AI Guides › Skills & Agents

Why Most People's First Skill Is Too Ambitious

By Nigel Guy · 3 min read

The idea usually arrives whole: automate the entire onboarding process, manage the whole inbox, run the whole weekly report end to end. It's not a bad instinct — the biggest, most annoying process is exactly the one you most want gone. It's also almost never the right first skill, and the reason isn't lack of ambition. It's that a first attempt is being asked to solve the hardest problem you have and teach you how skills work, at the same time.

The mechanism

1. Write the ambitious version down in full, don't discard it. The instinct behind it is usually right, and you'll want the full shape later. Get it out of your head and onto the page so it stops competing with the smaller version for attention.
2. Find the single step inside it that recurs most often, on its own. A process with ten steps usually has one or two that show up elsewhere too, independent of the rest. That step, isolated, is a real candidate for a first skill — smaller, and useful even outside the bigger process.
3. Cut anything that requires a judgement call you can't yet write down as a rule. If part of the ambitious version depends on "I'd just know what to do here," that part isn't ready to automate — not because the task is too hard, but because you haven't yet turned your own judgement into a stated procedure. Leave it out of version one.
4. Build the small piece, run it for real, and let it earn the next piece. Once the first slice is genuinely reliable, extend it — don't design the extension in advance. What the first slice actually revealed about the task is better information than what you guessed at the start.
5. Resist finishing the whole thing before using any of it. The temptation with an ambitious idea is to keep building toward completeness before testing anything. Ship the small piece and use it for real before adding the next.

What to skip

Skip trying to design the full, ambitious skill's architecture up front "so it's extensible later" — that's effort spent on a version of the problem you don't understand yet, since you haven't run the small piece for real. And skip abandoning the ambitious idea altogether out of caution; write it down, park it, and build toward it deliberately once the fundamentals are proven.

Guardrails

• Nothing here means big automations are wrong to want — many genuinely valuable skills are large. The point is sequencing: build the muscle on something small before you spend real effort on something big.
• The "one recurring step" test is a heuristic, not a rule with no exceptions — some processes don't decompose cleanly, and forcing an artificial small piece out of one that doesn't have one is its own kind of wasted effort.
• If the ambitious version involves anything irreversible or high-stakes, that's reason for even more caution about attempting it whole, not less — the size of the ambition and the size of the acceptable first mistake should move in opposite directions.

All 751 AI guides · JulieMango plans from £17/mo