Most people deciding between Claude Skills vs Custom GPTs never ask the one question that ended up moving my entire workflow off ChatGPT. I built custom GPTs for months before it hit me, and once it did, there was no going back.
What These Two Things Actually Are
A custom GPT is a version of ChatGPT you configure with your own instructions, knowledge files, and actions. You build it inside the GPT Builder, save it, and call it up when you need it. It lives inside ChatGPT and nowhere else.
A Claude Skill is different in a way that matters more than it sounds. It is a folder with a markdown file called SKILL.md inside it. That file holds your instructions, and Claude reads it only when your request matches what the skill is for. You can add scripts and reference files to the same folder.
Both solve the same problem on the surface. You are tired of re-explaining the same task to an AI every single time. You want it to already know your process. The difference is what you walk away owning.
What Finally Pushed Me Off GPTs
Nobody told me this when I was deep in the ChatGPT ecosystem. A custom GPT cannot be exported. There is no download button and no file you can grab. The GPT you spent hours tuning only runs inside ChatGPT, so if you ever want to leave, you start over from scratch.
A Claude Skill is a plain markdown file sitting on your computer. Copy it, back it up, move it to another machine, version it like any other document. If Claude Code disappeared tomorrow, my skills would still open in any text editor, and the instructions inside them would still make sense.
A custom GPT works a lot like renting an apartment. It serves you well while you are there, but you never own the walls. A skill is the deed, and you hold the actual asset.
How Each One Loads (And Why That Affects Quality)
When you open a custom GPT, you are inside that GPT for the whole chat. It is a separate space you switch into.
Claude handles skills the opposite way. All your skills sit quietly in the background. Claude reads only the short description of each one until your request actually needs it, then it pulls in the full file. This is called progressive disclosure, and it means you can have a dozen skills loaded without clogging the context window.
In practice, that lets me keep one skill per task instead of one giant mega-prompt. I have a separate skill for SEO blog posts, another for email, another for LinkedIn. Claude grabs the right one based on what I ask. With a custom GPT, I was always picking the GPT first, then giving the task. The skill model flips that and it feels more natural.
It also keeps each skill focused. A custom GPT tends to grow into a catch-all because switching between several GPTs mid-project is a pain, so you cram everything into one. That bloat waters down the instructions. Skills stay lean because Claude only loads the one you need, when you need it. My SEO skill knows nothing about my email skill, and that separation makes both of them better at their actual job.
Where Each One Works
This part is fair to both sides, so let me be precise.
Custom GPTs work inside ChatGPT on web and mobile. You need a paid ChatGPT plan to build one. Free users can use GPTs other people made, within limits, but they cannot create their own.
Claude Skills work across Claude apps, Claude Code, and the API. On claude.ai you need a paid plan with code execution turned on to use custom skills. Inside Claude Code, skills are just files in a folder, so there is no upload step at all.
One honest caveat so I am not overselling this. Your skill files are portable, but installing a skill on a new surface still takes a step. Moving a skill from your laptop to claude.ai means uploading it there, and the API has its own setup too. The files themselves travel anywhere, while the install happens per place. That is still a far better spot than a GPT that travels nowhere at all.
The reason this matters comes down to where you put your time. Hours spent tuning a custom GPT are locked to one platform forever. Hours spent on a skill build an asset you keep even if you change tools next year. For a casual user that gap is invisible, but for anyone running a business on these workflows, it adds up fast.
Your Skill Learns. A GPT Never Will.
This is the feature that quietly sold me. When Claude makes a mistake mid-task, I correct it once, and it can patch the skill file so the same mistake never happens again. The skill gets sharper the more I use it.
Here is a real example. My blog skill kept slipping the wrong dash into drafts, which I never use. Instead of fixing every draft by hand, I told Claude to add a rule banning them to the skill file itself. Every blog post since has come out clean, because the correction lives in the skill, not in my memory.
A custom GPT is static. You set it up, and it stays exactly as configured until you go back into the builder and manually edit it. There is no learning loop unless you do the work yourself every time.
If you want to see how far this goes, I built a system that updates my skills automatically after every workflow. I broke down that whole setup in my guide on Claude Code autoresearch.
The Case for Sticking With a Custom GPT
I am not here to pretend GPTs are useless. If you live inside ChatGPT, never plan to leave, and want the simplest possible no-code builder, a custom GPT is genuinely easy to set up. The GPT Store also gives you instant distribution if you want strangers to use your creation.
If your only goal is a slightly customized chatbot for casual use, the portability question may not matter to you at all. For a quick refresher on the broader ChatGPT side, I compared the two main options in my post on Custom GPTs vs ChatGPT Projects.
But if you are building a real workflow you depend on for income, ownership stops being a nice-to-have. It becomes the whole point.
How to Actually Make the Switch
You do not need to be technical for any of this. I am a marketer, not a developer.
The lowest-friction way to start is to open Claude, brain-dump your process out loud, and ask it to turn that into a skill for you. That is it. You now have a markdown file you own forever. If you are coming from ChatGPT entirely, I walked through the migration in how to switch from ChatGPT to Claude.
From there, build one skill per task instead of one giant one. Keep them small and specific. If you want a head start, I packaged the exact skills I use to run my business into the AI Skills Stack, so you can install proven ones instead of starting from a blank file.
Ryan’s Final Thoughts
Custom GPTs are fine for casual use inside ChatGPT. Claude Skills are what you build when you want to actually own your AI workflow. The portability alone is reason enough, and the self-improvement is the part you will not want to give up once you have it. I switched because I got tired of building assets I could never take with me. If you are building for the long haul, the deed beats the lease every time.
