Prompt engineering: chain-of-thought for complex tasks
Break hard problems into reasoning steps to improve agent output quality.
The technique
Instead of asking for an answer directly, ask the model to think step by step.
Example
Weak prompt:
Solve this math problem.
Strong prompt:
Solve this math problem. Show your reasoning step by step before giving the final answer.
Why it works
Chain-of-thought prompting forces the model to use more computation on the problem, surface intermediate reasoning, and catch its own errors.
Variations
- Zero-shot CoT: Add “Let’s think step by step.”
- Few-shot CoT: Provide examples with reasoning traces.
- Self-consistency: Generate multiple reasoning paths and pick the most frequent answer.
When to use
Use CoT when tasks involve math, logic, multi-step planning, or complex decision-making.