AI Skills vs Agents vs GPTs

Anyone trying to keep up with OpenAI's product lineup lately has probably felt a little lost. GPTs, Agents, and now Skills all promise roughly the same thing: a way to customize what a chatbot can do without writing actual code. But they're not identical, and the differences matter if you're trying to figure out which one to build on.

GPTs were the original idea, launched a while back as a way to bolt instructions, files, and simple actions onto a base model. Think of them as a costume for ChatGPT — same brain underneath, different personality and knowledge on top. They're easy to make and easy to share, which is why the GPT Store filled up fast with everything from resume reviewers to tarot readers.

Agents are the more ambitious cousin. Instead of just answering questions, an agent is built to take multi-step action on its own — browsing, clicking, filling out forms, chaining tasks together without a human nudging it at every turn. That autonomy is the whole point, and it's also why agents are harder to trust and harder to get right. A GPT waits for you to ask something. An agent goes and does something.

Skills sit in between, closer to a toolkit than a persona or a full autonomous worker. A skill is a narrow, reusable capability a model can call on when needed, rather than a standalone product you interact with directly. It's less flashy than an agent and less personality-driven than a GPT, but it's arguably the piece that makes the other two actually useful in practice.

The overlap between these three categories is real, and OpenAI hasn't done a great job drawing clean lines between them. That's partly because the underlying tech keeps shifting under everyone's feet — what counted as an ambitious agent demo a year ago is now a fairly ordinary skill. Naming things is hard, and naming things in AI right now is even harder.