Lesson 5 of 8
Break the job into a chain
6 min read
You ask for the whole thing in one go — "write me a complete launch plan" — and get back something broad and shallow. Break that same job into a few steps, each feeding the next, and the result transforms.
One giant ask versus a chain
A do-everything prompt forces the AI to juggle every part at once, and it does none of them well. [Prompt chaining](glossary://prompt-chaining) splits the job into a short sequence, where each answer feeds the next: first brainstorm the angles, then outline from the best one, then draft from the outline. Each step is small and focused, so each result is sharp — and they build on each other.
Prompt chaining breaks a big task into a sequence of smaller prompts, each output feeding the next. One focused step at a time beats a single giant request.
Catch mistakes before they spread
Chaining has a second payoff and a matching risk. The payoff: you see each step before moving on, so you can fix a wrong turn early. The risk: because each step builds on the last, a mistake that slips through early quietly corrupts everything after it. So glance at each result before continuing, and keep chains short — a handful of steps, not twenty, or the output starts to drift.
Each step feeds the next, so you can catch an error early — but one you miss spreads down the whole chain. Check each result, and keep the chain short.
You already do a simple version whenever you reply "good, now make it shorter" — that follow-up is the next link. Chaining is just doing it deliberately, planned from the start.
The gist
- —A short sequence of focused prompts beats one giant do-everything request
- —Each step's output feeds the next, so the work builds instead of arriving flat
- —Check each result as you go — an early mistake spreads to every step after it, and long chains drift
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