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LLM Lab 6: Chain-of-Thought Builder

Prompt the model to reason step by step and break complex tasks into smaller moves.

Published January 8, 2026

Previous

LLM Lab 5: Instructions and Guardrails

Next

LLM Lab 7: Context and Grounding

Teach the model to show its work

Asking for intermediate steps improves accuracy and debuggability.

Can You Guess?

Which prompt best encourages reasoning?

Decompose a messy task

Follow the steps and watch each checkpoint light up as you progress.

1

Step 1: State the goal

Example: Plan a workshop on prompt engineering.

2

Step 2: List constraints

Audience, time, tools, and must-have topics.

3

Step 3: Break into steps

Agenda draft, activities, examples, materials.

4

Step 4: Ask for reasoning

"Show your reasoning then propose the plan."

5

Step 5: Review and correct

Spot gaps in the reasoning path and ask for fixes.

Try this now

Debug a wrong answer

  • Ask a model a tricky logic question.
  • If it is wrong, ask it to explain how it got the answer.
  • Point out the incorrect step and request a corrected chain of thought.

    • Key Takeaways

    • ✓ Explicit reasoning reduces hallucinations.
    • ✓ Breaking tasks down yields better control.
    • ✓ You can inspect and correct the reasoning path.

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    Lesson: LLM Lab 6: Chain-of-Thought Builder

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