What is Chain-of-Thought Prompting(CoT)? Explained in Everyday Language for AI Beginners

If you’ve ever wanted to break down your answer step by step on a college math exam to get partial credit, then it’s the same Chain of Thought we’re discussing in AI — which means, it is important :)

So in this article, let’s go through the definition, advantages, examples, and how it works.

What exactly is Chain of Thought Prompting?

Chain of Thought prompting (short for CoT) was first introduced in 2022 through the paper titled: Chain-of-Thought Prompting Elicits Reasoning in Large Language Models, where, in the very first sentence, CoT is explained as follows:

We explore how generating a chain of thought — a series of intermediate reasoning steps — significantly improves the ability of large language models to perform complex reasoning.

As its name suggests, “chain of thought” aims to explicitly show thoughts step by step, linked together like a chain, instead of providing only the final answer. Thus, Chain of Thought prompting is a special method of instruction or prompt design that allows you to guide your AI in providing answers in a more transparent manner, revealing the AI’s thought process. In an everyday scenario, it is how you tell ChatGPT (or any AI models that take in prompts) to break down a problem and provide better answers.