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Lesson 2.2 — Chain-of-Thought Prompting
Ever notice an AI get a simple math or logic question wrong? Chain-of-thought prompting fixes a lot of that. It’s like asking someone to show their work on a math test instead of just writing the final answer.
Walking through the steps out loud catches mistakes that jumping straight to a conclusion would miss — and it works for scheduling, budgeting, and planning problems, not just math.
💬 Prompt
A store has 120 apples. They sell 45 in the morning and 30 in the afternoon, then restock with 60 more apples at closing. Think through this step by step, then give the final count.
✅ Sample AI Response
- Start with 120 apples.
- Subtract 45 sold in the morning → 75 remaining.
- Subtract 30 sold in the afternoon → 45 remaining.
- Add 60 restocked → 105 apples.
Final count: 105 apples
Practical Tip
Try this with a scheduling problem from your own week, like planning a project timeline. Ask the AI to think it through step by step before giving you the final plan.
Key Takeaway
Asking the model to reason step by step often improves the accuracy of the final answer, especially on anything with more than one moving part.