Overview

Large language models are powerful, but prompts alone don't build real systems. Real software needs structure, coordination, reliability, security, and deployment discipline. Mastering AutoGen shows you how to move beyond single prompts and build intelligent multi-agent systems that think, collaborate, and execute work like real teams. This is not a theory book. It is a hands-on engineering guide for developers who want to ship production AI applications. You will learn how to design agents with clear roles, connect them through conversations, integrate tools and APIs, enforce safety and governance, and deploy everything as reliable services that run in the real world. By the end of this book, you won't just ""use AI."" You'll engineer agentic systems. What makes this book differentMost AI books stop at prompts or simple wrappers. This book teaches you how to build: - Multi-agent collaboration architectures - Tool-using agents that call Python, APIs, and external services - Memory systems and long-running workflows - Deterministic, testable, production-safe behavior - Secure, sandboxed, enterprise-ready deployments - CI/CD pipelines and behavioral contract testing for agents - Real systems that solve real problems Every concept is backed by clean, runnable Python examples using AutoGen, not pseudo-code. What you will buildThroughout the book, you implement complete, working systems such as: - An autonomous research platform that plans, investigates, critiques, and writes reports - An AI software engineering team that designs, codes, and reviews solutions collaboratively - Enterprise workflow automation agents that route, validate, and execute business processes - Supervisor and manager agents that orchestrate complex tasks - Event-driven pipelines for scalable agent backends - Production-ready services deployed to cloud or on-prem environments These are the same patterns used to build serious AI infrastructure, not chatbots. Inside the bookYou will progressively move from foundations to advanced production topics: - Agent design and roles - Multi-agent communication and orchestration - Tool integration and execution - Human-in-the-loop systems - Memory and context management - Reliability, guardrails, and determinism - Performance and cost engineering - Security, sandboxing, and governance - Deployment, CI/CD, and observability - Real-world case studies - Practical appendices with API references, prompt patterns, troubleshooting, and production checklists Everything is explained in plain English, with a strong focus on how to build, ship, and operate. Who this book is forThis book is for: - Python developers - Backend engineers - AI/ML engineers - DevOps and platform teams - Architects building LLM-powered products If you want to move from experiments to production-grade agent systems, this book is for you. After reading this book, you will be able toDesign agent teams with clear responsibilities Build systems that reason through collaboration Integrate tools and external services safely Test and validate agent behavior like any other service Deploy agents confidently in real environments Architect scalable, secure AI workflows for enterprise use You'll stop thinking in prompts and start thinking in systems. Agentic AI is not the future. It's the next engineering discipline.Start building it today with Mastering AutoGen.

Full Product Details

9798246866948

Table of Contents

Reviews

Author Information

Tab Content 6

Countries Available