Chain of Thought (CoT)
TechniquesA prompting technique where the AI is guided to reason step-by-step before producing a final answer, significantly improving accuracy on complex tasks.
Full Explanation
Simply adding 'Let's think step by step' to a prompt — or showing examples of step-by-step reasoning — dramatically improves LLM performance on math, logic, and multi-step reasoning tasks. Chain of thought works because it forces the model to allocate more 'compute' to reasoning rather than jumping to an answer.
Instead of asking 'What is 25% of 480?', ask 'What is 25% of 480? Let's think step by step.'
Related Terms
The practice of crafting inputs to AI models to reliably get better, more accurate, or more specific outputs.
Providing a small number of input-output examples in the prompt to guide the AI's response format and style.
AI models specifically optimized for multi-step logical reasoning, math, and complex problem-solving — typically by using chain-of-thought at inference time.