Prompt Chaining

Prompt chaining treats a complex task as a pipeline: instead of asking a model to do everything at once, you break it into steps, using the output of each step as input to the next. For example, you might first ask a model to extract key facts from a document, then use those facts to draft a summary, then ask a separate call to review the summary for accuracy. This approach is more reliable than a single large prompt for complicated workflows because each step is a more focused, tractable task. The tradeoff is latency — multiple sequential calls take more time — and error propagation, where mistakes in early steps compound in later ones. For behavior architects, prompt chaining is a practical architectural pattern for improving reliability on complex, multi-stage tasks.