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Agentic AI
Planning & Control Flow
ReAct
Interleave a single thought, a single tool call, and a single observation per step so the agent reasons over fresh evidence.
Intent & Description
🎯 Intent
Interleave a single thought, a single tool call, and a single observation per step so the agent reasons over fresh evidence.
📋 Context
A team builds an agent for a task that cannot be answered from the model’s parametric knowledge alone — it has to look something up, query a database, search the web, or take an action against a real system. The next step often depends on what the previous tool call returned, so the agent cannot plan all calls up front. Tool calls cost latency and money and may have side effects, so each one needs to be deliberate.
💡 Solution
- On each step the agent emits Thought (private reasoning about what to do next), Action (a single tool call), and Observation (the tool’s result). - Repeat until the agent decides it has enough information to answer. - A step budget bounds the loop and prevents runaway execution.
Real-world Use Case
- The next action depends on what was learned from the previous action.
- The agent needs tool access during a multi-step task.
- Outputs from tools are short and inspectable so the model can react to them.
Source
Advantages
- Lowest-overhead path for simple lookups and single-field updates.
- Easy to inspect and debug step by step.
Disadvantages
- Sequential by nature; long traces are slow and expensive.
- No global plan; the agent can wander without a step budget.