Context Engineering for Multi-Agent Systems
Djan Wang
ISBN 13: 9798263691011
Verlag: Independently Published, 2025
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New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bestandsnummer des Verkäufers L0-9798263691011
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Context Engineering for Multi-Agent Systems: Optimizing Memory, Communication, and Workflow in AI Agents is a practical guide for developers, researchers, and system architects who want to design intelligent, reliable, and scalable agentic AI systems.
Modern AI agents cannot function effectively without well-structured context. From memory persistence to communication protocols, from orchestrating multi-agent workflows to integrating retrieval-augmented knowledge, context engineering is the backbone that determines whether agents collaborate productively—or collapse under complexity.
This book provides a hands-on, implementation-focused framework for mastering context in multi-agent systems. Readers will learn:
How to design short-term and long-term memory architectures for agents.
Strategies for communication across distributed agents, including message passing, routing, and shared state.
Practical approaches to building scalable workflows that integrate both SLMs and LLMs for cost-efficient reasoning.
Methods for connecting vector databases, retrieval-augmented generation (RAG), and external tools into multi-agent pipelines.
Debugging, optimization, and best practices for real-world deployment.
Packed with practical insights, annotated code examples, and actionable patterns, this book bridges the gap between conceptual AI frameworks and production-ready systems. Whether you are an AI developer, researcher, or product engineer, you will gain the skills to optimize memory, communication, and orchestration in your agent workflows.
If you’re ready to go beyond surface-level orchestration and master the real engine that drives intelligent agents-contex-this book will give you the blueprint.
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Titel: Context Engineering for Multi-Agent Systems
Verlag: Independently Published
Erscheinungsdatum: 2025
Einband: PAP
Zustand: New
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Paperback. Zustand: new. Paperback. Context Engineering for Multi-Agent Systems: Optimizing Memory, Communication, and Workflow in AI Agents is a practical guide for developers, researchers, and system architects who want to design intelligent, reliable, and scalable agentic AI systems.Modern AI agents cannot function effectively without well-structured context. From memory persistence to communication protocols, from orchestrating multi-agent workflows to integrating retrieval-augmented knowledge, context engineering is the backbone that determines whether agents collaborate productively-or collapse under complexity.This book provides a hands-on, implementation-focused framework for mastering context in multi-agent systems. Readers will learn: How to design short-term and long-term memory architectures for agents.Strategies for communication across distributed agents, including message passing, routing, and shared state.Practical approaches to building scalable workflows that integrate both SLMs and LLMs for cost-efficient reasoning.Methods for connecting vector databases, retrieval-augmented generation (RAG), and external tools into multi-agent pipelines.Debugging, optimization, and best practices for real-world deployment.Packed with practical insights, annotated code examples, and actionable patterns, this book bridges the gap between conceptual AI frameworks and production-ready systems. Whether you are an AI developer, researcher, or product engineer, you will gain the skills to optimize memory, communication, and orchestration in your agent workflows.If you're ready to go beyond surface-level orchestration and master the real engine that drives intelligent agents-contex-this book will give you the blueprint. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9798263691011
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Paperback. Zustand: new. Paperback. Context Engineering for Multi-Agent Systems: Optimizing Memory, Communication, and Workflow in AI Agents is a practical guide for developers, researchers, and system architects who want to design intelligent, reliable, and scalable agentic AI systems.Modern AI agents cannot function effectively without well-structured context. From memory persistence to communication protocols, from orchestrating multi-agent workflows to integrating retrieval-augmented knowledge, context engineering is the backbone that determines whether agents collaborate productively-or collapse under complexity.This book provides a hands-on, implementation-focused framework for mastering context in multi-agent systems. Readers will learn: How to design short-term and long-term memory architectures for agents.Strategies for communication across distributed agents, including message passing, routing, and shared state.Practical approaches to building scalable workflows that integrate both SLMs and LLMs for cost-efficient reasoning.Methods for connecting vector databases, retrieval-augmented generation (RAG), and external tools into multi-agent pipelines.Debugging, optimization, and best practices for real-world deployment.Packed with practical insights, annotated code examples, and actionable patterns, this book bridges the gap between conceptual AI frameworks and production-ready systems. Whether you are an AI developer, researcher, or product engineer, you will gain the skills to optimize memory, communication, and orchestration in your agent workflows.If you're ready to go beyond surface-level orchestration and master the real engine that drives intelligent agents-contex-this book will give you the blueprint. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9798263691011
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