Chain-of-Thought Prompting: How to Make AI Think Better
Chain-of-thought prompting is the single highest-leverage technique for improving AI reasoning. Learn how it works and when to use it.
In 2022, Google researchers discovered something surprising: adding the phrase 'Let's think step by step' to the end of a math problem dramatically improved AI accuracy. Not by fine-tuning. Not by using a bigger model. Just by adding six words.
This is chain-of-thought prompting. It works because large language models are fundamentally completion engines — they predict the most likely next token based on context. When you ask for an answer directly, the model skips to the output. When you ask it to reason step by step, you're adding a reasoning scaffold that prevents the model from jumping to a wrong conclusion.
Use it for: multi-step math problems, logical deductions, complex planning tasks, and any situation where an incorrect shortcut is worse than a slightly longer correct answer.