[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8},"actionData","errors","root",{"_28":-5,"_38":-5,"_39":40,"_41":42,"_43":44,"_45":46,"_47":48,"_49":50,"_51":52,"_53":54,"_55":56,"_57":58},"routes/_store+/_readers+/email_author.$slug/route",{"_9":10,"_11":-5},"book",{"_12":13,"_14":15,"_16":17,"_18":19,"_20":21,"_22":23},"currentUser","id","Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6Qm9va1Byb2R1Y3QvODI4OTU","title","Production RAG and GenAI Systems","state","unpublished","contactAuthorMethod","email","aboutText","

Production RAG and GenAI Systems is a practical guide to designing, building, evaluating, and operating Retrieval-Augmented Generation (RAG) and modern GenAI systems in production.

Starting with the foundations of embeddings, vector search, retrieval, context construction, and generation, the book gradually moves toward the engineering challenges that matter in real-world systems: document ingestion, chunking, metadata filtering, hybrid retrieval, reranking, evaluation, observability, security, reliability, cost, and production architecture.

The book also explores how RAG fits into the broader GenAI landscape, including tool use, agents, workflows, and architectural patterns for building systems that go beyond simple question answering.

Rather than focusing on a particular vendor or framework, the book emphasizes the underlying engineering principles and mental models that can be applied across technologies and platforms.

It is written for software engineers, backend engineers, architects, and AI engineers who want to move beyond experimenting with RAG and understand how to design GenAI systems that are reliable, measurable, maintainable, and ready for production.

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Kick off your book project, get started with GhostAI, get better at marketing, or spend the day doing all three! Free live workshops on Zoom. Saturday, June 27, 2026.

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