Prompt Chaining for Multi-Step AI Tasks

When a task involves research, analysis, writing and review, one giant prompt can become difficult to control. A prompt chain separates the work into smaller stages so each output can be inspected before it becomes an input to the next stage.

1. Stage 1: define the inputs

Write down the source documents, target audience, business goal and final deliverable. If an input is missing, the chain should make that obvious.

2. Stage 2: extract facts

Ask for factual extraction before asking for polished writing. This gives you a checkpoint where you can remove incorrect or irrelevant information.

3. Stage 3: organize

Turn the extracted material into a table, outline, checklist or decision framework. Structured intermediate results are easier to inspect.

4. Stage 4: draft

Use the approved structure as the input to the writing step. Tell the model which source material is authoritative.

5. Stage 5: review

Use a separate prompt to check the draft against the original requirements. A review step should identify problems, not simply say the draft is good.

Practical example

For a research-heavy article, use one stage to extract source facts, another to organize them, another to draft, and a final stage to compare the draft with the source. Each stage should have a visible output.

Common mistakes

• Giving the assistant a goal but not the source material or constraints that affect the answer.
• Judging an output by fluency alone instead of checking facts and requirements.
• Using a generic template without adapting it to the real audience and task.

FAQ

How much context is enough?

Enough to remove the important ambiguity, but not so much that the actual task becomes hard to find. Keep the source and instructions clearly separated.

Should AI output be used without review?

For important work, review the result against the original source and the requirements before publishing, sending or making a decision.