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Home > Computer programming / software engineering > Programming and scripting languages: general > Mastering Microsoft AutoGen: The Complete Guide to Building, Scaling, and Orchestrating Multi-Agent AI Systems with Python.
Mastering Microsoft AutoGen: The Complete Guide to Building, Scaling, and Orchestrating Multi-Agent AI Systems with Python.

Mastering Microsoft AutoGen: The Complete Guide to Building, Scaling, and Orchestrating Multi-Agent AI Systems with Python.


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About the Book

Stop Prompting. Start Orchestrating.The era of the simple chatbot is over. Welcome to the age of the autonomous
digital workforce.
In just a few years, we have moved from asking AI to "write an email" to
requiring AI to "run a company's research department." Single-prompt
interactions are no longer enough. To solve the complex challenges of 2026, you
need a team of specialized, collaborative, and self-healing AI agents.
Mastering Microsoft AutoGen is the definitive, code-rich guide for developers,
data scientists, and AI architects ready to lead the next revolution in software
engineering. Whether you are building a self-improving coding suite, a real-time
financial analyst, or a global supply chain swarm, this book provides the
professional blueprint for autonomous intelligence.
What's Inside the Laboratory?
This book takes you through a proven Dialogue-to-Deployment (D2D) framework,
moving from basic agent construction to industrial-scale orchestration. You will
master:
- The Core Architecture: Go deep into the DNA of ConversableAgent,
AssistantAgent, and the vital UserProxyAgent.
- Self-Healing Code: Build agents that write, test, and debug their own
software in secure Docker sandboxes.
- Advanced Orchestration: Move beyond simple chats into Sequential Workflows,
Nested Conversations, and Graph-Based (DAG) decision trees.
- Grounded Memory (RAG): Connect your agents to the real world using Vector
Databases like ChromaDB, Pinecone, and Qdrant.
- Skills & Tool Use: Teach your agents to use the web, query SQL databases,
and interact with any API.
- Production-Grade LLMOps: Scale your swarms with Redis caching, monitor
"agent thoughts" with LangSmith and Phoenix, and deploy using FastAPI and
Kubernetes.
- Safety & Governance: Protect your budget and your infrastructure with prompt
injection defense and economic circuit breakers.
In-Depth Professional Case Studies
Theory is nothing without application. This book culminates in the design of two
massive, real-world projects:
1. The Autonomous Financial Analyst: A multi-agent "War Room" that synthesizes
market data, performs quantitative math, and drafts investment memos.
2. The Digital Software House: A self-improving department where Product
Managers, Coders, and QA Engineers build and test software 24/7.
Who Is This Book For?
- Python Developers looking to transition into Agentic Workflows.
- AI Architects designing scalable multi-agent systems for enterprise.
- Tech Leads who need to implement secure, cost-effective LLM solutions.
- Innovation Managers ready to replace static chatbots with autonomous digital
workers.
Lead the Agentic Revolution
The world is moving from "AI as a tool" to "AI as a teammate." By mastering the
AutoGen framework, you aren't just learning a library-you are learning how to
architect the "Society of Mind" that will define the future of computing.
Don't just chat with the future. Build it.
Keywords: Microsoft AutoGen, AI Agents, Multi-Agent Systems, Python AI, LLMOps,
RAG, Autonomous AI, GPT-4o, Llama 3, Vector Databases, Docker for AI, FastAPI,
LangChain, CrewAI, Agentic Workflows.


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Product Details
  • ISBN-13: 9798197332813
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 254 mm
  • No of Pages: 178
  • Returnable: N
  • Sub Title: The Complete Guide to Building, Scaling, and Orchestrating Multi-Agent AI Systems with Python.
  • Width: 178 mm
  • ISBN-10: 8197332819
  • Publisher Date: 17 May 2026
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Spine Width: 10 mm
  • Weight: 372 gr


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