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The Bible of Agentic AI Systems Building Intelligent Agents with Python [#1045966]
The Bible of Agentic AI Systems: Building Intelligent Agents with Python
by Stefanos Drakos
English | 2026 | ASIN: B0GX67WDB6 | 339 Pages | Mobi | 1.02 MB
Agentic AI is no longer science fiction - it is production software. This book is a practical, hands-on guide for Python
developers who want to build real autonomous agents using the two most capable frameworks available today: the OpenAI
Agents SDK and the Claude Agent SDK.
Instead of shallow examples, you will build a complete agentic system from the ground up: an agent that perceives,
reasons, uses tools, calls other agents, remembers past conversations, runs on a schedule, and survives restarts in
production.
Inside you will learn how to:
* Understand the perception-reasoning-action loop that powers every modern agent
* Set up a clean async Python environment for agentic workloads
* Build your first agent with the OpenAI Agents SDK and with the Claude Agent SDK, and compare them side by side
* Design and register custom tools, function calling, and structured outputs
* Orchestrate multi-agent systems with handoffs, sub-agents, and delegation
* Add persistent memory with SQLite and vector embeddings for long-term recall
* Integrate Model Context Protocol (MCP) servers for reusable, framework-agnostic tools
* Implement guardrails, safety policies, cost limits, and prompt-injection defenses
* Stream responses over Server-Sent Events for responsive UIs
* Run agents autonomously in the background with schedulers, cron jobs, and daemons
* Deploy to production with FastAPI, Docker, and GitHub Actions
Every chapter ends with working code you can run immediately. The final project is a self-evolving assistant with memory,
skills, sub-agents, and MCP integration - the same architecture used by modern agentic products in industry.
Whether you are a backend engineer, an AI practitioner, or a founder building your first agentic product, this book will
give you the mental model and the code to ship agents with confidence.
Stop calling LLM APIs. Start building agents.
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