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AI Agents
8 topics across 7 chapters
Chapter 1
Agent fundamentals: perception, actions, policies
Chapter 2
LLM-based agent architectures (ReAct, tool use, planning loops)
Chapter 3
Tool integration: APIs, function calling, retrieval (RAG)
Chapter 4
Memory for agents: short-term, long-term, vector stores
Chapter 5
Multi-agent systems: roles, coordination, communication
Chapter 6
Evaluation & debugging: benchmarks, traces, unit tests
Chapter 7
Safety & alignment: guardrails, permissions, reliability

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