Build a multi agent system
€ 150,00 exl. VAT
This handbook is the direct continuation of my earlier guide on building single‑agent system from scratch. If you’ve completed that one, you already understand the fundamentals of LLM‑driven agents, tool use, memory, and orchestration. This new handbook expands those foundations into the world of multi‑agent systems, where coordination, communication, and distributed problem‑solving become the core challenges.
This handbook is a practical, architecture‑first guide to building multi‑agent systems from scratch using only Python and LLM APIs. It walks you through the essential components of multi‑agent design: roles, communication protocols, coordination patterns, planning, memory, tool use, and orchestration. Each module includes hands‑on exercises that gradually build toward a complete, production‑ready multi‑agent architecture.
Rather than relying on frameworks, this handbook teaches you the underlying mechanics so you can design systems that are transparent, debuggable, and fully under your control.
Why this handbook matters
Multi‑agent systems are becoming the backbone of advanced AI applications, from research assistants to workflow automation to complex reasoning pipelines. But most developers only see high‑level demos or framework abstractions. They never learn how these systems actually work. This handbook fills that gap.
It gives you the architectural intuition and engineering skills needed to:
- Design agents with clear roles and capabilities
- Build structured communication channels
- Coordinate distributed tasks
- Manage shared memory and tool access
- Prevent runaway interactions and ensure safety
- Deploy systems that behave predictably under real workloads
If you want to build AI systems that scale beyond a single agent, this is the roadmap.
Who this handbook is for
This handbook is designed for:
- Developers who want to build real multi‑agent systems without relying on frameworks
- Engineers who need to understand the architecture behind modern AI workfl ows
- Technical founders building AI‑powered products
- Researchers exploring agent collaboration and coordination
- Anyone who completed the single‑agent handbook and wants to take the next step
You don’t need advanced math or ML theory, just Python, curiosity, and a desire to build.
Where readers are now
If you’re coming from the previous handbook, you already know how to:
- Build a single agent with tools, memory, and reasoning loops
- Structure prompts and manage context
- Implement basic orchestration and safety checks
- Evaluate and debug agent behavior
You have the foundation, but single agents can only go so far. They struggle with parallelism, specialization, and complex workflows.
Where they will be after reading
By the end of this handbook, you will be able to:
- Design multi‑agent architectures with clear roles and responsibilities
- Implement structured communication protocols and routing logic
- Build coordination patterns like manager‑worker, parallel research, and consensus
- Manage shared and private memory across agents
- Handle tool permissions, conflicts, and parallel execution
- Build a full multi‑agent system that plans, researches, analyzes, and produces structured outputs
- Understand how to scale, monitor, and control multi‑agent interactions safely
You’ll walk away with the confidence and skills to build production‑grade multi‑agent systems from scratch, no frameworks, no magic, just engineering.
Note : This handbook also comes with a bundled glossary to help you quickly understand any technical terms you’re not familiar with.
FAQs
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Our courses are designed to be fast‑paced and short, helping you learn efficiently. Once enrolled, you receive lifetime access to all course materials, so you can revisit them anytime.
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Learners may not resell, share, or redistribute course materials; all content is provided solely for personal educational use
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Review
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A fresh handbook by Shiva on multi agent systems.
After I learned the basics of agents through single agent handbook, I learned a lot about the multi agents by this new handbook. The concepts and terminology were new to me, but the clear explanations, sample codes and figures (especially for workflows) made this hard learning process, simple. I can now better understand the interaction between the agents (like planner, researcher, writer, orchestrator, router etc.) and memory.
Thank you Shiva, well done!