ModelRefs / Prompt Chaining — AI Glossary
Prompt Chaining — AI Glossary
Passing the output of one LLM call as input to the next, breaking complex tasks into sequential steps. Error propagation is the main risk.
Overview
Prompt chaining enables tasks too long or complex for a single prompt: translate → summarize → classify. Each step can use a different model, temperature, or output parser. Error propagation is the main risk.
Reference details
| Topic | prompting |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
Commonly confused with
A chain is fixed: you decided the steps in advance and the sequence runs the same way every time. An agent chooses its next step at runtime. The distinction is worth holding because a chain is testable end to end and its cost is knowable before it runs, and most tasks described as needing an agent are chains that have not been written down yet.
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Frequently asked questions
What is Prompt Chaining?
Passing the output of one LLM call as input to the next, breaking complex tasks into sequential steps.
What concepts are related to Prompt Chaining?
Closely related concepts include agent workflow, prompt engineering.