Isbn: 9798276981970 - scaling llm agents: distributed cognition & multi-agent ecosystems: a practical guide to architecting collaborative, tool-driven, and self-optimizing ai systems: 2 (the agentic ai engineering series) (5 resultados)

Paperback. Condición: New.

Taschenbuch. Condición: Neu. Neuware - Build AI systems that don't just respond-they collaborate, adapt, and evolve.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 automationWho 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 engineeringIf 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 MattersThe 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.Order your copy today and start building the AI ecosystems of tomorrow.…

Paperback. Condición: New.

Paperback. Condición: new. Paperback. Build AI systems that don't just respond-they collaborate, adapt, and evolve.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 LearnHow to structure LLM agents into clusters with clear roles, capabilities, and communication protocolsCoordinator and scheduler patterns for robust multi-agent task executionDecentralized routing fabrics for fast, scalable message passingShared vector memory systems for persistent state, grounding, and context fusionReflection and optimization loops that help agents correct themselves and learn from outcomesTool-driven orchestration using APIs, function calling, and external workflowsMonitoring, evaluation, and telemetry layers to keep your multi-agent system safe, reliable, and transparentScalable system topologies for production workloads, real-time reasoning, and enterprise automationWho This Book Is ForAI engineers designing intelligent, high-performance systemsSoftware architects modernizing applications with agentic patternsFounders and CTOs building AI-first productsResearchers exploring distributed cognition and emergent behaviorsDevelopers wanting to go beyond prompts and learn real LLM engineeringIf 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 MattersThe 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.Order your copy today and start building the AI ecosystems of tomorrow. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condición: new. Paperback. Build AI systems that don't just respond-they collaborate, adapt, and evolve.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 LearnHow to structure LLM agents into clusters with clear roles, capabilities, and communication protocolsCoordinator and scheduler patterns for robust multi-agent task executionDecentralized routing fabrics for fast, scalable message passingShared vector memory systems for persistent state, grounding, and context fusionReflection and optimization loops that help agents correct themselves and learn from outcomesTool-driven orchestration using APIs, function calling, and external workflowsMonitoring, evaluation, and telemetry layers to keep your multi-agent system safe, reliable, and transparentScalable system topologies for production workloads, real-time reasoning, and enterprise automationWho This Book Is ForAI engineers designing intelligent, high-performance systemsSoftware architects modernizing applications with agentic patternsFounders and CTOs building AI-first productsResearchers exploring distributed cognition and emergent behaviorsDevelopers wanting to go beyond prompts and learn real LLM engineeringIf 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 MattersThe 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.Order your copy today and start building the AI ecosystems of tomorrow. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…