Chain-of-thought prompting
Chain-of-thought prompting is instructing a model to work through its reasoning step by step before giving an answer, rather than answering immediately.
It measurably improves accuracy on arithmetic, logic, and multi-step analysis, because generating intermediate steps gives the model more computation to reach the answer. It does not help — and often hurts — on short creative or stylistic tasks, where the deliberation shows up as stilted output.
Related terms
- Reasoning model
- A reasoning model is a language model trained to produce extended internal deliberation before answering, spending more computation on hard problems.
- Self-consistency
- Self-consistency is a technique that samples several independent answers to the same prompt and takes the most common result, instead of trusting a single response.
- Step-back prompting
- Step-back prompting is asking a model to state the general principle behind a question before answering the specific question.
More on techniques
See the full glossary, read the guides, or put it into practice in the prompt builder.