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Agentic AI Engineering with RAG: Build Scalable Modular Pipelines for Intelligent Automation Beyond Chatbots
Discover how to engineer next-generation AI systems that think, reason, and act beyond the limits of traditional chatbots. This book bridges theory and practice to help you build scalable, context-aware agentic pipelines powered by Retrieval-Augmented Generation (RAG).
In a world where intelligent systems are rapidly evolving, Agentic AI Engineering with RAG equips developers, researchers, and AI practitioners with the tools and mindset to design autonomous, modular agents capable of real reasoning and adaptive problem-solving.
Through a structured, hands-on approach, this book unpacks the mechanics of RAG, multi-agent collaboration, and the emerging MCP (Model Context Protocol) ecosystem. You’ll learn to connect data, memory, and decision layers to create robust AI architectures that can retrieve, reason, and act with precision and transparency.
From foundational principles to production-ready pipelines, every chapter blends conceptual clarity with practical code, real-world case studies, and modern frameworks helping you move from building chatbots to engineering truly agentic systems.
Benefits:
Master RAG architecture — Learn how to build context-driven, retrieval-augmented pipelines for precision and scalability.
Design agentic systems — Implement modular, multi-agent coordination using frameworks like LangChain, LlamaIndex, and MCP.
Bridge theory and code — Understand not just the “how” but also the “why” behind agentic decision-making.
Production-ready templates — Access reusable blueprints and code samples for enterprise-grade deployments.
Future-proof your skills — Stay ahead with insights into multimodal AI, ethical design, and next-gen automation trends.
Whether you’re an AI engineer, researcher, or innovator, this book will redefine how you think about automation. Start building the next generation of intelligent agents today.
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Paperback. Condizione: new. Paperback. Agentic AI Engineering with RAG: Build Scalable Modular Pipelines for Intelligent Automation Beyond Chatbots Discover how to engineer next-generation AI systems that think, reason, and act beyond the limits of traditional chatbots. This book bridges theory and practice to help you build scalable, context-aware agentic pipelines powered by Retrieval-Augmented Generation (RAG). In a world where intelligent systems are rapidly evolving, Agentic AI Engineering with RAG equips developers, researchers, and AI practitioners with the tools and mindset to design autonomous, modular agents capable of real reasoning and adaptive problem-solving.Through a structured, hands-on approach, this book unpacks the mechanics of RAG, multi-agent collaboration, and the emerging MCP (Model Context Protocol) ecosystem. You'll learn to connect data, memory, and decision layers to create robust AI architectures that can retrieve, reason, and act with precision and transparency.From foundational principles to production-ready pipelines, every chapter blends conceptual clarity with practical code, real-world case studies, and modern frameworks helping you move from building chatbots to engineering truly agentic systems.Benefits: Master RAG architecture - Learn how to build context-driven, retrieval-augmented pipelines for precision and scalability.Design agentic systems - Implement modular, multi-agent coordination using frameworks like LangChain, LlamaIndex, and MCP.Bridge theory and code - Understand not just the "how" but also the "why" behind agentic decision-making.Production-ready templates - Access reusable blueprints and code samples for enterprise-grade deployments.Future-proof your skills - Stay ahead with insights into multimodal AI, ethical design, and next-gen automation trends.Whether you're an AI engineer, researcher, or innovator, this book will redefine how you think about automation. Start building the next generation of intelligent agents today. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9798270820572
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Paperback. Condizione: new. Paperback. Agentic AI Engineering with RAG: Build Scalable Modular Pipelines for Intelligent Automation Beyond Chatbots Discover how to engineer next-generation AI systems that think, reason, and act beyond the limits of traditional chatbots. This book bridges theory and practice to help you build scalable, context-aware agentic pipelines powered by Retrieval-Augmented Generation (RAG). In a world where intelligent systems are rapidly evolving, Agentic AI Engineering with RAG equips developers, researchers, and AI practitioners with the tools and mindset to design autonomous, modular agents capable of real reasoning and adaptive problem-solving.Through a structured, hands-on approach, this book unpacks the mechanics of RAG, multi-agent collaboration, and the emerging MCP (Model Context Protocol) ecosystem. You'll learn to connect data, memory, and decision layers to create robust AI architectures that can retrieve, reason, and act with precision and transparency.From foundational principles to production-ready pipelines, every chapter blends conceptual clarity with practical code, real-world case studies, and modern frameworks helping you move from building chatbots to engineering truly agentic systems.Benefits: Master RAG architecture - Learn how to build context-driven, retrieval-augmented pipelines for precision and scalability.Design agentic systems - Implement modular, multi-agent coordination using frameworks like LangChain, LlamaIndex, and MCP.Bridge theory and code - Understand not just the "how" but also the "why" behind agentic decision-making.Production-ready templates - Access reusable blueprints and code samples for enterprise-grade deployments.Future-proof your skills - Stay ahead with insights into multimodal AI, ethical design, and next-gen automation trends.Whether you're an AI engineer, researcher, or innovator, this book will redefine how you think about automation. Start building the next generation of intelligent agents today. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798270820572
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