Foundation Model Engineering: From Theory to Production

"Foundation Model Engineering" is a technical textbook designed to help AI engineers and research-oriented readers move beyond surface-level understanding of foundation models by explaining how modern LLMs work, why the technology stack evolved as it did, and the engineering trade-offs involved in production systems. The book connects topics like Transformers, attention mechanisms, mixture of experts, RLHF, RAG, and agents into a unified narrative, focusing on building better engineering judgment rather than just memorizing terminology. It includes rigorous conceptual explanations, PyTorch examples, quizzes, and interactive visualizers, and is intentionally positioned as a deep technical resource rather than a beginner's introduction.