up call WordPress has gotten in a decade. The Yoast founder defection alone should make the WordPress core team uncomfortable. If plugins ship and editorial workflows mature, the calculus changes fast. For now, run a test site on EmDash, keep your real site on WordPress, and learn the new stack before you need it. Subscribe for more [AI Rabbit Holes episodes](https://youtube.com/playlist?list=PLzJwubkSKclOQ2_v7NBRSXCx1lOUHFxxa) covering tools like this one. *Nesil Ozer joining the AI Rabbit Holes episode to break down EmDash and what it means for SEO in 2026.* ### **Cloudflare EmDash CMS FAQs** #### **What is the Cloudflare EmDash CMS?** EmDash is Cloudflare's new open-source CMS, built on Astro and TypeScript as an agent-first alternative to WordPress. It runs serverless on Cloudflare Workers, sandboxes every plugin in an isolated Worker, and ships with native MCP and CLI support for AI agents to manage content directly. #### **Is EmDash a real WordPress alternative in 2026?** Not yet for most teams. EmDash is currently an MVP with no plugin ecosystem and weak editorial workflows for groups. Solo operators and developers can use it today. Most WordPress sites should keep watching it for two to three quarters before considering a migration. #### **How is EmDash different from headless CMS options?** EmDash is closer to a hybrid. It provides a familiar dashboard like WordPress but stores content as discrete fields LLMs can pull selectively, ships with native MCP and Agent Skills for AI tools, and runs serverless on Cloudflare. Most headless CMS platforms predate this AI-agent layer and require custom integration to match it. #### **Can I import my WordPress site into EmDash?** Yes. EmDash includes a built-in WordPress import feature in the admin panel. You enter your WordPress site URL or upload an XML export and it pulls posts, pages, and custom post types into EmDash. The feature is new, so test it on a staging site before trusting it for a production migration. #### **Should I switch from WordPress to EmDash today?** For most sites, no. WordPress still has the larger community, deeper plugin ecosystem, and proven team workflows. EmDash is worth a test install on a non-critical project to learn the architecture. Revisit the decision once plugins ship and editorial features mature later in 2026. --- ## Why Most AI Marketing Advice is Wrong (What You Should Do Instead) URL: https://ryandoser.com/ai-marketing-advice/ Markdown: https://ryandoser.com/ai-marketing-advice.md Published: 2026-04-30 | Updated: 2026-04-30 Categories: AI Tutorials, Claude Code > Most AI marketing advice tells you to chase volume and tools. Here is the contrarian approach I actually use to win in 2026. Most **AI marketing advice** floating around right now tells you to crank out more posts, chase every new tool drop, and let automation do the thinking. That advice is backwards, and this article explains the approach I actually use to win in 2026. ### **What Good AI Marketing Advice Looks Like in 2026** You've been told volume is the answer. Write 100 blog posts. Schedule 100 social posts. Let AI fill the gap. The problem is that volume is now free. AI can spit out a million blog posts in a minute, which means it does not move the needle anymore. I sat down with [Audrey Chia](https://www.linkedin.com/in/audrey-chia/) on her podcast, The AI Marketers Playbook, to talk through this. She runs [Close With Copy](https://closewithcopy.co/) and helps brands convert through positioning and strategy. We agreed: most AI marketing tips for beginners push the wrong direction. Quality and subject matter expertise are the new edge. AI slop is everywhere, and readers switch off the second they smell it. The best AI marketing advice for business owners is to stop optimizing for output and start optimizing for trust. Smaller pile of content. Real opinions. Real numbers. Real first-hand testing. *Inside Claude Code with skill markdown files for blog writing, social posts, and landing pages.* ### **The Wrong AI Marketing Advice You Should Ignore** Open YouTube and search any AI keyword. You'll see the same playbook on repeat. Five best AI tools for this. Ten insane AI tools I tested (even though they didn't). New model dropped, here's a hype video. That's not advice. It's a treadmill built to keep you clicking. If you [consume 100 AI hype videos a week](/ai-anxiety/), you're falling behind, not catching up. The people winning right now are the ones quietly testing tools in their own business while everyone else watches reaction content. The wrong AI marketing advice I see most often: - Pump out daily posts on every platform - Chase the newest model the day it drops - Hide behind your company logo instead of building a personal brand - Pick tools first, then look for problems to solve with them - Treat AI like a magic content button instead of a thinking partner Each one trains you to react instead of build. For more, see my breakdown of [how to avoid AI slop in your content](/avoid-ai-slop/). ### **The Best AI Marketing Advice for Small Business Owners** Start with the problem, not the tool. This is the one piece of AI marketing strategy advice I give every business owner who asks me where to begin. My [90-day implementation plan](/how-to-implement-ai-in-business/) turns that into a week-by-week sequence. Open a notes doc. Write down every task that eats 5, 10, or 15 hours a week. Lead follow-up. Content repurposing. Reporting. Inbound replies. That list is your real AI roadmap. Tools come and go. Problems stay. From there, pick one workflow and rebuild it with AI. Don't try to automate everything in week one. One workflow done well beats ten half-built ones. Two examples I shared with Audrey: - **Content repurposing.** Sit down once a week and record a 30-minute long-form video. Use AI to turn the transcript into a blog post, an email, social posts, and short clips. [One recording feeds the whole week](/ai-content-engine/). - **Lead follow-up.** Most lead gen businesses still email leads by hand. AI handles drip sequences, qualification questions, and follow-ups while you sleep. This alone can pay for the rest of your AI stack. If you want a full walkthrough of the tools I actually use, my breakdown of the [AI marketing stack I run every day](/ai-marketing-stack/) covers it. *My YouTube channel where keyword-driven videos consistently outperform hype content.* ### **AI Marketing Advice for Entrepreneurs Who Aren't Technical** "Ryan, I'm not technical. Can I still use this stuff?" Yes. I wasn't technical either. The first time I heard "terminal" and "code" I checked out for a year, then I stopped using that as an excuse. If you can write a prompt, you can run Claude Code. The interface looks scary for 20 minutes. After that, it feels like chatting with a teammate who happens to ship work for you. I spend eight to ten hours a day inside it. The path for a non-technical marketer in 2026: - Start in the Claude web app. Learn projects and skills there first. - Skip Claude Code wrapper tools if you're solo. Go straight into the real thing. - Pick one workflow you do every week. Build a skill markdown file for it. - Iterate that skill for a month before adding a second one. Marketers who learn an AI coding agent like Claude Code or Codex right now sit in the top 1%. That window will not stay open forever. For the full setup, see my guide on [how to use Claude Code as a marketer](/claude-code-for-marketing/). ### **AI Marketing Mistakes to Avoid Right Now** We're living in what I call the trust recession. People read something, watch something, and immediately ask if a real person made it. The default assumption is now skepticism. Brands hiding behind a logo are losing ground. The ones putting a face out front are winning. AI marketing mistakes to avoid if you want to stay on the right side of that shift: - Cloning yourself with HeyGen and pretending it's you on camera - Letting AI write LinkedIn posts in its default voice - Renting all your distribution on social and never building an email list - Treating AI as a replacement for thinking instead of a multiplier on it Show up on video. Say things you actually believe. Use AI to repurpose your real words, not to generate fake ones. I covered this in my piece on [personal branding for founders](/personal-branding-for-founders/). *The ryandoser.com blog where every YouTube video gets repurposed into a long-form article.* ### **Ryan's Final Thoughts** Most AI marketing advice rewards effort that no longer matters. Volume is free. Hype is free. Slop is free. What's rare in 2026 is a real person with real opinions doing real testing and publishing the results. Distribution beats everything else in marketing, and owned distribution beats rented distribution. Email and phone numbers beat algorithms because no one can take them away from you. Pick one channel, solve one real problem with AI, and put your face on it. The marketers doing this now will own the next five years. Picking that one problem and setting up the fix together is the agenda of every [AI Concierge call](/ai-concierge/) I run. For more, see the [official Claude Code documentation](https://docs.claude.com/en/docs/claude-code/overview) or my walkthrough of [Claude Code SEO automation](/claude-code-seo/). ### **AI Marketing Advice FAQs** #### **What is the best AI marketing advice for business owners in 2026?** Start with a problem, not a tool. List the tasks eating 10+ hours a week and ask which AI can shorten. Pick one workflow, rebuild it with AI, then move to the next. Tools change every month. Workflows you understand stay valuable for years. #### **What AI marketing mistakes should small businesses avoid?** Chasing volume, hiding behind your logo, and renting all your distribution on social. Volume is free now and worthless without quality. Hidden brands lose to brands with a real face. Rented audiences disappear when an algorithm changes. Build owned channels like email alongside any social play. #### **Should marketers really learn Claude Code in 2026?** Yes, if you want an edge. Marketers who know how to use Claude Code or Codex are in the top 1% right now. The skill compounds, the learning curve is short, and most of your competition is still hiding behind "I'm not technical." --- ## My AI Social Media System: 30 Days of Posts in 15 Minutes URL: https://ryandoser.com/ai-social-media-system/ Markdown: https://ryandoser.com/ai-social-media-system.md Published: 2026-04-27 | Updated: 2026-08-01 Categories: AI Tutorials, Claude Code > My AI Social Media System uses Claude Code, Blotato, and a video editor to ship 30 days of social media posts in only 15 minutes. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* ### **How My AI Social Media System Actually Works** Most "AI social media" tutorials end with content nobody opens. Mine ends with posts that pull 4,200 impressions on LinkedIn, 2,700 on a separate one, and around 1,000 daily views on YouTube Shorts. The unlock is not a magic prompt. It is the combination of three tools working together. The stack is simple. [Blotato](https://blotato.com/?ref=rdoser) handles scheduling and posting at $29 a month, which beats Buffer or Hootsuite at scale (I compared it with Buffer properly in [Blotato vs Buffer](/blotato-vs-buffer/)). Claude Code runs the writing through a custom skill markdown file. A short-form editor (human or [Opus Clip](https://www.opus.pro/)) chops long-form videos into clips. Three tools. Zero glue code. I tested five more before settling on these, and the full comparison is in my [social media automation tools roundup](/social-media-automation-tools/). *Kicking off the system with a Claude Code prompt that pulls in three YouTube transcripts.* ### **The Claude Code Social Media Workflow Step by Step** You have probably tried writing posts one at a time and burned an hour for two okay drafts. This workflow batches everything in one Claude Code session. I open a fresh Claude Code chat inside Visual Studio Code with my Ryan Doser social media skill markdown loaded. The first prompt asks for 20 text posts split between LinkedIn and X, optimized per platform, based on three recent [AI Rabbit Holes podcast](/best-ai-marketing-podcasts/) episodes. Claude Code transcribes the videos, finds the strongest moments, and writes the posts. The second chat handles short-form. I tell Claude Code to write captions for 10 short clips sitting in a Google Drive folder, optimized for YouTube Shorts, Instagram, and TikTok. Captions stay short, hashtags get added, and the file links come straight from Drive. Two prompts. Thirty posts. A few minutes of compute. ### **Connecting Google Drive and Blotato MCP to Claude Code** The piece that makes this fast is the MCP layer. Without it, you are copying captions into a scheduler by hand. For Drive access, I use the official [Google Workspace CLI](https://github.com/googleworkspace/cli) from GitHub. I dropped the repo URL into Claude Code, ran the auth flow, and Drive was readable inside my chats. For posting, I follow the [Blotato MCP setup guide](https://help.blotato.com/api/mcp/setup). Once that is connected, Claude Code can list my accounts, create posts, and assign dates without leaving the terminal. If you want a deeper read on why I run this stack, my breakdown of [Claude Code for social media](/claude-code-social-media/) covers the why behind the tooling choice. *A batch of LinkedIn posts produced by the system, each opening with a one-sentence hook.* ### **Reviewing the Drafts Before You Schedule** Only 12% of marketers actually review AI drafts before posting, in my experience watching teams ship slop. Do not skip this part. Strong LinkedIn and X posts live or die on the first sentence. I read each draft for a single hook line that drives emotion, like "AI doesn't replace entry-level marketers. It reshapes them." If the hook lands, the post stays. If it does not, I rewrite or cut. Short-form captions get a different read. I check the hashtags are search-relevant, not random tags, since hashtags still matter on TikTok, Instagram, and Shorts. Pros of this step: catches off-tone drafts before your audience does. Cons: adds 10 minutes. Worth it. The skill markdown improves over time as I add corrections. The next batch is always sharper than the last. ### **Batch Scheduling Across Platforms with One Prompt** Here is where 30 posts go from a doc to a calendar in under a minute. I tell Claude Code which posts to schedule, which accounts to send them to, and which dates and times to use. Example: "Schedule out XP15 through XP20 on my Ryan Doser X account for June 8th through June 12th, 2026 at 8 AM US Central." Claude Code calls the [Blotato](/blotato-review/) MCP, looks up the right account ID, and creates each scheduled post. For the short-form videos, I name the clips I like (captions 2, 5, 6, 8, 10) and give the same date range across YouTube, Instagram, and TikTok. Claude Code grabs the media URLs from Drive, attaches them, and schedules across all three. I refresh Blotato and the content calendar already shows June 8th through 12th filled in. *Claude Code calling the Blotato MCP to schedule X posts onto the content calendar.* ### **Ryan's Final Thoughts** This system is not a one-prompt miracle. The first run takes longer because you are reviewing output and tightening the skill file. By run three or four, 30 days of posts genuinely take 15 minutes. The compounding piece matters most. A LinkedIn post hitting 4,200 impressions, a Short doing 1,000 views a day, captions reused across three platforms. That stacks. If you already have long-form content sitting unused, this is the fastest way I have seen to put it back to work. I also packaged the repurposing half of this as the [**AI Content Engine**](https://engine.ryandoser.com/), for anyone who wants the week of posts without writing the skill files first. If you do not have a back catalog to repurpose yet, the other approach I run is [recording unscripted takes on a walk](/post-consistently-with-ai/) and letting the same tooling publish them. ### **AI Social Media System FAQs** #### **How long does the AI Social Media System actually take?** The first run takes 30 to 45 minutes because you are reviewing every draft and refining the skill file. Once the system is dialed in, generating and scheduling 30 days of posts runs in roughly 15 minutes. The time savings come from batching prompts, reusing existing video transcripts, and letting the Blotato MCP handle scheduling. #### **Do I need Claude Max to run this?** No. Sonnet 4.6 on the $20 a month Claude plan handles this workflow. Opus 4.7 will burn through the $20 plan quickly, so the $100 a month Max plan is the right fit if you want Opus for sharper writing. Start with Sonnet and upgrade only if you hit limits. #### **Can I run this without a video editor?** Yes. Opus Clip and similar AI clipping tools turn long-form videos into short-form clips automatically. I compared the main ones, and explained why I still keep a human editor, in [this breakdown of the clipping tools](/opus-clip-alternatives/). The captions and scheduling parts of the workflow stay identical. The only swap is who or what creates the clips before they hit your Google Drive folder. You can also drive the clipping straight from Claude Code by [connecting Opus Clip as an MCP server](/opusclip-mcp/). #### **What does the Blotato MCP actually do?** The Blotato MCP connects Blotato to Claude Code so the model can list your social accounts, create posts, attach media, and schedule on dates and times you specify. Without it, you would copy captions from Claude Code into Blotato by hand. With it, the whole flow stays inside one chat window. --- ## Why Every Business Owner Should Use Claude Code (New Interview) URL: https://ryandoser.com/claude-code-for-business-owners/ Markdown: https://ryandoser.com/claude-code-for-business-owners.md Published: 2026-04-24 | Updated: 2026-09-30 Categories: Claude Code > A recent podcast interview I was on sharing why every business owner should use Claude Code. Full marketing workflows explained. **Claude Code for business owners** is the shortcut most non-technical founders keep missing. I sat down with [Olivia Mansion on the Leading AI Agents podcast](https://www.linkedin.com/in/olivia-mansion/) to walk through exactly how I use it to run my marketing. ### **How Claude Code for Business Owners Actually Works** You've probably heard someone call Claude Code a "developer tool" and moved on. That is the mistake. I am one of the least technical marketers you will meet, and Claude Code runs most of my content engine now. In the episode, I share my screen and build real assets live with Olivia. SEO blog posts pulled from YouTube videos, landing pages for clients, a custom notes app, and a Google Drive backup system that runs daily. All of it sits inside one tool. If you want to go deeper on the stack I reference, I put together a full **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)** with the workflows and templates I actually run my business on. ### **The One Skill That Replaced My Content Team** Short version: I drop a YouTube URL into Claude Code, call my SEO blog post writer skill, and 5 to 10 minutes later I have a publish-ready post sitting as a draft in WordPress. Screenshots pulled from the video, internal links from my sitemap, external links, featured image, meta description, slug. No agency. No freelancer. The same pattern I describe in my deeper breakdown of [Claude Code SEO workflows](/claude-code-seo/). A skill is a folder built around one markdown file, SKILL.md. Think of it as an SOP for an AI agent. Instead of "write me a blog post, go," I hand Claude a recipe with every rule I care about. Voice, headings, banned words, word count, link placement. Consistent output every time. *My SEO blog post writer skill open in VS Code, acting as the SOP Claude Code follows on every article.* This is why **Claude Code for entrepreneurs** is such a big deal. You are not prompting a chatbot. You are hiring a junior employee with a written playbook and admin-level rules for what it is allowed to do. ### **Why Non-Technical People Freeze (and How to Get Past It)** I hear the same thing from almost every business owner in my community. They see the word "code" or "terminal" and they shut down. I did the same thing at first. The fix is Visual Studio Code. It is a free Microsoft app that gives you a visual wrapper around the terminal. I installed the Claude Code extension, added a few skill files, and started experimenting. Every time something broke, I learned. That is the whole curve. If you want the gentler on-ramp, I wrote a full guide on [AI for non-coders](/ai-for-non-coders/). Here is the setup I recommend for **Claude Code for non-technical people**: - A paid Claude plan (Pro at $20 or Max at $100 if you use it daily) - VS Code with the Claude Code extension installed - Sonnet 4.6 as the model, with extended thinking turned off to save tokens - One or two skill markdown files to start Once you are in, going back to a web app like Claude.ai or ChatGPT feels slow. The context, the files, the MCP connections, the skills. It all compounds. ### **Real Results With No Backlink Authority** I showed Olivia my Ahrefs profile on the podcast for a reason. Ryandoser.com has almost no backlink profile. No DR campaign. No link outreach. Yet the posts Claude Code produces are ranking in Google and showing up in AI Overviews. *Search Console data for ryandoser.com after running the Claude Code SEO workflow on YouTube repurposing.* Search "how to scrape LinkedIn profiles with Claude Code" and I rank. Search "best AI marketing communities" and I show up in the AI Overview. Vanity wins for now, but compounding weekly. My honest take: most AI content is slop. I will not pretend otherwise. But a post written with Sonnet 4.6, a tight skill file, real screenshots, and a subject matter expert at the wheel beats the average Fiverr writer. ### **What Business Owners Can Actually Build** The SEO workflow is the headline, but it is not the only use case. In the interview I walk through a landing page I built for a local client, Tire Heroes. I paid $10 for the domain on Cloudflare, pointed a Claude skill at their existing site, and the agent scraped colors, copy, and brand voice. Mobile-first page, floating call button, real conversions. I go deeper on this pattern in my [Claude Code for marketing](/claude-code-for-marketing/) breakdown. *Claude Code finishing a blog post draft and saving a local archive copy after publishing to WordPress.* Other things I run inside Claude Code: - A Google Drive backup script that runs every day - A custom notes app that replaces Obsidian for me - A social media manager skill that schedules posts via Blotato - A marketing dashboard pulling from a Google Sheet Before Claude Code I paid for 5 to 10 AI tools. Most were wrappers charging a premium for cheap models under the hood. ### **How to Use AI for Business Growth Without Getting Lost** My advice for employees and CEOs is the same. Start with the task you hate most. Research, data entry, social scheduling, repetitive email replies. Then ask AI how to automate it. If you are stuck, open a voice dictation tool, brain-dump your week, and let Claude draft a plan. The people winning with **AI marketing workflows for CEOs** are not the most technical. They have subject matter expertise and a willingness to iterate. Pair your expertise with the right tool and you are tough to beat. If you want a shortcut, my [Claude Code skills hack](/claude-code-skills-hack/) post shows how I structure each skill so it works the first time. ### **Ryan's Final Thoughts** Claude Code is not a dev tool anymore. It is the operating system most business owners should be running their marketing on, and it leads my roundup of the [top AI coding tools for 2026](/best-ai-coding-tools/). Start with one skill. Let it fail. Keep refining. The compounding is real. Watch the full interview with Olivia above, then grab my skills stack and start building. And if you would rather have a real person set it up with you than figure it out alone, that is exactly what my [AI Concierge](/ai-concierge/) is for. ### **Claude Code for Business Owners FAQs** #### **Do I need to know how to code to use Claude Code?** No. I am not technical and I run my entire marketing operation inside Claude Code. The key is using skill markdown files as written SOPs. If you can describe the task in plain English, you can build a skill for it. VS Code gives you a visual wrapper so you never have to live inside a terminal. #### **How much does it cost to run Claude Code for a business?** Claude Pro at $20 per month is enough to test it. Most business owners who use it daily move to Claude Max at $100 per month. That single subscription has replaced 5 to 10 AI tool subscriptions for me, so the net cost is often lower than the stack you are running. #### **Is content written by Claude Code considered AI slop?** Most AI content is slop because people prompt once and ship. Content written with Sonnet 4.6, a detailed skill file, real screenshots, and a subject matter expert reviewing it is not. My posts rank in Google with almost no backlink authority, which is the clearest signal that quality is holding up. #### **Where should a non-technical business owner start?** Install VS Code, add the Claude Code extension, get a paid Claude plan, and start with one skill for one repetitive task. Watch the Leading AI Agents interview above. Then visit my [YouTube channel](https://www.youtube.com/@RyanDoserAI) and [AI Marketing Insiders community](https://www.skool.com/ai-marketing-insiders). --- ## ChatGPT Images 2.0 is Here: Better Than Nano Banana? URL: https://ryandoser.com/chatgpt-images-2-0/ Markdown: https://ryandoser.com/chatgpt-images-2-0.md Published: 2026-04-22 | Updated: 2026-04-22 Categories: AI News, ChatGPT > ChatGPT Images 2.0 is here. I tested OpenAI's new image model on thumbnails and infographics against Nano Banana 2. Here's my honest take. OpenAI just shipped **ChatGPT Images 2.0**, and after testing it against Google's Nano Banana 2 on real business work, I think the balance has finally shifted. ### **OpenAI's New ChatGPT Images 2.0 Model** What if the model everyone else is chasing just got leapfrogged? That was my first reaction after running the new OpenAI image model through real YouTube thumbnails, branded infographics, and photorealistic tests. If you want to go deeper on how I build image workflows like this into my AI stack, I put together a free resource with my Claude Code skills, automation templates, and systems. Grab the **[AI Marketing Essentials Guide](/ai-marketing-guide/)** to follow along. The ChatGPT Images 2.0 model is available to free users inside ChatGPT, but advanced outputs with thinking require Plus, Pro, or Business. Inside the web app, click the plus icon, choose create image, then open the dropdown in the top left to pick standard or extended thinking. That thinking toggle is new for image work, and it matters for anything complex like infographics or thumbnails. *ChatGPT Images 2.0 rendering a clean photorealistic skyline with no visible watermark.* ### **Pricing: Why the New OpenAI Image Model Is 40% Cheaper** Here is a stat that caught me off guard. OpenAI GPT Images 2.0 runs about 4 cents per image. Gemini 3.1 Flash Image, also known as Nano Banana 2, runs closer to 7 cents per image. That is roughly 40% cheaper for the OpenAI model on standard calls. Batch processing flips the math. Nano Banana 2 gets cheaper than the OpenAI standard rate when you run large batches, but most marketers I talk to never touch batch mode. For one-off thumbnails, ad creative, and infographics, OpenAI wins on price. If you want to check the current rate card yourself, here is the [OpenAI API pricing page](https://openai.com/api/pricing/). And for independent ranking, the [LLM Arena text-to-image leaderboard](https://arena.ai/leaderboard/text-to-image) currently has GPT Image 2 sitting at number one, above both Nano Banana models. ### **Where ChatGPT Images 2.0 Actually Beats Nano Banana 2** Only 12% of AI image tools produce output I would send to a paying client without edits. The new OpenAI image model is one of them, and here is where it pulled ahead in my testing. Infographics with real branding. I uploaded my logo and a blog URL, asked for an on-brand infographic, and the first pass was usable. A quick follow-up prompt to tighten the text and keep the logo in one spot produced something I would actually share. Previous OpenAI image models could not do this cleanly. *An on-brand infographic built from one blog URL and a logo upload in two prompts.* No visible watermark. Every Nano Banana output still carries a watermark in the bottom right. Yes, you can strip it in Photoshop or Canva, but that is an extra step every time. The new OpenAI image model only embeds an invisible marker, so images ship ready. Invisible provenance marks are becoming standard across every lab, and I explained what that means for your content in my breakdown of [Anthropic watermarking Claude outputs](/claude-watermark/). YouTube thumbnails that look like a designer made them. I gave it one of my existing thumbnails, asked it to swap the text and update the background for the new OpenAI model, and the result was crisp. I then AB tested a version with a headshot replacement and the output was on par with paid designer work. ### **ChatGPT Images 2.0 vs Nano Banana 2 on the Same Prompt** Here is the honest side-by-side. I ran the same thumbnail prompt in Gemini Pro with Nano Banana 2 and in ChatGPT with the new image model. Gemini reused the original imagery, added a Nano Banana watermark, and missed the AB test variation when I uploaded a second headshot. *Nano Banana 2 reused the source imagery, added a watermark, and struggled with the AB test request.* ChatGPT Images 2.0 followed the brief, changed the background to something that actually fit the topic, and produced a second variation I would genuinely AB test on my channel. If you want to see the full walkthrough, here is the [OpenAI ChatGPT Images 2.0 demo](https://www.youtube.com/live/sWkGomJ3TLI). ### **How to Use the New ChatGPT Images Model in Your Workflow** You have three realistic access points for the new OpenAI image model: - ChatGPT web app, free or paid, with thinking toggles on Plus and above - OpenAI API directly, with full pricing on the [official ChatGPT Images 2.0 page](https://openai.com/index/introducing-chatgpt-images-2-0/) - [OpenRouter](https://openrouter.ai/openai/gpt-5.4-image-2) as a middleman, which is what I use so one API key unlocks every model The OpenRouter route is what I recommend for anyone running Claude Code. You get a single key, you can swap models per task, and you can plug the image model into a skill markdown file. My [Claude Code OpenRouter setup guide](/claude-code-openrouter/) walks through that connection step by step. From there, build a skill that takes a YouTube URL or a blog post and spits out an on-brand infographic or thumbnail. Pair this with my [Claude Code social media system](/claude-code-social-media/) and you have a pipeline from video to published post with real images attached. One caveat. The new OpenAI image model still struggles with fine text inside dense infographics on the first pass. Budget for one or two follow-up prompts per asset. ### **Ryan's Final Thoughts** ChatGPT Images 2.0 is the first OpenAI image release that pushed me to change a workflow. Nano Banana 2 was my default for thumbnails and infographics. This one is cheaper, cleaner, and produces output that looks designed instead of generated. I am moving my thumbnail and infographic work to this model inside Codex and OpenRouter, and I will only go back to Nano Banana 2 if Google ships a real answer. If you have tested it, drop your take in the YouTube comments. ### **ChatGPT Images 2.0 FAQs** #### **Is ChatGPT Images 2.0 free to use?** Yes, free ChatGPT users can generate images with the new OpenAI image model. Advanced outputs with standard and extended thinking are limited to Plus, Pro, and Business accounts. That thinking toggle is the key upgrade for infographics and YouTube thumbnails, so most serious users will want at least a Plus plan. #### **How does ChatGPT Images 2.0 compare to Nano Banana 2 on price?** The new OpenAI image model runs about 4 cents per image on the standard rate. Nano Banana 2, also known as Gemini 3.1 Flash Image, runs around 7 cents. That makes GPT Image 2 roughly 40% cheaper for one-off generations. Nano Banana 2 only gets cheaper when you run heavy batch processing. #### **Can I use the new OpenAI image model through an API?** Yes. You can call it directly through the OpenAI API, or route it through OpenRouter with a single key that also handles other models. OpenRouter is the cleanest path if you are already running Claude Code or Codex and want one setup that works across every provider. #### **Does ChatGPT Images 2.0 add a visible watermark?** No visible watermark. OpenAI embeds an invisible marker, but the output ships clean. That is a meaningful workflow win over Nano Banana 2, which still stamps a visible Gemini watermark in the bottom right of every image and forces an extra removal step before publishing. --- ## Anthropic Launches Claude Opus 4.7 (Best AI Model Yet) URL: https://ryandoser.com/claude-opus-4-7-model/ Markdown: https://ryandoser.com/claude-opus-4-7-model.md Published: 2026-04-16 | Updated: 2026-04-16 Categories: AI News, Claude Code > Claude Opus 4.7 brings major upgrades to coding, vision, and agentic tasks. See the full benchmarks, key features, pricing, and more. Anthropic just released **Claude Opus 4.7**, the latest flagship model in the Claude family. The upgrade hits hardest in coding, vision, and long-running agentic tasks. Here is everything you need to know about what changed and why it matters. ### **What Is Claude Opus 4.7?** Claude Opus 4.7 is Anthropic's most capable model to date, launched on April 16, 2026. It replaces Opus 4.6 as the top-tier option across Claude.ai, the Claude API, Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Foundry. The model ID is `claude-opus-4-7`. The headline improvements land in three areas: software engineering consistency, visual understanding, and instruction following. Anthropic describes the model as showing "rigor and consistency" on complex assignments while "paying precise attention to instructions." Early testers back that up with specific numbers, which I will get to in a moment. If you are already using Claude for coding or content work, this is the upgrade that makes agentic workflows feel production-ready rather than experimental. For context on how Claude fits into the broader AI model landscape, see my breakdown of [Claude Mythos](/claude-mythos/), the security-focused model Anthropic announced earlier this month. ### **Claude Opus 4.7 Benchmarks and Performance** The numbers tell the story better than any marketing copy. Here is where Opus 4.7 lands relative to its predecessor and the competition. *Claude Opus 4.7 leads or ties across nearly every benchmark category compared to Opus 4.6, GPT-5.4, and Gemini 3.1 Pro.* The full benchmark table paints the clearest picture. On SWE-bench Pro, Opus 4.7 hits 64.3% versus 53.4% for Opus 4.6 and 57.7% for GPT-5.4. SWE-bench Verified reaches 87.6% compared to 80.8% for Opus 4.6. Agentic terminal coding on Terminal Bench 2.0 lands at 69.4% versus 65.4% for the previous model. Finance benchmarks hit state-of-the-art with 64.4% on Finance Agent v1, ahead of GPT-5.4 at 61.5%. Graduate-level reasoning on GPQA Diamond scores 82.1% versus 69.1% for Opus 4.6. Visual reasoning on ChartQA Reasoning reaches 91.0% compared to 84.7% for the previous version. ### **Agentic Coding Gets a Major Boost** One of the most practical improvements is how Opus 4.7 handles sustained coding tasks at different effort levels. *Opus 4.7 outperforms Opus 4.6 at every effort level on agentic coding tasks, with the new xhigh setting filling the gap between high and max.* At every effort level, Opus 4.7 outperforms Opus 4.6. The new xhigh effort setting is the standout addition. It fills the gap between high and max, giving you finer control over how much compute the model spends on a given problem. At the xhigh level, Opus 4.7 scores around 71% compared to roughly 62% for Opus 4.6 at max effort, while using fewer tokens. Devin's CEO said the model "works coherently for hours" and "pushes through hard problems rather than giving up." That tracks with what the effort-level chart shows. The model does not just perform better on easy tasks. It scales more efficiently as problems get harder. ### **Knowledge Work and Real-World Tasks** Beyond coding, Opus 4.7 sets a new bar for knowledge-intensive work. *Opus 4.7 leads the GDPVal-AA knowledge work benchmark with an Elo score of 1753, ahead of GPT-5.4 at 1674.* On the GDPVal-AA knowledge work benchmark, Opus 4.7 scores an Elo of 1753. GPT-5.4 comes in at 1674 and Opus 4.6 at 1619. Gemini 3.1 Pro trails at 1314. This benchmark measures real-world knowledge tasks, not synthetic puzzles, so the gap here matters for anyone using AI to research, analyze, or draft complex material. Document reasoning improved by 21% fewer errors on enterprise document analysis. Notion's AI lead reported "+14% over Opus 4.6 at fewer tokens and a third of the tool errors." That combination of better results with lower cost and fewer failures is what makes this upgrade meaningful in production. ### **Multilingual and Multimodal Coding** Opus 4.7 expands beyond English-only coding benchmarks with strong multilingual and multimodal results. *Opus 4.7 scores 80.5% on SWE-bench Multilingual (up from 77.8%) and 34.5% on SWE-bench Multimodal (up from 27.1%).* On SWE-bench Multilingual, Opus 4.7 reaches 80.5% accuracy versus 77.8% for Opus 4.6. The multimodal coding benchmark shows a bigger relative jump, from 27.1% to 34.5%. That 27% relative improvement on multimodal coding reflects the 3x vision resolution upgrade working its way into practical coding tasks where the model needs to interpret screenshots, diagrams, or UI mockups alongside code. The vision upgrade processes images at up to 2,576 pixels on the long edge with roughly 3.75 megapixels of resolution. XBOW's CEO confirmed a 98.5% score on visual acuity benchmarks versus 54.5% for Opus 4.6. That is not incremental improvement. That is a generational leap. ### **Key Features and Improvements** Beyond raw benchmarks, several practical changes make Opus 4.7 feel different in daily use. **Better self-verification.** The model checks its own work before reporting results. Stripe's VP of Technology noted the model "catches its own logical faults during planning" and "significantly accelerates execution." **Improved instruction following.** Opus 4.7 takes instructions more literally than previous versions. Anthropic flags this as a potential adjustment point. If your prompts relied on the model inferring what you meant rather than following what you said, you may need to re-tune them. **File system memory.** Multi-session work gets better with improved file-based memory. The model picks up context from previous sessions more reliably, which matters for long-running projects. **Task budgets.** Now in public beta, task budgets let you set guardrails on how many tokens the model spends across a longer run. Useful for cost control on agentic coding tasks. **Ultrareview.** A new slash command in Claude Code dedicated to bug detection. If you use Claude Code for development, this is worth testing on your next pull request. For more on how to get the most out of Claude in practice, check out my [guide on why marketers should use Claude Code](/why-marketers-should-use-claude-code/). ### **Safety and Alignment** Anthropic also shared safety evaluations for Opus 4.7, comparing it to previous models on misaligned behavior. *Opus 4.7 shows lower misaligned behavior scores than Opus 4.6 and Sonnet 4.6, though Mythos Preview remains the best-aligned model.* On Anthropic's automated behavioral audit, Opus 4.7 scores around 2.45 on a 1-10 misalignment scale, down from 2.75 for Opus 4.6. Sonnet 4.6 sits at roughly 2.5. Mythos Preview remains the most aligned model at approximately 1.78, but it is not publicly available. The takeaway is that Opus 4.7 is modestly safer than its predecessor while being significantly more capable. Anthropic notes improved honesty and resistance to prompt injection attacks, though it is "largely well-aligned and trustworthy, though not fully ideal." ### **Pricing and Availability** Claude Opus 4.7 costs $5 per million input tokens and $25 per million output tokens, unchanged from Opus 4.6. It is available now on Claude.ai, the API, Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Foundry. One cost consideration worth flagging: Opus 4.7 uses an updated tokenizer, which means the same input may map to more tokens (roughly 1.0 to 1.35x depending on content type). The model also produces more output tokens at higher effort levels, especially in multi-turn agentic scenarios. Anthropic recommends using task budgets or adjusting effort levels to manage spend. For the full technical breakdown and migration guidance, see the [official Anthropic announcement](https://www.anthropic.com/news/claude-opus-4-7). ### **My Honest Take on Claude Opus 4.7** I have been running Opus 4.7 since it dropped this morning, and the coding improvements are real. The model sticks with problems longer, verifies its own output, and follows instructions with less drift. The vision upgrade is the kind of jump that opens up use cases that were not practical before. The tokenizer change is the one thing to watch. Same prompts, potentially higher costs. Anthropic says the net effect is positive on coding tasks because the model solves more problems per dollar, but your mileage will depend on your specific workload. If you are already paying for Claude, there is no reason not to switch. If you are evaluating AI models for serious coding or content work, this is the new bar. The gap between Opus 4.7 and everything else just got wider. --- ## 5 Best AI Marketing Podcasts in 2026 (No Hype) URL: https://ryandoser.com/best-ai-marketing-podcasts/ Markdown: https://ryandoser.com/best-ai-marketing-podcasts.md Published: 2026-04-09 | Updated: 2026-07-06 Categories: AI Resources > The 5 best AI marketing podcasts for 2026. Hosts who run real businesses, share real stacks, and skip the hype. Pick two and start listening. If you want to actually get better at marketing with AI, the **best AI marketing podcasts** are the ones where hosts build real businesses, not the ones reading headlines at you. ### **Why Most AI Marketing Podcasts Waste Your Time** A lot of shows in this space feel like recycled Twitter threads read aloud. You get 45 minutes of "AI is changing everything" with zero tactics, zero stacks, and zero proof the host has ever run a campaign. The list below is the opposite. Every host either runs a marketing team, an agency, or a content business that depends on getting this right. They share specific tools, real workflows, and honest takes on what is overhyped. I listen to these shows on walks, at the gym, and while prepping my own episodes. They have directly shaped how I build content systems for clients. ### **The 5 Best AI Marketing Podcasts for 2026** Each show below earned its spot by consistently publishing tactical, AI-focused episodes that marketers can apply the same week. No fluff, no hype cycles. #### **1. Authority Hacker Podcast** *The Authority Hacker Podcast YouTube playlist with hosts Gael Breton and Mark Webster.* Hosted by [Gael Breton and Mark Webster](https://www.youtube.com/playlist?list=PLEuTTL7V3hQ0Mq034ldQPgYTQP_o3lbIS) of [Authority Hacker](https://www.authorityhacker.com/podcast/), the podcast has been running since 2016 and pivoted hard into AI, automation, and SEO workflows for small business owners. Recent episodes cover Claude myths, Cloudflare versus WordPress, and running an "AI employee" inside a real content operation. These guys build and sell online businesses, so the tactics hold up when you test them. #### **2. AI Rabbit Holes** *AI Rabbit Holes on YouTube, the interview show I host featuring working AI marketers.* Full disclosure, this is my show. I started [AI Rabbit Holes](https://youtube.com/playlist?list=PLzJwubkSKclOQ2_v7NBRSXCx1lOUHFxxa) because I wanted honest conversations with marketers who are actually shipping with AI, not theorizing about it. Recent guests have walked through their Claude Code workflows, fractional Chief AI Officer businesses, and million-dollar SaaS builds driven off YouTube. Every episode is tactical, every guest reveals their stack, and I push for the specifics most hosts skip. #### **3. The Startup Ideas Podcast** *The Startup Ideas Podcast by Greg Isenberg on YouTube.* [Greg Isenberg](https://youtube.com/playlist?list=PLQHTakJAwGLMQxKVlKUVpC7aiYTZ2j2J9), the CEO of [Late Checkout](https://latecheckout.studio/) and former advisor to Reddit and TikTok, drops new episodes twice a week and the back catalog is deep. The show mixes AI business ideas, faceless YouTube plays, and operator interviews with founders building real products. If you market for a living, you walk away with three or four angles you can steal by lunch. Volume plus specificity is the reason it keeps earning my subscribe. #### **4. Marketing Against the Grain** *Marketing Against the Grain on YouTube with hosts Kipp Bodnar and Kieran Flanagan.* Kipp Bodnar (HubSpot's CMO) and Kieran Flanagan (HubSpot's SVP of Marketing and former Zapier CMO) host [Marketing Against the Grain](https://youtube.com/playlist?list=PLJ7YXFIg84xB0Na0vQKe9uBtnNXV7kaT7) on the [HubSpot Podcast Network](https://network.hubspot.com/), with new episodes weekly. They cover how AI is reshaping brand versus performance, SEO disruption from AI Overviews, and what CMOs are quietly changing right now. Their strength is the strategy lens. These are operators running marketing at public and venture-scale companies, so you hear the conversations happening inside real boardrooms. #### **5. Marketing Uncensored** *Marketing Uncensored on YouTube with hosts Sam Tomlinson and Collin Slattery.* Sam Tomlinson and Collin Slattery run [Marketing Uncensored](https://youtube.com/playlist?list=PL5IoeVzrr6DUEo_nfK2CDepxzkKAKgciW) ([marketinguncensored.com](https://www.marketinguncensored.com/)), and the title is accurate. Slattery runs a 7-figure paid media agency, Tomlinson focuses on analytics and strategy, and together they tear apart bad marketing thinking with a performance marketer's eye. Recent episodes hit why reporting is broken, the Cracker Barrel rebrand, and what actually drives revenue versus what just wins LinkedIn. If you want a counter-narrative to thought-leader slop, this is your show. ### **Ryan's Final Thoughts** The pattern across these five shows is simple. The hosts actually do the work. They ship campaigns, run teams, build products, and then talk about what they learned. That is why their advice survives contact with a real P&L. Pick two or three from the list, subscribe on YouTube, and start stealing the tactics that fit your business. If you want more AI picks beyond podcasts, here are my [best AI YouTube channels to follow in 2026](/ai-youtube-channels/), my roundup of the [best AI communities for marketers and creators](/best-ai-communities/), and a shortlist of [who is worth following outside of YouTube](/ai-content-creators-to-follow/). ### **Best AI Marketing Podcasts FAQs** #### **What makes a good AI marketing podcast in 2026?** A good one is hosted by someone who actually runs marketing or an agency, covers tools and workflows you can test that week, and avoids endless "AI will change everything" filler. Look for shows that name specific stacks, walk through real campaigns, and share honest takes on what is overhyped. If the host cannot tell you what they actually ship, skip it. #### **Are these podcasts free to listen to?** Yes. All five are free on YouTube and most also publish to Spotify and Apple Podcasts. You can subscribe through the playlist links above and start listening right away. A few hosts sell paid courses or communities on top of the free shows, but the podcast episodes themselves are free. #### **Which podcast should a beginner marketer start with?** Start with the Authority Hacker Podcast if you want foundational SEO and AI workflow coverage, or The Startup Ideas Podcast if you want a wider angle on AI business ideas and growth plays. Both are beginner friendly and publish frequently enough to give you a feel for the space fast. #### **How often should I listen to stay current on AI marketing?** Two to three episodes a week is plenty. The space moves fast, but most updates are noise. Focus on shows where hosts test tools before they recommend them, and skip anything that sounds like a press release. Pair podcasts with a weekly [newsletter digest](/best-ai-newsletters/) and you will stay ahead without drowning in content. --- ## The Fractional Chief AI Officer Playbook ($2M in 12 Months) URL: https://ryandoser.com/fractional-chief-ai-officer/ Markdown: https://ryandoser.com/fractional-chief-ai-officer.md Published: 2026-04-09 | Updated: 2026-09-04 Categories: AI Resources > Learn how the Fractional Chief AI Officer model works. Real playbook from a $2M founder including the framework, pricing, and a case study. The **Fractional Chief AI Officer** model is one of the fastest-growing AI service businesses in 2026, and John Cheney used it to clear $2M in revenue and over $1M in profit in year one. Here is how the playbook actually works. ### **How a Fractional Chief AI Officer Actually Works** Most mid-market companies know they need an AI strategy. Very few can afford a full-time Chief AI Officer. That gap is where John built [General AI Proficiency Institute](https://www.genaipi.com/), stepping in as an outsourced executive for a flat monthly retainer. The role is not a one-off consulting call. John sits in C-suite meetings, owns the answer to one question (where can AI actually move a number here), and is on the hook for measurable ROI inside six months. For adjacent models, see the [best ways to make money with AI](/best-ways-to-make-money-with-ai/). *John Cheney walking through why most AI rollouts stall without a dedicated owner.* ### **Why the Chief AI Officer Gap Exists in Mid-Market Companies** You have seen the stat: 95% of enterprise AI projects fail. The reason is simple. Companies drop a few million on ChatGPT seats, expect magic, and nobody owns the rollout. The CEO, CMO, and CTO all had full plates before AI showed up. A [dedicated Chief AI Officer role](https://www.ibm.com/think/topics/chief-ai-officer) fixes that, but only the biggest enterprises can justify a $300K salary plus equity. Fractional fills the middle at roughly 1% of revenue, around $10K to $15K per month. ### **The STE Framework John Uses on Every Client** John runs every engagement through three buckets: Strategy, Transformation, and Education (STE). - **Strategy:** Sit in on leadership meetings. Map where AI can cut cost or unlock revenue. Build a 90-day roadmap tied to a real KPI. - **Transformation:** Ship the work. Sometimes that means vibe coding a custom tool. Sometimes it means wiring APIs into existing software. - **Education:** Show CEOs and department heads what is possible. John walks clients through ElevenLabs, Grok, Midjourney, Claude, and yes, [even OpenClaw when it fits](/avoid-openclaw/). Most consultants skip the education bucket. [MIT Sloan research](https://mitsloan.mit.edu/ideas-made-to-matter/how-generative-ai-can-boost-highly-skilled-workers-productivity) shows the biggest productivity gains come when skilled workers are trained to use AI, not when the tool is dumped on their desk. *John breaking down the Strategy, Transformation, and Education buckets he runs every engagement through.* ### **A Real Fractional Chief AI Officer Case Study** One of John's clients is a California staffing company with 5,000 workers. State law requires an incident hotline, and every call has to be tracked start to finish. Before John showed up, three full-time staffers ran it on a platform built around 2003. Incidents took 39 days to close on average. John's team listened to a week of calls. Over 90% were status checks or minor issues. They built an AI voice agent to answer the phone, triage the case, and route anything serious to a human. Then they vibe coded a replacement intake platform in a few days. The results: - Staff reduced from 3 people to 1 - Average incident close time dropped from 39 days to 11 days - Annual savings north of $140K in salary and benefits alone That is the conversation a CEO wants when the retainer invoice hits. Real headcount decisions backed by numbers. ### **How to Price and Land Your First Fractional AI Client** Pricing is simple. John targets roughly 1% of annual revenue, paid monthly. Six months in, a client who has paid $90K wants to see a saved hire, a cut cycle time, or a new revenue line. Four things that made his pipeline work: - **Niche by revenue band, not industry.** John works with construction firms, law firms, dental groups, and staffing companies. The common thread is size, not vertical. - **Lead with education.** Early clients came from free workshops. The CEOs who said "I don't want to learn this, just do it for me" became retainers. - **Build a repeatable system.** Monthly reports, weekly syncs, an automated status email every Tuesday. Same cadence as a fractional CFO. - **Use AI to run the operation.** John is not a developer. He vibe codes internal tools with [Claude](https://www.anthropic.com/claude) to deliver what used to require a dev team. To get sharper on delivery, [Claude Code is the fastest way to ship client work](/why-marketers-should-use-claude-code/) without traditional coding skills. *John explaining how he prices retainers at roughly 1% of client revenue.* ### **What This Means for Solo Operators in 2026** John's closing advice was blunt. Look at the tasks you do every day, build a system that can do your entire job, then figure out how to sell that system to someone else. The fractional model works because most mid-market CEOs will not sit in Claude for 30 minutes a day. They want the outcome, not the craft. Deliver the outcome as a monthly service with a real report attached and you have a business. You can follow John's [LinkedIn profile](https://www.linkedin.com/in/johncheney/) for daily breakdowns of his work. ### **What a Fractional Chief AI Officer Costs (And Who Should Actually Pay It)** The number John targets, roughly 1% of revenue, is one way to price the role. The open market is wider than that. I pulled the published rate cards from the firms ranking on page one for this question, and the spread runs from $2,500 a month to north of $30,000. For a smaller company those figures are usually a signal to look at [the two lighter roles that sit below a CAIO](/ai-consultant-vs-ai-coach/). Here is what those vendors publish, grouped by what you are actually buying. | Engagement | Published rate | What you get | | Advisory only | $5,000 to $10,000/mo | 4 to 8 hours a week. Strategy input, no delivery. Per [HireAFractionalExec](https://hireafractionalexec.com/guides/fractional-caio-cost). | | Strategy plus governance | $10,000 to $20,000/mo | 8 to 15 hours a week, tooling decisions included. The most common band. | | Hands-on transformation lead | $18,000 to $30,000/mo | 15 to 20 hours a week. The tier where someone owns delivery, not just advice. | | Priced by headcount | $2,500 to $9,500+/mo | [Janis Consulting](https://www.janisconsulting.com/fractional-chief-ai-officer) scales it: $2,500 to $4,500 under 100 employees, $5,500 to $9,500 at 100 to 500. | | Marketplace retainer | From $5,000/mo | [Go Fractional](https://www.gofractional.com/hire/chief-ai-officer) starts here at 5 to 10 hours a week. Its [live rate benchmark](https://www.gofractional.com/insights/rates/chief-ai-officer) averaged $202/hour in September 2026. | | Monthly AI coaching | $999/mo | My [AI Concierge](/ai-concierge/), and it is the right buy only if you are small enough to be hands-on yourself, because you do the clicking while I direct. | [Iternal](https://iternal.ai/fractional-chief-ai-officer) and [Oshri Cohen](https://www.oshricohen.me/chief-ai-officer-cost/) land on the same headline range independently, at $5,000 to $30,000 a month. Iternal puts the typical mid-market engagement at $60,000 to $180,000 a year, which is 20% to 35% of what a full-time hire costs all in. The more useful question is whether you are the buyer for this role at all. A fractional CAIO earns the retainer when the work crosses teams and needs authority behind it. Someone has to sit in leadership meetings, settle the tooling argument, own the rollout, and answer for what happens to your data. Headcount is just the usual proxy for that. The real test is whether AI decisions at your company already require getting other people to agree. If you are still the one who would implement it, that test comes back no. You are the coordination layer. What you need is to know which two or three things to set up this quarter and how to run them yourself, and no retainer is going to hand you that. Worth naming the obvious bias: I sell the cheap end of this table. What I would not do is sell you a $999 coaching engagement when you have 300 employees and a stalled AI rollout. At that point you need someone with authority inside your org chart, and a monthly call with me will not give you that. ### **Ryan's Final Thoughts** The Fractional Chief AI Officer model is the cleanest productized service I have seen all year. It maps to a real market gap, the delivery is repeatable, and the price fits a company that cannot justify a full-time hire. John proved it with $2M in year one. The operators who win this decade will be the ones who build systems around AI, not the ones who wait for AI to come to them. And if you would rather run those systems inside your own business than sell them as a service, that is the gap my [AI Concierge](/ai-concierge/) covers: I build them with you instead of for you. ### **Fractional Chief AI Officer FAQs** #### **What is a Fractional Chief AI Officer?** A Fractional Chief AI Officer is an outsourced executive who owns a company's AI strategy, rollout, and training for a fraction of a full-time hire. The role runs on a monthly retainer and covers leadership meetings, hands-on delivery, and team education. #### **How much does a Fractional Chief AI Officer cost?** Pricing lands around 1% of the client's annual revenue, paid monthly. For a mid-market company doing $10M to $20M in top line, that works out to $10K to $15K per month. Enterprise scopes with custom builds run higher. #### **Do you need a technical background to become a Fractional Chief AI Officer?** No. John Cheney built a $2M business without being a developer. Tools like Claude, ChatGPT, and vibe coding workflows let a non-technical operator ship software and automate processes. The harder skill is translating business goals into AI projects with measurable ROI. #### **What does a Fractional Chief AI Officer actually do day to day?** The work splits into Strategy, Transformation, and Education. That means C-suite meetings, mapping AI opportunities to KPIs, building tools, and teaching the team what is possible. See the STE Framework section above. #### **What is the going monthly retainer for a Fractional Chief AI Officer in 2026?** Published rates run from about $2,500 to over $30,000 a month, which is wider than the 1%-of-revenue rule of thumb above. The most common band is $10,000 to $20,000 for 8 to 15 hours a week, per HireAFractionalExec's 2026 rate guide. Iternal and Oshri Cohen both put the full market range at $5,000 to $30,000 a month. Iternal prices the typical mid-market engagement at $60,000 to $180,000 a year, or 20% to 35% of a full-time hire. Some firms price by headcount instead: Janis Consulting charges $2,500 to $4,500 a month for companies under 100 employees. #### **Is a Fractional Chief AI Officer worth it for a small business?** Usually not, and the math is why. The role exists to coordinate AI across departments and own a rollout nobody else has time for. In a small business you are already that person, so you are paying executive rates for a coordination job that does not exist yet. The cheaper move is monthly coaching, where you learn the setup and run it yourself, and you can [compare what independent consultants charge](/best-ai-marketing-consultants/) before calling anyone. Hire the fractional CAIO when the bottleneck is getting a team aligned rather than getting yourself started. --- ## Claude Code Leak and a WordPress Killer (AI Weekly Roundup) URL: https://ryandoser.com/claude-code-leak-wordpress-killer/ Markdown: https://ryandoser.com/claude-code-leak-wordpress-killer.md Published: 2026-04-08 | Updated: 2026-09-30 Categories: AI News > Half a million lines of Claude Code source leaked this week. Plus Cloudflare's new WordPress killer and why your tokens are burning faster. This week's **AI weekly roundup** covers four stories that actually move the needle for marketers and creators: Anthropic accidentally leaked the entire Claude Code source, everyone hit the new usage limits at the same time, Cloudflare dropped a WordPress alternative nobody saw coming, and Anthropic quietly previewed a model that can find zero-day vulnerabilities on its own. Here is what happened, why it matters, and what I actually think. ### **Anthropic Leaked the Entire Claude Code Source** On March 31, Anthropic shipped an npm release missing one tiny config file. That mistake exposed a 59.8 MB source map. Inside it was roughly 512,000 lines of unobfuscated TypeScript across 1,906 files. The full agent loop. The permission system. The safety prompts. Feature flags gating 20+ unshipped capabilities. Even an unreleased autonomous daemon mode called KAIROS. Source: [VentureBeat coverage of the leak](https://venturebeat.com/technology/claude-codes-source-code-appears-to-have-leaked-heres-what-we-know) **Ryan's Take:** The model is not the moat, the scaffolding is. Claude Code wins because of the agent loop, the permission system, and the [skills architecture](/claude-skills/) wrapped around the model, not the model itself. ### **Claude Code Usage Limits Are Hitting Everyone** Starting March 26, Anthropic started draining the 5-hour session window faster during peak hours (8 AM to 2 PM Eastern, weekdays). Same query, more pain, if you work when everyone else works. The community response has been a flood of token-saving tips. Batch your prompts instead of firing three in a row. Reference specific files with @filename instead of dumping the whole repo into context. Kill [MCP servers](/claude-code-mcps/) you do not need (one server can eat 18,000 tokens per message). Push heavy refactors to nights and weekends. **Update:** the peak-hours penalty did not last. On May 6, 2026 Anthropic [removed the peak hours limit reduction](https://www.anthropic.com/news/higher-limits-spacex) on Claude Code for Pro and Max accounts and doubled the five-hour rate limits for Pro, Max, Team and seat-based Enterprise plans. The token-saving habits still pay off. The clock-watching does not. The MCP tip has aged too: Claude Code now defers MCP tool definitions by default with a feature called tool search, so only tool names and server instructions load until Claude needs a tool. On a standard setup, an idle server now costs far less than the 18,000 tokens a message people were quoting in April. Source: [Anthropic's official usage limits doc](https://support.claude.com/en/articles/11647753-how-do-usage-and-length-limits-work) **Ryan's Take:** Most people are burning tokens on context bloat they never look at. Audit your MCPs this weekend and you will probably cut your usage by 30% without changing how you work. ### **Cloudflare Just Built a WordPress Killer** On April 1, Cloudflare dropped EmDash, a full stack serverless CMS built on Astro 6.0 and written entirely in TypeScript. The pitch is security. WordPress plugins are responsible for 96% of the security issues on WordPress sites. EmDash fixes this by running every plugin inside a sandboxed Cloudflare Worker with explicit capability bindings. If a plugin did not declare it needs file access in its manifest, it does not get file access. Cloudflare rebuilt the whole thing from scratch with AI coding agents, used zero WordPress code, and shipped it under the MIT license. Source: [Cloudflare's official EmDash announcement](https://blog.cloudflare.com/emdash-wordpress/) **Ryan's Take:** This is not another AI tool wearing a costume, 95% of those are white labeled ChatGPT with a 10x markup. EmDash is actually different, but the architecture is right and the ecosystem is empty, so the real question is whether Cloudflare can convince developers to port. ### **Anthropic Previewed Claude Mythos and Launched Project Glasswing** On April 7, Anthropic dropped two announcements at once. The first is [Claude Mythos Preview](https://red.anthropic.com/2026/mythos-preview/), a frontier model that can discover and exploit zero-day vulnerabilities in major operating systems and web browsers on its own. The second is [Project Glasswing](https://www.anthropic.com/glasswing), a defensive program that gives security researchers and critical infrastructure operators early access to Mythos so they can find and patch holes before the model ships broadly. Anthropic is essentially saying the next generation of AI can break things at a scale no human red team can match, so they are giving the defenders a head start. Source: [Anthropic's Claude Mythos Preview writeup](https://red.anthropic.com/2026/mythos-preview/) **Ryan's Take:** This is the first AI release where the launch post is also a warning label. If you run any kind of web infrastructure for clients, the next 12 months are about closing every dumb vulnerability before AI finds it for someone with bad intent. ### **What This Means for Marketers** Four stories, one theme. The next 90 days are about discipline, not output volume. The Claude Code leak proved that scaffolding beats raw model power. The usage limits are forcing everyone to stop wasting tokens on context bloat. EmDash is a reminder that the AI infrastructure layer (real infrastructure, not white label slop) is where the next wave of tooling is actually being built. And Mythos plus Glasswing is the canary in the coal mine for anyone running client websites without a real security posture. If you want the same toolkit and workflows I use to run client work, my newsletter, and ryandoser.com, **[grab my Free AI Marketing Guide here](https://guide.ryandoser.com/).** --- ## Claude Mythos: Anthropic's Most Dangerous AI Model Yet URL: https://ryandoser.com/claude-mythos/ Markdown: https://ryandoser.com/claude-mythos.md Published: 2026-04-08 | Updated: 2026-04-08 Categories: AI News, Claude Code > Anthropic's Claude Mythos is so capable at hacking they refuse to release it publicly. Here's the benchmarks and what it means. Anthropic just announced **Claude Mythos** Preview, a frontier model so capable at cybersecurity tasks that the company decided not to release it to the public. The news broke on red.anthropic.com, and the benchmarks are the reason everyone in security is paying attention. ### **What Claude Mythos Actually Is** Anthropic calls it a general-purpose model. Security researchers are calling it something else. The first thing you notice in the [official post](https://red.anthropic.com/2026/mythos-preview/) is how openly the company admits the risk. Mythos Preview scored a 72.4% success rate on Firefox 147 JavaScript shell exploitation. Claude Opus 4.6 hit 14.4% on the same test. That jump is the whole story. A model that can autonomously write working browser exploits is not a productivity tool. It is a weapon with a chat interface. If you want to go deeper on how Claude is reshaping modern work, I put together the **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)** with every workflow I actually use. *Claude Mythos beats Opus 4.6 by roughly 5x on Firefox 147 JavaScript shell exploitation.* Opus 4.6 built a working Firefox exploit twice across hundreds of attempts. Mythos did it 181 times in the re-run. The post also mentions a 27-year-old OpenBSD TCP bug the model discovered on its own, plus a 16-year-old flaw in FFmpeg's H.264 codec that sat unnoticed for over a decade. ### **How Claude Mythos Performs on Software Benchmarks** Security was not the only area where Mythos pulled ahead. On SWE-bench Pro, the model scored 77.8% versus 53.4% for Opus 4.6. On SWE-bench Verified, Mythos reached 93.9%. GPQA Diamond came in at 94.6%, and the model also showed strong results on Humanity's Last Exam, a benchmark built to resist AI progress. *Claude Mythos posts 77.8% on SWE-bench Pro and 93.9% on SWE-bench Verified, well ahead of Opus 4.6.* What makes these numbers unusual is the method. Anthropic credits the gains to test-time compute scaling. The longer Mythos is allowed to think through a chain of reasoning, the more accurate it gets. That is different from training a bigger model. It means existing models can improve just by reasoning longer. For a deeper read on how this shift is playing out, see my take on [why marketers should use Claude Code](/why-marketers-should-use-claude-code/). ### **Why Anthropic Is Holding Claude Mythos Back** Here is where the story shifts from research paper to industry reckoning. Anthropic's own words: "We do not plan to make Mythos Preview generally available." Instead, the company launched [Project Glasswing](https://www.anthropic.com/project/glasswing), a limited access program with partners like AWS, Apple, Cisco, CrowdStrike, Google, JPMorganChase, Microsoft, NVIDIA, and the Linux Foundation. The program commits $100 million in usage credits and $4 million in direct donations to open source security organizations. The goal is defense-first. Get the model into the hands of the people patching critical infrastructure before anyone else can replicate what Mythos can do. Over 99% of the vulnerabilities Mythos has already found remain unpatched, which is why Anthropic refuses to share details. Simon Willison [called the restriction warranted](https://simonwillison.net/2026/Apr/7/project-glasswing/). I agree. The security risks here are credible in a way earlier "AI finds bugs" claims never were. If you are weighing which model to trust for serious work, my guide on [switching from ChatGPT to Claude](/switch-from-chatgpt-to-claude/) covers the practical tradeoffs. ### **My Honest Take on the Claude Mythos Rollout** The Anthropic IPO is coming, and a story this loud lands at a convenient time. I do not think the benchmarks are fake. I do think the framing matters. A defense-first narrative is the only way a company ships a model this powerful without regulators pulling the emergency brake. The cybersecurity angle is real. So is the marketing. Both things can be true. What I keep coming back to is the gap between 14.4% and 72.4% on the same exploitation test. That is not a slow climb. That is a cliff. If an aligned lab can produce this model today, an unaligned one can produce something similar soon. The defense window Anthropic keeps talking about is not rhetorical. It is a clock. For practical applications of safer Claude workflows, my post on [Claude Skills](/claude-skills/) walks through the day-to-day use cases I rely on. ### **Ryan's Final Thoughts** Claude Mythos is the clearest signal yet that AI capability gains are outrunning our ability to govern them. Anthropic made the right call holding it back. The harder question is what happens when the next lab does not. Keep watching Project Glasswing. The partners list tells you which companies already believe the threat is real. ### **Claude Mythos FAQs** #### **Is Claude Mythos available to use right now?** No. Anthropic has stated it will not release Mythos Preview to the general public. Access is limited to Project Glasswing partners, which includes critical infrastructure companies and open source security maintainers. Regular Claude users will not see Mythos in the app or API. #### **Why is Claude Mythos considered dangerous?** Mythos can autonomously find and exploit software vulnerabilities at a level previous models could not reach. It scored 72.4% on a Firefox exploitation benchmark where Opus 4.6 hit 14.4%. The same capabilities that make it useful for defenders would make it devastating in the wrong hands, which is why Anthropic is gating access. #### **What is Project Glasswing?** Project Glasswing is Anthropic's controlled deployment program for Mythos Preview. It gives limited model access to 12 partners including AWS, Apple, Cisco, CrowdStrike, Google, JPMorganChase, Microsoft, NVIDIA, and the Linux Foundation. Anthropic committed $100M in usage credits and $4M in donations to open source security organizations. #### **How does Claude Mythos compare to Claude Opus 4.6?** Mythos beats Opus 4.6 across every benchmark Anthropic shared. SWE-bench Pro jumped from 53.4% to 77.8%. SWE-bench Verified reached 93.9%. GPQA Diamond hit 94.6%, and the model also showed strong results on Humanity's Last Exam, a benchmark built to resist AI progress. The biggest gap is in cybersecurity, where Mythos scored nearly five times higher than Opus 4.6 on Firefox shell exploitation. --- ## How to Scrape LinkedIn Profiles With Claude Code (Free) URL: https://ryandoser.com/scrape-linkedin-profiles-claude-code/ Markdown: https://ryandoser.com/scrape-linkedin-profiles-claude-code.md Published: 2026-04-02 | Updated: 2026-04-02 Categories: Claude Code > Learn how to scrape LinkedIn profiles with Claude Code and Apify for free. Export post data to CSV with engagement analytics in minutes. If you want to pull post analytics from LinkedIn without paying for expensive tools, you can **scrape LinkedIn profiles with Claude Code** using a free Apify account and a simple skill file. ### **How to Scrape LinkedIn Profiles With Claude Code** Most AI chatbots will flat-out refuse this request. Ask ChatGPT, Claude's web app, or Google Gemini to scrape a LinkedIn profile, and you'll get the same response: "I'm not able to scrape LinkedIn directly." LinkedIn blocks automated scraping and requires authentication to access profile data. That means you need a workaround. The solution is pairing Claude Code with [Apify](https://apify.com/), a marketplace of pre-built scrapers for LinkedIn, Instagram, TikTok, Google Maps, and more. If you want to go deeper on building AI-powered marketing workflows, I put together a guide with everything I use daily. **[Get my free AI Marketing Essentials Guide](/ai-marketing-guide/)** *The Apify marketplace offers dozens of LinkedIn scrapers, including the Harvest API actor used in this tutorial.* ### **Setting Up Apify for LinkedIn Scraping** You only need two things to get started: a free Apify account and your API key saved in Claude Code. The specific scraper I use is the [LinkedIn Profile Posts Scraper from Harvest API](https://apify.com/harvestapi/linkedin-profile-posts). It costs $2 per 1,000 posts, requires no cookies, and works without a paid Apify subscription. Apify's free tier gives you $5 of usage every month, which covers roughly 2,500 posts. Here is how to connect it: - Create a free account on Apify - Go to Settings, then API and Integrations - Copy your API token - In Claude Code, tell it to save your Apify API key in your environment file Storing API keys in an .env file is more secure than pasting them directly into a chat. This matters as you scale and add keys for other services. If you're new to [Claude Code integrations and MCPs](/claude-code-mcps/), that approach keeps everything organized. ### **Running the LinkedIn Profile Scraper Skill** Once your API key is saved, open a fresh Claude Code chat and tell it to use your LinkedIn profile scraper skill. Point it at any public LinkedIn profile URL and specify how many posts you want scraped. In my test, I scraped my last 50 LinkedIn posts and asked Claude Code to export everything as a CSV file. The fields included post date, URL, post type, likes, comments, shares, and a custom engagement score that ranks posts against each other. *Claude Code generates a CSV file with post dates, URLs, engagement metrics, and custom scoring for all scraped LinkedIn posts.* The whole process took a few minutes. Claude Code called the Apify actor, pulled the data, and formatted it into a clean spreadsheet. You can download my LinkedIn scraper skill from my **[Claude Code Skills Stack](https://claude-code-skills-stack.rdoser13.workers.dev/)** and drop it right into your setup. ### **Analyzing Your LinkedIn Post Data** Reading a CSV in VS Code is not ideal for analysis. I dragged the file into Google Drive and opened it with Google Sheets. That gives you sorting, filtering, and a much cleaner view of your post performance. The engagement score column stood out immediately. My highest-scoring post (a 10 out of 10) was a personal update about expecting my first child. Personal posts consistently outperform promotional content on LinkedIn, and the data confirmed that pattern across all 50 posts. *Dragging the CSV into Google Sheets makes it easier to sort, filter, and analyze your LinkedIn post performance.* Every row links back to the original post URL. You can click through to see exactly what performed well and why. The post text column also gives you raw copy to reference when planning future content. If you're looking for more ways to use [Claude Code for marketing](/claude-code-for-marketing/), scraping LinkedIn is one of the most practical starting points. ### **What This Costs (Almost Nothing)** My 50-post scrape cost $0.10. That is ten cents for a full breakdown of post dates, engagement metrics, URLs, and content text. You could run this 50 times on the free tier before hitting the $5 monthly limit. The [Apify API documentation](https://docs.apify.com/platform/integrations/api) covers rate limits and additional configuration if you want to scale beyond the free tier. For most individual creators and marketers, the free plan handles everything you need. One thing to watch: Apify actors change over time. Pricing can shift, and some actors move behind paid plans. If that happens, Claude Code will often search for alternative scrapers automatically. Building [Claude Code skills](/claude-skills/) around these workflows makes it easy to swap actors without rebuilding from scratch. ### **Final Thoughts from Ryan** Scraping LinkedIn profiles with Claude Code takes minutes to set up and costs almost nothing. The real value is in the analysis. Once you have post-level engagement data in a spreadsheet, you can spot patterns in what resonates with your audience and double down on those formats going forward. ### **Scrape LinkedIn Profiles Claude Code FAQs** #### **Do I need a paid Apify account to scrape LinkedIn with Claude Code?** No. Apify's free tier includes $5 of monthly usage. The Harvest API LinkedIn scraper costs $2 per 1,000 posts, so you can scrape thousands of posts each month without spending anything. #### **Does this scraper require LinkedIn cookies or login credentials?** The Harvest API actor works without cookies or authentication. You do not need to log into LinkedIn or share any credentials with Apify to pull public profile post data. #### **Can I scrape any LinkedIn profile or just my own?** You can point the scraper at any public LinkedIn profile URL. It works for your own profile, competitor profiles, or any creator whose content you want to analyze. #### **What data fields does the LinkedIn scraper export?** The CSV includes post date, post URL, content text, post type, likes, comments, shares, and a custom engagement score. You can add or remove fields by adjusting your Claude Code prompt. --- ## How I Vibe Coded a Digital Product With Claude Code (And Made $1000) URL: https://ryandoser.com/vibe-code-digital-product-claude-code/ Markdown: https://ryandoser.com/vibe-code-digital-product-claude-code.md Published: 2026-04-01 | Updated: 2026-04-01 Categories: Claude Code > I vibe coded a digital product with Claude Code and made over $1000. Here is the full breakdown from idea to revenue. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* ### **How I Built a $1,000 Digital Product With Claude Code** Most creators build digital products and then spend weeks figuring out how to sell them. I did the entire thing in one sitting with Claude Code and Opus 4.6. I sat down with Sabrina Ramonov to break down the entire process. Sabrina is one of the top AI content creators in the world with over 300K subscribers on YouTube. She also founded [Blotato](https://www.blotato.com/?ref=rdoser), an AI content tool I use daily in my own workflows. I had 20+ Claude Code skills for marketing, SEO, email, YouTube, and social media locked inside my [Skool community](https://www.skool.com/ai-marketing-insiders). Only members could access them. So I packaged everything into a standalone digital product called the Claude Code Skill Stack. I fed the product files directly into Claude Code. It had the full context of what I was selling, so it wrote accurate copy with zero guessing. I gave it my brand guide, my Stripe payment link, and a reference landing page I liked. One prompt later, the full sales page was ready. About $1,000 in Stripe revenue followed from a soft launch with zero paid ads. Just a few email newsletter mentions and organic traffic. *Stripe dashboard showing revenue from the Claude Code Skill Stack digital product.* Want to build AI-powered marketing systems like this? Grab my free guide. **[Free AI Marketing Essentials Guide](https://guide.ryandoser.com/)** ### **What You Need to Vibe Code a Digital Product** Four free or low-cost tools are all that stand between you and a live sales page. Here is the full list. - **Claude Pro subscription** ($20/month minimum). I use the $100/month Max plan with Opus 4.6 for front-end design and copywriting. - **[Stripe](https://stripe.com) account** (free). Create a product, set your price, and Stripe gives you a hosted checkout link. - **GitHub account** (free). Your landing page files live here before deployment. - **[Cloudflare Pages](https://developers.cloudflare.com/pages/)** (free). Connects to your GitHub repo and makes your site publicly accessible. You also need a Claude Code web design skill. [Anthropic publishes free skills](https://docs.anthropic.com/en/docs/claude-code/skills) including a front-end design template. I customized that template with my brand colors, typography, and layout preferences. That step separates a generic page from one that looks like your brand. For the Claude Code Stripe integration, you skip the custom checkout headache entirely. Stripe gives you a public URL that handles payments and security. Paste that link into your prompt and Claude Code wires the button. ### **The Prompt That Built a Vibe Code Landing Page That Makes Money** One prompt generated the entire sales page with product sections, testimonials area, and a working checkout button. Context is doing all the heavy lifting here. My prompt included five things: my Claude Code web design skill, my brand style guide, the actual digital product files, my Stripe payment link, and a reference URL from a high-converting landing page by creator Brooke Wright. I told Claude Code to use her format and style, but keep my brand and product intact. That "remix" approach is a shortcut worth stealing. I covered the full landing page building process in my [guide to building landing pages with Claude Code](/claude-code-landing-pages/). That walks through prompt structure, iterations, and common mistakes. ### **How to Deploy a Claude Code Site With GitHub and Cloudflare** Getting from local files to a live URL takes less than five minutes. Create a GitHub repository, upload your HTML and assets, connect that repo to Cloudflare Pages, and hit deploy. Free hosting, instant public URL. I used this same workflow for a client. Medix Dental IT needed a conversion-optimized landing page for Google Ads. I embedded their HubSpot CRM form, applied their brand guide, and deployed through the same pipeline. It works whether you are selling a $29 digital product or generating B2B leads. *The Claude Code Skill Stack sales page deployed via GitHub and Cloudflare Pages.* ### **How I Repurpose YouTube Videos to Blog Posts With Claude Code** My site hit 43,000 impressions and 468 clicks in about 30 days on a domain rating of 1.8. Practically brand new with almost zero backlinks. The traffic engine is my Claude Code SEO blog post writer skill. I use [Blotato](https://www.blotato.com/?ref=rdoser) to transcribe YouTube videos right inside Claude Code, then the skill produces a full SEO-optimized blog post. Keyword placement, heading structure, internal linking, and meta descriptions all handled automatically. It goes further than text. Claude Code watches the video, finds engaging moments, and extracts real screenshots at those timestamps. Those frames get compressed, uploaded to WordPress, and placed with optimized alt text. Real images from my actual videos, not AI-generated filler. The publishing pipeline connects through a [WordPress MCP](/claude-code-mcps/). Claude Code creates the draft, uploads the featured image, assigns categories, and sets Yoast SEO fields automatically. I am [using Claude Code for SEO](/claude-code-seo/) across my entire content operation now. *Google Search Console results from ryandoser.com after 30 days of publishing repurposed content.* ### **Ryan's Final Thoughts** You are probably sitting on existing content that could become a digital product. SOPs, guides, community modules, course materials. All of it can be repackaged and sold through a landing page you vibe code in an afternoon. If you want to learn how to sell digital products with Claude Code, start with what you already know, package it, and ship it. The market will tell you if it works. For more ideas on monetizing AI skills, check out my breakdown of the [best ways to make money with AI](/best-ways-to-make-money-with-ai/). ### **Vibe Code Digital Product Claude Code FAQs** #### **Can you really make money selling digital products with Claude Code?** Yes. I made over $1,000 from a single digital product with zero paid advertising. Claude Code handled the sales page and Stripe processed payments. No inventory, no shipping, no custom checkout code. #### **What tools do you need to vibe code a digital product landing page?** Claude Pro ($20/month minimum), a free GitHub account, a free Cloudflare account, and a free Stripe account. Anthropic also offers a free front-end design skill you can customize. #### **How do you connect Stripe to a Claude Code landing page?** Create a product in your Stripe dashboard and generate a payment link. Paste that link into your Claude Code prompt when building the page. Claude Code wires the checkout button to that URL automatically. #### **How long does it take to build a digital product sales page with Claude Code?** The first draft generates in three to five minutes. Plan another 10 to 15 minutes for iterations. Deploying to GitHub and Cloudflare adds a few more minutes. Total time is usually under 30 minutes. #### **How do you drive traffic to a digital product built with Claude Code?** I repurpose every YouTube video into an SEO-optimized blog post using a Claude Code skill. This generated 43,000 impressions in 30 days on a brand new domain. Email newsletters and organic social work well for soft launches too. --- ## The AI Marketing Stack Behind a 100K YouTube Channel URL: https://ryandoser.com/ai-marketing-stack/ Markdown: https://ryandoser.com/ai-marketing-stack.md Published: 2026-03-30 | Updated: 2026-08-27 Categories: AI Rabbit Holes > See the exact AI marketing stack a 100K YouTuber uses daily. Grace Leung shares her tools, workflows, and system thinking approach. Every marketer wants to know what **ai marketing stack** a successful creator actually uses day to day. I sat down with Grace Leung, an AI marketing expert with over 146,000 YouTube subscribers, to find out exactly that. ### **Inside This YouTuber's AI Marketing Stack** Grace's answer might surprise you. She doesn't juggle dozens of tools. Her core stack runs on three platforms. Claude handles roughly 80% of her daily marketing work. She uses both the web application and Claude Code, building reusable skill files and connected workflows that compound over time. For market research, she turns to Perplexity. And for deep topic analysis, NotebookLM remains her go-to. That's it. Three tools powering a six-figure YouTube channel and consulting business. The pattern matters more than the specific tools. Grace picked platforms that do multiple jobs well instead of stacking single-purpose apps. This reflects a broader shift in 2026: frontier AI models like Claude and Gemini now handle presentations, landing pages, animations, and content creation. Standalone SaaS tools that only did one thing are getting replaced fast. ### **Why System Thinking Beats Tool Chasing** I asked Grace whether marketers still using ChatGPT are behind. Her answer was blunt: most people haven't used any AI at all. If you're using ChatGPT and building real workflows, you're already ahead of the majority. *Grace Leung explaining why system thinking matters more than which AI tool you pick.* But Grace pushed back on something I said. I argued that marketers winning right now are moving toward IDEs and terminals like Claude Code. She agreed with the direction but added a caveat: the tool isn't what makes the difference. How you think about your work is what matters. "People say ChatGPT is dumb, so I'm going to jump to Claude," Grace said. "But if you use Claude like a chatbot, you'll get chatbot results. Start with whatever you have. Build a system around it." This is the core of her ai content creation workflow. She builds reusable SOPs and skill files that work across platforms. If Claude disappeared tomorrow, her systems would transfer because the thinking is portable. The tool is just a container. The biggest waste of time she sees? FOMO. Marketers [chasing every new feature](/ai-anxiety/) and never building anything that compounds. Remember Sora? People spent hours learning a tool that no longer exists. ### **How Grace Uses AI for YouTube Content** Grace doesn't automate her content creation. That might sound contradictory for someone with 127K subscribers, but her reasoning is practical: "When we talk about impact, about actually generating clients and building trust, full automation isn't there yet." Instead, she uses AI for the strategic layer of her ai marketing automation workflow: - **Finding angles and framing** for new videos using Claude - **Content gap analysis** to spot what competitors miss - **ICP critiques** where AI reviews her content from her target audience's perspective - **Pattern analysis** across her existing content to find what resonates She'll feed Claude her ideal customer profile and ask it to critique a video draft. Does it resonate? Is the pacing right? AI becomes a strategic reviewer, not a content factory. For research, she relies on [NotebookLM for marketing](https://notebooklm.google/) because it only uses the sources you provide. It won't mix in random training data the way a GPT or project might. She extracts structured data tables from NotebookLM, then feeds those back into Claude for deeper analysis. That loop between tools is where the real power lives. ### **Claude Code for Marketing: Grace's Setup** Grace walked through her actual Claude Code project structure during our conversation. She organizes it the way a real business runs. *Grace's Claude Code project structure organized by marketing function.* Her setup includes: - **Context files** covering brand identity, target audience, product offerings, and marketing strategy - **Skill markdown files** for repeatable workflows like branded decks and campaign briefs - **Agent configurations** that group related skills for focused output *Inside one of Grace's skill markdown files with brand context and business details.* The key insight: start with skill files before building agents. A creative designer agent only works well when you've already defined the skills it should pull from. Skills are the foundation. Agents are the orchestration layer you add later. Both Grace and I use [Claude Code for marketing](/claude-code-for-marketing/) inside Visual Studio Code. It's free, approachable for non-coders, and keeps everything local. If Claude Code disappeared tomorrow, your skill files still work with whatever AI coding tool comes next. For marketers just getting started, Grace recommends beginning with the [Claude web application first](/why-marketers-should-use-claude-code/). Build a project. Write a system prompt. Create your first skill. Then graduate to Claude Code when the web app starts limiting you. ### **YouTube as Your Content Foundation** Grace and I agree on this: YouTube should be the starting point for your ai marketing tools 2026 strategy, not an afterthought. YouTube videos now appear in almost every Google search result page. Gemini, ChatGPT, and Perplexity all scrape YouTube transcripts as knowledge sources and cite videos directly in AI-generated answers. Your YouTube content feeds blog posts, social media, newsletters, and podcast clips. That originality is what Google's algorithm rewards through "information gain." Grace recommends using AI to analyze Reddit threads, YouTube comments, and forum discussions to uncover audience pain points. That's a stronger content foundation than copying whatever the current top search results say. For more on building [Claude Skills](/claude-skills/) that automate repurposing, or connecting external data sources through [MCPs in Claude Code](/claude-code-mcps/), I cover both in separate walkthroughs. If you want the repurposing workflow ready-made instead of built from scratch, that is what my [**AI Content Engine**](https://engine.ryandoser.com/) is. ### **Final Thoughts from Ryan** Grace's ai marketing stack proves that fewer tools with better systems will always beat a bloated toolkit. Three core platforms. Reusable skill files. A system thinking mindset that transfers regardless of which AI tool is on top next month. Start with what you have, build a system around it, and upgrade only when the tool genuinely limits your output. Follow [Grace Leung on YouTube](https://www.youtube.com/@graceleungyl) for more on AI marketing systems. You can also find her on [her website](https://www.graceleung.com/) and [LinkedIn](https://www.linkedin.com/in/grace-leung-yl/). ### **AI Marketing Stack FAQs** #### **What is an AI marketing stack?** An AI marketing stack is the set of AI tools and systems a marketer uses for daily work. A strong stack connects a few core platforms through reusable workflows rather than juggling disconnected apps. Grace Leung's stack centers on Claude, Perplexity, and NotebookLM. #### **Do I need Claude Code to build an AI marketing stack?** Not right away. Grace recommends starting with the Claude web application. Build a project, write a system prompt, and create repeatable skill documents there first. Move to Claude Code once the web app starts limiting you. #### **How many AI tools should be in my marketing stack?** Fewer than you think. Grace runs her entire 127K-subscriber channel and consulting business on three core tools. The trend in 2026 is consolidation, not expansion. Pick platforms that handle multiple workflows well. #### **Is ChatGPT still a viable AI marketing tool in 2026?** Yes. Most marketers haven't adopted any AI yet. If you're actively building workflows in ChatGPT, you're ahead of the majority. The tool matters less than the systems you build with it. #### **What's the biggest mistake marketers make with AI tools?** Chasing every new feature and product launch instead of building systems that compound. Grace calls it FOMO. Tools like Sora attracted massive attention and then vanished. The marketers who invested in reusable workflows instead of hype stayed ahead. --- ## How to do Keyword Research in Claude Code (The Future of SEO) URL: https://ryandoser.com/claude-code-keyword-research/ Markdown: https://ryandoser.com/claude-code-keyword-research.md Published: 2026-03-24 | Updated: 2026-09-30 Categories: Claude Code > Claude Code keyword research gives you access to high-quality SEO data without expensive tools. Learn how to connect these tools via MCP. **Claude Code keyword research** gives you access to high-quality SEO data without spending hundreds on traditional tools. ### **How Claude Code Keyword Research Actually Works** Most marketers default to typing "give me keyword ideas" into ChatGPT or Claude's web app. That approach falls short for one reason: those models don't have real-time keyword data. Monthly search volume, keyword difficulty, CPC, and intent signals come from platforms like [Data for SEO](https://dataforseo.com/?aff=245611) and [Ahrefs](https://ahrefs.com/). Generic AI models can brainstorm topics, but they can't pull live metrics the way dedicated SEO platforms can. That gap is exactly what Claude Code fills when you connect it to external data providers via MCP. Data for SEO is the one I settled on for daily work, and I wrote up [a full review of the platform](/dataforseo-review/) covering its real costs. The workflow has three parts. First, you create a Claude Code skill dedicated to keyword research. Second, you connect an external data provider through MCP (Model Context Protocol). Third, you run queries and refine results in real time. I'll break down each step. ### **Create a Keyword Research Skill First** You might wonder why a skill file matters when you could just prompt Claude Code directly. A skill acts as an SOP that tells Claude Code exactly how to format results, which columns to include, and what quality bar to hit. Without one, you'll get inconsistent outputs every time you run a query. I built a keyword research skill that pulls metrics like monthly search volume, keyword difficulty, CPC, and search intent. It also generates SEO title suggestions for each keyword. If you don't have a skill file yet, I recommend creating your own first to understand the mechanics. You can learn more about [how Claude Code works for marketing](/claude-code-for-marketing/) in my earlier walkthrough. The real power shows up when you chain skills together. After pulling keyword data, I can immediately tell Claude Code to use my SEO blog post writer skill to draft an article targeting one of those keywords. That kind of workflow stacking is what separates Claude Code from every other AI tool for keyword research. ### **Connect Data for SEO via MCP** Data for SEO is the easiest entry point because you pay only for the calls you make. I compare it against the other [SEO MCP servers worth connecting](/best-seo-mcp-servers/) and break down what each one really costs. You sign up, get API credentials, and connect through an [MCP server in Claude Code](/claude-code-mcps/). The whole setup takes about five minutes. You fund the account first, and the pricing page currently sets a $50 minimum payment. Each query costs roughly five to ten cents, so that balance covers hundreds of keyword pulls rather than a handful. Once connected, you paste a prompt like "find me 15 relevant keyword ideas based on the root topic of Claude Code marketing." Claude Code calls the Data for SEO MCP, pulls real metrics, and returns a formatted table. Run this on Opus 5.5, the current Claude Code default, for the highest quality output. The results include monthly search volume, keyword difficulty, CPC, and intent classification. If you don't like certain keywords in the list, you tell Claude Code to swap them out and add new columns. The skill updates your results in real time without starting over. If you would rather see those same DataForSEO numbers in a dashboard with rank tracking built in, I weighed [whether OpenSEO is worth paying for](/openseo-review/) against this direct setup. *Data for SEO keyword results inside Claude Code showing search volume, keyword difficulty, CPC, and SEO title suggestions.* ### **Upgrade to the Ahrefs MCP for Better Data** Data for SEO works well for getting started. But if you're deep in SEO and already paying for [Ahrefs](https://ahrefs.com/pricing) ($129/month minimum), the Ahrefs MCP is a significant upgrade. Ahrefs is one of the premier platforms for organic keyword data, and their API recently became available on lower-tier plans. I set up the Ahrefs MCP live for the first time on camera. The process is straightforward: copy the MCP documentation, paste it into Claude Code, authenticate through the Ahrefs website, and you're connected. After that, update your keyword research skill to point at the Ahrefs MCP instead of Data for SEO. The quality difference is noticeable. Ahrefs pulls from a larger index with more accurate difficulty scores and better keyword suggestions. If you're serious about [Claude Code SEO workflows](/claude-code-seo/), this connection is worth setting up. Which one you should actually point Claude at depends on whether you are buying data or an index, and I worked through that tradeoff in [DataForSEO vs Ahrefs](/dataforseo-vs-ahrefs/). *Ahrefs MCP keyword research results for "Claude Code Marketing" pulled directly inside Claude Code.* ### **Backlink Analysis and Beyond** Keyword research is just the starting point. With the Ahrefs MCP connected, I can also pull backlink profiles straight from Claude Code. I ran a query asking for the best backlinks on my website sorted by domain rating and topic relevance. Claude Code returned a full breakdown with DR scores, monthly traffic, dofollow status, and relevance ratings. That opens up bigger opportunities. You could analyze competitor backlinks, build outreach lists, and even draft cold emails using other [**Claude Code Skills Stack**](https://skills.ryandoser.com/) files. All without leaving your terminal. The ability to stack keyword research with blog writing, backlink analysis, and outreach planning inside one interface is what makes this an AI keyword research tool that actually replaces expensive SaaS subscriptions. *Backlink analysis pulled from the Ahrefs MCP inside Claude Code, sorted by domain rating and topic relevance.* ### **Ryan's Final Thoughts** Claude Code keyword research replaces the manual process of bouncing between SEO platforms, spreadsheets, and AI chatbots. Connect Data for SEO for pay-as-you-go pulls or Ahrefs for premium data, build a skill file, and let Claude Code handle the heavy lifting. Once that is running, [the other servers worth connecting alongside it](/mcp-servers-for-marketers/) are where the rest of the leverage sits. The workflows you can chain from a single keyword query (blog posts, YouTube strategy, backlink outreach) are what make this approach worth trying today. ### **Claude Code Keyword Research FAQs** #### **Is Claude Code keyword research free?** Data for SEO is pay-as-you-go, and its pricing page currently sets a $50 minimum payment to fund your account. Each query costs about five to ten cents, so that balance stretches a long way. Claude Code itself requires a Claude Pro or Max subscription. Ahrefs integration requires a paid plan starting at $129 per month. #### **Do I need coding skills to do keyword research in Claude Code?** No. Claude Code runs in a terminal, but the keyword research workflow is entirely prompt-based. You type natural language queries and Claude Code handles the API calls through MCP connections. Building a skill file is as simple as writing instructions in a markdown document. #### **What is the difference between Data for SEO and Ahrefs for keyword research?** Data for SEO is pay-as-you-go and provides solid keyword metrics for most use cases. Ahrefs offers a larger keyword index, more accurate difficulty scores, and additional features like backlink analysis. If you already pay for Ahrefs, their MCP connection delivers higher quality data inside Claude Code. #### **Can I combine keyword research with other Claude Code skills?** Yes. After pulling keyword data, you can chain it with a blog post writer skill, YouTube SEO skill, or any other skill in your system. This is one of the biggest advantages of running keyword research inside Claude Code versus standalone SEO tools. #### **What AI model should I use for keyword research in Claude Code?** Opus 5.5, the current Claude Code default, is my pick for keyword research queries. It produces higher quality analysis and better formatted results compared to Sonnet. Sonnet 5.5 also works and stretches your plan's usage further, but may need more prompting to refine outputs. --- ## How to Update Your Claude Code Skills on Autopilot (Autoresearch) URL: https://ryandoser.com/claude-code-autoresearch/ Markdown: https://ryandoser.com/claude-code-autoresearch.md Published: 2026-03-23 | Updated: 2026-03-31 Categories: Claude Code > Learn how Claude Code autoresearch auto-updates your skill files after every workflow. Built on Karpathy's system, this saves hours. Most Claude Code users manually update their skill files after every session. **Claude Code autoresearch** eliminates that step entirely by turning your skills into self-improving systems that learn from every workflow. ### **How Claude Code Autoresearch Actually Works** You finish a workflow in Claude Code. Maybe you wrote an email newsletter or repurposed a YouTube video into a blog post. Normally, you'd scroll back through the chat, spot the corrections you made, and manually update the skill file so those mistakes don't repeat. Autoresearch flips that process. After every skill run, it silently evaluates the output against the skill's own rules. It logs failures to an improvements file. Once three or more similar failures stack up, it auto-patches the skill markdown. You get a one-line notification. That's it. Creative skills need the most rounds. My podcast intro skill took eight versions over two days before one shipped, which I cover in my [AI podcast intro test](/ai-video-editing/). The concept comes from [Andrej Karpathy's autoresearch GitHub repository](https://github.com/karpathy/autoresearch). Karpathy, one of the co-founders of OpenAI, built this as a system for running autonomous research experiments. I adapted it for something more practical: keeping my marketing skills in Claude Code sharp without babysitting them. *Andrej Karpathy's autoresearch GitHub repository, the system behind self-improving Claude Code skills.* ### **Setting Up Autoresearch in Claude Code** You don't need to clone Karpathy's repo or run Python scripts. The entire setup happens inside Claude Code through two prompts. First, I asked Claude Code to create a new skill markdown file based on the [autoresearch repository](https://github.com/karpathy/autoresearch). I pointed it at the GitHub URL and let it read the README, project structure, and core logic. Within a few minutes, it generated a skill file that captures the passive improvement system in a format Claude Code understands natively. The second prompt is where it gets personal. I told Claude Code to customize the autoresearch skill for my specific workflows. It pulled from my CLAUDE.md file and recent chat history to identify which skills I use most. For me, that meant my [SEO blog post writer](/claude-code-skills-hack/), email newsletter skill, social media crossposting, and YouTube thumbnail workflows. *Claude Code building the autoresearch skill file from scratch using the GitHub repo as context.* ### **Why Self-Improving Skills Matter for Marketers** Every correction you make during a Claude Code session is a lesson. Before autoresearch, those lessons lived only in your memory. Maybe you remembered to update the skill file. Maybe you forgot. Either way, it was manual work that interrupted your flow. With Claude Code self-improving skills, the system catches patterns you might miss. My email newsletter skill picked up three new rules after a single session. One was about formatting. Another was about CTA placement. The third caught a voice inconsistency I hadn't consciously noticed. I didn't prompt any of those updates. The skill evaluated its own output, logged the failures, and patched itself. That's the difference between a static prompt template and a living system that gets better every time you use it. If you want the full set of [Claude Code skills](/claude-skills/) I run in production, including the autoresearch skill, you can grab my **[Claude Code Skills Stack](https://skills.ryandoser.com/)**. It has 20+ skill files for marketing and content workflows. *Autoresearch in action, automatically updating the email newsletter skill with three new lessons after a workflow run.* ### **Start With Your Top Five Skills** I wouldn't recommend turning autoresearch on for every skill at once. Claude Code needs enough context from real sessions to understand what "good" looks like for each skill. If you rarely use a skill, it won't have enough data to make meaningful improvements. Pick your five most-used skills. For me, those were the SEO blog post writer, email newsletter, news scan, social media, and thumbnail designer. These are the workflows I run multiple times per week. They generate the most corrections, the most edge cases, and the most opportunities for the system to learn. Once autoresearch proves itself on your core skills, expand from there. Karpathy designed this system to run quietly in the background. It shouldn't slow you down or require constant attention. If you want to hear more about Karpathy's thinking behind the project, I'd recommend watching [this interview](https://youtu.be/kwSVtQ7dziU?si=9fDecPj58hOlBFl5) where he goes deep on autonomous AI research systems. The real productivity gain isn't the time saved on individual updates. It's the compounding effect. Every session makes your skills slightly better. After a few weeks, your [Claude Code marketing workflows](/claude-code-for-marketing/) run noticeably cleaner with fewer corrections needed from you. ### **Final Thoughts from Ryan** Autoresearch turned my Claude Code skills from static documents into living systems. The setup took two prompts and a few minutes. The payoff compounds with every workflow I run. If you're spending time manually updating skill files after each session, this single hack will give you that time back. ### **Claude Code Autoresearch FAQs** #### **What is Claude Code autoresearch?** Claude Code autoresearch is a passive skill improvement system based on Andrej Karpathy's autoresearch repository. It silently evaluates your skill outputs after every run, logs failures, and auto-patches the skill markdown file once three or more similar failures accumulate. No manual updates required. #### **Do I need to install anything to use autoresearch in Claude Code?** No. You don't need to clone repos or install dependencies. The entire system lives inside a skill markdown file that Claude Code reads natively. You create it with a prompt, customize it with a second prompt, and it runs passively from that point forward. #### **How many skills should I start with for autoresearch?** Start with your top five most-used skills. Autoresearch needs real session data to identify patterns and make meaningful improvements. Skills you rarely use won't generate enough context for the system to learn effectively. Expand to additional skills once you see results on your core workflows. #### **Will autoresearch break my existing Claude Code skills?** The system is designed to make small, targeted patches rather than sweeping rewrites. It logs every change to an improvements file, so you can review what was updated and revert if needed. It also stays silent by default, only sending a one-line notification when a patch is applied. --- ## Why Marketers Should Use Claude Code (Or Fall Behind) URL: https://ryandoser.com/why-marketers-should-use-claude-code/ Markdown: https://ryandoser.com/why-marketers-should-use-claude-code.md Published: 2026-03-18 | Updated: 2026-07-08 Categories: AI Rabbit Holes, Claude Code > This explains why marketers should use Claude Code instead of ChatGPT. See the 10x productivity gap, how Skills work, and what to build. **Why marketers should use Claude Code** comes down to one thing: the productivity gap between those who adopt it and those who don't is already 6-10x and growing fast. ### **Why Marketers Should Use Claude Code Right Now** Most marketers hear "Claude Code" and think it's for developers. That assumption is costing them real money. I sat down with Mark Webster, co-founder of [Authority Hacker](https://www.authorityhacker.com/), to talk about his switch from ChatGPT to Claude Code. Mark is not a developer. He runs a marketing education company. And he called Claude Code the single biggest productivity shift he's seen in a decade of building online businesses. You can find Mark on [LinkedIn](https://www.linkedin.com/in/markwebster1/) and on the [Authority Hacker YouTube channel](https://www.youtube.com/@AuthorityHackerPodcast). The name itself is part of the problem. Mark put it bluntly: "They have done themselves a disservice by naming it Claude Code." If Anthropic had called it "Claude for Knowledge Workers," ten times more people would have downloaded it by now. *Mark Webster's testimonial video editor skill inside Claude Code, showing how Skills act as reusable SOPs for AI.* ### **The Real Difference Between Claude Code and ChatGPT for Marketing** So here's the thing about using ChatGPT for marketing work. You write copy in one tab. Then you switch to your email tool. Then you ask a designer for an image. Then you go back to schedule the post. That back-and-forth orchestration eats hours every week. Claude Code eliminates that entire loop. Through MCPs (Model Context Protocol) and direct API connections, it stays in one interface. Write the email, connect to your sending platform, generate the image, schedule the post. All without leaving your workspace. Mark compared the learning curve to switching from PC to Mac. "You feel useless for the first few days." But then it clicks. The real obstacle is not technical difficulty. It's resistance to change. I talk to marketers daily who refuse to move past GPTs and Projects. That's a mistake. Claude Code's Opus 4.5 and 4.6 models changed everything for non-technical users. Now you can type "fix it" and the tool corrects its own errors nine out of ten times. ### **How Claude Code Skills Transform Marketing Workflows** Skills are the feature that makes Claude Code worth the switch. Think of them as SOPs for AI. They're reusable instruction files that tell Claude Code exactly how to handle a specific task. Anthropic even published an [open-source skills library on GitHub](https://github.com/anthropics/skills) to help you get started. Once you know the format, the next question is which ones to install, and I rounded up [the Claude skills worth installing first](/best-claude-skills/). Here's what makes Skills different from ChatGPT's custom GPTs or Projects. You can tell Claude Code to update its own skill files based on your feedback. Mark called this the key differentiator: "I never go back and update my system prompt." With Skills, that problem disappears because the tool updates itself. Mark showed two workflows during our conversation that made the productivity gap obvious: - **Video testimonial editing:** Claude Code reads transcripts from [Descript](https://www.descript.com/), scores each segment for hook quality and CTA potential, proposes an edit script, then generates prompts that auto-edit the entire video. Zero manual editing required. - **Thumbnail generation:** AI generates backgrounds, logos, and text. Then a Python script (that Claude Code wrote itself, for a non-developer) composites real headshot photos on top. It even categorized all photos from a shoot by mood and cut out backgrounds automatically. Mark does not know Python. Claude Code wrote the script for him. That's [Claude Code marketing automation](/claude-code-for-marketing/) in action. Mark teaches these workflows inside the [Authority Hacker AI Accelerator](https://www.authorityhacker.com/ai-accelerator/) community. *Claude Code reading a skill file and editing a Python script for thumbnail generation, all inside VS Code.* ### **The 6-10x Productivity Gap Is Growing** The numbers from this conversation are hard to ignore. Marketers using Claude Code are seeing a 600 to 1,000 percent productivity gain over those still using ChatGPT alone. Mark's prediction: "That 6 to 10x gap might be 12 to 20 in a year's time." Not because the models will necessarily get better (though they will), but because compounding skills and workflows make each week more productive than the last. This has real implications for AI marketing tools. Claude Code can already replace thumbnail generators, form plugins, and other single-purpose SaaS products, and it sits at the top of [the AI coding tools I use](/best-ai-coding-tools/) every day. Only platforms with genuine moats, like email delivery platforms, payment processors, and membership tools with uptime requirements, are safe from this shift. I'm not someone who jumps on every new trend. I call out people who do. But Claude Code is the real thing. As I told Mark: "This is that one thing you need to pay attention to." ### **What Non-Technical Marketers Should Build First** If you're a marketer with zero coding experience, start with an email response agent. Connect Claude Code to your email tool and have it draft responses based on your voice and preferences. It's a low-risk way to experience the difference. From there, build a [Claude Code marketing workflow](/claude-code-for-marketing/) around your most repetitive task. Content repurposing, social scheduling, keyword research. Whatever eats the most time becomes your first skill. If you want a shortcut, [here are the ten I run in production](/best-claude-marketing-skills/). Once that skill works, the natural next move is handing it off to run on its own, which is where [the automation tools that run those workflows for you](/best-ai-automation-tools/) come in. [Token pricing from Anthropic](https://docs.anthropic.com/en/docs/about-claude/pricing) is cheap compared to hiring developers at hundreds of dollars per hour. And since Claude Code writes its own code, you don't need a developer on staff. Mark's advice for getting past the initial friction? Stop overthinking it. Open Claude Code, give it a task, and when it breaks, type "fix it." That habit separates adopters from stallers. *Mark's transcript format reference file inside Claude Code, demonstrating how Skills handle complex workflows for non-developers.* ### **Ryan's Final Thoughts** The gap between marketers using Claude Code and those relying on ChatGPT alone is already massive. [Skills](/claude-skills/), MCPs, and API access give you an unfair advantage that compounds over time. The learning curve is hours, not weeks. Whether you start with an email agent or a full content repurposing system, start now. The marketers who move first will be the ones hiring, not the ones getting replaced. Employers are already asking for this. In [what AI marketing jobs ask for](/research/ai-marketing-jobs/), about a third of the posts that name Claude ask for Claude Code, Claude Skills or Cowork specifically. ### **Why Marketers Should Use Claude Code FAQs** #### **Is Claude Code only for developers?** No. Despite the name, Claude Code works for anyone who does knowledge work. Mark Webster from Authority Hacker has no coding background and runs complex workflows through it daily. The Opus 4.5 and 4.6 models made it reliable enough for non-technical users. #### **How is Claude Code different from ChatGPT for marketing?** ChatGPT works in isolated conversations. Claude Code connects to your workflow through MCPs and APIs, handling everything from one interface. Skills also self-update based on your feedback, something ChatGPT's custom GPTs cannot do. #### **What should I build first in Claude Code as a marketer?** Start with an email response agent. Connect Claude Code to your email platform and let it draft replies in your voice. It's a low-risk first project before tackling larger workflows like [content repurposing](/claude-code-agent-teams/) or ad automation. #### **How much does Claude Code cost for marketing use?** Claude Code runs on Anthropic's token-based pricing, which is far cheaper than hiring developers. Most marketing workflows cost pennies per execution. The 6-10x productivity gain means the ROI is immediate for anyone doing repetitive marketing tasks. #### **Will Claude Code replace marketing SaaS tools?** Some of them. Thumbnail generators, form plugins, and other single-purpose tools are already being replaced. Platforms with genuine moats, like email service providers and payment processors, are safe. The tools at risk wrap a single AI feature in a subscription. --- ## Which AI Model Picks the Best NCAA March Madness Bracket? URL: https://ryandoser.com/ai-march-madness-bracket/ Markdown: https://ryandoser.com/ai-march-madness-bracket.md Published: 2026-03-17 | Updated: 2026-03-31 Categories: AI Tutorials > I tested 5 AI models to fill out March Madness brackets. See which AI picked the best 2026 NCAA tournament bracket and how they compared. Your **AI March Madness bracket** could look completely different depending on which model you ask. I tested five of the top AI models head-to-head to find out which one makes the smartest picks for 2026. ### **How AI March Madness Bracket Predictions Actually Work** Most people open ChatGPT, type "fill out my bracket," and call it a day. That approach misses the point entirely. I wanted to go deeper this year. So I built a March Madness predictor skill inside Claude Code that factors in KenPom efficiency ratings, current form, injuries, player availability, coaching experience in March, travel logistics, game locations, NBA draft prospects, and historical seed performance. Then I ran that same skill across five different AI models through OpenRouter's API. Same prompt. Same data inputs. Five different sets of picks. The goal was simple: remove my own bias and let the models compete against each other. *The LMArena leaderboard helped identify the top-ranked AI model from each company for the bracket test.* ### **The 5 AI Models I Tested for March Madness** Here is a breakdown of every model I put through the bracket gauntlet. I pulled from the top of the [LMArena leaderboard](https://lmarena.ai/) to pick the smartest model from each company. - **Claude Opus 4.6** (Anthropic) - **GPT-series latest** (OpenAI) - **Gemini** (Google) - **Grok** (xAI) - **DeepSeek** (DeepSeek) Each model received the identical predictor skill file. I created a separate markdown file for every model's picks, covering each round from the Round of 64 all the way to the national championship. Then I filled out actual brackets on [NCAA.com](https://www.ncaa.com/news/basketball-men/mml-official-bracket/2026-03-17/2026-ncaa-tournament-printable-bracket-schedule-march-madness) with each model's results. *Claude Opus 4.6 picked Arizona to beat Duke in the national championship on NCAA.com.* ### **Who Did Each AI Model Pick to Win It All?** Three out of five models picked Arizona to cut down the nets. That alone tells you something about how similarly these AI NCAA tournament bracket tools process matchup data. Claude Opus 4.6 had Arizona beating Duke 67-62 in the title game. OpenAI and Gemini landed on nearly identical brackets, also picking Arizona. Grok went with Michigan, which was the boldest pick of the group. And DeepSeek picked Duke to win it all, with the most chaotic bracket by far. ### **DeepSeek Had the Most Upsets by Far** If you want chaos in your March Madness AI picks, DeepSeek is your model. It picked every single 12-over-5 upset in the tournament. Northern Iowa over St. John's. High Point over Wisconsin. MCN State over Vanderbilt. Texas over Gonzaga. The other four models played it safe. Claude, OpenAI, and Gemini produced what bracket nerds call "chalky" results, meaning they heavily favored higher seeds. Almost every Final Four slot across those three brackets went to a one or two seed. That makes sense when you think about it. AI models trained on historical data will gravitate toward patterns. And the pattern says higher seeds win more often. DeepSeek either weighted different variables or interpreted the skill file with more risk tolerance. One thing almost every model agreed on: Michigan State over UConn in that 3-vs-2 matchup. That kind of consensus across five separate models is worth paying attention to. *Claude Code comparison showing DeepSeek picked the most upsets across all five AI brackets.* ### **How to Use AI for Your Own March Madness Bracket** You do not need Claude Code or [OpenRouter](https://openrouter.ai/models) to get started. But having a structured prompt makes a massive difference versus just asking "who wins?" Here is what worked for me: - **Give context beyond stats.** Injuries, coaching history in the tournament, and travel distance all matter. Feed that into your prompt. - **Compare multiple models.** One model gives you one perspective. Three or five give you consensus picks and outliers worth investigating. - **Use AI as a researcher, not a psychic.** These models spot patterns in data. They cannot predict buzzer-beaters or freshman breakout performances. - **Build a reusable skill or prompt.** I created a [Claude Code skill](/claude-code-skills-hack/) that I can run year after year. The structure stays the same even as the bracket changes. If you have tried [different AI tools](/chatgpt-alternatives/) for other projects, the same principle applies here. The model you choose shapes the output you get. ### **What the AI Models Got Wrong (and Right)** No AI model is going to nail a perfect bracket. The NCAA tournament exists because unpredictable things happen. A cold shooting night. A last-second foul. A 15-seed that just will not go away. But AI March Madness predictions do give you a data-driven starting point. The consensus picks (Arizona, Michigan State advancing) carry more weight than any single expert's gut feeling. And the outlier picks from DeepSeek might be exactly the [Cinderella upsets](https://sports.yahoo.com/articles/march-madness-predictions-2026-using-231952977.html) that win your office pool. I will be tracking all five brackets through the tournament and comparing final results. The real test is not which model sounds smartest. It is which one gets the most games right. ### **Ryan's Final Thoughts** Testing five AI models against each other for March Madness bracket predictions was one of the more fun experiments I have run this year. The biggest takeaway: AI models are more alike than different when it comes to picking favorites. The real value shows up in how they handle toss-up games and potential upsets. If you want to follow along with my bracket results or grab the free [Claude Code predictor skill](/claude-skills/), check the video description. And drop your picks in the comments. I want to know which AI model you are trusting with your bracket this year. ### **AI March Madness Bracket FAQs** #### **Can AI accurately predict March Madness brackets?** AI models spot statistical patterns and historical trends better than most humans. But they cannot account for random events like injuries during games or clutch performances. Use AI as a research tool to inform your picks, not as a guaranteed oracle. #### **Which AI model is best for March Madness predictions?** In my 2026 test, Claude Opus 4.6, OpenAI, and Google Gemini all produced similar "chalk" brackets favoring higher seeds. DeepSeek picked the most upsets. The best approach is comparing multiple models and looking for consensus picks. #### **How do you use AI to fill out a March Madness bracket?** Give the AI model context beyond basic stats. Include KenPom ratings, injury reports, coaching tournament history, and travel logistics. A structured prompt or skill file produces far better results than a vague "pick my bracket" request. #### **Is using AI for bracket predictions considered cheating?** Not at all. AI is just another research tool, similar to reading expert analysis or checking Vegas odds. Most bracket pools have no rules against using technology. The tournament is still unpredictable enough that AI will not guarantee a perfect bracket. #### **What factors should AI consider when picking March Madness games?** Strong AI bracket predictions factor in efficiency ratings, current win streaks, defensive vs. offensive matchups, coaching records in March, player injury status, historical seed performance, and even travel distance to game locations. --- ## How to Build a Strong Personal Brand for Founders (AI Proof) URL: https://ryandoser.com/personal-branding-for-founders/ Markdown: https://ryandoser.com/personal-branding-for-founders.md Published: 2026-03-17 | Updated: 2026-03-31 Categories: AI Rabbit Holes > Learn how to build a strong personal brand for founders that drives revenue. Personal branding is more important in an AI-first world. **Personal branding for founders** is no longer optional if you want to drive real leads and revenue in 2026. I sat down with [Colin Rutherford](https://www.youtube.com/@CollinRutherford), two-time founder and CEO of [FounderBrands](https://www.founderbrands.io/ryan-landing-page), to break down what actually works. ### **What Personal Branding for Founders Actually Looks Like** Most founders hear "build a personal brand" and think it means posting motivational quotes on LinkedIn. That could not be further from the truth. Colin put it simply. You have to post. Every single day. You have to educate, add value, and share your personality. That is the bare minimum. But here is the part most people miss. The best leads often never like your posts. They lurk. They read your content for weeks or months before ever reaching out. Colin calls sales calls and revenue the only real metrics. Everything else, likes, impressions, comments, those are vanity numbers that social media platforms made up. So if you are 30 days into posting and seeing crickets, that is normal. Extend your time horizon to five years and keep refining what resonates. ### **Why Your Founder Brand Beats Your Company Brand** You have probably noticed that company pages on LinkedIn and Facebook get almost zero organic reach. Unless you are paying for ads, those algorithms cap your posts hard. Colin confirmed this from his own data. [FounderBrands](https://www.founderbrands.io/ryan-landing-page) does not work with a single business profile. It is 100 times easier and 100 times more effective to build a personal brand than to post from a company page. People do not care about your logo. They cannot connect with a faceless brand. The founder brand vs company brand debate is settled. Personal pages win. Colin has seen it across 50+ clients. The founders who put their face and story front and center consistently outperform companies hiding behind corporate accounts. And here is what makes a founder personal brand strategy AI-proof. AI cannot replicate your career journey, your specific opinions, or your personality. Share how you got where you are today. Share what you are testing right now in your business. That content is impossible to fake. ### **The Content System That Drives Leads** Colin built Founder Brands to solve his own problem. He was spending 30 to 35 hours a week on content creation and had to get back to running his business. His personal brand content system has two core pieces: - **A brand book** that captures your tone, experience, and client pain points. Every post runs through this lens to maintain authenticity. - **A one-hour monthly recording** where a content manager pulls stories and insights from you. That transcript becomes 30 days of social media posts. For platform strategy, Colin recommends text plus image posts on both [X](https://x.com) and LinkedIn. Video is not outperforming other formats despite what the algorithms want you to think. On LinkedIn, post once a day max to [avoid cannibalizing your own reach](https://sproutsocial.com/insights/social-media-metrics/). On X, you can go two to three times daily since posts have a shorter shelf life of about 48 hours. One critical rule Colin follows: 95% value, 5% selling. Give away everything you know for free. People will still pay you for the implementation. ### **How to Get Leads From Personal Branding** This is where Colin shared the exact LinkedIn DM outreach strategy his team uses to drive thousands of dollars in monthly revenue for clients. **Finding leads from four sources:** - New followers who match your ideal customer profile - Similar accounts (use the suggested accounts feature on X to chain-find prospects) - Inbound commenters who are already warm from reading your content - [LinkedIn Sales Navigator](https://www.linkedin.com/business/sales/blog/sales-navigator) for profile view targeting **Building rapport before the DM:** Comment on their posts for two to three weeks first. Not generic praise like "great post." Add real value, nuance, or invite discussion. Colin's team does 10 quality comments per day. One outbound specialist got 30,000 impressions on a single comment with only 200 followers. **The five-step DM conversion system:** - Add value first. Reference a recent post or company situation. Never pitch in the first message. - Poke the bear. Ask open-ended questions that make them articulate their problem. - Qualify the lead. Confirm revenue match, decision-making authority, and urgency. - Pitch with context. Share how you fixed this for similar clients. Include a case study if you have one. - Follow up with value. Every follow-up should give them something useful. Colin uses Claude to compile custom lead lists and DM scripts for prospects as a follow-up gift. That last point matters. Instead of saying "did you review my proposal?" Colin sends prospects a deliverable. That is the difference between a [LinkedIn lead generation for founders](/best-ways-to-make-money-with-ai/) approach that works and one that gets ignored. ### **Final Thoughts from Ryan** How to build a personal brand in 2026 comes down to a few things. Post daily, share real experience, and build a system that converts attention into revenue. Your personal brand is the only moat AI cannot copy. Colin said it best. The more AI becomes prevalent, the greater that moat becomes. If you do not have 30 hours a week to figure this out alone, consider working with a team that has done it for 50+ founders. Follow [Colin on X](https://x.com/collin_ruth89) to see his process in action. The opportunity cost of trying to go it alone is real. Want to see a founder who is absolutely crushing personal branding right now? Check out [Shannon Jean on X](https://x.com/ShannonJean). He built a reseller mastermind community of 3,000+ members and drives most of his revenue through personal brand content. Colin named him the top founder doing this right now. We are living in a trust recession. The founders who invest in their [personal brand now](/avoid-ai-slop/) will own their market in 12 months. ### **Personal Branding for Founders FAQs** #### **How long does it take to see results from personal branding?** Colin recommends extending your time horizon to at least five years. The first 30 days will likely show minimal engagement. Focus on refining your content and voice rather than tracking vanity metrics. Real results, meaning sales calls and revenue, typically start showing up after consistent daily posting for several months. #### **Should founders post from personal accounts or company pages?** Personal accounts outperform company pages by a wide margin. Algorithms limit organic reach on business profiles. People connect with other people, not logos. Colin's agency works exclusively with personal profiles because they are 100 times more effective for driving leads and revenue. #### **How do you avoid sounding like AI when using AI for content?** Start with a brand book that captures your real voice, tone, and experience. Record yourself talking for an hour each month and use that transcript as source material. AI creates the base post, but a human editor refines it. The combination of real source content and skilled editing prevents your posts from reading like [AI slop](/avoid-ai-slop/). #### **What is the best platform for founder personal branding in 2026?** It depends on your audience, but Colin favors X over LinkedIn for lead generation. He drives 80% of his clients from X. LinkedIn posts last longer (two to three weeks of reach), while X posts peak within 48 hours. Text plus image posts outperform video on both platforms right now. #### **How many times a day should founders post on social media?** Once per day on LinkedIn is the sweet spot. Posting more frequently can cannibalize your own reach. On X, two to three posts daily works well since content cycles faster. Colin considers one post per day across platforms the bare minimum for building a meaningful [personal brand](/ai-for-small-businesses/). --- ## How to Grow SaaS With YouTube (SaaS Millionaire Advice) URL: https://ryandoser.com/how-to-grow-saas-with-youtube/ Markdown: https://ryandoser.com/how-to-grow-saas-with-youtube.md Published: 2026-03-09 | Updated: 2026-03-31 Categories: AI Rabbit Holes > Learn how to grow a SaaS business with YouTube. A SaaS millionaire explains his organic video strategy on YouTube as his main growth driver. Vasco Aries bootstrapped his AI SEO platform Arvow to $70K MRR, and the primary growth engine was YouTube. This article breaks down exactly **how to grow SaaS with YouTube** based on my conversation with him. ### **How to Grow SaaS With YouTube (The Actual Playbook)** Most SaaS founders throw money at paid ads and wonder why nothing sticks. Vasco took a different path. He built trust on camera, one video at a time. His logic was simple. People buy from people they know, like, and trust. Video does that faster than any other medium. So on his [YouTube channel](https://www.youtube.com/@VascoAiresChannel), Vasco started making SEO tutorials, talked about what he knew from years of running an agency, and plugged [Arvow](https://arvow.com/) naturally at the end. "You can do all this manually, or you could just use our software to do it for you in a tenth of the time." That was the whole pitch. The results speak for themselves. One of Vasco's creators made a Portuguese-language video three years ago that still pulls 200 views per day. Try getting that kind of longevity from a tweet or a LinkedIn post. *Ryan Doser and Vasco Aries discussing how YouTube became the primary growth channel for Arvow.* ### **Why YouTube Beats Paid Ads for Bootstrap SaaS** Vasco tried Facebook ads to webinar funnels. He tested YouTube ad campaigns with high-ticket offers. None of it scaled for a bootstrapped company competing against VC-backed rivals who can afford to lose money for six months acquiring a customer. Organic YouTube content costs time, not cash. And the compounding effect is real. His channels pulled 38,000 views in February alone, with a large chunk coming from videos posted a year or two earlier. That is the definition of an [evergreen content strategy](https://support.google.com/youtube/answer/9314355). YouTube is also the [second largest search engine](https://backlinko.com/youtube-users) in the world. And according to Vasco, it is the most cited domain by LLMs. So your YouTube content feeds both human viewers and AI models pulling information for answers. ### **The Multi-Channel YouTube Strategy Behind Arvow** You might assume one YouTube channel is enough. Vasco hit a ceiling posting one video per day on a single channel. Two videos per day showed diminishing returns. So he launched new channels and hired dedicated creators for each. Each creator gets a unique coupon code. Each video gets a dedicated UTM link in the description and pinned comment. That tracking tells Vasco exactly which videos bring paying customers. No email nurture sequence needed. YouTube IS the nurture. Unlike TikTok where users might watch ten clips in a row, a 15-minute YouTube tutorial is a bigger commitment. Spreading content across multiple channels captures more total attention without exhausting a single audience. *Vasco explaining his multi-channel YouTube strategy and why one video per day per channel is the sweet spot.* ### **Is SaaS Dead in 2026? (Not Even Close)** "The pendulum swings," Vasco told me. "When something is dead, two weeks later it's more alive than ever." The SaaS model is changing. Vasco's own team uses [AI agents](https://blog.google/products/search/) that interact with software on their behalf through natural language. The future of SaaS will be more agentic, with agents using UIs instead of humans clicking buttons. But the idea that you can vibe code a replacement for Slack or any production SaaS tool? That ignores the opportunity cost. You spend hours (and hundreds in API costs) building something that still has bugs. Then you maintain those bugs forever. Vasco draws a clear line: vibe coding internal micro-tools for your own workflow makes sense. Trying to sell a vibe-coded B2B product to thousands of paying users is a different story entirely. If you are thinking about [making money with AI](/best-ways-to-make-money-with-ai/), building distribution matters more than building the product itself. ### **SEO Is Not Dead (And the Data Proves It)** [Google still owns over 90% of search market share](https://gs.statcounter.com/search-engine-market-share). ChatGPT accounts for roughly 1% of all search volume globally. People want to throw a parade when they get a lead from ChatGPT but dismiss the 50 leads that came from Google. Top-of-funnel informational SEO has shifted. AI overviews and LLM-generated answers are changing how people find content. But demand for products and services has not gone away. LLMs still pull from page one of Google and Bing to generate answers. Foundationally, it still starts with search. If you want to see how I use [Claude Code for SEO](/claude-code-seo/), that breakdown covers my full workflow. For the bottom-of-funnel pages that still convert, see my episode with Sam Dunning on [SaaS SEO that drives pipeline](/saas-seo/). Both Vasco and I agree: GEO and AEO are just [repackaged SEO](https://www.youtube.com/creators/) concepts. If someone is selling you a dedicated "AEO service" as a replacement for your marketing team, be skeptical. *Vasco's YouTube Studio analytics showing 68K impressions and 3.5K views on a top-of-funnel video.* ### **The Real SaaS Moat Is Distribution** I asked Vasco a pointed question: "A developer with Claude Code clones Arvow over a weekend. What do you have that they don't?" His answer was one word. Distribution. Building software is easier than ever. That is exactly why distribution matters more than ever. A working product, solid customer support, and a real acquisition channel separate SaaS businesses that survive from those that fade after a Product Hunt launch. The 10K MRR milestone that everyone flexes online? Vasco calls it "broke." After costs, team members, support staff, and co-founder splits, you are working 16-hour days for less than a good salary. The opportunity is unlimited if you scale past that point. But most people never talk about the ugly middle. For [small businesses using AI](/ai-for-small-businesses/), understanding this reality upfront saves a lot of pain. ### **Ryan's Final Thoughts** **How to grow SaaS with YouTube** comes down to a simple formula. Build trust on camera. Create evergreen content that compounds over time. Track everything with UTM links and coupon codes. And treat YouTube as your primary acquisition channel, not a side project. Vasco proved this playbook works at scale. The question is whether you are willing to put in the reps. ### **How to Grow SaaS With YouTube FAQs** #### **Does YouTube actually work for SaaS marketing?** Yes. Vasco bootstrapped his AI SEO tool Arvow to $70K MRR using YouTube as the primary growth channel. Long-form tutorials build trust with potential customers, and evergreen videos continue driving traffic years after publishing. The key is creating content that educates viewers on problems your product solves. #### **Should SaaS founders use YouTube ads or organic content?** Organic content is the better play for bootstrapped SaaS companies. Paid ads mean competing against VC-backed companies that can afford longer payback periods. Organic YouTube videos compound over time and cost nothing beyond production effort. #### **How do you convert YouTube viewers into SaaS customers?** Vasco uses dedicated UTM links in every video description and pinned comment. No email nurture funnel, no free lead magnet. YouTube itself acts as the trust-building mechanism. Viewers watch multiple videos, build familiarity with the product, and convert directly through tracked links. #### **Is SaaS dead in 2026 with vibe coding and AI agents?** No. SaaS is evolving toward agentic interfaces where AI uses software UIs on behalf of humans. But vibe coding a production SaaS replacement ignores the opportunity cost of building, maintaining bugs, and handling customer support. Established SaaS products with real distribution still hold a massive advantage. #### **What is the biggest moat for a SaaS business today?** Distribution. When anyone can clone a product over a weekend with AI coding tools, the differentiator is your ability to reach customers. YouTube, brand trust, and a content library that compounds over time create an acquisition channel that competitors cannot replicate overnight. --- ## Is AI Replacing Marketing Agencies? Why Most are Behind URL: https://ryandoser.com/ai-replacing-marketing-agencies/ Markdown: https://ryandoser.com/ai-replacing-marketing-agencies.md Published: 2026-03-06 | Updated: 2026-03-31 Categories: AI Rabbit Holes > AI is replacing marketing agencies, but not how you think. Here's the inside view from an AI startup founder on what agencies are missing. **AI replacing marketing agencies** is the question every agency owner is quietly Googling right now. I sat down with Josh Geribo, on the founding team of LEO (an AI marketing startup), to get an honest answer from someone actually building in this space. ### **Is AI Replacing Marketing Agencies Right Now?** Short answer: not yet. But the gap is widening fast. Josh put it plainly. Most agencies haven't integrated AI in any meaningful way. They're buried in client work, worried about churn, and don't have a dedicated team to figure out where to start. That's the honest reality from someone actively selling to these agencies every day. According to a [2026 industry analysis](https://www.marketing-interactive.com/by-2026-can-agencies-rewrite-the-playbook-fast-enough-to-survive), agencies face triple pressure from AI, the rise of in-house teams, and industry consolidation. The Omnicom-IPG merger eliminated an estimated 4,000 positions worldwide. This isn't a warning. It already happened. ### **The "Button Clicker" Problem in Marketing Agencies** I've said this for years: there are a lot of button clickers out there. People who log into the ads manager, check a few search terms, make surface-level tweaks, and call it strategy. No real insight. No creative thinking behind the numbers. That job is going away. Josh agreed without hesitation. The manual media buyer who just moves knobs in a platform is being replaced. What survives is the ability to understand your customer and bring real creative instinct to the work. A [Harvard Business Review analysis from 2026](https://hbr.org/2026/02/ai-is-upending-marketing-on-two-fronts) found that AI is eroding the middle layers of marketing fastest, hitting execution-heavy roles like media planners and junior analysts first. The agencies that pull ahead will look more like orchestrators. A senior strategist who understands the full funnel, deploys AI to handle the manual work, and makes decisions based on data no human analyst could pull manually. That's the model Josh is building toward with LEO. I ranked [nine AI agents on whether they can publish unattended](/ai-agent-for-content-creation/) in a previous post if you want to see what this looks like in practice. *Josh Geribo (LEO) on the future marketer: a CMO-level orchestrator who deploys AI to handle the manual work.* ### **Why Context Separates Good AI from Garbage AI** Here's where most marketers fail. They open ChatGPT or Claude, write a sophisticated prompt, and wonder why the output is generic slop. If you're weighing those two options, I compared [switching from ChatGPT to Claude](/switch-from-chatgpt-to-claude/) in a separate breakdown. The answer is always context. Josh described how [LEO](https://www.leoads.ai/) handles onboarding: they scrape a client's website and use it as foundational context for every piece of content the AI produces. That single step closes most "it's not on brand" complaints agencies throw at AI tools. I do the same. Before AI does real work for any client, it needs transcripts, writing samples, a style guide, and documented strategy. Skipping that step means you're amplifying noise, not intelligence. As Josh put it: "You can have a 100-node automation setup, but if you don't understand what good looks like for an email or a blog post, none of that matters." This is also why AI agents get a bad reputation. It's rarely the model's fault. It's a missing context problem. The [marketers winning with AI agents in 2026](https://martech.org/how-ai-agents-will-reshape-every-part-of-marketing-in-2026/) are the ones who invested time upfront in proper context and workflow design. *Ryan and Josh on Claude Code vs LEO: why API reliability and autonomous scheduling matter for agency workflows.* I wrote a full walkthrough on [using Claude Code for marketing](/claude-code-for-marketing/) if you want the hands-on version of what I run on my own accounts. ### **What AI Still Cannot Do in Marketing** Josh didn't sugarcoat it. AI video is still bad. LEO chose to focus only on static ad creatives because reliability matters more than novelty. When you're managing ad spend for clients, "sometimes it works" is not good enough. Beyond video, the deeper issue is emotion. Every piece of content that genuinely breaks through has emotion tied to it. An emotional hook. An image that stops the scroll. A moment of real human connection. AI can assist with everything around that last 10%, but it cannot manufacture the authentic thing. By 2028, Josh predicts that data analyst roles inside ad platforms will be fully automated. [eMarketer's agency research](https://www.emarketer.com/topics/topic/advertising-agencies) backs this up, pointing to AI disruption as one of the forces reshaping the entire agency model. What won't be automated is distribution strategy and genuine community. You can have the most technically advanced AI setup in your niche. If you don't know how to reach people, none of it moves the needle. For a practical starting point, I put together a guide on [AI tools that actually work for small businesses](/ai-for-small-businesses/). ### **The Future Marketer Is an Orchestrator** So what does the marketer who survives look like? Josh described it as a CMO-level thinker who understands the full picture and deploys agents to handle the manual work. They're not clicking buttons. They're setting direction, reviewing AI-generated insights, and making the calls that matter. The agencies building toward this model now will look back in two years and wonder how anyone ran accounts the old way. The ones waiting until AI feels "safe" are already behind. [LEO](https://leoads.ai) is built specifically for this shift, connecting your marketing stack and automating the workflows that eat agency time. ### **Ryan's Final Thoughts** Is AI replacing marketing agencies? Not all of them. The ones being replaced are the ones built on execution without strategy. The ones that survive will be the ones that stop treating AI as a threat and start building it into how they work. If you're a marketer, the skills that protect you are the ones that have always mattered. Know what good looks like. Understand your customer. Bring real creative instinct to the work. Let AI handle the rest. Talk soon, Ryan ### **AI Replacing Marketing Agencies FAQs** #### **Will AI fully replace marketing agencies?** No. AI is replacing specific functions, particularly execution-heavy roles like manual media buying, reporting, and basic content production. Agencies built around strategy, creative direction, and customer insight are much harder to automate. The ones at risk charge primarily for execution with no strategic differentiation. #### **Is AI replacing marketers right now?** Yes, in certain roles. Entry-level and junior positions in sales and marketing saw roughly a 20% reduction in headcount from AI in recent years. Execution roles are most exposed. Senior marketers who own strategy and results are significantly harder to replace. #### **What marketing jobs are most at risk from AI?** Roles centered on manual data analysis, ad platform management, basic reporting, and templated content production are most at risk. By 2028, most in-platform data analyst work is likely to be automated. Creative strategy, brand positioning, and community building remain human-dependent. #### **How should marketing agencies adapt to AI?** Start by identifying which internal tasks are manual and repeatable, then find tools that handle those specifically. Invest time building proper context documents before deploying AI on client accounts. The agencies winning now moved from "we should try AI" to "here is our specific workflow for onboarding, reporting, and creative production." #### **What skills protect marketers from being replaced by AI?** Understanding what good output looks like in your niche. Deep customer insight. Creative instinct. Distribution strategy. Community building. These are the skills AI cannot replicate reliably. Pair those with working knowledge of AI tools and you become very hard to replace. --- ## How to Avoid AI Slop in 2026 (Advice from AI Content Expert) URL: https://ryandoser.com/avoid-ai-slop/ Markdown: https://ryandoser.com/avoid-ai-slop.md Published: 2026-03-06 | Updated: 2026-08-18 Categories: AI Rabbit Holes > Learn how to avoid AI slop in 2026 with real advice from a seven-figure AI content creator. Practical strategies to humanize AI content and build trust. Learning to **avoid AI slop** is the difference between content that builds trust and content that quietly kills your brand. ### **How to Avoid AI Slop: What the Best Creators Actually Do** You've seen it. A LinkedIn post with a hook that reads "not X, not Y, but THIS." A blog post that uses the same five AI buzzwords in every paragraph. A YouTube script with no opinion, no edge, and no reason to exist. That's AI slop. And it's everywhere in 2026. I recently sat down with [Ole Lehmann](https://x.com/itsolelehmann), creator of the AI Solopreneur, 160,000 followers, seven-figure business built on content. His take on AI slop cut straight to it: the worst kind starts before AI writes a word. It starts when someone asks AI what to write about. No point of view. No original thought. Just automated mediocrity posted at scale. ### **What Is AI Slop and Why It Hurts Your Brand** Most people think AI slop is just bad writing. It's not that simple. [AI slop](https://en.wikipedia.org/wiki/AI_slop) was named the 2025 Word of the Year by the [American Dialect Society](https://www.americandialect.org/2025-word-of-the-year-is-slop) and flagged by [Merriam-Webster](https://www.merriam-webster.com/wordplay/word-of-the-year) as one of the defining terms of the era. That tells you how mainstream the problem has gotten. Here's how Ole defined it: AI slop tries to agree with everyone. There's no spice. Nothing interesting. It's not bad enough to call out, but it's not good enough to remember. And because the floor of minimum quality has risen, average is now invisible. Video has the same problem. On my podcast, Aaron Makelky called a bare "edit my video, make it good" prompt the new version of AI slop, and I show [why AI video edits drift into slop](/ai-video-editing/) without direction. Two types worth knowing: - **Full automation slop:** Someone runs a 100-post automation and hits publish without reading a word. Maybe one goes viral. None of them convert. - **Checklist mentality slop:** A real person uses AI but treats content like a task to cross off. Facebook done. Instagram done. No originality, no editing, no thought. Both kill your brand. One just does it faster. *Ryan Doser and Ole Lehmann break down exactly what AI slop is and why it kills brand trust.* ### **AI Content Creation Strategy That Actually Works** Here's the reality: AI is not the problem. How people use it is. Ole's workflow is deceptively simple. He uses voice-to-text tools like Whisper Flow to capture raw ideas throughout his day, thoughts, observations, people he met, products he tested. He rarely types. He just talks. Then AI handles the production. Not the thinking. My own background is in SEO, and I told Ole the same thing applies there. I could spin up an automation that cranks out 100 SEO blog posts a day. Someone is now selling that automation as a product, and [I went through what you actually get for $99 a month](/outrank-review/). That won't move the needle. Someone who actually understands H2 and H3 hierarchy, internal linking strategy, and search intent? They use AI to produce something that ranks and converts. The skill comes first. AI amplifies it. Three things that separate AI content that works from slop: - **Ideas come from you.** Your POV, your experience, your observations. Feed AI your raw voice, not a topic prompt. - **You know what good looks like.** Ole built a list of 13 "slopification markers" to watch for before posting anything AI-assisted. - **You edit with intent.** Read it like a skeptic. If you would scroll past it, start over. If you want a deeper look at how I build AI-powered content systems that don't produce slop, check out my ranking of [which AI agents can actually publish a finished post](/ai-agent-for-content-creation/) and how I approach [Claude Code for marketing workflows](/claude-code-for-marketing/). Repurposing is where slop shows up worst, so that is also where [keeping drafts in your own voice](/ai-content-engine/) matters most. ### **How to Humanize AI Content Before It Goes Live** You have probably read something recently that felt off. Something in your brain flagged it without you being able to say why. Ole can tell when a YouTube script was written by Claude or ChatGPT. He can spot the AI voice clone. Most audiences are developing that same instinct, whether they realize it or not. When someone detects slop, two things happen fast: they lose trust in the creator, and they feel cheated for giving it their attention. That's not something you recover from with a better hook next time. What actually humanizing AI content looks like: - **Start with your voice.** Record yourself talking through the idea. Use that audio as source material. AI cleans the structure. Your personality stays in. - **Cut the tells.** Patterns like "not X, not Y, but THIS" and reflexive triple-item lists are instant slop signals. Learn to spot them and cut them before publishing. - **Add something AI can't.** A result from your own testing. A quote from a real conversation. A contrarian take you've thought through. These are what make content worth reading. The [rise of AI-powered search](https://blog.google/products-and-platforms/products/search/generative-ai-search/) means Google is getting better at surfacing content built on real expertise. Slop gets filtered out faster than ever. First-hand experience in the content is not just good for readers. It's good for rankings. *Ole explains how voice transcription tools like Whisper Flow keep ideas human before AI touches them.* ### **Why Trust Is the Real AI Content Strategy** Ole called it the "trust recession." That framing is accurate. When everything can be automated, text, images, voices, video scripts, the one thing that cannot be faked at scale is a track record of being real. Long-form content and live video are growing right now partly because of AI. People are hungry for something a prompt could not generate. A 10-minute YouTube video builds more trust than a hundred tweets. Ole pointed out something most people miss: YouTube is the second-largest search engine, and its transcripts feed directly into AI models like Google Gemini. According to [research on AI content trends](https://blog.hootsuite.com/ai-content-creation/), creators who publish consistent long-form video are building equity that compounds. A LinkedIn post from last Tuesday is already dead. A YouTube video from two years ago can still send you leads today. The creators who win in the AI era are not running the biggest automations. They're the ones who stayed real when real became rare. For more on building content systems that actually work, see how I handle [AI replacing marketing agencies](/ai-replacing-marketing-agencies/) and my take on [using AI to grow a YouTube channel](/clone-youtube-channel-with-ai/). The quality gate I built to catch this in my own content ships inside my [**AI Content Engine**](https://engine.ryandoser.com/): every draft is checked against slop markers before it reaches you. *Ryan and Ole discuss the "trust recession" and why long-form content is the answer to AI slop flooding feeds.* ### **Ryan's Final Thoughts** **Avoid AI slop** by keeping the one thing AI cannot replicate: your actual point of view. Use AI to produce. Use your brain to think. Feed the machine your raw voice and real experience, then edit with the same standard you'd apply to anything going out under your name. Ole built a seven-figure business on content. His edge was not a smarter tool. It was understanding the craft well enough to know what good looks like, and caring enough to hit that bar every time. That's still the whole game. ### **Avoid AI Slop FAQs** #### **What is AI slop?** AI slop is low-quality content generated by AI without meaningful human input, editing, or original perspective. It reads as generic and agreeable to everyone, devoid of any specific insight. The American Dialect Society named "slop" the 2025 Word of the Year because of how widespread AI-generated filler content has become online. #### **How do I know if my content is AI slop?** Read it out loud and ask: would I scroll past this? Common tells include overused structural patterns like "not X, not Y, but THIS," reflexive triple-item lists, and a complete absence of first-hand examples or opinions. If you can't point to one thing in the piece that came from your own experience, it's likely slop. #### **Can AI-generated content rank on Google in 2026?** Yes, but generic AI content is increasingly filtered out. Google's E-E-A-T framework rewards content showing real Experience, Expertise, Authoritativeness, and Trustworthiness. Content built around first-hand testing, specific results, and genuine expertise will outrank AI slop in search every time. #### **What's the best way to humanize AI content?** Start with your voice before touching AI. Record yourself talking through the idea, use that as your source material, then let AI clean up the structure. After AI produces a draft, read it out loud, cut the structural clichés, and add at least one specific detail, result, or opinion that only you could write. #### **Is all AI content bad?** No. AI is a production tool, not a replacement for thinking. The problem is not using AI. It's skipping the thinking part and letting AI do everything. Creators like Ole Lehmann use AI heavily and build seven-figure businesses. The difference is they bring the ideas, the point of view, and the editorial judgment. AI handles speed and formatting. --- ## 5 Best Ways to Make Money With AI (Advice from AI Millionaire) URL: https://ryandoser.com/best-ways-to-make-money-with-ai/ Markdown: https://ryandoser.com/best-ways-to-make-money-with-ai.md Published: 2026-03-06 | Updated: 2026-04-19 Categories: AI Rabbit Holes, AI Side Hustles > Discover the best ways to make money with AI in 2026. This includes AI education, workshops, communities, automation, SaaS, and more. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* But unlike every other piece of content on this topic, I'm actually going to tell you truth about making money with AI and what to avoid. ### **Best Ways to Make Money With AI in 2026** Sabrina Ramonov is one of the top AI content creators in the world, founder of Blotato, and someone who has actually built a real business using every method on this list. She recently presented at the AI Advantage Summit alongside Tony Robbins and Dean Graziosi, where 100,000 to 150,000 people tuned into the free YouTube Live alone. That doesn't count the VIP Zoom rooms. The demand for AI education is bigger than most people in this space realize. That context matters. Because what surprised Sabrina at that summit reshaped how she thinks about this whole topic. #### **1. AI Education** Sabrina put this first on her list for a reason. She called it the easiest entry point with the highest chance of success. After the AI Advantage Summit, she saw firsthand that the beginner market is far larger than even she expected. Lawyers, accountants, real estate professionals, people from every traditional industry who don't know how to take a screenshot of a ChatGPT prompt, let alone use it. *Sabrina Ramonov Explaining her AI Education Idea* Her exact advice for someone who wants to start in 30 days: open TikTok, find her popular videos, copy the hooks, and post three videos per day for a month. See if you like content creation. Teaching forces you to clarify your thinking, and it helps people at the same time. The "it's saturated" objection doesn't hold up. Step outside the AI bubble, ask your family members, and you'll quickly see most people are still at the beginner level. There are also deep niches within AI education that are wide open. One example of this model working at scale: [Sabrina's YouTube channel](https://www.youtube.com/@sabrina_ramonov) and [her newsletter](https://www.sabrina.dev/) built the audience that eventually supported everything else, including Blotato. #### **2. AI Workshops** If you have any working knowledge of AI tools, even just ChatGPT, you can run a workshop. Sabrina's suggestion for hitting $10K a month fast was direct: go door-to-door to local businesses, offer to show them how ChatGPT works, and do a live demo. That's it. Most employees in most industries are already using AI informally. A workshop gives companies a structured way to get consistent results from tools their people are already reaching for. You're not selling hype. You're reducing risk and wasted time. The pitch is simple. The setup is minimal. You don't need a polished deck or a certification. You need to know one workflow better than the person you're teaching. #### **3. AI Communities** Paid communities create recurring revenue without requiring you to constantly trade time for money. The model works because people aren't just paying for information. They're paying for access to others solving the same problems. My own community, [AI Marketing Insiders](https://www.skool.com/ai-marketing-insiders), runs on Skool with over 500 members. The revenue is predictable month over month. More valuable than the income is what you learn from the community itself. Real questions from real people constantly sharpen your content and product thinking. Joining a few before you launch is the cheapest research you can do, so here are the [AI communities I actually recommend](/best-ai-communities/) and what they cost. Skool handles payments, community structure, and courses in one place. The only requirement is a clear niche and consistent presence. Communities without active hosts don't retain members, which is the core of what [running one actually takes day to day](/how-to-build-an-online-community/). #### **4. AI Automation Services** AI automation freelancers on platforms like [Upwork](https://www.upwork.com/) are billing $60-$150 per hour because they can build systems that solve recurring problems without ongoing manual effort. That's a different value proposition than standard freelance work. Sabrina was direct about the warning here though. A lot of people teaching "AI automation agency" courses make more money from the course than from running an actual agency. Her advice: look at where the person teaching you gets most of their income. If it's the course, that tells you something. *Sabrina Explaining her Content Repurposing Automation* [Blotato](https://www.blotato.com/?ref=rdoser) is a good real-world example of what AI automation can do. It handles social media publishing at scale, built by Sabrina as a tool she needed herself. If you want to see what packaged automation looks like in practice, [Blotato's automation templates](https://help.blotato.com/api/templates) are worth exploring. Build your own automated workflow first. Document it. That documentation becomes your case study and gets you the first client. #### **5. AI SaaS (Vibe Coding)** Sabrina put SaaS last on her list, and she was clear about why. Building a SaaS requires two entirely different skill sets: building the product and building distribution for it. Most people have neither when they start. Her background from a Silicon Valley startup gave her an edge when launching Blotato. She knows most people don't have that context, and she's honest about it. If you don't know what to build, that's a signal you should be consulting or working in the space first, not shipping a product. For what the consulting route looks like with real prices, see [how Corey Ganim runs a no-code AI business](/how-to-start-an-ai-business/). Vibe coding tools have lowered the technical barrier significantly. But a product nobody knows about is still a product nobody buys. The ceiling on SaaS is the highest of the five paths. The timeline is also the longest. Expect one to five years to build something that generates real monthly recurring revenue, not weeks. If you want faster returns, start with education or workshops. Come back to SaaS once you understand the market from the inside. ### **Ryan's Final Thoughts** Sabrina's framework is worth paying attention to because she's built all five of these, not just theorized about them. The common thread across every method that actually works: personal brand forces accountability, and accountability keeps you ethical. Her take on passive income is the most realistic thing you'll hear in this space. Almost everything requires ongoing effort. Plan for one to five years, not one to five weeks. And own your email list. Every platform is rented land. ### **Best Ways to Make Money With AI FAQs** #### **What is the fastest way to make money with AI?** The fastest path is AI education or workshops. If you've been using AI tools for even a couple of months, you know more than most people. Sabrina's advice: post three TikTok videos a day for 30 days copying popular hooks, or go door-to-door to local businesses and demo ChatGPT. Both require zero upfront investment and generate real feedback quickly. #### **Is the AI automation agency model actually worth it?** Be careful here. Sabrina pointed out that most people teaching AI automation agency courses make more from the course than from running an agency. Running an actual agency means walking into a business with disparate systems and being expected to fix everything. It's messier than the courses suggest. That doesn't mean it's not viable, but verify that who you're learning from is actually doing the thing they're teaching. #### **Do you need a technical background to make money with AI?** No. AI education, workshops, and communities require no coding. Even AI automation services can be learned from scratch. SaaS is the one path where some technical familiarity helps, though vibe coding tools have lowered that bar. What matters more is understanding a problem deeply enough to build or teach a solution. #### **How long does it realistically take to make money with AI?** Sabrina's honest answer was one to five years for a real business. Workshops or education content can generate income faster, sometimes in 30 to 90 days. SaaS and communities take longer to build. Anyone promising passive income in weeks is selling you something. #### **What's the best platform to build an AI business on?** Sabrina's answer was none of the social platforms. The best platform is your email list because you own it. You're not dependent on an algorithm or a platform policy change. Social media builds awareness. Email converts and retains. Build both, but prioritize the list you own. --- ## How to Use Claude Code AI Marketing Agents (Your AI CMO) URL: https://ryandoser.com/claude-code-ai-marketing-agents/ Markdown: https://ryandoser.com/claude-code-ai-marketing-agents.md Published: 2026-03-06 | Updated: 2026-03-31 Categories: AI Rabbit Holes, Claude Code > Build a real AI CMO system with Claude Code marketing agents, based on a talk with a Fortune 500 marketer who runs one. Most marketers are using Claude like a fancy search engine. **Claude Code AI marketing agents** are something else entirely. ### **How Claude Code AI Marketing Agents Actually Work** You've probably opened Claude or ChatGPT, typed a prompt, and copy-pasted the result somewhere. That workflow has a ceiling. Claude Code operates differently. It reads and writes files directly on your machine. That single capability changes everything about what's possible. Adam Sandler (not that one) figured this out without a technical background. He's a veteran marketer who ran content at American Express and spent years at Nestle. No programming degree. He taught himself Claude Code and built a working AI marketing system he calls his SLC CMO agent. I sat down with Adam on the AI Rabbit Holes series to break down how it works. Watch it here: The core idea: instead of starting from scratch every session, you build agents that carry context forward. They know your brand, your audience, your past campaigns. The system handles the repetitive work. You do the thinking. ### **The AI CMO: What an Orchestrating Agent Actually Does** Most people hear "agent" and picture something futuristic. The reality is simpler. When you launch Claude Code, it reads your `CLAUDE.md` file. That's just a text file with instructions. You control what it says. That's your agent's starting point. Adam built his CMO agent on top of that foundation. It's a set of instructions that starts each Claude Code session with full knowledge of his marketing context, client goals, and campaign frameworks. Instead of briefing a blank chatbot every time, the agent already knows his business. It handles campaign development: brand campaigns, competitive analysis, social media rollouts, launch sequences. Adam bakes his own marketing instincts into the instructions. When it behaves in a way he wouldn't, he refines it. That's the human-in-the-loop part most AI demos skip. ### **Skills, Sub-Agents, and Context: The Building Blocks of Claude Code** Here's where **Claude Code AI agents** get genuinely useful. Three terms matter most. **Skills** are reusable instructions saved to a file. Build a process once, save it, call it with a slash command. Adam has a skill that scrubs call transcripts of small talk before saving them as context. One command, every time. [My Claude Code Skills Stack](https://skills.ryandoser.com/) has 20+ skills I use daily to automate marketing and content creation with a one time fee and lifetime updates. **Sub-agents** are separate Claude Code sessions your main agent launches automatically. Each gets a fresh context window, does one job, reports back, and disappears. Claude Code can run multiple sub-agents in parallel. Writing 10 blog posts takes the same time as writing one. **Context** is the resource you're managing. Long sessions eat tokens and degrade output quality. Adam's CMO agent has tight instructions for what to read and when. Irrelevant files stay out. Relevant ones load on demand. *Adam's VS Code setup with two Claude Code sessions open: one for his website project and one for his marketing agent.* ### **Real-World Example: Google Analytics MCP Integration** The screen share in the video is where things get concrete. Adam built a custom MCP tool connecting Claude Code to his Google Analytics and Search Console data. From inside VS Code, he dictates one prompt: "Look at my recent Analytics and Search Console performance and recommend 10 blog posts based on what's trending." Claude Code pulls live data and returns 10 recommendations grounded in actual traffic patterns. Not generic brainstorming. Real data. Old workflow: export from Analytics, screenshot charts, upload to a chat window, prompt it, copy the output somewhere. New workflow: one sentence. The loop closes in the same session. From there, he asks Claude Code to write the articles. It already has his brand voice, style guidelines, and site structure loaded. The output reflects his actual brand. *The marketing agent project structure in VS Code, with dedicated folders for agents, commands, skills, memory, and client context.* ### **Getting Started Without a Technical Background** Adam's advice for anyone overwhelmed by the terminal: start with a small research prompt. Pick a competitor. Ask Claude Code to research them and store the output in a structured CSV. That's session one. Next session, analyze trends across the competitors. Session after that, turn those trends into a draft email drip. Each session adds one layer. Adam's comparison stuck with me. Early SEO felt like a technical wall for non-developer marketers. At some point you had to learn what a meta description was. Claude Code is that same moment. The baseline you need is shallower than it looks. One practical tip: use voice dictation. Adam uses [Super Whisper](https://superwhisper.com/). Typing constrains how you think. Talking to Claude Code changes the output quality. It's free at the entry level. *Claude Code's browser control in action, fetching the Viable Edge website to build initial brand context during the onboarding flow.* ### **One Watch-Out Before You Start** Do not chase the bots. Claude Bots, Open Claw, every new agentic wrapper that dropped this week. Without a solid Claude Code foundation and a working skill setup, those tools will eat months of your attention. Start with [Claude Code's overview documentation](https://code.claude.com/docs/en/overview). Twenty minutes of reading. Build the foundation first, then the wrappers actually make sense. ### **Final Thoughts from Ryan** Start small. You don't need to architect the whole system first. Run one research prompt. Save the output. Build on it next session. Adam is the proof. Corporate marketing background. No code. He built a working AI CMO from scratch by iterating. Find him at [The Viable Edge on YouTube](https://www.youtube.com/@ViableEdge), on [X](https://x.com/@TheViableEdge), at [viableedge.com](https://www.viableedge.com/), or on [LinkedIn](https://www.linkedin.com/in/adamsandler/). The gap between marketers using AI as a chat window and marketers running real AI workflows is growing. This is what the second group looks like. ### **Claude Code AI Marketing Agents FAQs** #### **What is a Claude Code AI marketing agent?** A Claude Code AI marketing agent is a customized set of instructions that starts each Claude Code session with pre-loaded brand context, marketing frameworks, and workflow rules. It behaves like a briefed team member, not a blank chatbot. You build it once and refine it as your needs change. #### **Do you need to know how to code to use Claude Code for marketing?** No. Adam built a full AI marketing agent system without a programming background. The learning curve is in understanding context, files, and sessions, not in writing code. Simple research prompts are enough to start. #### **What is an MCP tool in Claude Code?** MCP (Model Context Protocol) is how Claude Code connects to external data sources. Adam's custom MCP integration pulls live data from Google Analytics and Search Console directly into his Claude Code session, no manual export needed. #### **What's the difference between Claude Code agents and sub-agents?** Your main session is the agent. Sub-agents are separate sessions it spins up to handle specific tasks. Each sub-agent gets a fresh context window. Multiple sub-agents run in parallel, which is what makes batch content production fast. #### **How is Claude Code different from Claude or ChatGPT on the web?** Claude Code reads and writes files on your machine and builds on previous work across sessions. Web chat starts fresh every time and lives in the copy-paste loop. That's the core difference. --- ## Why You Should Avoid OpenClaw (Advice from AI Expert) URL: https://ryandoser.com/avoid-openclaw/ Markdown: https://ryandoser.com/avoid-openclaw.md Published: 2026-03-05 | Updated: 2026-03-31 Categories: AI Rabbit Holes > AI experts Gael Breton and Ryan Doser break down why you should avoid OpenClaw, the real security risks, and what to use instead. ### **Why You Should Avoid OpenClaw in 2026** ### **The OpenClaw Hype Cycle (ClawdBot, Moltbot, and Moltbook)** *Gael Breton explaining the OpenClaw hype cycle and why the repeated rebranding from ClawdBot and Moltbot is a red flag worth noticing.* ### **Is OpenClaw Safe? The Real Security Risk** ### **What Gael Breton Uses Instead (and Why)** *Ryan and Gael on why safer, human-in-the-loop AI tools produce better outcomes than autonomous agents like OpenClaw.* ### **Final Notes from Ryan** ### **Avoid OpenClaw FAQs** #### **Is OpenClaw safe to use?** #### **What is the difference between OpenClaw, ClawdBot, and Moltbot?** #### **What are the best OpenClaw alternatives?** #### **Why is OpenClaw getting so much hype?** #### **Should I use OpenClaw for marketing automation?** --- ## How to Use Claude Code for SEO (Rank High on Google) URL: https://ryandoser.com/claude-code-seo/ Markdown: https://ryandoser.com/claude-code-seo.md Published: 2026-03-05 | Updated: 2026-09-30 Categories: Claude Code > Rank on Google using Claude Code as your SEO workflow. The full setup, the tools it calls, and real results from this site with zero backlinks. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* ### **How Claude Code SEO Actually Works** Most AI SEO tutorials show you a tool and stop there. They skip the part where you actually rank. So here is what my setup looks like in practice. I feed Claude Code a YouTube video URL, and it produces a fully optimized blog post in roughly 60 seconds. That post gets published directly to WordPress through an MCP connection. No copying, no pasting, no switching between tabs. The workflow handles everything: heading structure, keyword density, meta descriptions, screenshots from the video, alt text, featured images, and even permalink optimization. All of it runs from a single Claude Code skill file I built called the SEO Blog Post Writer. *A finished blog post created by the Claude Code SEO workflow, published directly to ryandoser.com.* ### **Setting Up Your Claude Code SEO Skill** You need four things before this workflow runs smoothly. First, a [Claude Code](https://docs.anthropic.com/en/docs/claude-code/overview) subscription. I use the Claude Max plan at $100 per month. The Pro plan works for testing at $17 per month, but it may not hold up at scale based on my experience. Second, a Claude Code skill that knows how to write SEO content. Mine includes rules for heading hierarchy, word count limits, keyword placement, image handling, and my personal writing style. You can grab a copy free from my AI Marketing Essentials Guide linked above and then repurpose it with your own voice. [My Claude Code Skills Stack](https://skills.ryandoser.com/) has 20+ skills I use daily to automate marketing and content creation with a one time fee and lifetime updates. Third, an MCP connection between Claude Code and your website. I run WordPress with a plugin called [AI Engine MCP](https://wordpress.org/plugins/ai-engine/). That plugin gives Claude Code direct access to create posts, upload images, and set meta fields without me touching the WordPress dashboard. Fourth, a transcript scraping tool. I use [Blotato](https://www.blotato.com/?ref=rdoser) to pull YouTube transcripts automatically. Their paid plan starts at $29 per month, and if something genuinely does not work, they say to email within 14 days and they will make it right. *The Claude Code SEO Blog Post Writer skill running in VS Code with progress tracking.* ### **Running the SEO Workflow Step by Step** Once everything is connected, the process takes about a minute from start to finish. Open Claude Code in VS Code (or your preferred IDE). Paste a YouTube video URL along with your target keyword and secondary keywords. Add your preferred blog title. Hit enter. Claude Code then scrapes the video transcript through Blotato, analyzes the content, researches competing articles for gaps, writes the full post following your skill rules, extracts screenshots from the video at key timestamps, uploads everything to WordPress as a draft, and sets all Yoast SEO fields automatically. I recommend switching to Sonnet 4.6 for this task. Opus 4.6 works but burns through your usage faster for a job that Sonnet handles well. Also toggle off extended thinking mode to save tokens. One critical note: always save as a draft first. I review every post before it goes live. The system handles structure and optimization, but a human eye catches nuance that AI misses. ### **Real Results from This AI SEO Agent** Here is where most Claude Code SEO content falls short. People show the setup but never show the results. I started testing this workflow about a week before filming the video. At that point, ryandoser.com had roughly ten blog posts and zero backlinks. That is not a site with any domain authority to speak of. Despite that, searching "Claude Code productivity hack" in an incognito window showed my article at position one. Other keywords related to my content were consistently landing on the first page of Google search results. That matters because it proves the system works even without a backlink profile. Google's [E-E-A-T guidelines](https://developers.google.com/search/blog/2022/12/google-raters-guidelines-e-e-a-t) reward firsthand experience and expertise. Blog posts built from real video demonstrations carry that signal naturally. For context, I also manage SEO for a major client where we generate millions of clicks and impressions annually. This is not theory. It is a production-tested system applied to a brand-new domain. *WordPress draft with Yoast SEO and readability both showing green from the automated workflow.* ### **Why This Beats Traditional AI SEO Tools** Standard AI writing tools generate generic content from a prompt. They lack context about your voice, your audience, and your actual experience with the topic. Encoding the plan as a file is the whole point, and it is why I think [the publishing half of SEO content strategy](/seo-content-strategy/) now decides who ranks. A Claude Code SEO skill is different. It carries your writing rules, keyword strategy, heading structure preferences, and publishing workflow in one reusable file. Every post comes out consistent with your brand voice because the skill enforces those constraints automatically. The MCP connection removes the entire copy-paste step. Posts arrive in WordPress with correct permalinks, categories, meta descriptions, and featured images already in place. That eliminates 15 to 20 minutes of manual formatting per article. The video-to-blog repurposing approach adds another layer. YouTube videos provide authentic, firsthand content that search engines reward. Converting that into written form creates content that is both original and backed by demonstrated expertise. ### **Final Thoughts from Ryan** This Claude Code SEO workflow turned a brand-new domain with zero backlinks into a site ranking on the first page of Google within a week. The entire system runs from one skill file, a few MCP connections, and about 60 seconds per blog post. The key is starting with real content from your own YouTube videos, letting the skill handle optimization, and always reviewing before you publish. If you want my exact SEO Blog Post Writer skill and the templates behind this system, grab the free guide linked above. ### **Claude Code SEO FAQs** #### **Do I need a paid Claude plan to use Claude Code for SEO?** Yes. Claude Code requires at least a Pro plan ($17 per month). For publishing multiple posts per week, the Max plan at $100 per month provides more headroom. The Pro plan may hit usage limits quickly if you run the full workflow at scale. #### **Can Claude Code connect directly to WordPress?** It can through MCP (Model Context Protocol). Install the AI Engine MCP plugin on your WordPress site, configure the connection in Claude Code, and it gains the ability to create posts, upload media, and set SEO metadata without manual effort. #### **How long does it take to create one SEO blog post with Claude Code?** The automated workflow runs in about 60 seconds once your skill and MCP connections are configured. Initial setup takes 30 to 60 minutes. After that, each new post requires only a YouTube URL, a target keyword, and a quick review before publishing. #### **Does this work for websites besides WordPress?** The core concept works with any CMS that supports MCP connections. WordPress is the most mature option right now with the AI Engine plugin. If your CMS supports API access, you can likely build a similar integration. Research what MCP tools exist for your platform before committing. --- ## Why Small Businesses Ignoring AI Won't Survive in 2026 URL: https://ryandoser.com/ai-for-small-businesses/ Markdown: https://ryandoser.com/ai-for-small-businesses.md Published: 2026-03-04 | Updated: 2026-03-31 Categories: AI Rabbit Holes > Small businesses using AI are pulling ahead fast. Here's small businesses ignoring AI won't survive in 2026 and beyond. **AI for small businesses** is no longer a future thing. It's already separating the operators who are growing from the ones who are grinding. ### **AI for Small Businesses: What's Actually Working Right Now** Most articles hand you a list of 30 tools and call it a day. That's not useful. What matters is where small business owners are seeing real returns without needing a tech team. I sat down with [Bodhi Gallo](https://www.youtube.com/@BodhiStrykerDigital), co-founder of [Stryker Digital](https://www.stryker-digital.com/), to talk through exactly that. Bodhi works with local service businesses daily. He knows what's working in the real world, not in a webinar. His first recommendation? Start with your inbox. Specifically, Bodhi uses ChatGPT to draft email replies. He screenshots the email, pastes it in, and gets a solid draft in under 30 seconds. No special setup. No workflow to configure. Just a quick win that saves him time every single day. That's the move most people miss. They want a full AI system before they've saved a single hour. Start with one task. Get comfortable. Build from there. *Ryan and Bodhi breaking down the simplest entry point for AI in a small business.* ### **Why Small Business AI Adoption Is So Low** You'd think with all the hype, every small business owner would be all-in on AI by now. They're not. Bodhi sees two camps constantly. The first is overwhelmed. They don't know where to start, so they don't start. The second is skeptical. They've watched too many demos that looked impressive and delivered nothing. Either camp eventually considers paying someone to sort it out, which is its own decision. I put together [the questions worth asking before you hire that help](/ai-consultant-for-small-business/). Both are falling behind. [The U.S. Small Business Administration](https://www.sba.gov/business-guide/manage-your-business/ai-small-business) has published AI guidance for SMBs. That tells you how mainstream this has gotten. It's not experimental anymore. It's operational. The businesses dragging their feet aren't just missing a productivity boost. Competitors are automating follow-up, writing content faster, and responding to leads in minutes instead of hours. Waiting is not a neutral choice. Every month you delay is a month someone else gains ground. #### **The One Foundation You Need Before Anything Else** Bodhi made one thing clear in our conversation: before you add any AI tool, you need a CRM. That's not a glamorous answer. But it's the right one. Without organized customer data, you're automating chaos. If you don't have a CRM today, that's step one. Everything else comes after. ### **The Small Business AI Stack Bodhi Actually Uses** Here's the practical side. Bodhi outlined his core AI setup for local service businesses, and it's simpler than you'd expect. For content and communication, [Bodhi](https://x.com/irentdumpsters) runs a combination of Claude and ChatGPT. Neither does everything perfectly. Claude is stronger for longer-form copy and following brand tone. ChatGPT handles quick tasks and real-time questions well. Both together cost under $50 a month. For calls, he pointed to Open Phone (now rebranded as Quo). It transcribes sales calls automatically. Feed those transcripts to AI, and you can identify objection patterns and sharpen your sales script without guessing. For reviews, he and his team built [Review Rover](https://reviewrover.co/), a tool specifically designed to help local businesses collect and respond to customer reviews with less friction. Reviews matter for local SEO. Automating the ask and the response saves time and improves your average star rating. None of this requires a developer. It does require you to actually set it up. *Bodhi walking through his preferred AI stack for local service businesses.* #### **AI for Local Businesses and the SEO Question** A lot of small business owners are worried AI is killing SEO. The short answer: local SEO is not going away. AI Overviews are reshaping organic traffic. That's real. But local search still runs on proximity, reviews, and relevance. Your Google Business Profile still matters. Your citations still matter. In my field test of 250 AI recommendations for local home-service businesses, almost every pick was a real local business, but [fewer than a quarter came from Google's top 3 map results](/research/does-chatgpt-recommend-local-businesses/). **Small business AI** tools can help you write meta descriptions, generate location-specific content, and respond to reviews at scale. Without hiring a full-time SEO person. If you would rather have someone work through it with you, that is what I do for [businesses around the Des Moines metro](/ai-marketing-consultant-des-moines/) and further afield. The businesses that stay consistent online will out-rank the ones that don't. ### **AI Marketing for Small Businesses: Where the ROI Is Real** Let's talk specifically about **AI marketing small business** use cases, because this is where most owners see results fastest. Content creation is the obvious one. Blog posts, social captions, email newsletters. AI speeds up the first draft. A human still edits and approves. That combination cuts production time by 50-70% for most teams. Less obvious: call analysis. AI can transcribe and score every sales call automatically. You find out which objections come up most, which reps close and why. That data was never accessible to small businesses before. Also underrated: ad copy testing. **AI tools small business** owners can use include Claude and ChatGPT for generating 5-10 headline variations in minutes. Test them. Keep what converts. The pattern is always the same. AI handles the first pass. You handle the judgment call. Human in the loop, always. ### **Final Thoughts from Ryan** So here's the thing. The gap between small businesses using AI and those that aren't is already widening. By 2026, it will be hard to close. Bodhi's advice: start simple. One task. ChatGPT or Claude. One win this week. Build from there. If choosing that one task is the part you are stuck on, I wrote a [90-day plan for picking it](/how-to-implement-ai-in-business/). You don't need a full **AI for SMBs** strategy on day one. You need a starting point. The operators who find one now will look back at 2025 as the year they got ahead. You can follow Bodhi on [LinkedIn](https://www.linkedin.com/in/bodhigallo/) and check out what he's building at Stryker Digital. If this list leaves you sure AI matters but unsure where to start in your own business, that is the gap my [done-with-you AI Concierge](/ai-concierge/) covers: one focused call a month where we set the next improvement up together. ### **AI for Small Businesses FAQs** #### **What is the easiest way to start using AI for a small business?** Start with email. Paste a message into ChatGPT or Claude and ask it to draft a reply. No setup, no integrations. One task, five minutes, immediate time savings. Once that feels natural, add one more use case. #### **Do small businesses actually see ROI from AI tools?** Yes. Content creation and email drafting show returns within the first week. Sales call analysis and review management take a few weeks to show patterns. Businesses seeing the best ROI started simple and built gradually. #### **Will AI replace employees at small businesses?** No. AI handles drafts, analysis, and repetitive tasks. A human still makes judgment calls, approves outputs, and manages relationships. Think of it as a fast first-pass tool, not a replacement. Human in the loop is not optional. #### **What AI tools are best for small business marketing?** Claude and ChatGPT are the two most practical starting points for **AI marketing small business** owners. Claude handles brand-consistent long-form copy better. ChatGPT is faster for quick tasks. For reviews, check out Review Rover if you run a local service business. #### **Is local SEO still worth investing in for small businesses?** Yes. Local SEO is not going away. AI Overviews are changing traffic patterns, but local search still runs on proximity, reviews, and relevance. Use AI to stay consistent on your Google Business Profile. That consistency compounds over time. Worth knowing that the same profile does far less work inside ChatGPT, which [cites directories and forums instead](/how-to-rank-in-chatgpt/). --- ## Custom GPTs vs ChatGPT Projects: Here's What You Should Use URL: https://ryandoser.com/chatgpt-projects-vs-custom-gpts/ Markdown: https://ryandoser.com/chatgpt-projects-vs-custom-gpts.md Published: 2026-03-04 | Updated: 2026-09-25 Categories: ChatGPT > Custom GPTs vs ChatGPT Projects compared. Projects win on organization, memory, and advanced features. See when GPTs still make sense. The debate over **ChatGPT Projects vs Custom GPTs** comes up constantly, and after using both daily for months, I have a clear recommendation. ### **How ChatGPT Projects vs Custom GPTs Actually Work** Most people assume these two features do the same thing. They don't. Custom GPTs are pre-built AI assistants trained on specific instructions, files, and conversation starters. You configure them once. Every new chat starts fresh from those instructions. Projects, on the other hand, are dedicated workspaces. You group related chats, upload files, set instructions, and keep everything organized in one place. Think of GPTs as a single tool. Projects are more like a filing cabinet with a built-in assistant. Update, September 2026: OpenAI is retiring custom GPTs on December 11, 2026. Per OpenAI's [GPT help article](https://help.openai.com/en/articles/8554397-creating-a-gpt), personal plans can no longer create new GPTs and only Business, Enterprise, and Edu workspaces still can, though the pricing page still lists GPT creation on paid personal plans. Projects are open to free users with heavy limitations. *A ChatGPT Project with organized chats sorted by date, making it easy to find past conversations.* ### **Why Projects Beat GPTs for Chat Organization** You've spent 20 minutes scrolling through the ChatGPT sidebar hunting for a conversation you had last week. That's the GPT experience. Inside a project, every chat is grouped and sorted by date. I can pull up what I discussed with a client three weeks ago in seconds. With a GPT, those chats scatter across your sidebar alongside every other conversation. There's no way to filter by GPT. You're stuck searching and hoping the title rings a bell. Projects also let you move existing chats into them. Had a great conversation in the main ChatGPT window? Click three dots, choose "add to project," and it's organized. That flexibility alone saves me time every single day. ### **Sharing and Accessibility: The One Area GPTs Win** Here's where Custom GPTs still have an edge, at least until they retire on December 11, 2026. You can share a GPT publicly with a single link. Anyone on the internet can use it. There's an entire [GPT Store](https://academy.openai.com/public/clubs/work-users-ynjqu/resources/projects) where the community publishes and discovers custom builds. Projects? Unless you're on a Teams or Enterprise plan, you cannot share them. I use projects every day, and this is my biggest frustration with the feature. OpenAI recently added sharing for all paid plans, but it's still limited compared to the open GPT marketplace. So if your goal is distributing a custom AI tool to clients or the public, GPTs remain the only option. For everything else, keep reading. *The Custom GPT editor where you configure instructions, knowledge files, and conversation starters.* ### **Advanced Features That Make Projects Superior** Custom GPTs give you web search, canvas, and image generation. That's it. Projects unlock deep research, ChatGPT agent mode, study and learn, and all the same features GPTs offer. The gap is significant. Running deep research inside a project with full context of your uploaded files produces dramatically better results than starting from scratch in a GPT. Agent mode is the real differentiator here. It lets ChatGPT take multi-step actions, browse the web, and work through complex tasks autonomously. You simply cannot access this from a custom GPT. That limitation alone makes GPTs feel outdated. *Projects unlock deep research, agent mode, and other advanced features not available in Custom GPTs.* ### **Memory, Files, and Knowledge Limits** Projects now support project-only memory. ChatGPT remembers context specific to that workspace without bleeding into your other conversations. GPTs have no memory at all. Every chat starts clean from the base instructions. For knowledge uploads, GPTs cap at 20 files. Projects allow 25 files on Plus and up to 40 on Enterprise. I hit that GPT ceiling fast. One client project already has 17 files uploaded, and I'm still adding to it. Both support the same AI models now. OpenAI recently updated GPTs to allow model switching, something Projects always had. That's no longer a differentiator. ### **What About Third-Party Connections?** GPTs technically support [Actions](https://developers.openai.com/api/docs/actions/introduction/) for connecting to external APIs. But honestly, that feature is complicated to set up and mostly irrelevant now. ChatGPT's developer mode gives you access to hundreds of third-party apps through MCP connectors. Zapier, Notion, Google Sheets, Asana, and more. The catch: developer mode only works in the main ChatGPT window. Neither Projects nor GPTs can access it directly. So the third-party integration argument is a wash. Neither option wins here. Developer mode handles it separately for both. ### **Final Thoughts from Ryan** **Custom GPTs vs ChatGPT Projects** comes down to one question: do you need to share your setup publicly? If yes, use a GPT. For literally everything else, Projects are the better choice. Chat organization, memory, file limits, and access to advanced features like agent mode and deep research all favor Projects. I use them every day for client work, content creation, and personal brand management. If you are weighing this against Anthropic's side of the fence, I ran the same comparison for [Claude skills versus custom GPTs](/claude-skills-vs-custom-gpts/). Don't trust anyone hyping up GPTs or selling pre-built ones like they're the future. Projects have made GPTs mostly obsolete. The sooner you switch, the less time you'll waste hunting through scattered conversations and working without memory. If you're still on the free plan, upgrading to [ChatGPT Plus](https://openai.com/chatgpt/pricing/) for $20 a month unlocks the full power of Projects. That's where the real productivity gains live. ### **ChatGPT Projects vs Custom GPTs FAQs** #### **Can free ChatGPT users create Projects and Custom GPTs?** Free users can now create Projects, but with heavy restrictions on features and usage limits. OpenAI's help center says no personal plan can create new custom GPTs anymore, though its pricing page still lists GPT creation on paid personal plans, and all custom GPTs retire on December 11, 2026. For serious results with Projects, ChatGPT Plus at $20 per month removes most of those limits. #### **Are Custom GPTs going away?** Yes. OpenAI announced on September 11, 2026 that custom GPTs will retire on December 11, 2026, or February 11, 2027 for Enterprise workspaces with an approved deferral. Its migration turns a GPT into a plugin whose instructions become a skill, though custom actions do not transfer. I covered what that means for your options in [my Claude Skills vs Custom GPTs update](/claude-skills-vs-custom-gpts/). #### **Can I use ChatGPT agent mode inside a Custom GPT?** No. Agent mode is only available inside ChatGPT Projects and the main chat window. This is one of the biggest functional gaps between the two options. If multi-step autonomous tasks matter to your workflow, Projects are the only path. #### **Should I migrate my Custom GPTs to Projects?** If you built a GPT for personal use, yes. Recreate those instructions as project instructions, upload the same files, and you'll gain chat organization, memory, and access to advanced features. Public or shared GPTs are not a reason to wait, because every custom GPT retires on December 11, 2026. --- ## This Claude Code Productivity Hack Will Save You Hours URL: https://ryandoser.com/claude-code-productivity-hack/ Markdown: https://ryandoser.com/claude-code-productivity-hack.md Published: 2026-03-04 | Updated: 2026-03-31 Categories: Claude Code > This article explains a Claude Productivity Hack that includes bypassing permissions and running multiple Claude Code tabs at once. The **Claude Code productivity hack** most people overlook isn't a prompt trick. It's two settings buried inside the VS Code extension that completely change how you work. ### **How Claude Code Productivity Actually Breaks Down** You've been there. Claude Code asks for permission. You click yes. It asks again. You click yes again. Ten minutes in, you've approved the same thing six times and your flow is completely broken. This is the default behavior, and it's killing your output. If you're running Claude Code for real work, marketing tasks, content creation, or business workflows, you don't need a babysitter checking in every two minutes. You need it to run. Here's how to fix it. Open a new Claude Code chat inside VS Code, click the slash icon, and type `config`. Select "General Config under Settings." That opens the Claude Code extension settings panel. Find the setting called **Claude Code allow dangerously skip permissions** and check it on. *The "Allow Dangerously Skip Permissions" setting in the Claude Code extension panel.* I know. "Dangerously" sounds alarming. It's not as scary as it reads. If you're instructing Claude Code to delete files or do something destructive, yes, that's a risk. But if you're generating social posts, drafting emails, or running content workflows? The risk is essentially zero. Use your judgment. Once that's enabled, go back to Claude Code. On the bottom left of the chat, you'll see your mode options: plan mode, bypass permissions, ask before edits, edit automatically. Click through until you land on **bypass permissions**. *Switching to bypass permissions mode from the mode selector at the bottom of Claude Code.* From that point forward, Claude Code runs tasks start to finish without stopping to ask. ### **Run Multiple Claude Code Tabs at the Same Time** Here's where the **Claude Code productivity** gains get real. Most people run one Claude Code session at a time. That's a bottleneck you don't have to accept. Go back to that same settings panel. `/config` in a new chat, click "General Config." This time, look for **Claude Code preferred location**. By default it's set to "sidebar." Change it to **panel**. That's it. Once you switch to panel mode, Claude Code lives in tabs at the top of your VS Code window instead of locked to the sidebar. Open a second tab. Open a third. Each one runs independently. Now combine this with bypass permissions. Start a task in tab one. Open tab two, paste a different task, hit send. Both run in parallel, neither waiting for the other. I tested this live in the video above. Gave both tabs the same prompt to generate social media posts from a YouTube video URL. Tab two finished before tab one. Both came back clean with no permission interruptions. *Four Claude Code tabs running simultaneously in panel mode, each processing a separate task.* Think about what that means for batch work. If you have five pieces of content to create, you don't run them one at a time. You open five tabs, start all five, and walk away. Come back to completed drafts. Each tab can run different Claude Code skills for different tasks. [My Claude Code Skills Stack](https://skills.ryandoser.com/) has 20+ skills I use daily to automate marketing and content creation with a one time fee and lifetime updates. ### **What to Know About Usage and Scale** One honest caveat worth mentioning on this **AI productivity hack**: your plan matters. I'm on Claude Max at $100 a month, which gives me more runway than Claude Pro at $20. If you're on a lower tier, you'll hit usage limits faster when running parallel tabs. That's not a reason to avoid this workflow. Just know your ceiling and plan accordingly. The [Claude Code documentation](https://docs.anthropic.com/en/docs/claude-code/overview) is worth bookmarking if you're going deeper on setup. And if you're just getting started with the VS Code extension, [VS Code's AI documentation](https://code.visualstudio.com/docs/editor/artificial-intelligence) covers the basics of how extensions work inside the editor. For context on how permission models work across AI coding tools, [Anthropic's research on Claude's character](https://www.anthropic.com/research/claude-character) is a useful read. It explains why the default permission behavior exists and what the tradeoffs are. The bottom line: bypass permissions removes friction for trusted workflows. Multiple tabs remove the bottleneck of sequential execution. Together, they turn Claude Code from a capable tool into a system that actually scales. ### **Ryan's Final Thoughts** Two settings. That's all this is. Enable bypass permissions for tasks you trust. Switch to panel mode for multiple tabs. Run them in parallel and watch your output per hour go up without adding more hours to your day. If you're using Claude Code for marketing, content, or business workflows, this is the **Claude Code hack** that pays for itself in the first week. You're not waiting on AI anymore. The AI is waiting on you. ### **Claude Code Productivity Hack FAQs** #### **Is it safe to enable "dangerously skip permissions" in Claude Code?** For most marketing, content, and business workflows, yes. The risk only matters if you're asking Claude Code to delete files, modify system settings, or take destructive actions. If you're generating content, drafting posts, or running standard automations, the exposure is minimal. Use your judgment based on what you're actually asking it to do. #### **How do I run multiple Claude Code tabs in VS Code?** Type `/config` in a new Claude Code chat, select "General Config," and find the "Claude Code preferred location" setting. Switch it from "sidebar" to "panel." Your Claude Code sessions will now appear as tabs at the top of the VS Code window, and you can open as many as you need. #### **Does running multiple Claude Code tabs at once use more credits?** Yes. Each tab runs its own session and consumes usage. If you're on Claude Pro ($20/month), you'll hit limits faster than on Claude Max ($100/month). Plan your parallel sessions based on your tier and the complexity of each task. #### **What's the difference between bypass permissions and auto-edit mode in Claude Code?** Auto-edit mode still pauses for certain high-risk actions. Bypass permissions removes nearly all approval prompts entirely, letting Claude Code run a task from start to finish without interruption. Bypass permissions is the more aggressive setting and works best when combined with tasks you've already validated. #### **Can I use bypass permissions and multiple tabs together for batch content work?** Yes, that's the whole point. Start a task in tab one with bypass permissions enabled, open tab two, start another task. Both run simultaneously without interruptions. For batch work like generating multiple social posts, drafting email sequences, or processing several pieces of content at once, this setup is a significant time saver. --- ## How Non-Coders are Winning With AI (Advice from AI Expert) URL: https://ryandoser.com/ai-for-non-coders/ Markdown: https://ryandoser.com/ai-for-non-coders.md Published: 2026-03-03 | Updated: 2026-03-31 Categories: AI Rabbit Holes > A former teacher explains why AI for non-coders means ditching browser apps for IDEs. Real workflows, real time savings, no coding required. The following article explains why**AI for non-coders** is no longer about finding the right chatbot. It's about which tools actually move work forward. ### **AI for Non-Coders: Why IDEs Beat Web Apps** Most people open ChatGPT or Claude in a browser tab, copy something in, paste something out, and call it AI. That's the workflow for roughly 80% of people right now. Aaron Makelky has a different take. A former high school teacher turned marketing manager at [Descript](https://www.descript.com/), Aaron tests no-code AI tools and IDE setups daily. His verdict: the copy-paste browser approach is already obsolete. We talked about where non-technical people are falling behind, what changed when Aaron switched from web apps to an IDE, and which tools actually hold up in 2026. *Ryan Doser and Aaron Makelky discussing why non-coders should move beyond browser-based AI tools.* ### **The AI Workflow That Changed Everything** You've probably spent two or three hours pulling data from different platforms, dumping it into a spreadsheet, and writing up takeaways. That's the manual version most marketers still do every week. Aaron's company ran a training in December 2025 where a software engineer walked the non-technical team through setting up [Cursor](https://cursor.com/) for non-coding work. The task that clicked was a weekly analytics report. Old workflow: download CSVs from X, LinkedIn, and the blog, open a spreadsheet, write the narrative in Notion. New workflow: create a folder on his desktop, drop the files in, open Cursor, point it at the folder, and tell it to find trends and compare against last week. "Something that took two to three hours manually, Cursor could do as well as me. The storytelling, the takeaways -- that's now 15 or 20 minutes. I feel like I had a data analyst on my desktop." The files stay local. You own them. You can run any model against them. You're not copy-pasting into a rate-limited web app and hoping the history is still there. He also ran the same folder through [Google Antigravity](https://antigravity.google/) with Gemini, then had one model critique the other's report. That used to require a dev. *Aaron walking through a real-world Claude Code example: converting a video file without downloading sketchy third-party software.* ### **Claude Code for Non-Coders: It's Not What the Name Suggests** The word "code" in Claude Code stops a lot of people. Aaron's take: "If you're using [Claude Code](https://code.claude.com/docs/en/overview), whether inside Cursor, Antigravity, or VS Code, you're not sitting in a terminal coding like a programmer. It's more of a file management system. You create files, edit files, connect to APIs." He had a video file in MKV format. His software needed MP4. Old move: find a free online converter and hope it's not spyware. New move: open Claude Code, point it at the file, ask it to convert. "All that matters is I open it and it's an MP4 and it works." For **Claude Code for non-technical** users, that's the unlock. You describe the problem. Claude Code figures out the steps. [Aaron's YouTube channel](https://www.youtube.com/channel/UC8vjf5_1lXrXYJfD4dICGRg) shows a lot of this in action. He's also on [X](https://x.com/theaaron) and [LinkedIn](https://www.linkedin.com/in/aaron-makelky-m-a-ed-038b852a3/). ### **Why Skills Beat Custom GPTs for Claude Code for Marketers** Custom GPTs were impressive when they launched. Skills are better for **AI tools for marketers**, and here's why. A skill is a markdown file with instructions for a specific task. It only loads when you call it. A custom GPT pumps all instructions through the system prompt on every message, burning context on rules that don't apply. Second, you can map skills to slash commands. Aaron uses `/meeting-internal` for team updates and `/meeting-external` for client calls. The agent always runs the right script. Third, the file goes anywhere. Aaron put his on GitHub. When Claude hit rate limits, he opened the same zip file in a different IDE and ran the task with Gemini. A custom GPT doesn't travel. I put those two side by side in more depth in my [skills versus custom GPTs breakdown](/claude-skills-vs-custom-gpts/). His advice for getting started: "Open up Claude Code, tell it what you do, what apps you work in, and say come up with ways you can help me. You'll be blown away." One more tool: Aaron uses [Whisper Flow](https://wisprflow.ai/) for voice-to-text across desktop, laptop, and phone. The cross-device sync is what keeps him paying for it over free alternatives. ### **Ryan's Final Thoughts** The skill gap Aaron described is real. Most people are still in a browser, copy-pasting. For daily marketing work, that costs you hours every week. **AI for non-technical** people doesn't mean dumbed-down tools. It means knowing what problem needs solving, pointing the right tool at a local folder, and letting it run. You don't need to write code. You need to stop being afraid of a terminal. Start there. ### **AI for Non-Coders FAQs** #### **Can non-coders really use Claude Code or Cursor?** Yes. Neither requires writing actual code. You describe the task in plain English, point the tool at a file or folder, and it figures out the steps. Aaron Makelky has no CS background and uses Cursor daily for analytics, model comparisons, and file conversions. #### **What is the difference between using AI in a browser vs. an IDE?** Browser tools require manual copy-paste and store your conversations on the company's servers. IDEs like Cursor and Claude Code work with local files directly, let you switch models freely, and keep your data on your own machine. #### **What are the best no-code AI tools for marketers in 2026?** Based on this conversation: Cursor for local file analysis, Claude Code for task automation, Google Antigravity for Gemini-based workflows, Whisper Flow for voice-to-text, and Descript for video work. The common thread is tools that work with files you own. #### **What is a "skill" in Claude Code or Cursor?** A skill is a markdown file with instructions for how an AI agent should handle a specific task. It's portable, model-agnostic, and only loads when called. Map it to a slash command and the agent always runs the right script. #### **Is it safe to use business data in an IDE like Cursor?** Your files stay local rather than going to a web app's servers. That's a privacy advantage over browser tools. Review your IDE's privacy policy and your company's data guidelines before connecting to cloud-based model APIs. --- ## Google Gemini vs ChatGPT: 5 Reasons Why I Prefer Gemini URL: https://ryandoser.com/google-gemini-vs-chatgpt/ Markdown: https://ryandoser.com/google-gemini-vs-chatgpt.md Published: 2026-03-03 | Updated: 2026-09-30 Categories: AI Tool Reviews, ChatGPT > I tested Google Gemini vs ChatGPT side by side. Here are five reasons why I prefer Gemini over ChatGPT for content creation and research. The following article explains why I switched to **Google Gemini vs ChatGPT** for most of my daily AI workflows, and the five specific reasons that drove that shift. ### **Google Gemini vs ChatGPT in 2026: What Actually Changed** Most AI comparison articles read like spec sheets. This one doesn't. I'm still paying for ChatGPT Plus. I use ChatGPT at least once a day. So when I say Gemini has become my default, that's not hype. Gemini 3 changed that. ### **Reason 1: Content Creation (Images, Video, Infographics)** The biggest shift for me came from Nano Banana Pro inside Gemini. Before Gemini 3, AI image generation was mostly fine for generic visuals. Text in images was a mess. Infographics with actual data looked broken. Nano Banana Pro fixed that. I've created full infographics for clients with dense text, branded colors, and accurate icons, and I haven't found a single text error. That's a first in my experience with AI image tools. Real example: I generated an infographic for a client in cybersecurity on age verification laws. One prompt, logo uploaded, zero text errors, and on brand. I did the same for my personal brand using a LinkedIn post as source material. The output looked like something a designer spent an hour on. *Ryan's Gemini Pro interface showing the Create image and Create video tools, with a notification that Nano Banana Pro is now available on Gemini 3 Pro.* Beyond images, Google VO 3.1 is now inside Gemini. Take a Nano Banana image and convert it to a short video clip directly in the interface. It takes about 60 seconds. A subtle animated post performs better than a static one. That's worth the $20/month for [Google AI Pro](https://one.google.com/about/plans) on its own. The free Gemini account gives you Nano Banana Pro. VO 3.1 requires upgrading. ### **Reason 2: Research Quality with Gemini 3** You've probably heard that GPT 5.1 thinking mode is solid for research. It is. But after running the same prompts through both, Gemini 3 consistently gives me more current, more structured output. Part of the reason is plumbing. Gemini can ground its answers in Google Search and answer questions about public YouTube videos. When I asked Gemini to research Warren Buffett's latest energy plays, it pulled from recent earnings calls and financial data. ChatGPT can search the web too, and in my test its research answer was the less useful of the two. I ran that exact prompt. Gemini returned a structured "Power Stack Portfolio" with company analysis and an Export to Google Sheets option. ChatGPT gave me a generic overview. *Gemini 3's research output for a Berkshire Hathaway energy sector analysis, showing a structured portfolio table with ticker symbols, risk levels, and an Export to Sheets option.* One note: toggle "Thinking with 3 Pro" on for serious research prompts. Surface-level questions don't need it. Anything requiring synthesis across multiple sources does. ### **Reason 3: Native Google Workspace Integration** This one is practical, not flashy. ChatGPT has third-party connectors for Google Drive, Gmail, and Google Calendar. They work, mostly. But there's a data question attached to every connection you make with a third-party AI. Gemini's integration is native. Google already has your data. I'd rather use it in their ecosystem than give OpenAI access to my Gmail and Drive files. In practice: I have a Google Drive folder with video transcript files. Instead of opening each file and copying transcripts, I drop the folder URL into Gemini and ask it to repurpose everything into social posts. One prompt, one URL, done. Same with Google Sheets. I paste the URL of my content calendar and ask Gemini to analyze captions and suggest improvements. It reads live sheet data. No copy-paste. The [Google Workspace integration](https://workspace.google.com/blog/productivity-collaboration/google-workspace-gemini) covers Slides, Docs, and Drive. As it expands into Maps and YouTube history, the use cases will only grow. ### **Reason 4: Data Extraction and Summarization** ChatGPT can't natively read a YouTube URL. You copy the transcript, paste it, then ask your question. That adds two minutes to every research task. In Gemini, you paste the YouTube URL directly. I dropped a 2.5-hour Joe Rogan interview with the Nvidia CEO into Gemini and got three timestamped takeaways in under 30 seconds. The same works with PDFs. A 60-page earnings report becomes a structured summary in about the same time. *ChatGPT's Apps and Connectors panel in the 5.1 interface, requiring third-party connections to access Google Drive and Gmail, unlike Gemini's native integration.* According to [Google's Gemini API documentation](https://ai.google.dev/gemini-api/docs), Gemini 3 Pro supports a 1 million token context window. ChatGPT's paid tier tops out around 128K. That gap explains why long-document extraction performs so differently between the two. ### **Reason 5: Google's Long-Term Data Advantage** This one is about where this is heading. VO 3.1 is the best AI video model I've tested. Google has YouTube at its disposal. Billions of hours of training data. No one else has that. Same logic applies to images. Nano Banana Pro leads the market now. Google's image training data, sourced from its search index, compounds that advantage over time. For research, they have [Google Search](https://support.google.com/gemini/answer/13594961) and Google Scholar. Microsoft and Meta compete on compute. Google's data moat is a different category. Unless they self-sabotage, the trajectory points up. That's why I'm investing time in Gemini now. ### **Final Thoughts from Ryan** Not canceling ChatGPT Plus. GPT 5.1 is still solid for writing. Claude Pro leads on long-form. For content creation, research, and data work, I'm defaulting to Gemini 3. The Google integration, 1M token context, Nano Banana Pro, and real-time search data push it ahead. Same $20/month. Test it for a month. ### **Google Gemini vs ChatGPT FAQs** #### **Is Google Gemini better than ChatGPT in 2026?** For content creation, research, and data extraction, Gemini 3 is the stronger choice. The native Google Workspace integration, real-time search, and Nano Banana Pro image model pull it ahead. ChatGPT still leads in creative writing and structured reasoning. #### **Can Gemini read YouTube videos without copying the transcript?** Yes. Paste a YouTube URL directly into Gemini and it reads the transcript natively. ChatGPT requires you to copy and paste the transcript manually before it can process the content. #### **Is Google AI Pro worth $20 a month?** Both plans cost $20/month. Google AI Pro includes Gemini 3.1 Pro, Nano Banana Pro, Veo 3.1, 5TB of Google One storage, and expanded NotebookLM access. For content creators, that bundle is hard to match at the same price. #### **Why does Gemini give better research results than ChatGPT?** Gemini can ground answers in Google Search and read public YouTube videos. ChatGPT can search the web as well. In my own tests on time-sensitive topics like earnings reports and recent news, Gemini's research answers were the more current and more useful of the two. #### **What is Nano Banana Pro?** Nano Banana Pro is Google's AI image model built into Gemini 3. It generates infographics and branded visuals with accurate text. Prior AI image models handled text poorly. That improvement is the main reason I moved visual content creation into the Gemini ecosystem. --- ## How to Switch from ChatGPT to Claude in 5 Minutes URL: https://ryandoser.com/switch-from-chatgpt-to-claude/ Markdown: https://ryandoser.com/switch-from-chatgpt-to-claude.md Published: 2026-03-03 | Updated: 2026-03-31 Categories: AI Tutorials, ChatGPT > Learn how to switch from ChatGPT to Claude in minutes using Anthropic's import tool. Transfer your data, memory, and context with ease. **Switching from ChatGPT to Claude** is now a five-minute process, and Anthropic built a tool that does most of the heavy lifting for you. Here's exactly how this process works. ### **How to Switch from ChatGPT to Claude Using the Import Tool** You've probably accumulated months (or years) of context inside ChatGPT. Preferences, project history, how you like things explained. Starting over with a new AI feels wasteful. Anthropic solved that problem. Head to [claude.com/import-memory](https://claude.com/import-memory) and click "Get started." If you're already logged into Claude, it redirects you straight to the memory settings. If you're not, create a free account first. Memory is available on all paid plans. ### **What Claude Gives You to Copy** Once you're inside the import tool, Claude displays a pre-written prompt. Copy it exactly as-is. This prompt is designed to extract structured memory context from any LLM, including ChatGPT and Google Gemini. Open ChatGPT, paste the prompt in a standard chat, and hit send. Wait for the full response before copying anything. One note: if you're on a paid ChatGPT plan, use a higher reasoning model. Ryan tested this with a standard response and the output was noticeably shallow. OpenAI has little incentive to surface detailed context when they know users are leaving. A thinking-mode model pushes harder on the prompt. If you use a specific ChatGPT Project or custom GPT for certain work, run the prompt inside that project too. You'll get context that's relevant to that workflow, not just your general chat history. ### **The Honest Truth About ChatGPT's Output** Here's what you should expect: disappointment. Ryan ran the prompt inside ChatGPT and the response started from September 2024, even though he had been a paid user since 2022. Over two years of daily usage, essentially missing. That's not a bug. OpenAI is aware that Anthropic built this tool, and they know users are copying this prompt specifically to move away from ChatGPT. The incentive to produce a thorough memory export is minimal on their end. *ChatGPT's response to the memory export prompt, showing timestamped entries starting from September 2024 despite years of prior usage.* So set expectations accordingly. You'll get something, just not everything. What you do get is still better than manually rebuilding your context from scratch. ### **How to Paste the Memory into Claude** Take ChatGPT's response, copy all of it, and head back to the Claude import page. Paste the text into the memory details field, then click "Add to memory." Within a few seconds, Claude processes the input and surfaces a summary. You'll see categories like work contacts, projects, preferences, and a brief interaction history. Click the pencil icon to edit or add anything Claude missed. To verify what transferred, open a new Claude chat and ask: "What did you learn about me?" Claude checks the memory and returns a structured breakdown of everything it stored. It's a clean way to spot gaps before you rely on it for real work. *The full ChatGPT memory export output, including more recent project context, before copying into Claude's memory import field.* ### **How to Do a Full ChatGPT Data Export Instead** The import prompt is fast, but it's not complete. For a proper **transfer of ChatGPT to Claude**, you want your full data export. In ChatGPT, click your profile icon, go to Settings, then Data Controls. You'll see an option to export all your data. Request it. OpenAI emails you a download link, usually within a few minutes. Fair warning: if you've used ChatGPT for a few years, that file is large. Ryan's was massive. The raw JSON export is not something you can just upload directly into Claude. The workaround: use a terminal command to split the JSON file into smaller Markdown files. Once broken up, you can upload those individual files into Claude, Gemini, or NotebookLM without hitting file size limits. Ryan covers this in a [separate tutorial on splitting the ChatGPT export](/transfer-chatgpt-memory/). For most people, the import prompt approach covered above gets you 80% of the way there in five minutes. The full export is worth doing if your ChatGPT history contains specific project context, client details, or workflow preferences you can't afford to lose. ### **Why People Are Making the Move** Claude has been the better model for marketing and content work for a while now. Ryan has used it for at least two years. The reason it's getting mainstream attention now comes down to branding. Claude Code and Claude.ai's recent visibility pushed the name into the mainstream. [Anthropic's Claude platform](https://www.anthropic.com/claude) hit the top of the iOS App Store in late February 2026. Public figures started posting about switching publicly. The reality is, for copywriting, content creation, and general business use, Claude produces better output than ChatGPT with less prompting effort. It follows brand voice guidelines more consistently. It holds context across long conversations without drifting. And it doesn't need five rounds of "make it less generic" before the output is usable. That said, ChatGPT still wins in specific spots: real-time web browsing, quick image generation, and ecosystem integrations through the GPT store. The goal isn't to delete ChatGPT. The goal is to make Claude your primary workspace while keeping the other tools on standby. You can read more about [how Anthropic approaches Claude's values and character](https://www.anthropic.com/research/claude-character) if you want to understand what makes it different at a design level. And if you want to review your own conversation history from Claude going forward, [Anthropic's support page covers how to export your Claude history](https://support.anthropic.com/en/articles/8114494-how-do-i-export-my-claude-conversation-history) the same way you just did with ChatGPT. ### **Final Notes from Ryan** The process to **move from ChatGPT to Claude** takes under five minutes using the import tool at claude.com/import-memory. The output from ChatGPT is incomplete by design, but it's still a useful starting point. For a full migration, pair it with the data export method. Claude is not perfect. No model is. But for marketing and content work, it's the one I'd start with in 2026. If you've been putting off the switch, this is the easiest it's ever been. ### **Switch from ChatGPT to Claude FAQs** #### **How do I switch from ChatGPT to Claude without losing my history?** Use the import tool at [claude.com/import-memory](https://claude.com/import-memory). Copy the provided prompt into ChatGPT, paste the response back into Claude's memory field, and Claude updates its memory automatically. For a complete transfer, also request a full data export from ChatGPT's Data Controls settings and split the file into smaller chunks before uploading. #### **Does Claude have a ChatGPT data import feature?** Yes. Anthropic launched an official import tool at claude.com/import-memory. It generates a structured prompt you paste into ChatGPT (or Gemini). ChatGPT returns your stored context, which you then paste into Claude. The feature is available on all paid Claude plans. #### **Is moving from ChatGPT to Claude worth it for marketers?** For most marketing use cases, yes. Claude handles long-form content, brand voice consistency, and detailed instructions more reliably than ChatGPT in most head-to-head comparisons. It requires less re-prompting to get usable output. ChatGPT still has an edge for real-time search and image generation, so [many marketers run both tools](/is-chatgpt-pro-worth-it/). #### **Can you migrate ChatGPT to Claude for free?** The import tool requires a paid Claude plan. Claude Pro starts at $20/month. The process itself (copy-pasting the prompt and response) costs nothing beyond your existing subscription. If you're on ChatGPT Plus, you're already paying the same amount monthly. #### **What if the ChatGPT memory export is incomplete?** It likely will be. OpenAI's output from the import prompt is often shallow, especially for long-time users. To get more complete data, use ChatGPT Projects or custom GPTs to run the prompt in context-specific areas. For a thorough migration, request the full JSON data export from ChatGPT settings and break it into smaller Markdown files before uploading to Claude. --- ## How to Automate Infographics With AI (From YouTube Videos) URL: https://ryandoser.com/automate-infographics/ Markdown: https://ryandoser.com/automate-infographics.md Published: 2026-03-02 | Updated: 2026-03-31 Categories: AI Automations > Learn how to automate infographics with AI from YouTube videos. This workflow uses Make, Blotato, and OpenRouter, and more. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* This is the exact workflow I built inside Make.com and use in production. ### **How to Automate Infographics with AI** Most tutorials on this topic either require Python skills or give you a list of tools with no workflow. Neither is useful if you want something running today. Here's what I built: a Make.com scenario that watches my YouTube channel, grabs the video transcript, generates a high-quality infographic prompt with AI, creates the infographic inside Blotato, writes a platform-specific social caption, and posts everything automatically across LinkedIn, X, Instagram, and Threads. The setup costs under $30 a month in tools. Each run costs less than a penny in AI credits. That math is hard to argue with. *The complete Make.com infographic automation scenario: YouTube trigger, Blotato transcript fetch, OpenRouter prompt generation, infographic creation, and multi-platform social posting.* ### **The Tool Stack for AI Infographic Automation** You only need three tools: - [**Make.com**](https://www.make.com/) (free to start): your automation platform. [n8n](https://n8n.io) and Zapier work too. - **[Blotato](https://www.blotato.com/?ref=rdoser)** ($29/month, 7-day trial): handles transcript fetching, infographic generation, and social posting via API. - **[OpenRouter](https://openrouter.ai/docs)** (pay-as-you-go): one API key for every major model. Add $5 to $10 in credits to start. Most AI tools are a complete scam. Blotato at $29/month is the exception. The infographic quality, the API access, and the social integrations make it worth it. OpenRouter is the same: one key beats managing twelve. ### **Step-by-Step: Building the Infographic Automation** #### **Step 1: Set Up the YouTube Trigger** In Make.com, start with a YouTube module. Connect your Google account and point it to your channel using the ID Finder. Set the limit to one video per run. This fires every time a new video publishes. You're not limited to your own channel. Any YouTube channel works fine here. #### **Step 2: Fetch the Transcript with Blotato** The second module fetches the video transcript using Blotato's API. Set the source type to URL and map the video ID from the YouTube module into the URL field. Blotato handles the pull automatically. Add a 5-second sleep module after this step. Blotato needs a moment to process before the next module reads the result. Skip it and the automation breaks. #### **Step 3: Generate the Infographic Prompt via OpenRouter** This module sends the transcript and video title to Claude Opus 4.5 via OpenRouter. A detailed system prompt tells the model how to structure an infographic prompt that gets strong visual output from Blotato. You get this system prompt when you download my template. No writing from scratch needed. Opus 4.5 costs less than one cent per run here. I checked my OpenRouter logs during testing: four runs on February 17th, each under a penny. Opus 4.6 is more capable, but for prompt generation at this scale, Opus 4.5 is the right call on cost. #### **Step 4: Generate the Infographic in Blotato** This module sends the generated prompt to Blotato's visual creation API. Select your preferred template from the dropdown. I use the whiteboard template. It produces clean, highly readable visuals that perform on LinkedIn and Instagram. *Blotato's template dropdown inside Make.com, showing the whiteboard option alongside newspaper, AI video, graffiti, and t-shirt styles.* Blotato is actively expanding templates: newspaper, TV wall, constellation, graffiti, t-shirt, and more. Pick what fits your brand. For the infographic description field, use the video title from your YouTube module. For the CTA text, write whatever action you want your audience to take. I use "Follow Ryan Doser for more AI tips." #### **Step 5: The 90-Second Sleep (Non-Negotiable)** After triggering the infographic generator, add a sleep module set to 90 seconds. Blotato needs that time to render the image. Shorten it and the fetch step fails because the image URL won't exist yet. #### **Step 6: Fetch the Finished Infographic and Generate a Caption** This module pulls the completed infographic URL from Blotato using the visual ID from the previous step. That URL is what gets posted to social media. #### **Step 7: Generate a Social Caption** Another OpenRouter module handles caption generation. Same setup as Step 3: system prompt with your brand voice, video title, and transcript, Opus 4.5 as the model. Customize the system prompt with your name and tone. Do not leave my name in there. #### **Step 8: Route and Post Across Platforms** A router module splits the workflow and posts to multiple platforms at once. Clone the posting module for each platform you want. Connect LinkedIn, X, Instagram, or Threads inside Blotato. Each module gets the same caption and infographic URL. ### **Test Before You Go Live** This is the step most people skip. Before running on your real accounts, set up a test route. I use a LinkedIn company page with about 10 followers. Only that test route is active when I first run it. Live routes are disabled. If something outputs wrong, my audience never sees it. Once everything checks out in your Blotato dashboard and OpenRouter logs, enable the live routes. The whiteboard output for my podcast episode "Why Small Business Owners Ignoring AI Won't Survive" was accurate, well organized, and had no typos. The AI-written caption hook: "Small business owners who say AI isn't for me are making the same mistake Blockbuster made about streaming." Under a penny to produce that. *The finished result: a live LinkedIn post with an AI-generated whiteboard infographic and caption, published automatically by the Make.com scenario.* ### **Ryan's Final Thoughts** The whole workflow is eight modules in Make.com, two paid tools, and under $30 a month. What you get is an infographic live on every platform the same day a video goes up. That's content repurposing on autopilot. If you want the same result without Make.com, my [**AI Content Engine**](https://engine.ryandoser.com/) runs it inside Claude or any AI tool from one video, graphics included, rendered in code with your brand colors. As a reminder, you can get the free automation template inside my [**Free AI Marketing Guide**](https://guide.ryandoser.com/). ### **Automate Infographics FAQs** #### **How do I automate infographics from YouTube videos?** Use a Make.com scenario with a YouTube trigger, Blotato for transcript extraction and infographic generation, and OpenRouter for AI-generated prompts and captions. The automation fetches each new video's transcript, creates a custom infographic, and posts it to your social accounts. See the full breakdown above. #### **What tools do I need for AI infographic automation?** Make.com (free), Blotato ($29/month, 7-day trial), and OpenRouter (pay-as-you-go). Total monthly cost is under $35. Each run costs under one cent using Claude Opus 4.5 via OpenRouter. #### **Can I use n8n or Zapier instead of Make.com?** Yes. The same logic applies across any automation platform. Make.com is Ryan's preferred tool because it's free to start, but the Blotato and OpenRouter connections work the same way in n8n and Zapier. #### **How long does it take to generate an infographic automatically?** About two to three minutes per run. The 90-second sleep module accounts for most of that time. Blotato needs it to render the image before the fetch step can pull the URL. #### **What infographic templates does Blotato offer?** As of early 2026, Blotato offers whiteboard, newspaper, TV wall, constellation, graffiti, and t-shirt templates, with more being added over time. The whiteboard template produces the most readable, shareable visuals for LinkedIn and Instagram. --- ## How to Clone a YouTube Channel With AI (NotebookLM Hack) URL: https://ryandoser.com/clone-youtube-channel-with-ai/ Markdown: https://ryandoser.com/clone-youtube-channel-with-ai.md Published: 2026-02-27 | Updated: 2026-03-31 Categories: AI Tutorials > This shows how to clone any YouTube channel with AI using NotebookLM. Step-by-step tutorial to build a source-isolated creator clone. This guide shows you how to **clone a YouTube channel with AI** in minutes using NotebookLM. The result is a research tool that actually sounds like the creator you're studying. ### **How to Clone a YouTube Channel With AI Using NotebookLM** Most people go straight to a custom GPT when they want to study a creator's style. That's the wrong move. Here's the problem with custom GPTs: even when you upload knowledge files, the model still pulls from OpenAI's training data and the broader web. You're not getting a clean signal. You're getting a blend. NotebookLM works differently. It pulls responses only from the sources you load into the notebook. No outside training data, no random web references. Every answer comes with a citation pointing to the exact YouTube video or document it pulled from. That's a big deal when you're trying to clone a specific creator's voice and frameworks. *The NotebookLM homepage at notebooklm.google.com, where you create notebooks and upload your source content.* ### **Two Chrome Extensions You Need First** Before loading any sources, install two Chrome extensions. **Grabbit** lets you box-select multiple YouTube thumbnails and copy all their URLs to your clipboard at once. Without it, you're copying URLs one by one. **WebSync** is a site importer for NotebookLM. Paste your URL list into it and it pulls everything into your notebook automatically. Install both and pin them in your toolbar. Links are in the video description above. ### **Step-by-Step: Loading Sources Into Your NotebookLM Clone** Go to [notebooklm.google.com](https://notebooklm.google.com) and create a new notebook. Name it something obvious, like "Alex Hormozi YouTube Clone." The free plan gives you 50 sources per notebook. The paid [Gemini Advanced plan](https://one.google.com/about/plans) gets you more. For most clones, 50 is enough to start. **Step 1: Pull URLs with Grabbit** Go to the creator's YouTube channel and open Grabbit. Add a new action, set it to copy URLs to clipboard, assign a mouse button, and draw a box over the thumbnails you want. Grabbit copies all those URLs at once. Paste them into a Google Doc first to confirm they copied correctly. Keep batches under 20. More URLs in one batch means more room for errors. **Step 2: Import with WebSync** Open WebSync, select your notebook, paste the URLs, and click Import Video URLs. NotebookLM pulls in each transcript automatically. Ryan loaded 24 Hormozi videos in two batches in about a minute. *WebSync open on Alex Hormozi's YouTube channel with video URLs pasted and ready to import into the NotebookLM notebook.* **Step 3: Add non-video sources** You can go deeper than video transcripts. Ryan added [Hormozi's book](https://www.goodreads.com/book/show/58612786-100m-offers) as a PDF. NotebookLM ingested the whole thing, so the clone can pull from his written frameworks too. PDFs, Google Docs, and web pages all work as sources. ### **What to Actually Do With Your Clone** Once your sources are loaded, start the chat with this prompt: > Act as a chatbot that perfectly mimics the voice, tone, and style of the video creator from these sources. Use their catchphrases, humor, values, and energy. Never break character. From there, put it to work. **Content ideation:** Ask for YouTube video ideas in the creator's style. Add context to get useful output: "My channel is about AI and marketing. Apply Hormozi's style and make it relevant to my niche." Generic prompts get generic results. **Social media posts:** Ask for 10 posts in the creator's voice. Good for studying how they frame value and handle objections. Use it as a framework, not copy-paste content. **Offer and funnel feedback:** Ryan loaded his own business details and asked the Hormozi clone to critique the offer using frameworks from the $100M book. The response cited exact passages from the source. The citations are what make this different. Every answer points to the specific video or page it drew from. *The full prompt set Ryan uses with the NotebookLM clone, covering content ideation, social posts, and offer feedback.* This is a research and ideation tool. You're studying how a creator thinks and what language they use. The human-in-the-loop step is taking those inputs and building something original with them. Using someone else's voice wholesale backfires. Use it for learning. Write in your own voice. ### **Ryan's Final Thoughts** NotebookLM is one of the few AI tools that actually does what it says. Source isolation matters. Citations matter. You can study any creator's body of work in a way custom GPTs can't touch. Start with 20-30 videos from a creator you want to learn from. Add a book if they have one. Then use the clone to think through your own content in their style. The free plan is enough to start today. No credit card needed. ### **Clone YouTube Channel With AI FAQs** #### **How do I clone a YouTube channel with AI for free?** Use NotebookLM. It's free with a Google account. Install Grabbit and WebSync to bulk-import video URLs. The free plan supports 50 sources per notebook. See the step-by-step walkthrough above. #### **Is it legal to clone someone else's YouTube channel with AI?** Using NotebookLM for research on public content is fine. The line gets crossed when you republish that creator's work as your own or impersonate them publicly. Use it to study frameworks and style. Write your own content from those insights. #### **What's the difference between NotebookLM and a custom GPT for this?** A custom GPT still pulls from OpenAI's training data even with uploaded files. NotebookLM is source-isolated. Responses come only from what you load in, and each one cites the exact source. That makes it more reliable for studying a specific creator's voice. #### **How many videos do I need for a good clone?** 20-30 is a solid start. You can mix video transcripts with PDFs at the 50-source limit. Focus on the creator's most representative work first, not just their most recent. #### **Can I use NotebookLM to clone my own YouTube channel?** Yes. Load your own videos and use the clone to generate content ideas or draft posts in your own voice. It becomes a searchable, citable version of your own body of work. --- ## How to Transfer ChatGPT Memory to Gemini or Claude URL: https://ryandoser.com/transfer-chatgpt-memory/ Markdown: https://ryandoser.com/transfer-chatgpt-memory.md Published: 2026-02-27 | Updated: 2026-03-31 Categories: ChatGPT > Learn how to transfer ChatGPT memory and your conversation data to NotebookLM, Claude, or Gemini using a one-shot terminal command. **Transfer ChatGPT memory** without losing three-plus years of conversation history. Here's exactly how. ### **How to Transfer ChatGPT Data Step by Step** You've probably built up months (or years) of useful context inside ChatGPT. Custom instructions. Writing style preferences. Business context. It's sitting in a 247MB JSON file you've never looked at. If you're moving to Claude, Gemini, or [Google NotebookLM](https://notebooklm.google.com/), you don't have to start from scratch. You just need to know how to get that data out in a usable format. ### **Step 1: Export Your ChatGPT Data** Go to ChatGPT and click your profile icon in the bottom left. Select Settings, then Data Controls. You'll see an Export Data button. Click it, confirm, and OpenAI will send a download link to your email. Open that email and click Download Data Export. A zip file lands in your Downloads folder. On Mac, double-click it to unzip automatically. Once it's done, rename the unzipped folder to exactly "chatgpt data" (no caps, no hyphen). That name matters for the next step. Inside that folder, you'll see a file called `conversations.json`. That's your entire chat history. The problem? It's massive. At 247MB, no AI platform can process it as a single file. ### **Step 2: Split the JSON Into Usable MD Files** This is where most guides stop. They tell you to export but don't explain what to do with a 247MB file that won't upload anywhere. The fix is a one-shot terminal command that splits `conversations.json` into separate Markdown files. Credit to [Corey McClain](https://www.youtube.com/@iamcoreymcclain) for the original command. You can find it linked in Ryan's video description. Open Terminal on Mac (Windows users will need to find an equivalent). Paste the command and hit return. When it finishes, you'll see "done" in the terminal output, and a new folder called "notebook lm ready" will appear inside your Downloads folder. That folder contains 14 separate MD files covering your full conversation history. Drag it to your desktop for easy access in the next step. ### **Step 3: Upload to NotebookLM** Here's why [NotebookLM](https://notebooklm.google.com/) is the right starting point instead of going straight to Gemini or Claude. NotebookLM extracts data from your sources verbatim. It doesn't mix in outside training data or internet information. When you ask it something, it pulls answers directly from your uploaded files. That matters when you want to analyze your own conversation history without AI hallucinating additions. Open NotebookLM and create a new notebook. Name it something like ChatGPT Data. Click Add Sources, then Upload Sources, and select all 14 MD files from your desktop folder. Upload time varies based on file size, but it's manageable. Once they're uploaded, you can start chatting with your own history. A simple prompt like "Act as a chatbot that perfectly mimics the voice, tone, and style of the person from the sources" gets you going immediately. NotebookLM will cite specific conversations as it responds. You can also use NotebookLM's other output formats: audio overviews, infographics, slide decks, flashcards. Your chat history becomes a fully searchable knowledge base. ### **Step 4: Connect NotebookLM to Gemini or Claude** NotebookLM's built-in chat runs on Gemini Flash, not the more advanced Gemini Thinking or Pro models. To use your full chat history with a stronger model, you need to link it. Inside [Google Gemini](https://gemini.google.com/), click Add Files, then select NotebookLM. Find the notebook you just created and click Add. Switch your model to Gemini Thinking or Pro. Now you're running a top-tier model against your full ChatGPT history. One practical limit: Gemini accepts up to 10 file attachments per chat window. NotebookLM sidesteps that cap, which is the real reason to route through it first. For Claude, the process is more direct. Claude accepts all 14 MD files at once without hitting Gemini's 10-file limit. Create a Claude Project, upload your files, and you're done. What can you actually do with this? One high-value use case: paste a Brand DNA construction prompt into Gemini with your notebook attached. Gemini will generate a personal brand style guide based on three-plus years of your writing. Tone, structure, word choice, reading level. All pulled from your actual work, not guesswork. That output is useful for training AI agents in [Claude](https://www.anthropic.com/claude), building automation modules in Make or Zapier, or setting up a Google Gem that writes in your voice from day one. ### **Step 5: Export Claude Data Too** Worth noting: you can run this same export from Claude. Click your icon in the bottom left, go to Settings, then Privacy, and select Export Data. Claude will email you a zip file with your full conversation history. The same terminal command that splits ChatGPT's JSON will work on Claude's export. If you're a heavy Claude user and want to move workflows to Gemini or a new tool, this is how you do it without starting over. ### **Final Thoughts from Ryan** The point isn't to abandon ChatGPT out of frustration. The point is that your conversation history has real value, and you shouldn't leave it locked in a platform you're using less. Three-plus years of context, writing patterns, business decisions, and problem-solving is sitting in that JSON file. Once you move it into NotebookLM, Gemini, or Claude, it becomes an active asset instead of a forgotten archive. The process takes about 20 minutes. The terminal command is the only mildly technical part, and it's a copy-paste job. ### **Transfer ChatGPT Memory FAQs** #### **Can you transfer ChatGPT memory automatically?** No automatic tool exists for this yet. The process requires manually exporting your data from ChatGPT's settings, splitting the conversations.json file using a terminal command, and uploading the resulting MD files to NotebookLM, Claude, or Gemini. It takes around 20 minutes and is mostly copy-paste work. #### **How do I transfer ChatGPT data to Claude?** Export your ChatGPT data from Settings > Data Controls > Export Data. Unzip the file, rename the folder to "chatgpt data," and run the one-shot terminal command to split conversations.json into MD files. Then create a Claude Project and upload all 14 MD files directly. Claude accepts the full batch without a file cap. #### **How do I transfer ChatGPT memory to Gemini?** Follow the same export and split process, then upload the MD files into a NotebookLM notebook. Inside Google Gemini, click Add Files > NotebookLM, select your notebook, and switch to Gemini Thinking or Pro. This routes around Gemini's 10-file-per-chat limit and gives you access to stronger models. #### **How do I transfer ChatGPT memory to NotebookLM?** After exporting and splitting your ChatGPT data into MD files, create a new notebook in NotebookLM and upload all files as sources. NotebookLM will index everything verbatim, letting you query your full conversation history without mixing in outside training data. #### **What is the conversations.json file in ChatGPT data export?** It's a single file containing your entire ChatGPT conversation history. It's typically too large (200MB or more) to upload directly to any AI platform. The terminal command splits it into smaller MD files that NotebookLM, Gemini, and Claude can each process. --- ## How to Use Claude Code for Marketing (Beginners Guide 2026) URL: https://ryandoser.com/claude-code-for-marketing/ Markdown: https://ryandoser.com/claude-code-for-marketing.md Published: 2026-02-26 | Updated: 2026-08-29 Categories: Claude Code > Learn how to use Claude Code for Marketing with zero coding. Skills, folder structure, and thumbnail generation in this step-by-step guide. **Claude Code for marketing** sounds technical. It's not. I use it every single day for copywriting, content creation, email drafts, and even generating YouTube thumbnails. Zero coding required. ### **How Claude Code for Marketers Actually Works** Most people hear "code" and assume they need a computer science degree. The name is misleading. Claude Code runs inside a free app called VS Code, and you interact with it by typing plain English. No programming languages. No command-line wizardry. Just conversation with an AI that can read your files, follow your brand guidelines, and produce real marketing assets. The difference between Claude Code and regular Claude chat? Claude Code lives inside your workspace. It reads your folders, references past work, and modifies documents on the fly. Regular chat forgets everything the moment you close the tab. ### **Setting Up Claude Code (5 Minutes, No Coding)** You might expect a painful install process. It takes less time than brewing coffee. Here's the full setup: - Download [VS Code](https://code.visualstudio.com/) (free, works on Mac and Windows) - Create a dedicated folder on your desktop for all marketing work - Open that folder inside VS Code - Search "Claude Code" in the Extensions tab and install the official extension by [Anthropic](https://www.anthropic.com/) - Connect your paid Claude subscription That's it. You're ready to start prompting. One honest note on pricing. Claude Pro at $17/month gives you access. But after months of daily use, the $100/month Max tier is where the real value lives. Extended thinking mode, longer sessions, and higher usage caps make a measurable difference when you're running content workflows at volume. ### **Why Folder Structure Makes or Breaks Your Results** This one setting change cuts your output quality in half if you skip it. Claude Code reads every file in your workspace. A messy folder means messy context. Organized folders mean Claude pulls the right references every time. Here's how I structure mine: - **Marketing/** (clients, email, SEO, social media) - **Skills/** (writing style guides, image generation rules, anti-slop filters) - **YouTube/** (thumbnails, podcast assets, video packaging) - **Community/** (Skool resources, member content) Every subfolder serves a purpose. When I ask Claude Code to draft a LinkedIn post, it automatically finds my social media skill file, reads my anti-slop rules, and produces output that matches my voice. No re-explaining. No copy-pasting brand guidelines into every prompt. That Skills folder is where most of the leverage ends up living. I've documented [the ten marketing skills I actually run in production](/best-claude-marketing-skills/) for SEO, email, social, and video, and a separate set built specifically for [the SEO jobs an agency would bill you thousands for](/claude-skills-for-seo/). I've spent hours refining this structure. The payoff compounds with every task. [My Claude Code Skills Stack](https://skills.ryandoser.com/) has 20+ skills I use daily to automate marketing and content creation with a one time fee and lifetime updates. ### **Claude Code Skills: The Feature That Changes Everything** You've probably used custom GPTs or Claude Projects. Skills are similar in concept but radically different in practice. A skill is a markdown file that tells Claude Code how to handle a specific task. Voice guidelines, formatting rules, tone preferences, output structure. All codified in one document that gets referenced automatically. Here's what makes skills powerful for Claude Code marketing workflows. When Claude produces an output you don't love, you tell it what went wrong AND ask it to update the skill file. The correction is permanent. That mistake never happens again across any future session. I told Claude Code to stop using em dashes in my social posts. It patched the skill file instantly. Now every post, email, and blog draft follows that rule without me mentioning it. Building a skill takes minutes. Paste the [Claude Skills documentation](https://docs.claude.com/en/docs/claude-code/skills) into a conversation, describe your task and preferences, and save the output as a .md file. Drop it into your skills folder and you're done. If you'd rather start from something that already works, I've broken down [the eight skills worth installing first](/best-claude-skills/), including which ones are free and which are worth paying for. ### **Generating YouTube Thumbnails With Claude Code** Most tutorials about Claude Code for marketing stop at text generation. But I'm using it to create visual assets too. By pairing Claude Code with Google's Nano Banana Pro API through [OpenRouter](https://openrouter.ai/), I generate YouTube thumbnails directly from my project folder. It pulls my thumbnail skill, headshots, and logos from asset folders, then produces two variations in about 60 seconds. The results aren't always perfect on the first pass. Sometimes headshot placement needs work. My current workflow: let Claude Code generate the background, text overlays, and logo placement. Then I finish in Canva with a pre-cut headshot PNG. That extra 30 seconds produces a polished final thumbnail. The key here is giving Claude Code enough visual context. I uploaded my five best headshots, brand logos for tools I review, and 15+ thumbnail examples from my channel. The more reference material, the better each generation gets. ### **Ryan's Final Thoughts** Claude Code for marketing is not a developer tool with a marketing use case bolted on. For me, it's become the center of my daily content production. Skills that learn from mistakes, persistent workspace context, and real asset generation beyond just text. The setup takes five minutes. The learning curve is a conversation. If you can type a prompt, you can run Claude Code. ### **What to Learn Next in Claude Code** The setup above gets you working. Below is the order I would learn things in if I were starting over, because most people burn a month on the wrong part. **First, decide if this is even your tool.** If you are not sure Claude Code is even the right surface, [Claude chat vs Cowork vs Code](/claude-ai-vs-cowork-vs-code/) covers when to graduate from one to the next. The case for bothering at all is in [why marketers should use Claude Code](/why-marketers-should-use-claude-code/), and a business owner's take is in [this interview](/claude-code-for-business-owners/). **Next, stop wasting money.** Model choice is the biggest lever nobody touches. [Which Claude model to use](/which-claude-model-to-use/) maps Fable, Opus, Sonnet, and Haiku to real jobs with the token costs attached, and [ten usage tips](/claude-code-usage-tips/) covers the rest. If you want models outside Anthropic's lineup, [OpenRouter](/claude-code-openrouter/) gets you GPT and Gemini from the same window, and [running Codex alongside Claude Code](/claude-code-and-codex-together/) is the split I settled on. **Then connect it to the tools you already pay for.** That is what [MCP setup](/claude-code-mcps/) is for. From there the workflows get real: [the SEO workflow I ran on this site](/claude-code-seo/), [pulling keyword data without paying for a tool](/claude-code-keyword-research/), [a posting agent that writes and schedules](/claude-code-social-media/), [turning one video into a publish-ready blog post](/claude-code-repurpose-youtube-videos/), and [exporting LinkedIn post data to a CSV](/scrape-linkedin-profiles-claude-code/). **Once that works, ship something a customer sees.** [Landing pages with no coding](/claude-code-landing-pages/), then [the conversion formula and paid-ads playbook](/ai-landing-pages/) I use, because generating a page is the easy half. Whole sites are covered in [building websites with Claude Code](/vibe-code-websites-claude-code/). For visuals, [Nano Banana](/nano-banana-claude-code/) covers image generation with a real cost breakdown, and [Seedance, Veo and Kling](/claude-code-ai-video/) run through the same OpenRouter connection. **Last, make it run without you.** [Agent teams](/claude-code-agent-teams/) splits one job across parallel agents and covers the cost tradeoff, [marketing agents](/claude-code-ai-marketing-agents/) is the same idea shaped around a Fortune 500 marketer's org chart, and [autoresearch](/claude-code-autoresearch/) patches your skill files after each run so you stop fixing the same mistake twice. Two smaller things that save real hours: [running several Claude Code tabs at once](/claude-code-productivity-hack/), and [ASCII planning, a Gemini workhorse and a Codex review pass](/claude-code-hacks/). If you want the tactics without the Claude Code framing, that is [five AI marketing hacks](/ai-marketing-hacks/). ### **Claude Code for Marketing FAQs** #### **Do I need coding experience to use Claude Code for marketing?** No. Despite the name, Claude Code requires zero coding knowledge. You interact entirely through plain English prompts inside VS Code. The setup process is five steps, all point-and-click except for connecting your Claude subscription. #### **How much does Claude Code cost for marketers?** Claude Pro starts at $17/month and gives you basic access. Upgrading to the $100/month Max tier unlocks significantly more usage, which matters for daily output. API-based pricing through Anthropic Console exists but gets expensive fast for heavy users. #### **What's the difference between Claude Code and regular Claude chat?** Claude Code operates directly in your project folder. It scans directories, references skill files, edits documents live, and preserves full context between sessions. The standard web chat is stateless. It loses everything when you close the browser and has no access to local files. #### **Can Claude Code generate images for marketing?** Yes. By connecting Google's Nano Banana Pro through OpenRouter, Claude Code produces thumbnails, social graphics, and visual assets. Output quality depends on your reference images, skill file detail, and prompt clarity. #### **What are Claude Code Skills and why do marketers need them?** Skills are markdown files that store your preferences, voice guidelines, formatting standards, and task-specific instructions. They act as permanent memory for Claude Code. When you correct a mistake and patch the skill, that fix carries forward into every future session. For marketers running repetitive workflows, skills eliminate re-prompting entirely. --- ## How to Use Claude Code Agent Teams in 10 Minutes URL: https://ryandoser.com/claude-code-agent-teams/ Markdown: https://ryandoser.com/claude-code-agent-teams.md Published: 2026-02-25 | Updated: 2026-07-06 Categories: Claude Code > Learn how to set up Claude Code agent teams for real content workflows. Includes cost tradeoffs, real output examples, and MCP publishing. *Disclosure: some links in this post are affiliate links. If you buy through them I may earn a commission at no extra cost to you. I only recommend tools I actually use. [Full disclosure](/disclosure/).* ### **How Claude Code Agent Teams Actually Work** ### **Setting Up Agent Teams (Step Zero)** ### **A Real-World Agent Team Use Case** > *"Before writing, each agent should read the full transcript and identify the three most compelling insights. Have them share chosen insights with each other so no two platforms lead with the same angle."* #### **What the Output Looked Like** ### **The Cost and Speed Reality** ### **Taking the Output Further with Blotato** ### **Ryan's Final Thoughts** ### **Claude Code Agent Teams FAQs** #### **What is the difference between Claude Code agent teams and subagents?** #### **How do you set up agent teams in Claude Code?** #### **Are Claude Code agent teams expensive to run?** #### **Can I check on agents while they are running?** #### **What is the best use case for Claude Code agent teams?** --- ## This Claude Code Skills Hack Will 10x Your AI Results URL: https://ryandoser.com/claude-code-skills-hack/ Markdown: https://ryandoser.com/claude-code-skills-hack.md Published: 2026-02-25 | Updated: 2026-03-31 Categories: Claude Code > Learn the Claude Code Skills hack that changes your AI output quality. Personalize skill files with your own context for better results. The **Claude Skills hack** that actually changes your output quality isn't about prompting harder. It's about making downloaded skills yours before you use them. ### **How the Claude Skills Hack Actually Works** Most people grab a skill file, drop it into Claude Code, and wonder why the results feel generic. That's not a Claude problem. That's a context problem. Skill markdown files are SOPs. They tell Claude how to approach a task, what structure to follow, and what quality looks like. But they're written for everyone, which means they're tuned for no one. A LinkedIn post writer skill doesn't know your voice. A front-end design skill doesn't know your brand fonts or style guide. Without that extra layer, you're getting average outputs from a tool that's capable of much more. Here's the fix: upload the skill file you want to use, add your own examples and context, and tell Claude to rewrite the skill around your style. The result is a personalized skill that produces outputs that actually sound like you. ### **What Goes Into a Good Claude Code Skills Hack** You need three things to pull this off. First, the original skill file. That could come from [Anthropic's official skills marketplace](https://claude.com/skills), another creator, or a community repository. The source doesn't matter much. The starting point is a working skill, not a blank page. Second, a repurposing prompt. This tells Claude what you want it to do with the skill. You're asking it to rewrite every instruction, template, and example to match your tone, style, and voice while keeping the structural best practices intact. You can find a ready-to-use version of this prompt in my Free AI Marketing Essentials Guide. Third, your examples. This is where most people underdeliver. Paste in your highest-performing posts, your best emails, your actual copy. The more examples you give, the more Claude can pattern-match your voice. Five examples beat one. Ten beat five. According to [Anthropic's official Skills documentation](https://support.claude.com/en/articles/12512180-using-skills-in-claude), skills work by injecting specific context and instructions into Claude's workflow. That architecture is exactly why personalization matters so much. The skill is the frame. Your context is what makes it sharp. [My Claude Code Skills Stack](https://skills.ryandoser.com/) has 20+ skills I use daily to automate marketing and content creation with a one time fee and lifetime updates. ### **The Live Example: LinkedIn Post Writer** Here's what the process looks like in practice, straight from the video. Start by downloading a LinkedIn post writer skill. Open a fresh chat in Claude Code. Drag the skill markdown file directly into the chat window. Then paste your repurposing prompt and your best LinkedIn post examples into the same message. Claude reads the original skill, processes your examples, and rewrites the file. What comes back isn't just a renamed copy. In the video, the rewritten skill included changes to the voice section, post structures, hook rules, closing lines, formatting, link guidelines, and the recursive quality loop. It stripped out generic engagement questions that didn't match the writing style and replaced them with patterns pulled from the actual example posts provided. That's the [Claude Code skills](https://code.claude.com/docs/en/skills) system working as designed. The skill file is the skeleton. Your examples give it a personality. #### **One Extra Tool Worth Having** If you want to streamline this further, use a skill creator skill. This is a dedicated skill file for building other skills. It handles the structure and formatting automatically, so you don't have to think about how to write a valid skill file from scratch. Ryan's skill creator skill is free in the AI Marketing Essentials Guide. Once you have it, the repurposing workflow becomes a standard loop: download skill, run repurposing prompt, save the new file, repeat for the next task. ### **Why Generic Skills Fail (And What to Do Instead)** You're going to see more skill files released in 2026. Anthropic is shipping their own. Creators are packaging theirs. Companies will start offering skills as part of their toolkits. The reflex is going to be: download, upload, use. That reflex is wrong. A front-end design skill built for a SaaS company doesn't know your color palette. A content repurposing skill built for a news publication doesn't know your newsletter audience. Without your context, those skill files produce outputs that are structurally sound but completely off-brand. This Claude Skills tip applies to every skill you touch: treat downloaded skills as drafts, not finished tools. Personalize before you deploy. The [Claude Code documentation](https://docs.anthropic.com/en/docs/claude-code/skills) covers how skills load and activate, but it won't tell you this. Generic in, generic out. The fix takes about ten minutes. You upload the file, paste your examples, let Claude rewrite it. What you get back is a skill tuned to your actual workflow, not someone else's. ### **Ryan's Final Thoughts** Skills are one of the most underrated features in Claude Code. They work. But they only work at full power when they know who you are. That file is also what separates the agents that hold your voice from the ones that forget it, which is how I ended up ranking [nine content creation agents on what they can actually publish](/ai-agent-for-content-creation/). The Claude Skills hack covered in this post isn't a workaround. It's how the system is supposed to function. Every skill file you find online is a starting point. Make it yours before you use it. That extra ten minutes of setup pays back every time the skill fires. If you're building out your Claude Code skill library and want a shortcut, the [AI Marketing Essentials Guide](https://guide.ryandoser.com/) has the repurposing prompt, the skill creator skill, and a few other skills ready to download. Start there. ### **Claude Skills Hack FAQs** #### **What is the Claude Skills hack for better outputs?** The hack is simple: don't use downloaded skill files as-is. Upload the skill to Claude Code with a repurposing prompt and your own writing examples. Claude rewrites the skill around your voice and style. The result is a personalized version that produces outputs that sound like you, not a generic template. #### **Do I need to know how to code to use Claude Code skills?** No coding required. Skills are markdown files, which are plain text files with simple formatting. You create them, save them, and Claude reads them. The entire process shown in the video involves dragging a file into a chat window and typing a prompt. #### **Where can I find Claude skill files to download?** [Anthropic's skills marketplace](https://claude.com/skills) is the official starting point. You can also find community-built skills on GitHub and from creators who share them publicly. Ryan's AI Marketing Essentials Guide includes a few ready-to-use skills for marketers and content creators. #### **What examples should I include when personalizing a skill?** Your best-performing content. For a LinkedIn skill, paste your highest-engagement posts. For an email skill, paste your best-converting emails. The more examples you provide, the more Claude can identify your patterns. Aim for at least five examples. Ten is better. #### **How is a Claude skill different from a regular prompt?** A prompt gives Claude instructions for one task. A skill is a persistent markdown file that loads into Claude's context every time it's triggered. Skills can include voice guidelines, structural templates, quality checklists, and recursive improvement loops. They're reusable, shareable, and much more powerful than one-off prompts. --- # Original research ## Does ChatGPT Recommend Local Businesses? 250 AI Picks Tested URL: https://ryandoser.com/research/does-chatgpt-recommend-local-businesses/ Markdown: https://ryandoser.com/research/does-chatgpt-recommend-local-businesses.md Author: Ryan Doser Published: 2026-10-07 | Updated: 2026-10-08 Type: Field test > Does ChatGPT recommend local businesses that exist? A 2-city test of 4 AIs: nearly all picks were real, under a quarter were Google's top 3. Data downloads: https://ryandoser.com/research/does-chatgpt-recommend-local-businesses/ (CSV and JSON links at the top of the page). Free to use with a link to the page. **97.6%** of the 250 AI recommendations were real businesses serving the metro area **22.8%** were in Google's top 3 map results. Given how many businesses each answer named, the most possible was about 56% **0 of 12** questions where all four AIs listed the same business first **2 of 250** recommendations failed outright when re-checked against live listings ### **Does ChatGPT Recommend Local Businesses That Actually Exist?** Almost always, in this test. Each finding below stands on its own, so you can quote any one of them with its source. Key findings - In a two-city test on October 7, 2026, 97.6% of 250 local business recommendations from ChatGPT, Claude, Gemini and Perplexity were real businesses serving the metro area, including 98.3% of ChatGPT's 58 picks. - In the same two-city test, only 22.8% of the 250 AI recommendations were in Google's top 3 map results for the matching search, out of a possible 56.4%. ChatGPT matched most often, at 31.0% of its picks. - Across 12 local home-service questions in Omaha and Boise, the four AI assistants never all listed the same business first, and only 6 of 72 head-to-head comparisons of their first picks matched. - In this two-city test, only 2 of 250 AI recommendations failed outright when re-checked against live listings, and both came from Claude. - In this two-city test, phone-number mismatches outnumbered outright failures: in 7 of 250 AI recommendations, the number given did not match the company's live Google listing, against 2 failures. How this test worked [Full method and limits](#method) #### Where this started Before the test, I had a Claude agent ask ChatGPT for the best emergency septic service in Des Moines. One of the options it listed was desmoinesseptic.com, which is my own [rank and rent](/rank-and-rent-seo/) site (a real local septic company takes its calls). That site doesn't name the company behind it, though. By this test's own rules, an outside checker couldn't verify the operator, so it would count as a lead-gen failure. In other words, ChatGPT put a site with no named operator right next to real septic companies in an emergency answer. My site showing up there is part of why the test ran in Omaha, Nebraska and Boise, Idaho, where I own nothing. My sites and client sites are excluded from every number on this page. The same answer also got a real company's details wrong: | Detail | In ChatGPT's answer | On Google Maps (October 7, 2026) | | Rating | 1.0 stars from 2 reviews | 4.3 stars from 84 reviews | | Phone | Two different numbers: (515) 517-2917 on its business card and (515) 262-9174 in the text | (515) 517-2917, so only the card's number matched | When the same setup ran the question again after the test, ChatGPT made Bob's its top pick and left my site out of the answer. The 1.0-star card and the two phone numbers were still there. ### **What Happened to All 250 Recommendations** Each dot below is one recommendation, grouped by what the checks found. A business can appear more than once, since several were named by more than one assistant. Nearly every AI pick was a real local business All 250 AI recommendations, one dot each, by what the checks found - **In Google's top 3: 57 - **Maps listing in the metro area, not Google's top 3: 178 - **Real operator, Maps listing not found: 9 - **Failed a live re-check: 2 - **Outside the metro area or unresolved: 4 Chart data: In Google's top 3: 57. Maps listing in the metro area, not Google's top 3: 178. Real operator, Maps listing not found: 9. Failed a live re-check: 2. Outside the metro area or unresolved: 4. *One dot per recommendation (phrasing "Who is the best [service] in [City, ST]?", first run). The gray dots cover 3 real businesses based outside the metro area and 1 that could not be resolved either way. Failures and the closed-business flags were re-checked against live listings on October 7, 2026.* [Download chart (PNG)](/research/does-chatgpt-recommend-local-businesses/charts/c-outcomes.png) | Outcome | Recommendations | Share | | In Google's top 3 | 57 | 22.8% | | Maps listing in the metro area, not Google's top 3 | 178 | 71.2% | | Real operator, Maps listing not found | 9 | 3.6% | | Failed a live re-check | 2 | 0.8% | | Outside the metro area or unresolved | 4 | 1.6% | ### **Most AI Picks Are Real, and Most Aren't Google's Top 3** ChatGPT came closest to Google, and even so, only 31.0% of its picks were in Google's top 3. The other three assistants matched less often. ChatGPT matched Google's top 3 most often Share of each assistant's recommendations in Google's top 3. Dark bar: the actual share. Light bar: the most possible, given how many businesses each assistant named. Chart data: ChatGPT: 31.0% of a possible 62.1%. Perplexity: 26.7% of a possible 73.3%. Claude: 18.5% of a possible 44.4%. Gemini: 18.2% of a possible 54.5%. *Google's top 3 = the first three local pack results for the matching search, such as "roofing company Omaha NE", pulled the same day. An assistant that names more businesses per answer has a lower ceiling, because the map pack has only three slots.* [Download chart (PNG)](/research/does-chatgpt-recommend-local-businesses/charts/c-surface.png) | Assistant | In Google's top 3 | Most possible | | ChatGPT | 31.0% | 62.1% | | Perplexity | 26.7% | 73.3% | | Claude | 18.5% | 44.4% | | Gemini | 18.2% | 54.5% | | Assistant | Recommendations | In Google's top 3 | Matched a Maps listing in the metro area | Real, serving the metro area | | ChatGPT | 58 | 31.0% | 98.3% | 98.3% | | Perplexity | 45 | 26.7% | 95.6% | 97.8% | | Claude | 81 | 18.5% | 87.7% | 95.1% | | Gemini | 66 | 18.2% | 97.0% | 100.0% | Claude's lower match rate comes mostly from naming smaller operators that are real but had no Maps listing the checks could find. Counting those, 95.1% of its picks were real businesses serving the metro area. #### Overlap by trade Top-3 overlap varied more across trades than across assistants in this sample. Roofing barely overlapped for any of the four. Roofing picks almost never matched Google's top 3, for any assistant Recommendations in Google's top 3, out of each assistant's recommendations for that trade. Darker = higher share. - **0 - **Under 15% - **15 to 29% - **30 to 44% - **45% or more Chart data: Septic pumping: ChatGPT 4 of 10, Perplexity 3 of 7, Claude 5 of 14, Gemini 4 of 8, all four 16 of 39 (41.0%). Garage door repair: ChatGPT 4 of 10, Perplexity 4 of 8, Claude 2 of 14, Gemini 4 of 11, all four 14 of 43 (32.6%). HVAC repair: ChatGPT 2 of 9, Perplexity 2 of 10, Claude 3 of 15, Gemini 2 of 10, all four 9 of 44 (20.5%). Junk removal: ChatGPT 5 of 11, Perplexity 1 of 9, Claude 2 of 14, Gemini 1 of 12, all four 9 of 46 (19.6%). Emergency plumber: ChatGPT 3 of 10, Perplexity 2 of 4, Claude 3 of 15, Gemini 0 of 12, all four 8 of 41 (19.5%). Roofing: ChatGPT 0 of 8, Perplexity 0 of 7, Claude 0 of 9, Gemini 1 of 13, all four 1 of 37 (2.7%). *Small samples: each assistant's cell covers 4 to 15 recommendations, so read the rows, not single cells. All four = both cities and every assistant combined.* [Download chart (PNG)](/research/does-chatgpt-recommend-local-businesses/charts/c-heat.png) | Trade | ChatGPT | Perplexity | Claude | Gemini | All four | | Septic pumping | 4 of 10 | 3 of 7 | 5 of 14 | 4 of 8 | 16 of 39 (41.0%) | | Garage door repair | 4 of 10 | 4 of 8 | 2 of 14 | 4 of 11 | 14 of 43 (32.6%) | | HVAC repair | 2 of 9 | 2 of 10 | 3 of 15 | 2 of 10 | 9 of 44 (20.5%) | | Junk removal | 5 of 11 | 1 of 9 | 2 of 14 | 1 of 12 | 9 of 46 (19.6%) | | Emergency plumber | 3 of 10 | 2 of 4 | 3 of 15 | 0 of 12 | 8 of 41 (19.5%) | | Roofing | 0 of 8 | 0 of 7 | 0 of 9 | 1 of 13 | 1 of 37 (2.7%) | On the original Omaha roofing search, none of the four named any of the three roofers Google showed first. When Claude agents pulled that exact search twice more the same afternoon, three minutes apart, the second pull had swapped one of the three for McCoy Roofing, which was ChatGPT's first pick. Google's map pack moves too. Treat any overlap figure, including mine, as a snapshot. The two cities landed within a few points of each other on every measure. With only two cities, that is a consistency check, not proof the pattern holds everywhere. | Share of AI recommendations | Omaha, NE (124) | Boise, ID (126) | | In Google's top 3 | 22.6% | 23.0% | | Matched a Maps listing in the metro area | 91.9% | 96.0% | | Real businesses serving the metro area | 96.8% | 98.4% | Two more numbers came up after the test rather than being planned. Looking from Google's side, the four AIs together mentioned 29 of the 36 businesses in Google's top 3 (three per search, 12 searches) at least once. Those top-3 businesses were also more likely to be listed first. They made up 35.4% of first picks, compared with 22.8% of all recommendations. For a related but different question, [SOCi studied multi-location brands](https://www.soci.ai/news/in-ai-driven-discovery-few-brands-are-chosen-most-disappear/) and found ChatGPT recommends just 1.2% of brand locations, compared with an average 35.9% appearance rate in Google's local 3-pack. ### **Explore Every Answer** Pick a city and a trade to see Google's top 3 next to every business each assistant recommended, in the order it listed them. ##### Google's top 3 - Crown Pumping (5 stars, 207 reviews) - Omaha Pumping Services (5 stars, 1 review) - Midland Pumping Service (4.8 stars, 39 reviews) ##### ChatGPT - Crown PumpingGoogle's top 3 - Midland Pumping ServiceGoogle's top 3 - S & S Pumping Service - AAA Sewer & Septic LLC - Nebraska SepticOutside metro area ##### Claude - Midland Pumping ServiceGoogle's top 3 - Crown Pumping LLCGoogle's top 3 - CB Septic IncMaps listing not found - Great Plains Septic - S & S Pumping Service - Bill's Sewer ServiceMaps listing not found - Allen SepticOutside metro area - Ruda SepticOutside metro area ##### Gemini - Crown Pumping LLCGoogle's top 3 - Norm's Pumping & Septic Service - Omaha PumpingGoogle's top 3 - G&T Services ##### Perplexity - Crown Pumping LLCGoogle's top 3 - Midland Pumping ServiceGoogle's top 3 Google search: "septic tank pumping company Omaha NE". Business names are as each assistant wrote them. Untagged names matched a Google Maps listing in the metro area, per the Claude-agent checks. Google rounds review counts above 1,000. ### **The Four AIs Rarely List the Same Local Business First** Across these 12 questions, the four assistants usually listed different businesses first. Each assistant's first pick was compared with every other assistant's first pick, question by question. head-to-head comparisons of first picks matched (8.3%). The grid below shows where. Only 4 of the 12 questions had any two AIs list the same business first Each dot is one assistant's first pick for one question. - **Another assistant listed the same business first - **No other assistant listed it first Chart data: Omaha septic pumping: ChatGPT Crown Pumping (shared), Perplexity Crown Pumping LLC (shared), Claude Midland Pumping Service, Gemini Crown Pumping LLC (shared). Omaha garage door repair: ChatGPT Spring Kings Omaha, Perplexity Garage Doors Of Omaha, Claude Norm's Door Service, Gemini Omaha Door & Window. Omaha hvac repair: ChatGPT Skradski Heating & Cooling, Perplexity Xtreme Heating & Cooling, Claude Getzschman Heating & Air Conditioning, Gemini Complete Comfort Heating and Cooling. Omaha junk removal: ChatGPT 1-800-GOT-JUNK? Omaha, Perplexity Horizon Junk Pros, Claude R & R Hauling, Gemini Junk King Omaha. Omaha emergency plumber: ChatGPT Omaha Emergency Neighborhood Plumbers, Perplexity PlumbRite, Claude Roto-Rooter, Gemini Eyman Plumbing Heating & Air. Omaha roofing: ChatGPT McCoy Roofing, Perplexity Erie Home, Claude Royalty Roofing (shared), Gemini Royalty Roofing & Renovations (shared). Boise septic pumping: ChatGPT ABC Pumping Service (shared), Perplexity American Septic, Claude ABC Pumping Service (shared), Gemini Sweet's Services. Boise garage door repair: ChatGPT A1 Garage Door Service, Perplexity Garage Door Store Boise, Claude Legacy Garage Doors, Gemini Overhead Door Company of Southwestern Idaho. Boise hvac repair: ChatGPT Owyhee Heating and Air Conditioning, Perplexity Wickstrom Plumbing Heating Cooling, Claude Western Heating & Air Conditioning, Gemini A-1 Heating, Air Conditioning & Electric. Boise junk removal: ChatGPT Junk Holler, Perplexity 1-800-GOT-JUNK? Boise, Claude Junk King Boise, Gemini Full House Junk Removal. Boise emergency plumber: ChatGPT Roto-Rooter Plumbing & Water Cleanup (shared), Perplexity Roto-Rooter (shared), Claude All Star Plumbing & Restoration, Gemini Diamond Heating, Cooling, Plumbing & Electric. Boise roofing: ChatGPT Bork Roofing, Perplexity Blue Goat Roofing, Claude E & H Roofing, Gemini Signature Roofing. *Matches use the business name each assistant gave, cleaned of suffixes like "LLC". Hover or tap a dot to see the business. The full list is in the table below and in the explorer above.* [Download chart (PNG)](/research/does-chatgpt-recommend-local-businesses/charts/c-first.png) | Question | ChatGPT's first pick | Perplexity's first pick | Claude's first pick | Gemini's first pick | | Omaha septic pumping | Crown Pumping (shared) | Crown Pumping LLC (shared) | Midland Pumping Service | Crown Pumping LLC (shared) | | Omaha garage door repair | Spring Kings Omaha | Garage Doors Of Omaha | Norm's Door Service | Omaha Door & Window | | Omaha hvac repair | Skradski Heating & Cooling | Xtreme Heating & Cooling | Getzschman Heating & Air Conditioning | Complete Comfort Heating and Cooling | | Omaha junk removal | 1-800-GOT-JUNK? Omaha | Horizon Junk Pros | R & R Hauling | Junk King Omaha | | Omaha emergency plumber | Omaha Emergency Neighborhood Plumbers | PlumbRite | Roto-Rooter | Eyman Plumbing Heating & Air | | Omaha roofing | McCoy Roofing | Erie Home | Royalty Roofing (shared) | Royalty Roofing & Renovations (shared) | | Boise septic pumping | ABC Pumping Service (shared) | American Septic | ABC Pumping Service (shared) | Sweet's Services | | Boise garage door repair | A1 Garage Door Service | Garage Door Store Boise | Legacy Garage Doors | Overhead Door Company of Southwestern Idaho | | Boise hvac repair | Owyhee Heating and Air Conditioning | Wickstrom Plumbing Heating Cooling | Western Heating & Air Conditioning | A-1 Heating, Air Conditioning & Electric | | Boise junk removal | Junk Holler | 1-800-GOT-JUNK? Boise | Junk King Boise | Full House Junk Removal | | Boise emergency plumber | Roto-Rooter Plumbing & Water Cleanup (shared) | Roto-Rooter (shared) | All Star Plumbing & Restoration | Diamond Heating, Cooling, Plumbing & Electric | | Boise roofing | Bork Roofing | Blue Goat Roofing | E & H Roofing | Signature Roofing | The clearest agreement was Omaha septic, where ChatGPT, Gemini and Perplexity all put Crown Pumping first. Claude said there was no single best and listed Midland Pumping Service first. This lines up with the [Steady Demand AI Citation Ledger](https://www.steadydemand.com/ai-citation-ledger/), which found ChatGPT and Gemini name the same top business only 4.9% of the time. The answers also drift. The test reran 12 of the 48 answers, and an average of 79.1% of the businesses from the first run showed up again. ### **Where the AI Recommendations Went Wrong** A bad recommendation can waste a homeowner's call and send the job away from a real business. These were the clearest misses, each re-checked by Claude agents against live listings on October 7, 2026. FailedClaude · Boise HVAC **Carlon Heating & Air** No current Google listing. An older Maps record marks it permanently closed, and its old web address was serving a gambling spam page when checked. FailedClaude · Omaha garage door repair **A1 Garage Door Service, LLC** A real multi-state company, but its Omaha location shows as closed on Yelp and its own site lists no Nebraska service areas. Wrong detailPerplexity · Omaha junk removal **Horizon Junk Removal (Perplexity called it “Horizon Junk Pros”)** The phone number Perplexity gave matched neither the company's Google listing nor its Facebook page. Wrong detailChatGPT · Omaha HVAC **Anderson Comfort** A real company with a 5.0 rating, but the website ChatGPT gave for it now redirects to a domain marketplace page. Correction to this testClaude · Boise septic **ASAP Septic** An old cached record said permanently closed. The live listing shows it open with 5.0 stars from 47 reviews. Claude was right, and the first-pass check was wrong. The 7 phone-number mismatches can mean an old number, a tracking line or a plain mistake. Either way, call the number on the listing. The ASAP Septic card is a correction of the test itself. The Claude agents' first pass flagged 7 recommendations as closed, not found or lead-gen, and a live re-check cleared 4 of them, with 1 more unresolved either way. For a separate check of a different engine, [Whito tested Google AI Mode](https://whito.co.uk/research/ai-recommended-businesses-unverifiable-uk/) in 20 UK towns and found 5.2% of the businesses it called trustworthy could not be verified as active companies trading in that town. It checked company registry records, so its unverifiable category is not directly comparable to the 2 failures here. ### **What This Means If You Run a Local Business** The errors documented here included stale or conflicting details: an old closed listing, a dead domain, a phone number that differs from the listing. The test can't prove what caused each error, but those gaps are the ones you control. *The misses in this test involved a listing, a website or a phone number. If your listing, site and phone agree, the AI has less to get wrong.* - Keep your [Google Business Profile](https://business.google.com/us/business-profile/) current, especially your hours and phone number. - Use one main phone number everywhere: your listing, your site, Facebook and every directory. - Keep your domain renewed. A dead domain can still get handed to customers. - Close or merge old listings when you move, rebrand or sell, so a stale record cannot outlive the real one. None of that is new. My take from this pilot: for local service businesses, getting named correctly by AI starts with the same fundamentals that already pay off on Google. Getting named more often is a different question. I covered which sources ChatGPT actually reads in [my test of how to rank in ChatGPT](/how-to-rank-in-chatgpt/). If you are on the other side of this, looking for a plumber at midnight, open the business's Google listing before you call the number an AI gave you. ### **How I Ran This Field Test** - **Questions.** "Who is the best [service] in [City, ST]?" for 6 urgent home services (septic pumping, emergency plumber, HVAC repair, roofer, junk removal, garage door repair) in Omaha and Boise. That is 12 questions and 48 answers. - **Assistants.** ChatGPT through its consumer app with web search on, collected with [DataForSEO's AI Optimization API](https://dataforseo.com/apis/ai-optimization-api). Claude, Gemini and Perplexity through their APIs, with web search confirmed on every answer but no user location. The results apply to these four setups and may differ in the consumer apps. - **Recommendations.** Every business an answer presented as a recommendation, which came to 250 entries covering about 160 different businesses. Businesses named only as warnings did not count, and Claude's first-listed business counted as its first pick. - **Google comparison.** The local pack top 3 for the matching Google search (for example, "roofing company Omaha NE"), pulled the same day in each city. - **Checks.** Claude agents matched each recommendation to Google Maps listings and websites, checked the 57 top-3 matches against the saved search results, live-checked every closed, lead-gen or not-found flag, and confirmed the 7 phone mismatches against live listings. - **Reliability.** A separate Claude model re-checked 50 randomly drawn recommendations against live listings or the saved search results and agreed with the labels on 48 (96%), above the 90% bar set in advance. Both disagreements were the same plumber, a real business matched to the wrong Maps listing on its name alone. That fix is in the numbers above, but other name-only Maps matches were not re-checked one by one, so the 94.0% Maps figure could run slightly high. - **One inconsistency.** Claude sometimes included names from a third-party list. Eight of those were counted in three answers but left out of a roofing answer, and removing them moves every headline figure by about a point or less. - **Disclosure.** Claude ran the checks and is also one of the four assistants tested, and I sell a Claude Code product. The same rules applied to every assistant, and Claude finished near the bottom on top-3 overlap and had both hard failures. Before collecting any data, the plan set criteria for expanding to a full 10-city study. Top-3 overlap had to land at 50% or above, or 20% or below, or hard failures had to reach 10% (closed, not found, or a lead-gen site with no verifiable operating company behind it). Overlap came in at 22.8% and hard failures far below 10%, and the pilot also ran over the plan's cost and workload limits. So the test stopped at two cities, and I'm reporting it as a field test. The agreement figures, the 29-of-36 coverage figure, the first-pick figure, the city comparison and the trade-by-assistant grid were not part of that plan, so treat them as observations. The bigger limits: two cities, 12 questions, one day. ### **The Picks Were Real. The Details Weren't Always.** Does ChatGPT recommend local businesses that are real? In this test, the four assistants named real, local businesses 97.6% of the time. I ran this test from Claude Code. The marketing skills I run there every week are in my **[Claude Code Skills Stack](https://skills.ryandoser.com)**, which is my own product, so weigh my Claude Code bias accordingly. The assistants often disagreed with Google and with each other, and the details they repeated were not always current. The part you control is whether those details are right when an AI does name you. ### **Does ChatGPT Recommend Local Businesses FAQs** #### Can ChatGPT recommend a local business that is closed? This test did not catch ChatGPT recommending a closed business. Across 250 recommendations from ChatGPT, Claude, Gemini and Perplexity, only 2 failed outright, and both came from Claude. ChatGPT's misses were mostly about details, like a website that now redirects to a domain marketplace and phone numbers that did not match the live Google listing, plus one business based outside the metro area. #### Do ChatGPT, Gemini, Claude and Perplexity recommend the same businesses? Rarely as the first business they list. Across 12 local questions, the four assistants never all listed the same business first, and only 6 of 72 head-to-head comparisons of first picks matched. Each answer named about five businesses, so a company can show up in several answers without being anyone's first choice. Steady Demand found a similar pattern for ChatGPT and Gemini, at 4.9%. #### What share of AI local recommendations are in Google's top 3? In this two-city test, 22.8% of 250 AI recommendations were in Google's top 3 for the matching search, out of a possible 56.4%. ChatGPT matched most often, at 31.0% of its picks. The four assistants still mentioned 29 of Google's 36 top-3 businesses at least once, and 35.4% of their first picks came from that top 3. This test cannot show that the ranking caused the mention. #### How often do AI assistants give the wrong phone number for a local business? In this test, 7 of 250 recommendations (2.8%) came with a phone number that did not match the main number on the company's live Google listing. Some of those may be tracking lines rather than errors, so check the number on the business's Google listing before you call. ### **Cite This Field Test** You are welcome to use any figure, chart or table here with a link to this page. Please keep the collection date and the two-city scope with any figure you use, and find the full dataset in the downloads at the top. ``` Doser, R. (2026). Does ChatGPT recommend local businesses? A field test of 250 AI recommendations in Omaha and Boise. ryandoser.com. https://ryandoser.com/research/does-chatgpt-recommend-local-businesses/ ``` #### Chart images Each chart below is a 1600-pixel PNG with its title and source line built in. - [All 250 AI recommendations, by what the checks found (PNG)](/research/does-chatgpt-recommend-local-businesses/charts/c-outcomes.png) - [Share of each assistant's picks in Google's top 3 (PNG)](/research/does-chatgpt-recommend-local-businesses/charts/c-surface.png) - [Google's top-3 overlap by assistant and trade (PNG)](/research/does-chatgpt-recommend-local-businesses/charts/c-heat.png) - [First picks shared between assistants (PNG)](/research/does-chatgpt-recommend-local-businesses/charts/c-first.png) --- ## AI Marketing Jobs: What 1,229 Job Posts Actually Ask For URL: https://ryandoser.com/research/ai-marketing-jobs/ Markdown: https://ryandoser.com/research/ai-marketing-jobs.md Author: Ryan Doser Published: 2026-10-07 | Updated: 2026-10-08 Type: Study > What do AI marketing jobs ask for? 1,229 US job posts: 39% want AI skills, few name a tool, and Claude is named most. Data downloads: https://ryandoser.com/research/ai-marketing-jobs/ (CSV and JSON links at the top of the page). Free to use with a link to the page. **38.7%** of these US marketing job posts ask for AI skills, nice-to-haves included **84.2%** of those AI skill asks name no specific tool **59 vs 34** posts asking candidates for Claude vs ChatGPT by name **22.4%** of entry-level posts ask for AI, against 43.7% at director level and above ### **What AI Marketing Jobs Ask For in 2026** Here is the short version, from 1,229 US marketing job posts at 605 companies that were live on October 7, 2026. Each finding stands on its own, so you can quote any one with its source. Key findings - In a sample of 1,229 US marketing job posts live on October 7, 2026, 38.7% asked candidates for AI skills, nice-to-haves included. - In the same October 2026 sample, 84.2% of the 476 US marketing job posts that asked for AI skills never named a specific AI tool. - Across 119 candidate asks for six major AI assistants in 1,229 US marketing job posts, Claude accounted for 59 (49.6%), ahead of ChatGPT, Gemini, Perplexity and the two Copilots. A post could count toward more than one assistant. - In this October 2026 sample, 19 of the 59 US marketing job posts asking for Claude named Claude Code, Claude Skills or Claude Cowork specifically. - In this October 2026 sample of US marketing job posts, 22.4% of entry-level posts asked for AI skills, against 43.7% at director level and above. How this study worked [Full method and limits](#method) I ran this whole study inside [Claude Code for marketing work](/claude-code-for-marketing/): Claude agents collected the posts and labeled every sentence, and a separate Claude model checked 50 of the posts. The full method and its limits are further down. ### **Most AI Asks in Marketing Jobs Name No Tool** Of the 476 posts that asked for AI skills, 401 never named a specific AI tool in those asks. That is 84.2% of them. Roughly five out of six AI skill asks never named a tool The 476 job posts that asked for AI skills - **No specific tool named: 401 (84.2%) - **Named a specific AI tool: 75 (15.8%) Chart data: 401 of 476 posts (84.2%) named no specific AI tool. 75 (15.8%) named one. *Company-clustered 95% range for the no-tool share: about 81% to 88%.* [Download chart (PNG)](/research/ai-marketing-jobs/charts/c-notool.png) *Most posts that want AI stop at generic fluency. A smaller group names a tool, and Claude is named most often.* Here is what the typical ask sounds like, copied from live posts: - You use AI tools fluently in your own work and are always looking for new ways to move faster and think sharper.Fin, Principal Product Marketing Manager - Knowledge of how generative AI tools can aid in PR processes.Taboola, Public Relations Manager - Fluent with AI and LLM tools as a creative accelerant...MERGE, Social and Content Manager That cuts against a popular read of the market. In June, [CXL's analysis of about 1,750 marketing job descriptions](https://cxl.com/blog/ai-marketing-jobs-skills-demand/) found ChatGPT in 5.5% of May posts and Claude in 4.6%, and concluded that specific tool fluency is becoming the filter. Both things can be true. CXL tracked how often each tool was mentioned, while this study only counted what a post asks the candidate to bring. ChatGPT shows how big that gap is. It appeared somewhere in 7.1% of posts, but only 2.8% asked the candidate to use it. Most of the other ChatGPT mentions were about getting a brand cited in ChatGPT, advertising on it, or describing the company. ### **When AI Marketing Jobs Name a Tool, Claude Comes First** Adzuna's methodology names six AI assistants: ChatGPT, Claude, Gemini, Perplexity, Microsoft Copilot and GitHub Copilot. Across those six, the labeled posts held 119 asks, and Claude took 59 of them while ChatGPT took 34. Claude was the AI assistant job posts asked for most Job posts asking the candidate to use each AI assistant Chart data: Claude: 59. ChatGPT: 34. Gemini: 14. Perplexity: 6. Microsoft Copilot: 3. GitHub Copilot: 3. *Counted only where a sentence asks the candidate to bring the skill. A post can appear under more than one assistant, so the bars add to more than the 75 posts that named any AI tool. A company's own posts never count toward its own tool, and Claude includes Claude Code.* [Download chart (PNG)](/research/ai-marketing-jobs/charts/c-tools.png) | AI assistant | Job posts asking for it | | Claude | 59 | | ChatGPT | 34 | | Gemini | 14 | | Perplexity | 6 | | Microsoft Copilot | 3 | | GitHub Copilot | 3 | Claude's share of those six came to 49.6%. I picked my comparison point before collecting any data: [Adzuna's AI Mentions Index](https://www.adzuna.co.uk/blog/claude-just-overtook-copilot-as-the-most-requested-ai-tool-in-uk-and-us-job-ads/), where Claude held 34% of UK named-tool mentions as of its September 2026 update. One caution: Adzuna counts every mention in UK job ads across sectors, so treat the gap between 49.6% and 34% as a signal and not a precise comparison. Counted the way most trackers count, as any mention, Claude and ChatGPT are close: 7.6% and 7.1% of posts. The gap opens when you count real asks: 63% of posts that mention Claude ask applicants to use it, against 39% of posts that mention ChatGPT. ChatGPT gets mentioned almost as often as Claude, but asked for far less Share of all 1,229 job posts - **Mentioned anywhere in the post - **Named in a candidate skill ask Chart data: ChatGPT: mentioned in 7.1% of posts, asked for in 2.8%. Claude: mentioned in 7.6% of posts, asked for in 4.8%. *"Mentioned" counts any sentence naming the tool, including company descriptions and AI search work. "Asked" counts only sentences asking the candidate to bring the skill.* [Download chart (PNG)](/research/ai-marketing-jobs/charts/c-mention.png) | Assistant | Mentioned anywhere | Named in a candidate skill ask | | ChatGPT | 7.1% | 2.8% | | Claude | 7.6% | 4.8% | The more useful detail is how employers ask for Claude. Here are three of the asks: - Claude Code/Codex and tools like it are already part of how you work every day, and you can show how they changed your output rather than just that you've tried them.Basis AI, Content Marketing Manager - Experience with Claude skills and agents.impact.com, Product Marketing Manager II - Experience using Claude or similar AI tools to support campaign drafting, performance reporting, and day-to-day marketing workflows.GLG, Campaign Manager Copilot barely registers here, which likely reflects the sample. These platforms lean toward tech and startup employers, and Adzuna points out that Microsoft 365 Copilot often lands through company-wide rollouts. ### **Which AI Marketing Jobs Ask for AI the Most** In this sample, lifecycle and growth roles asked for AI most often, and brand roles asked least. Post counts are in parentheses. Lifecycle and growth roles asked for AI most often Share of job posts asking for AI skills, by role family Chart data: Lifecycle and CRM (51): 51.0%. Growth (197): 49.2%. Content (88): 47.7%. Product marketing (203): 40.4%. SEO (27): 37.0%. Social media (85): 36.5%. General marketing (394): 33.5%. Communications and PR (112): 32.1%. Brand (72): 27.8%. [Download chart (PNG)](/research/ai-marketing-jobs/charts/c-family.png) | Role family | Share asking for AI | | Lifecycle and CRM (51) | 51.0% | | Growth (197) | 49.2% | | Content (88) | 47.7% | | Product marketing (203) | 40.4% | | SEO (27) | 37.0% | | Social media (85) | 36.5% | | General marketing (394) | 33.5% | | Communications and PR (112) | 32.1% | | Brand (72) | 27.8% | The rate climbs steadily with seniority. Director-level posts asked for AI most, entry-level least Share of job posts asking for AI skills, by seniority Chart data: Entry level (76): 22.4%. Mid level (502): 36.7%. Senior (374): 41.2%. Director and above (277): 43.7%. [Download chart (PNG)](/research/ai-marketing-jobs/charts/c-band.png) | Seniority | Share asking for AI | | Entry level (76) | 22.4% | | Mid level (502) | 36.7% | | Senior (374) | 41.2% | | Director and above (277) | 43.7% | Inside role families, the pattern is messier. Communications and PR posts at director level asked for AI less often than mid-level ones (21.2% of 33 vs 38.9% of 36), so treat seniority as the overall pattern in this sample, not a rule for every role. AI asks rose with seniority overall, but not inside every role Share of job posts asking for AI skills, by role family and seniority. Cells under 10 posts show the post count only. - **Under 25% - **25 to 39% - **40 to 54% - **55% or more - **Too few posts Chart data: Lifecycle and CRM: Entry level 1 posts, too few, Mid level 57.1%, Senior 47.4%, Director and above 50.0%. Growth: Entry level 27.3%, Mid level 43.6%, Senior 46.2%, Director and above 64.3%. Content: Entry level 5 posts, too few, Mid level 48.0%, Senior 48.1%, Director and above 6 posts, too few. Product marketing: Entry level 5 posts, too few, Mid level 37.0%, Senior 46.6%, Director and above 34.5%. SEO: Entry level 1 posts, too few, Mid level 21.1%, Senior 4 posts, too few, Director and above 3 posts, too few. Social media: Entry level 4 posts, too few, Mid level 34.0%, Senior 42.3%, Director and above 5 posts, too few. General marketing: Entry level 15.6%, Mid level 31.1%, Senior 30.2%, Director and above 45.4%. Communications and PR: Entry level 30.8%, Mid level 38.9%, Senior 36.7%, Director and above 21.2%. Brand: Entry level 4 posts, too few, Mid level 15.8%, Senior 50.0%, Director and above 22.2%. *Rows are sorted by each role family's overall rate. Percentages are rounded here. The table below and the CSV download carry the exact counts.* [Download chart (PNG)](/research/ai-marketing-jobs/charts/c-roleband.png) | Role family | Entry level | Mid level | Senior | Director and above | | Lifecycle and CRM | 0 of 1 | 12 of 21 (57.1%) | 9 of 19 (47.4%) | 5 of 10 (50.0%) | | Growth | 3 of 11 (27.3%) | 34 of 78 (43.6%) | 24 of 52 (46.2%) | 36 of 56 (64.3%) | | Content | 2 of 5 | 24 of 50 (48.0%) | 13 of 27 (48.1%) | 3 of 6 | | Product marketing | 1 of 5 | 30 of 81 (37.0%) | 41 of 88 (46.6%) | 10 of 29 (34.5%) | | SEO | 1 of 1 | 4 of 19 (21.1%) | 2 of 4 | 3 of 3 | | Social media | 1 of 4 | 17 of 50 (34.0%) | 11 of 26 (42.3%) | 2 of 5 | | General marketing | 5 of 32 (15.6%) | 46 of 148 (31.1%) | 32 of 106 (30.2%) | 49 of 108 (45.4%) | | Communications and PR | 4 of 13 (30.8%) | 14 of 36 (38.9%) | 11 of 30 (36.7%) | 7 of 33 (21.2%) | | Brand | 0 of 4 | 3 of 19 (15.8%) | 11 of 22 (50.0%) | 6 of 27 (22.2%) | If you're early in your career, that low number is not a pass. CXL found entry-level AI mentions flat between January and May, and read that as employers assuming juniors have already absorbed AI on their own. Clay was named more often than Zapier, n8n or Make Job posts naming each automation tool as a candidate ask Chart data: Clay: 19. Zapier: 5. n8n: 4. Make: 1. [Download chart (PNG)](/research/ai-marketing-jobs/charts/c-auto.png) | Automation tool | Job posts | | Clay | 19 | | Zapier | 5 | | n8n | 4 | | Make | 1 | ### **Explore Your Role** Pick a role family to see how often its posts asked for AI, broken out by seniority. Cells under 10 posts are shown as counts only. | Seniority | Job posts | Asked for AI | Share | | Entry level | 32 | 5 | 15.6% | | Mid level | 148 | 46 | 31.1% | | Senior | 106 | 32 | 30.2% | | Director and above | 108 | 49 | 45.4% | ### **How to Stand Out for AI Marketing Jobs** If most posts say "AI fluency" without defining it, my bet is that the candidate who defines it for them has the edge. A hiring manager can't test "uses AI to move faster," but they can look at a system you made. - Pick one real marketing task you repeat every week, like a campaign brief or a performance report. - Build it into a repeatable AI workflow, ideally in [Claude Code](https://claude.com/product/claude-code) with a skill file, so the steps live in writing. - Write down the before and after: hours saved, output shipped, quality checks kept. - Name your stack on your resume and in interviews, since most posts won't name it for you. The Basis AI post above asks you to show how the tools "changed your output rather than just that you've tried them." Proof of changed output is exactly what that employer is screening for. If you want a head start on those workflows, my **[Claude Code Skills Stack](https://skills.ryandoser.com)** is the exact set of marketing skills I run every week. It is my own product, so weigh my Claude Code bias accordingly. If you're new to building this way, start with [why marketers should use Claude Code](/why-marketers-should-use-claude-code/), then work through [what Claude Skills are](/claude-skills/). ### **How I Ran This Study** Every figure on AI marketing jobs above comes from public job boards, a written rulebook and a second-model check. Here is exactly how, including what it can't tell you. - **Sources.** The public job board feeds from [Greenhouse](https://docs.greenhouse.io/job-board.html), Lever and Ashby. Claude agents found 1,014 company boards through Google searches of those platforms. - **Filters.** US locations, marketing titles, and exact duplicates (same company, title and location) removed. I excluded job aggregators, staffing firms and demo boards. - **Balance.** At most three posts per company, so a few big employers can't swing the results. That took 2,052 posts down to 1,229. - **Labeling.** Every sentence that mentioned AI or an AI tool was labeled by Claude against a fixed rubric. Only sentences asking the applicant to bring a skill counted, not company descriptions, AI as a product topic, AI search work or hiring-process notes. - **Vendors.** A company's own posts never counted toward its own tool. ChatGPT includes asks for GPT models by name. - **Disclosure.** I sell a Claude Code product, and Claude did the labeling. The rubric applies the same test to every tool, tool names are pulled straight from the sentences marked as asks, and the raw mention counts above come from the same sentences before any labeling. - **Claude's lead.** My pre-set measure used five assistants (50.9%). Adzuna's methodology lists six, adding GitHub Copilot, and on that matching basis the figure is 49.6%. Across every AI tool named, including Midjourney and Jasper, it is 48.0%. - **Check.** A separate, stronger Claude model re-read 50 randomly drawn posts (25 counted as AI asks, 25 not) against the labels and agreed with all 50. Two earlier keyword-matching versions failed that same check (88% and 84%), so I replaced them before the final run. - **Cross-model check.** A Claude labeler judging Claude asks could lean toward Claude, so GPT-6.1 Sol, an OpenAI model, re-labeled the 181 sentences that name Claude or ChatGPT outside each vendor's own posts, with the tool names hidden. It agreed on 177 (97.8%), and on its stricter labels Claude still leads, 58 posts to 33. - **Ranges.** 95% confidence ranges treat each company as one unit, since posts from one company share wording. The no-tool share runs from about 81% to 88%. Claude's six-assistant share runs from 41.8% to 58.1%, entirely above Adzuna's 34%. The limits matter. These platforms lean toward tech companies and startups, so this is not every US employer. It is also a single snapshot from one day, from a different sample than CXL's, so the two studies can't be lined up as a trend. The role-by-seniority grid and the mention-vs-ask comparison were added after the main analysis, so treat them as observations. ### **Bring Proof of an AI Workflow** Nearly four in ten marketing posts want AI skills, and most never say which tool. When they do, Claude leads, often as Claude Code or Claude Skills. My take: if you can point to a working system and explain what it changed, you are answering the question most of these posts leave vague. ### **AI Marketing Jobs FAQs** #### Do marketing jobs require AI skills in 2026? Many do, though not most. In this sample of 1,229 postings live on October 7, 2026, 38.7% wanted AI skills from applicants, counting nice-to-haves. The rate climbs with seniority, from 22.4% of entry-level posts to 43.7% of director-level posts. By job family, lifecycle and growth roles ask most often, at about half of their posts. #### What AI tools do employers want marketers to know? Most of the sampled posts don't say. Only 15.8% of the posts asking for AI skills named any specific tool. When one is named, Claude comes first, then ChatGPT, Gemini, Perplexity and the two Copilots. Among automation tools, Clay was named in more posts than Zapier, n8n or Make. #### Which AI tool do marketing job posts name most? In this October 2026 sample, Claude. It appeared in 59 job posts as a candidate ask, compared with 34 for ChatGPT, and about a third of the Claude asks named Claude Code, Claude Skills or Cowork specifically. CXL's June study used a different method and sample and had ChatGPT slightly ahead in May, so the two aren't directly comparable. #### How should I show AI skills on a marketing resume? Name the tools and describe one workflow you built with them, plus the result. Most job posts only ask for "AI fluency," so a concrete example does the defining for the hiring manager. One specific line about what that system changed beats a list of logos. ### **Cite This Study** You are welcome to use any figure, chart or table here with a link to this page. Please keep the collection date and the sample (company job boards on three hiring platforms, at most three posts per company) with any figure you use. ``` Doser, R. (2026). AI marketing jobs: what 1,229 US job posts actually ask for. ryandoser.com. https://ryandoser.com/research/ai-marketing-jobs/ ``` #### Chart images Each chart below is a 1600-pixel PNG with its title and source line built in. - [AI skill asks with and without a named tool (PNG)](/research/ai-marketing-jobs/charts/c-notool.png) - [Job posts asking for each AI assistant (PNG)](/research/ai-marketing-jobs/charts/c-tools.png) - [Any mention vs an actual ask, ChatGPT and Claude (PNG)](/research/ai-marketing-jobs/charts/c-mention.png) - [AI asks by role family (PNG)](/research/ai-marketing-jobs/charts/c-family.png) - [AI asks by seniority (PNG)](/research/ai-marketing-jobs/charts/c-band.png) - [AI asks by role family and seniority (PNG)](/research/ai-marketing-jobs/charts/c-roleband.png) - [Automation tools named as candidate asks (PNG)](/research/ai-marketing-jobs/charts/c-auto.png) ---