Simon Says – Musings of a Technology CTO

As AI becomes more embedded in day-to-day work, the real advantage is no longer just asking better questions. It is teaching the system to handle repeatable work in a more consistent way. That is where Skills come in.

A Skill is a reusable workflow that teaches ChatGPT how to do a specific task more reliably. A skill can include instructions, examples, and even code so that the same job gets done with more consistency each time. OpenAI describes skills as reusable, shareable workflows that can be installed and then used automatically when helpful in a conversation.

That makes skills different from a GPT.

A GPT is a custom version of ChatGPT that can be tailored with instructions, knowledge, and capabilities for a broader use case or persona. In practical terms, I think of a GPT as the overall assistant, while a skill is a focused operating procedure the assistant can invoke when the situation calls for it. GPTs shape the experience at a higher level; skills sharpen execution for a specific task. OpenAI’s documentation describes GPTs as custom versions of ChatGPT, while skills are reusable workflows that can also be used inside ChatGPT.

That distinction matters. If you want a broad assistant for a function, team, or domain, build a GPT. If you want a repeatable way to perform one concrete job such as summarizing customer interviews, writing board updates, reviewing contracts, or rewriting emails in a specific voice, build a skill. That is usually the cleaner and more scalable pattern. This is also consistent with OpenAI’s positioning: GPTs combine instructions, knowledge, and capabilities for a custom assistant, while skills package a repeatable workflow that can be shared and reused.