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quiz vs the machine

Silver1130

Machine Learning

The ReAct Reasoning Pattern

Interleaving thought and action to ground an agent's decisions.

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The ReAct Reasoning Pattern

ReAct stands for reasoning and acting. It is a prompting pattern where the model alternates between writing a short thought and taking an action, rather than committing to an answer immediately.

The rhythm

  • Thought: the model reasons about what it knows and what it needs next.
  • Action: it calls a tool to gather that missing information.
  • Observation: the tool result returns and feeds the next thought.

Why interleaving helps

Pure reasoning can drift into confident hallucination because nothing checks it. Pure acting fires tools blindly without a plan. ReAct ties the two together so each action is justified by a thought, and each thought is grounded by a real observation. This grounding sharply reduces fabricated facts on knowledge tasks.

Practical notes

The thoughts are usually kept in the context but hidden from the user. Because the model explains its reasoning before acting, ReAct traces are also easier to debug. You can read why an agent chose a tool and spot where its logic went wrong, which makes the pattern popular for both reliability and transparency.

Key idea

ReAct interleaves thoughts and actions so reasoning stays grounded in real observations instead of drifting into hallucination.

Check yourself

Answer to earn rating on the learn ladder.

1. What does ReAct interleave?

2. Why does grounding actions in observations help?