by Amit Shekhar · 11 July 2026
How does Chain-of-Thought (CoT) Prompting work?
How Chain-of-Thought (CoT) Prompting works. We will also see why a model that jumps straight to the answer often gets it wrong, how making it reason step by step fixes this, the difference between zero-shot and few-shot CoT, and where this technique is truly useful.
Read on Outcome School ↗then come back to lock it in
Before you read, guessWhat technique involves asking the model to write out reasoning steps before providing the final answer?
Ten seconds, a guess, then read — a wrong guess still makes the answer stick.
What this article covers
- What is a prompt?
- What is an LLM ?
- The problem: when the model jumps straight to the answer
- What is Chain-of-Thought (CoT) Prompting?
- A simple example without CoT and with CoT
- Zero-shot CoT vs Few-shot CoT
- A step-by-step walkthrough of a reasoning chain
- Why does Chain-of-Thought Prompting work?
- Where Chain-of-Thought Prompting is useful
- Things to keep in mind
The article lives on outcomeschool.com. Read it there, then come back: the tutor in the margin has read it and will answer questions, and the questions below check what stayed.