Chain of Thought
Asking an AI to work through a problem step by step, showing its reasoning as it goes, rather than jumping straight to an answer. Much like a person thinking out loud, this often leads to a more accurate result. This step-by-step reasoning is called chain of thought.
When a question needs a bit of reasoning, an AI that leaps straight to an answer can trip up. Chain of thought is the habit of asking it to slow down and work through the steps first. Adding a line like “think it through step by step” to your request invites the AI to lay out its reasoning before giving a final answer.
Think about how you tackle a tricky sum in your head. If you rush, you might slip up. If you work through it piece by piece, you are far more likely to land on the right answer. The same turns out to be true for AI. Reasoning in the open tends to produce better results on anything involving logic, maths, or several linked steps.
For you, this is a quick and genuinely effective tool. If an AI gives a confident but wrong answer to a problem that needed some working out, try asking it to explain its reasoning step by step. You will often get a better answer, and as a bonus you can see how it got there and spot where it went astray.
Chain of thought is one of the most reliable techniques in prompt engineering. It costs you nothing more than a few extra words in your prompt, and it plays to a real strength of the large language models behind today’s chat tools.