Chain-of-Thought Prompting

Chain-of-thought prompting asks a model to show its work — rather than jumping straight to an answer, it’s guided (or instructed) to reason through the problem step by step. This often produces more accurate results on complex tasks because it forces the model to consider intermediate steps before committing to a conclusion. The technique was popularized when researchers discovered that including the phrase “let’s think step by step” in a prompt could dramatically improve performance on math and reasoning problems. For behavior architects, chain-of-thought prompting is a useful tool for improving reliability on tasks that require multi-step reasoning, but it also makes the model’s reasoning visible — which can surface where it goes wrong.