The analogy
In cooking you don't throw all the ingredients into the pot together and hope for the best. First you make the soffritto, then you add the tomato, let it reduce, and at the end you stir it through. Each phase prepares the next, and at each one you taste and adjust if needed. A recipe is a chain of steps, not a single gesture.
Prompt chaining is that sequence applied to AI. You break a complex task into stations — gather, structure, write, review — and at each station you check before moving on. The final dish comes out better because you didn't ask for everything at once.
How it really works
A complex task done in one go forces the AI to hold too many things together, and something slips. By breaking it up, each request is focused on a single operation, which the AI performs better, and its result becomes the clean base for the next step. On top of that you see the intermediate results and correct them right away, instead of discovering the error only at the end, when it's fused into the finished product. No special tool is needed: you just continue the conversation one step at a time.
What you can do in practice
- Break the work into ordered phases. For an article: gather the points, order them into an outline, write one section at a time, then review.
- Run a step, check the result, correct it if needed, and only then ask for the next, building on that.
- Keep each request to a single operation: one thing done well at a time.
- When a step went wrong, redo only that one, not everything from scratch.
A common misconception
People believe that asking for everything at once is more efficient, because it "saves messages". Usually it's the opposite: the mega-request produces a result that's mediocre across the board, because the AI had to do ten things at once. Breaking it up costs a few extra exchanges, but each piece comes out better and you keep control along the way. The time you seem to save with a single go you pay back correcting the muddled result.
Frequently asked questions
When is it worth chaining instead of asking for everything together?
Every time the task has several distinct phases: research plus writing, analysis plus synthesis, draft plus review. For a simple question it's not needed; for a complex job it's what makes the difference between a rough result and a refined one.
Does it need a program or a technical skill?
No. Prompt chaining in its basic form is just continuing the chat one step at a time, using each answer as a springboard for the next request. You do it with the normal conversation.
Isn't it slower?
A bit, in terms of exchanges. But the time spent guiding the steps is less than what you'd lose taking apart and redoing a single result that came out badly. The more complex the task, the more the chain is worth it.
Doesn't breaking up the work risk making the AI lose the thread?
On the contrary, if the steps are clear. A huge task all in one request is exactly what makes it lose the thread. A sequence of focused steps is easier to perform well, and the one keeping the thread of the project is you, checking at each station instead of relying on a single shot in the dark.