Build. Train. Deploy. Scale. The AI revolution is no longer theoretical-it's practical. The LLM Builder's Handbook is your complete, end-to-end guide to building, training, and deploying large language models (LLMs) that actually work in production. Written for engineers, data scientists, and technical leaders, this handbook turns complexity into clarity. From data collection and architecture selection to fine-tuning, deployment, and lifecycle management, every chapter provides actionable, field-tested insights grounded in real-world engineering. You'll learn how to: Design scalable data pipelines and training workflows.Choose, fine-tune, and optimise open-source LLM architectures.Implement retrieval-augmented generation (RAG) and parameter-efficient training (LoRA, PEFT).Deploy models using modern inference stacks and Kubernetes.Monitor, evaluate, and continuously improve models after release.Apply responsible AI governance, cost control, and ethical safeguards.Whether you're prototyping your first chatbot or building enterprise-grade AI infrastructure, this book equips you to go from zero to production with confidence.