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Part 5: Planning & Reasoning

Overview

What makes an agent different from a chatbot? Reasoning and planning.

This section covers how agents think about problems, break them into steps, and adapt when things don't go as expected.


Core Concepts

Concept Description
Chain-of-Thought Step-by-step reasoning visible in output
Tree-of-Thought Exploring multiple reasoning branches
Decomposition Breaking goals into sub-goals
Adaptation Adjusting strategy based on results

Chapter Map


Why This Matters

  • Reliability: Explicit reasoning is debuggable
  • Transparency: You can see why agent did something
  • Quality: Better reasoning = better decisions
  • Adaptability: Agents adjust to changing conditions

Key Insight

Reasoning is not thinking harder—it's thinking differently

A model using CoT on a hard problem might use 50% more tokens but get 30% more accurate answers. The extra tokens are spent on reasoning, not memorization.


Next: Start with Planning Fundamentals


Last Updated: August 9, 2026