Prompt Chaining
1 min read · Reviewed 17 Oct 2026
In short
Breaking one big request into a sequence of smaller ones, each using the last answer.
In plain English
Instead of asking for the whole thing at once, you ask for one part, check it, and feed it into the next request. Each step is small enough to judge, and a mistake gets caught where it happens rather than three pages later.
A real example
Asking for a complete sales page in one prompt gives you six sections all making roughly the same argument in slightly different registers, because the model had one idea and six headings to spread it across. Asking section by section — problem, then offer, then proof — against the same brief keeps them distinct, and lets you fix the proof section without regenerating the page.
Why it matters
The longer the single request, the more the output drifts toward generic, because the model is averaging across everything you asked for at once. Chaining also gives you a place to intervene: you pick the strongest version at each step rather than accepting a whole draft. It costs a few more minutes and saves the rewrite.
