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Chain-of-thought prompting: make the model show its reasoning

How to elicit step-by-step reasoning to improve accuracy on complex tasks.

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When it helps
  • Multi-step math, logic, or planning where errors compound.
  • Any task where intermediate steps matter, not just the final answer.
  • Debugging decisions: seeing the chain lets you spot exactly where reasoning broke.
How to trigger it
  • Add 'Think step by step before answering.' to any prompt.
  • Or ask for a scratchpad: 'First, reason through it. Then give the final answer.'
  • For structured output, separate the reasoning block from the answer block with tags.
  • Ask it to check its own reasoning before committing to the answer.
Templates
Step-by-step reasoning (general)
Problem: [describe the task or question]

Think step by step:
1. Restate what is being asked.
2. Identify what information is known vs. what is missing.
3. Work through the logic in small steps.
4. State your conclusion.

Format:
<reasoning>
[steps here]
</reasoning>
<answer>
[final answer only]
</answer>
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Decision audit (spot the error)
Review this decision chain and find the first point where the reasoning breaks down.

Decision:
"""[paste reasoning or plan]"""

Do this:
1. Restate each step in one sentence.
2. Mark the first step you believe is wrong or unsupported.
3. Explain why and propose a fix.
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FAQ
Does chain-of-thought always help?
No. For simple tasks it adds noise and wastes tokens. Use it for tasks with multiple logical steps where order matters.
What if I need a short final answer?
Separate reasoning from the answer with tags or sections. Ask for the reasoning first, then a single-sentence conclusion.