What is Chain of Thought?

A prompting technique that guides AI models to break down complex reasoning into step-by-step thought processes.

🤖

Definition

Chain of Thought (CoT) is a prompting technique that encourages AI models to show their reasoning process by breaking down complex problems into intermediate steps, making their decision-making process more transparent and often more accurate.

🎯

Purpose

CoT aims to improve AI reasoning accuracy on complex tasks by mimicking human problem-solving approaches where we think through problems step-by-step rather than jumping directly to conclusions.

⚙️

Function

CoT works by providing examples or instructions that demonstrate step-by-step reasoning, encouraging the AI to generate intermediate thoughts and logical connections before arriving at a final answer.

🌟

Example

Instead of asking "What's 23 × 47?", using CoT: "Let's solve 23 × 47 step by step: First, I'll break it down: 23 × 40 = 920, then 23 × 7 = 161, so 920 + 161 = 1,081."

🔗

Related

Connected to Prompt Engineering, Reasoning Models, Few-Shot Learning, Problem Solving, and AI Interpretability research.

🍄

Want to learn more?

If you'd like to go deeper into Chain of Thought (CoT) —or bring this kind of training to your team— let's talk. I help teams understand and apply these concepts. I'd love to hear from you!