Definition

Prompt chaining is the technique of connecting several prompts together in sequence so an AI model can tackle complex tasks in steps. Each prompt builds on the last, allowing the AI to reason, plan, or break down its actions across multiple stages.

Example

“First, ask the AI to list 3 blog ideas. Then, in a second prompt, tell it to write a full post based on one idea—that’s prompt chaining.”

How It’s Used in AI

Prompt chaining is common in ReAct frameworks, AI agents, and workflow automation tools like LangChain. It’s used for structured tasks like writing, planning, coding, and decision-making.

Brief History

Originally used in manual prompt crafting, prompt chaining became standard with the rise of agents and frameworks that needed more structured task execution. It’s now built into many no-code AI platforms and pipelines.

Key Tools or Models

• LangChain, CrewAI, OpenAI Assistants API

• Works well with tools like memory, tool use, and retrieval

• Enhances reliability and control in multi-step workflows

Pro Tip

Use prompt chaining when tasks require reasoning or transformation in steps. Keep prompts short and focused for best results.