{"product_id":"the-generative-ai-engineering-manual-a-practical-guide-to-architecting-rag-pipelines-ai-agents-and-production-llm-systems-9798248827862","title":"The Generative AI Engineering Manual: A Practical Guide to Architecting RAG Pipelines, AI Agents, and Production LLM Systems","description":"\u003cp\u003e • Author(s): Ralf Kohl\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Data Science - Data Modeling \u0026amp; Design\u003c\/p\u003e\u003cp\u003e\u003cb\u003eThe Generative AI Engineering Manual: \u003c\/b\u003e\u003cbr\u003e\u003cb\u003eA Practical Guide to Architecting RAG Pipelines, AI Agents, and Production LLM Systems\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eAre you building generative AI systems, or just experimenting with prompts?\u003c\/b\u003e\u003cbr\u003eIt's easy to generate text with a large language model. It's much harder to architect a Retrieval-Augmented Generation (RAG) pipeline, engineer autonomous AI agents, control cost, ensure reliability, and deploy production-ready LLM systems that scale under real traffic.\u003cbr\u003e\u003cb\u003eThe Generative AI Engineering Manual\u003c\/b\u003e is your blueprint for moving from prototype to infrastructure. This book delivers a practical, engineering-first framework for designing, building, testing, deploying, and scaling modern generative AI systems. It focuses on real-world architecture, RAG pipelines, vector databases, model selection, agent orchestration, LLMOps, monitoring, security, and cost engineering, so you can build systems that are measurable, resilient, and enterprise-ready.\u003cbr\u003eInstead of theory-heavy discussions or surface-level tutorials, this guide walks you through the full lifecycle of production AI systems. You'll learn how to structure ingestion pipelines, optimize embeddings and retrieval, design deterministic agent workflows, enforce API contracts, implement regression testing, and deploy with containerized and distributed architectures.\u003cbr\u003eBy the end of this book, you will be able to: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eArchitect scalable RAG pipelines with clean separation of ingestion, retrieval, and generation layers\u003c\/li\u003e\n\u003cli\u003eEngineer AI agents with structured tool integration and controlled execution depth\u003c\/li\u003e\n\u003cli\u003eSelect models based on performance, latency, and cost trade-offs\u003c\/li\u003e\n\u003cli\u003eImplement automated test suites for generative outputs\u003c\/li\u003e\n\u003cli\u003eDeploy using Docker, Kubernetes, and CI\/CD pipelines\u003c\/li\u003e\n\u003cli\u003eMonitor latency, token usage, hallucinations, and drift in production\u003c\/li\u003e\n\u003cli\u003eApply cost optimization tactics and horizontal scaling strategies\u003c\/li\u003e\n\u003cli\u003eAvoid common architectural pitfalls in enterprise AI systems\u003c\/li\u003e\n\u003c\/ul\u003eWhether you're a data professional, backend engineer, AI architect, or technical leader, this book equips you with the system-level thinking required to build production-grade LLM applications.\u003cbr\u003eGenerative AI is no longer a novelty, it's infrastructure. The difference between experimentation and engineering is discipline.\u003cbr\u003eIf you're ready to design scalable RAG systems, deploy autonomous AI agents, and build reliable production LLM platforms, this manual belongs on your desk.\u003cbr\u003eStart building AI systems that work, at scale.","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47569327554711,"sku":"9798248827862","price":3031.0,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798248827862.webp?v=1774874683","url":"https:\/\/atlanticbooks.com\/products\/the-generative-ai-engineering-manual-a-practical-guide-to-architecting-rag-pipelines-ai-agents-and-production-llm-systems-9798248827862","provider":"Atlantic Books","version":"1.0","type":"link"}