ReAct (Reason + Act)

What ReAct Is

ReAct (Reason + Act) is an agent pattern where a model interleaves an explicit reasoning step with a tool call, then reads the result before deciding what to do next. The name comes from the 2023 paper "ReAct: Synergizing Reasoning and Acting in Language Models", from researchers at Princeton and Google Research.

Not to be confused with React, the JavaScript UI library — same name, unrelated concept.

The Loop

ReAct repeats three parts as many times as needed:

• Thought — the model reasons about the current state and what it needs to do next
• Action — the model calls a tool to gather information or take a step
• Observation — the result of that tool call gets added to what the model can see

How It Works Mechanically

Each tool call is the model pausing generation with a tool_use stop reason: it names a tool and its arguments, the calling code executes it, and the result is sent back as a tool_result so the loop can continue. The model never runs a tool itself — it requests, your system executes.

Why It Matters

ReAct is the default single-agent pattern behind most production agents, including LangGraph's create_react_agent and Claude Code's own loop. Newer patterns like plan-and-execute and reflection build on top of ReAct rather than replacing it, usually by adding an upfront plan or a self-critique step around the same core reason-act-observe cycle.