Scaling LLM Agents Distributed Cognition & Multi-Agent Ecosystems A Practical Guide to Architecting Collaborative,

Large Language Models changed the world.
Multi-agent LLM ecosystems will redefine it.
In Scaling LLM Agents, Mira S. Devlin takes you inside the next revolution of AI architecture-where networks of specialized LLM agents coordinate, reason, reflect, and self-optimize to accomplish what a single model could never do alone.
This is not another "prompting" book.
This is a systems-engineering blueprint for building scalable, resilient, and tool-driven AI ecosystems that behave more like distributed organizations than standalone chatbots.
Drawing from modern AI orchestration frameworks, emerging research on distributed cognition, and real-world production patterns, this book shows you how to design agent clusters, shared memory fabrics, routing layers, evaluators, and tool hubs that dynamically adapt and continuously improve.
What You'll Learn
How to structure LLM agents into clusters with clear roles, capabilities, and communication protocols
Coordinator and scheduler patterns for robust multi-agent task execution
Decentralized routing fabrics for fast, scalable message passing
Shared vector memory systems for persistent state, grounding, and context fusion
Reflection and optimization loops that help agents correct themselves and learn from outcomes
Tool-driven orchestration using APIs, function calling, and external workflows
Monitoring, evaluation, and telemetry layers to keep your multi-agent system safe, reliable, and transparent
Scalable system topologies for production workloads, real-time reasoning, and enterprise automation
Who This Book Is For
AI engineers designing intelligent, high-performance systems
Software architects modernizing applications with agentic patterns
Founders and CTOs building AI-first products
Researchers exploring distributed cognition and emergent behaviors
Developers wanting to go beyond prompts and learn real LLM engineering
If you've mastered prompting, tinkered with agents, or built early prototypes-this is the book that takes you into the next era: true multi-agent AI ecosystems that scale.
Why This Book Matters
The future will not belong to the biggest model...
but to the best-organized constellation of collaborating models.
This book gives you the architecture, patterns, and practical frameworks to build them.

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