May 06, 2026
One-shot prompting is rarely sufficient for complex, multi-step tasks. Prompt chaining—the process of breaking a goal into sequential steps where the output of one prompt becomes the input for the next—is the secret to building high-performance AI systems.
Don't ask your LLM to "write a full book chapter." Instead, ask it to: (1) Outline the argument, (2) Research sources for each point, (3) Draft the paragraphs, (4) Critique and iterate, and (5) Final Polish. By forcing the model to solve smaller, focused segments, you maintain consistency and significantly reduce hallucination risks.
Implement "reflection steps" in your chain. Before moving to the final output, include a "critic" prompt that evaluates the output of the previous step against a set of constraints. If the critic finds issues, the agent can retry that specific step rather than wasting compute on downstream tasks.