Overview

Building Production LLM Systems is the comprehensive engineering guide for deploying open-source language models at enterprise scale. Written by Cedar Moon, a veteran who has shipped multiple million-dollar LLM systems, this practitioner's handbook covers everything from selecting the right model family (LLaMA, Mistral, Mixtral) to building production-ready infrastructure that rivals proprietary APIs. Across 15 detailed chapters, you'll master quantization techniques that run 70B models on consumer GPUs, inference optimization strategies delivering 3-8× higher throughput, fine-tuning pipelines for 405B parameters on a single card, and RAG systems ready for regulatory scrutiny. The book includes production-tested code, real infrastructure cost models, security hardening for regulated industries, and MLOps patterns for continuous improvement. This isn't theory-it's battle-tested wisdom from real deployments across finance, healthcare, and defense. Whether you're running your first 7B model or orchestrating a thousand-GPU cluster, you'll gain the complete playbook to build LLM systems that are faster, cheaper, and more secure than any API-while maintaining full ownership of your AI stack. Stop renting intelligence. Start owning it.

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