Chain-of-Thought Prompting
Chain-of-thought prompting improves accuracy on multi-step problems by forcing the model to generate intermediate steps rather than jumping to a conclusion. It also makes the reasoning inspectable, which helps you catch where it went wrong. Note that the stated reasoning is not guaranteed to be the actual computation — it is a useful artefact, not a proof. In practice: ‘Work through the calculation step by step, then state the final figure.’ ...