Large Language Models are transforming software development, automation, and intelligence-driven applications. But moving from proof-of-concept to robust, real-world production systems requires more than prompting skills or experimentation. It demands engineering discipline, architectural clarity, reliability strategies, and an understanding of how LLMs behave under real-world constraints.
The Complete Guide to Deploying LLMs in Production is the definitive, end-to-end handbook for engineers, architects, product builders, and technical leaders looking to successfully design, deploy, scale, and monitor LLM-powered applications. Written by expert technical author Rylan Corma, this comprehensive guide walks you through every layer of the production stack from data pipelines and retrieval systems to cost optimization, observability, cloud deployment patterns, and advanced evaluation techniques.
Whether you're building a customer-facing chatbot, an intelligent agent workflow, a data-processing automation layer, or an entire enterprise AI platform, this book gives you the frameworks, tools, patterns, and checklists to make your systems reliable, efficient, and trustworthy.
You'll learn how to architect scalable LLM services, integrate retrieval augmented generation (RAG), create production-ready agent systems, mitigate hallucinations, enforce policy guardrails, and build continuous evaluation pipelines all with real-world practicality.
If you want one book that turns LLM knowledge into production-grade capability this is it.
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