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AI Agents from First Principles: A Practical Python Guide to Tools, Memory, and RAG
Paperback
Publisher: Independently Published
Published: Oct 19 2026
Pages: 272
Weight: 0.81
Height: 0.57 Width: 6.00 Depth: 9.00
Language: English
Build an AI agent in plain Python. No frameworks, no magic, no API key required to start.
Everyone talks about AI agents. Few people can explain what happens inside one: how it decides, when it should ask a human for permission, what it should remember, and how it answers from documents without making things up.
This book answers those questions by building one. You'll follow Rosa, who runs a small neighborhood bakery and wants an AI assistant to take cake orders. Chapter by chapter, her assistant learns to use tools, wait for approval before acting, avoid recording the same order twice, remember customers without leaking their data, and look things up in documents while citing its sources.
What makes this book different
- No frameworks. No LangChain, LangGraph, or CrewAI. You build each piece in plain Python and see exactly what frameworks hide, so learning and debugging any of them becomes much easier.
- Starts from everyday life. Part I has almost no code. Concepts come with examples everyone understands, before the technical vocabulary.
- Tested, open-source code. Five hands-on projects on GitHub, MIT-licensed, with automated tests. The local examples run without an API key, even in Google Colab.
- Honest about limits. Every hands-on chapter ends with What's missing for production, and one chapter covers when not to use an agent at all.
What you'll learn
- What an agent is, and isn't: environments, goals, the five classic agent types, and how much autonomy to give one
- The agent loop: tool calling, ReAct, planning, self-review, budgets, and how loops fail
- Safe tools: structured calls, validation, permissions, human approval, and idempotent actions that never charge a customer twice
- Context and memory: what the model needs now, what to save for later, what to forget, and how memory can become an attack surface
- RAG: keyword and semantic search, access filters, answers with citations, and an honest I couldn't find it
Who this book is for
Developers who use agent frameworks and want to understand what's underneath; computer science students; and managers and tech leads who need to make decisions about AI agents. Basic Python helps in the later hands-on chapters, and an appendix walks you through setting up your environment.
About the author
Humberto Jorge de Moura Costa, PhD, is a professor and researcher at the Federal Institute of Rio Grande do Sul (IFRS), Brazil, and an IEEE Senior Member. He leads a software lab where he teaches AI to developers.
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