Use AI Skills to Get Better Results, Faster

What you’ll need

An AI tool that supports saved, reusable instructions — Claude (Pro, Max, Team, or Enterprise; skills also work on the API), or a comparable feature like ChatGPT’s Custom GPTs. No coding required to start: a basic skill is plain Markdown, nothing more. Budget an hour for your first one, most of which is thinking through your own process rather than writing.

What is an AI skill, actually?

A skill is a saved set of instructions — usually a short Markdown file — that an AI tool references automatically when a task matches what the skill covers, rather than something typed fresh into every conversation. Instead of re-explaining your formatting preferences, your review checklist, or your brand voice every single time, you write it once, save it, and the AI applies it when relevant. Claude’s own version, released in October 2025, needs nothing more than plain Markdown to get started — code and scripts are optional additions for when instructions alone aren’t enough, not a requirement to begin.

This isn’t unique to one product anymore, either. The underlying format has been adopted well beyond Claude, with tools including ChatGPT, GitHub Copilot, and Google’s Gemini CLI supporting comparable versions of the same idea. The specific menus differ — Claude calls them Skills, ChatGPT’s closest equivalent is a Custom GPT — but the underlying concept is the same across all of them: teach the tool your process once, stop repeating yourself.

What’s the most common mistake people make with this?

Not using skills at all — doing everything from scratch in a chat window, and often starting a brand-new chat each time rather than building on saved context. That’s the single biggest gap between people getting real leverage from AI and people re-explaining the same instructions weekly without noticing the pattern.

The second mistake is subtler and shows up after someone’s already convinced: building one skill that tries to handle an entire process end to end, rather than breaking the process into modular pieces. A single mega-skill for “write and publish an article” is harder to build correctly, harder to fix when one part breaks, and harder to reuse for a slightly different task than the one it was written for. Anthropic’s own documentation backs this up directly, not just as a style preference: skills are explicitly designed so a tool can draw on several of them within one task automatically, without the user manually invoking each one — composability the documentation calls “one of the most powerful parts of the skills feature.” Building several focused skills that combine is the intended way to use the feature, not a workaround.

How do I actually build my first skill?

Start with whatever task eats the most repeated effort — the thing you or your team explains to an AI tool multiple times a week in roughly the same way. That repetition is exactly what a skill is for, and starting with something familiar makes it obvious whether the skill is actually working, since you already know what a good result looks like.

Before writing anything, map the real steps of that task as you actually do it — not an idealized version. If the task is “write a product description,” what do you actually check first, second, third? What do you always forget and have to add back in? This step matters more than the writing that comes after it; a skill built on a vague sense of the process produces vague results.

Then write the skill with the AI’s help, not alone. Describe the process in plain language and let the tool draft the instructions — Claude, for example, can build a skill directly from a conversation or even a screen recording of you doing the task, then hand you a file to review and adjust rather than starting from a blank page. This is the fastest path to a working first skill, and it’s a genuinely different experience than trying to write a perfect instruction set from scratch.

Should one skill handle the whole process?

No — and this is the distinction that separates people getting real leverage from people who tried skills once and found them underwhelming. Break a multi-step process into a skill per sub-step, then chain them together, rather than building a single skill that tries to do everything.

Implai’s own content production runs exactly this way, and it’s the clearest real example available: separate skills handle drafting a review skeleton, formatting a piece for AI-search visibility, and generating the metadata layer, each one triggered at the right point in the process rather than one skill attempting the entire pipeline in a single pass. What used to be a fully manual chain — sketch the core points, analyze the SERP and competitors, write a brief, draft the piece (or send it out), review it, revise it, adapt it for AI-search visibility, write every meta tag, add internal links and images — took roughly 2–3 hours per article, depending on length and complexity. With the skills handling their respective pieces of that chain, the same output now takes a few tens of minutes up to an hour, depending on the same factors, with a specialist directing and checking the result rather than producing every step by hand.

How do I turn several skills into an actual system?

Once two or three skills exist for the pieces of one process, the sequencing matters as much as the individual skills. Implai’s pipeline runs a fixed order — draft, then structural check, then metadata — because each stage depends on the previous one being done first; running metadata generation before the piece is actually finished produces metadata for a draft that’s about to change. Map the real dependencies in your own process the same way before assuming skills can run in any order.

Skills can’t explicitly call each other by name, but a capable AI tool will use multiple relevant skills together automatically within one conversation when the task calls for it — the composability that makes chaining possible without needing to manually invoke each one in sequence.

When should I still just use the chat?

When the task is genuinely a one-off, or when you’re still figuring out what the “right” process even looks like. Building a skill for something you’ve done exactly once formalizes a process you haven’t actually validated yet — better to do it a few times in plain chat first, notice what’s actually repeatable, and turn that into a skill once the pattern is real rather than assumed.

What you built

A repeatable way to convert your own most-repeated process into modular, reusable instructions — not one skill trying to do everything, but several focused ones that combine into a real system. That’s the same shift that took Implai’s own article production from roughly 2–3 hours of fully manual work down to a few tens of minutes to an hour, with the repetitive parts automated and a specialist directing the result rather than producing every step by hand.

For the piece that puts this system to work on a specific output — formatting content so AI search engines actually cite it — see Implai’s guide to that workflow, built using exactly this kind of chained-skill approach.