Chain-of-Thought Basics
Chain-of-Thought (CoT) prompting asks the AI to show its reasoning process. This dramatically improves accuracy on complex problems requiring logic, math, or multi-step reasoning.
What is Chain-of-Thought?
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The reasoning process catches errors and ensures logical consistency.
Triggering Chain-of-Thought
Simple phrases that activate CoT:
- "Let's think step by step"
- "Think through this carefully"
- "Explain your reasoning"
- "Show your work"
- "Walk me through your thinking"
Exercise: Add Chain-of-Thought
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When CoT Helps Most
Chain-of-thought is most valuable for:
Math Problems
Calculate the compound interest on $1000 at 5% for 3 years.
Think through each year step by step.
Logic Puzzles
Three friends are standing in a line. Alice is not first. Bob is behind Carol. What's the order?
Reason through the constraints.
Decision Making
Should we build vs buy this feature?
Walk through the considerations methodically.
Debugging
This code returns undefined. What's wrong?
Trace through the execution step by step.
CoT Structure Patterns
Simple CoT
Q: [Question]
Let's think step by step.
Structured CoT
Q: [Question]
Analysis:
Step 1: [First consideration]
Step 2: [Second consideration]
Step 3: [Conclusion]
Answer: [Final answer]
Verification CoT
Q: [Question]
Let me solve this:
[Work]
Let me verify:
[Check the answer]
Final answer: [Confirmed result]
Exercise: Structured CoT for Analysis
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CoT for Error Reduction
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Practice: Apply CoT
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Chain-of-thought transforms AI from a quick-answer machine into a careful reasoner.
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