What is chain-of-thought prompting and when does it help?

Chain-of-thought (CoT) prompting asks the model to reason step by step before answering, which improves accuracy on multi-step problems like maths, logic, and complex reasoning. It works because generating intermediate steps gives the model 'room' to work through the problem rather than jumping to an answer. Trade-offs: it uses more tokens and can be slower, and for simple tasks it adds cost without benefit. Some newer models reason internally, reducing the need to prompt for it explicitly.