Learning Path 03

Agents From First Principles

Turn models into systems that plan, use tools, maintain state, search alternatives, revise work and verify outcomes.

Build agent behavior from explicit mechanisms so each layer has a clear purpose and measurable effect.

Agent Systems 10 chapters Sequential or reference
Start at chapter 00 Use with AI
Complete curriculum

Chapters

Work through the path in order, or jump directly to the mechanism you need.

  1. 00What Is an Agent, Really?
  2. 01AI Agent Gives Inconsistent Answers? Generate Multiple Candidates and Rank Them
  3. 02AI Agent Keeps Making the Same Mistake? Add a Critique-and-Revision Loop
  4. 03AI Agent Fails on Multi-Step Tasks? Separate Planning From Execution
  5. 04AI Agent Gets Stuck in a Loop? Add State, Feedback and Stopping Conditions
  6. 05AI Agent Chooses the Wrong Tool? Design Better Tool Interfaces, Schemas and Routing
  7. 06AI Agent Forgets Previous Work? Add Working, Semantic and Episodic Memory
  8. 07AI Agent Picks the First Solution? Add Search Instead of One-Shot Generation
  9. 08AI Agent Says It Worked When It Didn’t? Verify the Result Outside the LLM
  10. 09AI Agent Returning Invalid Tool Calls? How to Validate LLM Actions