Post by @aiwithgreg

It’s what you build around it. Most people are still using ChatGPT and Claude like a blank text box. They open a new chat, paste in a prompt, tweak it, copy it into a notes app, forget where they saved it, rewrite it next week, then wonder why the output is inconsistent. That is not really a workflow. It is a workaround. The better way is to turn repeat tasks into reusable AI Skills. A Skill is basically a reusable work system for a task you do again and again. Instead of starting from scratch every time, you define the role, the process, the rules and the output format once, then reuse that structure whenever you need the same kind of result. This matters because most useful AI work is repeatable. Meeting summaries. Research briefs. Client updates. Proposal reviews. Content repurposing. Board papers. Sales follow-ups. Project status reports. Policy drafts. Decision logs. If you do the task more than once, it probably deserves a reusable setup. A good Skill tells the AI four things: Role: what should the AI act as? Process: how should it work through the task? Rules: what should it avoid, check or flag? Output: what should the final answer look like? That last part is where most people go wrong. They ask for “a summary” and get a different structure every time. One day it gives bullets. The next day it gives paragraphs. The next day it misses the risks, forgets the actions and buries the follow-ups halfway down the response. If you want consistent outputs, you need to lock the format. For example, a meeting notes Skill might say: Take these messy notes or transcript. Extract the key decisions. Identify actions, owners and deadlines. Flag risks, blockers and open questions. Do not invent missing information. Mark anything unclear as unclear. Return the output in this structure: summary, actions, risks, follow-ups. That is much more useful than just asking: “Summarise this meeting.” The point is not to make AI more complicated. It is to stop making yourself do the same setup work every time. This works whether you prefer ChatGPT or Claude. The product features and setup routes may differ, but the underlying idea is the same: stop treating every repeated task as a brand-new conversation. Build a reusable system that tells the model how to handle that task properly. The big shift is moving from prompts to workflows. A prompt is usually a one-off instruction. A Skill is a repeatable way of working. A prompt says: “Do this.” A Skill says: “When I give you this kind of input, follow this process, obey these rules, and return this kind of output.” That is why Skills are useful for work. They make the output more consistent, easier to review and easier to reuse. The simplest way to build one is: Step 1: Pick one repeat task. Do not try to build a Skill for everything. Start with one painful recurring task, like meeting notes, research briefs or client updates. Step 2: Define the input and method. What will you give the AI? Notes, transcripts, drafts, data, documents, emails? Then decide what it should do first, second and third. Step 3: Lock the output format. Tell it exactly what sections you want back. For example: summary, key points, risks, gaps, next steps and final draft. That is the whole game. Not magic prompts. Not 200 saved prompt templates. Not hoping the AI guesses what you mean. Just repeatable workflows for repeatable work. The best AI users are not necessarily the people with the longest prompts. They are the people who know how to turn messy recurring tasks into clean reusable systems. So the next time you find yourself copy-pasting the same prompt again, ask: Should this be a Skill? Want the template I use to structure these? Comment SKILL and I’ll send it. #ai #chatgpt #claude #skills