Chain‑of‑Thought (CoT)
Sometimes a question is too hard to answer in one go. Chain‑of‑Thought (CoT) prompting asks the AI to show its reasoning step by step before giving the final answer. This dramatically improves accuracy on math, logic, and multi‑step problems.
Chain‑of‑Thought = tell the AI to "think step by step" before answering.
Example: Without CoT
Question: Roger has 5 balls. He buys 2 cans of 3 balls each. How many now?
AI answer (without CoT): 11 (correct, but may guess wrong for harder problems).With Chain‑of‑Thought
Question: Roger has 5 balls. He buys 2 cans of 3 balls each. How many now? Let's think step by step.
AI answer: He starts with 5 balls. He buys 2 cans × 3 balls = 6 balls. Total = 5 + 6 = 11 balls.Zero‑Shot CoT
You don’t need to give examples. Just add the magic phrase: "Let's think step by step." This works for many reasoning tasks.
Q: A bat and a ball cost $1.10. The bat costs $1 more than the ball. How much is the ball? Let's think step by step.When to Use CoT
- Math word problems
- Logic puzzles
- Multi‑hop reasoning (e.g., combining facts from different paragraphs)
- Any task where the answer requires several intermediate steps
Two Minute Drill
- CoT forces the model to show reasoning.
- Add "Let's think step by step" to activate zero‑shot CoT.
- Greatly improves accuracy for multi‑step problems.
- The reasoning steps also help you debug wrong answers.
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