AI Vocabulary · 03 Working with AI
What is Chain of Thought?
Getting a model to work through a problem step by step before answering, which tends to improve results on multi-step tasks.
Chain of thought describes intermediate steps a model writes out before its final answer: breaking a problem into parts, calculating, checking. Researchers found that prompting models to "think step by step" improved results on maths and logic tasks. Reasoning models now do this by default.
The steps are generated text, like everything else a model produces. They often help, but they are not a guaranteed record of how the answer came about, and a confident chain of steps can still end in a hallucination.
Why it matters for you
For anything with several steps, such as calculations, comparisons and plans, ask the model to show its working or use a reasoning mode. Visible steps also make it easier for you to spot where it went wrong.
Own it
Read the steps, don't just trust the conclusion. The working is where you catch wrong assumptions before they become decisions.
Where it comes from
Google researchers led by Jason Wei named the technique in 2022 in Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. They showed that a few worked examples with written-out steps made large models much better at maths and logic puzzles. A few months later, another team found that simply adding "Let's think step by step" to a prompt had a similar effect (Kojima et al., 2022).
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