AI Engineering: Building Applications with Foundation Models

Description AI Engineering: Building Applications with Foundation Models by Chip Huyen is the ultimate guide for engineers, developers, and data scientists building modern AI-powered applications. Released in December 2024 by O’Reilly Media, this highly anticipated book introduces a clear, actionable framework for working with foundation models like GPT, Claude, and open-source LLMs. Unlike traditional machine learning books, AI Engineering focuses on applied AI system design—bridging the gap between research models and scalable, production-ready AI apps. �� Key Topics Covered: Prompt Engineering: Techniques to steer and optimize LLM outputs Retrieval-Augmented Generation (RAG): Build smarter, context-aware applications AI Agents & Workflows: Design autonomous systems for complex tasks Evaluation at Scale: Including cutting-edge methods like AI-as-a-judge Latency, Cost, and Hallucination Mitigation: Real-world deployment strategies You’ll also learn how to choose the right model, tune for performance, and integrate AI seamlessly into product workflows. Each chapter blends conceptual clarity with industry examples, making this a practical AI engineering guide for real-world systems. Written by Chip Huyen, Stanford lecturer and author of Designing Machine Learning Systems, this book is a go-to reference for: AI engineers ML ops teams Technical product managers Anyone working with large language models (LLMs) Whether you’re building chatbots, AI tools, or enterprise-grade systems, AI Engineering helps you go from idea to deployment—fast, safe, and smart.