The Designing Multi-Agent Systems Book is Complete and now Available!
It took only 2 years-ish, but I finished writing the multi-agent systems book and it is now available!
A few of you who have been around here for a while might recall I mentioned I was working on a book on AI agents. I’m excited to share that Designing Multi-Agent Systems: Principles, Patterns, and Implementation for AI Agents is now available in both print and digital editions on Amazon!
Get your copy:
Digital edition (PDF and EPUB)
If you’d like to read a free preview of the first two chapters to decide if this is the right book for you - check it out here!
What’s in the Book
The book takes an unusual approach by teaching multi-agent systems from first principles. It presents important theory (the first 3 chapters in Part I), but also carefully walks the reader through building a feature-complete (but hackable) multi-agent framework from scratch (picoagents) - agents (model clients, memory, tools, structured output, agentic memory, human input, agents as tools, observability etc), multiagent patterns (round robin, magentic one etc) and deterministic workflows (agentic systems as computational graphs). This way, you understand not just how to use existing frameworks, but why their architectures work, and how to make informed design decisions as the ecosystem evolves.
It is the hands-on learning experience (395 pages) I would recommend to anyone wanting to understand/implement AI agents and multi-agent systems.
The book covers:
Multi-Agent Fundamentals: Core concepts, design patterns, and user experience principles
Implementation from Scratch: Building agents, workflows, and orchestration by creating a complete Python library called
picoagentsEvaluation and Optimization: Testing, measuring performance, and optimizing for reliability and scale
Production Deployment: Integrating your agents into web applications, deploying them (containers), as well as security, ethics, and responsible AI considerations for real-world applications
Domain Applications: Complete implementations for unstructured data processing with deterministic workflows, and how to build a software engineering agent with autonomous behaviours.
Across 15 chapters, you’ll find 186 code snippets, 50 figures and diagrams, 26 tables, 76 callout boxes, and 73 references. All code examples are available in the companion GitHub repository.
A Personal Journey
Writing this book has been an exploration of one of the fastest-evolving fields in technology. It began with my work on LIDA (one of the first systems for automatic data visualization using LLMs), evolved through building AutoGen / AutoGen Studio at Microsoft Research, and based on work advising dozens of teams on implementing multi-agent systems in production environments.
The journey from that initial idea in December 2023 to holding the finished book has been equal parts exhilarating and humbling.
Thank You
To everyone who has been part of this journey whether through, thoughtful questions, design discussions, or early feedback on drafts thank you. This book stands on your shoulders.
My hope is that this book provides both the technical foundation and the judgment to build effective multi-agent systems, and to recognize when simpler approaches might serve you better.
If there’s interest, I’d be happy to write more about what this process was like - why I wrote the book, how long it took, what tools were helpful, how I came to self-publish the book, what I’m most proud of, and lessons learned along the way. Share thoughts on the comments!
Until then thank you again, and if you grab a copy, please let me know what you think!
More Resources:
Digital version : buy.multiagentbook.com
Book on amazon : https://www.amazon.com/dp/B0G2BCQQJY
Book website with interactive labs: multiagentbook.com
GitHub repository with lots of code: github.com/victordibia/designing-multiagent-systems