Some IA tasks are too big for one prompt. Ask a model to read forty interview excerpts, derive themes, propose a taxonomy, and validate that taxonomy against the themes, and you will get something plausible for all four steps and dependable for none, the later steps quietly invent the evidence the earlier steps were supposed to supply. A prompt chain splits the work into stages, each with its own prompt, its own output format, and a point where you look at the result before it becomes the input to the next stage.
Chains earn their complexity when there is a genuine handoff: discovery producing material that analysis consumes, analysis producing candidates that synthesis ranks. They are wasted effort when the stages are really one question cut into pieces. Be concrete about where a human has to look, because that is the part a model will otherwise design away in the interest of a tidy workflow. Then read the chain it produces and check the handoffs specifically, if stage three's prompt does not name the exact output stage two produced, the chain breaks the first time you run it.
The value of a chain isn't the number of steps. It's the checkpoints between them, the places where a wrong turn gets caught before it's baked into everything downstream.
Fill in your own details below; the prompt updates as you type. When it's ready, copy it into Claude or whatever AI tool you use.
Design multi-step prompt workflows where the output of one prompt becomes the input to the next, creating systematic processes for complex IA tasks with built-in validation checkpoints.