Chain-of-Thought Prompting

Also known as: CoT, CoT prompting

Chain-of-thought prompting instructs the model to produce an explicit reasoning trace — a sequence of intermediate steps — before committing to a final answer. By externalizing reasoning into text, the model can condition its next step on prior logic, which substantially improves accuracy on tasks requiring arithmetic, multi-step planning, or causal reasoning. CoT can be elicited with a simple instruction ('think step by step') or with few-shot examples that model correct reasoning chains.