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Context Engineering for Multi-Agent Systems

Context Engineering for Multi-Agent Systems

By : Denis Rothman
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Context Engineering for Multi-Agent Systems

Context Engineering for Multi-Agent Systems

4 (1)
By: Denis Rothman

Overview of this book

Generative AI is powerful, yet often unpredictable. This guide shows you how to turn that unpredictability into reliability by thinking beyond prompts and approaching AI like an architect. At its core is the Context Engine, a glass-box, multi-agent system you’ll learn to design and apply across real-world scenarios. Written by an AI guru and author of various cutting-edge AI books, this book takes you on a hands-on journey from the foundations of context design to building a fully operational Context Engine. Instead of relying on brittle prompts that give only simple instructions, you’ll begin with semantic blueprints that map goals and roles with precision, then orchestrate specialized agents using the Model Context Protocol. As the engine evolves, you’ll integrate memory and high-fidelity retrieval with citations, implement safeguards against data poisoning and prompt injection, and enforce moderation to keep outputs aligned with policy. You’ll also harden the system into a resilient architecture, then see it pivot across domains, from legal compliance to strategic marketing, proving its domain independence. By the end of this book, you’ll be equipped with the skills to engineer an adaptable, verifiable architecture you can repurpose across domains and deploy with confidence. *Email sign-up and proof of purchase required
Table of Contents (16 chapters)
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12
Other Books You May Enjoy
13
Index

Summary

In this chapter, we successfully elevated the context engine to an economically efficient system by directly addressing the enterprise constraints of API costs and context limits. Our technical journey involved architecting and implementing a new specialist, the Summarizer agent, designed to act as an intelligent gatekeeper for large volumes of information. By integrating this agent into the engine's dynamic planning framework, we have equipped our system with a powerful new capability: proactive context management.

Our approach mirrored the professional workflow of a true context engineer, extending beyond mere coding. We began with a conceptual analysis of the architecture, methodically implemented the new agent, and integrated it into the discoverable Agent Registry. Crucially, we subjected our upgraded system to rigorous validation, performing backward compatibility checks to ensure new features did not compromise existing stability before proving the Summarizer&apos...

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