What is Prompt Chaining?
Breaking complex AI tasks into sequential prompts where each step's output feeds into the next step's input.
Definition
Prompt chaining is the technique of decomposing a complex task into a sequence of simpler prompts, where the output of one prompt becomes the input (or context) for the next. This approach improves reliability and quality for multi-step tasks that a single prompt would handle poorly. Each step can have its own system prompt, temperature setting, and validation logic. Common patterns include: generate-then-critique, research-then-synthesize, outline-then-expand, and translate-then-verify. Prompt chaining is foundational to AI agent architectures and workflow automation tools. It trades latency and cost for significantly better output quality on complex tasks.
Examples
Why It Matters
Prompt chaining is the key technique for getting reliable results from AI on complex tasks. Learning to break problems into steps dramatically improves the quality of AI assistance you receive.
Related Terms
Function Calling
An AI model's ability to output structured requests to invoke external functions, APIs, or tools during a conversation.
Tool Use
An AI model's ability to select and invoke external tools like search engines, calculators, or code interpreters.
Multi-Agent Systems
Architectures where multiple specialized AI agents collaborate, debate, or coordinate to solve complex tasks.
AI Orchestration
Managing and coordinating multiple AI models, tools, and workflows to complete complex end-to-end tasks.
Common Questions
What does Prompt Chaining mean in simple terms?
Breaking complex AI tasks into sequential prompts where each step's output feeds into the next step's input.
Why is Prompt Chaining important for AI users?
Prompt chaining is the key technique for getting reliable results from AI on complex tasks. Learning to break problems into steps dramatically improves the quality of AI assistance you receive.
How does Prompt Chaining relate to AI chatbots like ChatGPT?
Prompt Chaining is a fundamental concept in how AI assistants like ChatGPT, Claude, and Gemini work. For example: Step 1: Generate an outline → Step 2: Write each section → Step 3: Edit for consistency Understanding this helps you use AI tools more effectively.
Related Use Cases
AI Models Using This Concept
See Prompt Chaining in Action
Council lets you compare responses from multiple AI models side-by-side. Experience different approaches to the same prompt instantly.