Includes bibliographical references and index.

Introduction to building AI applications with foundation models -- Understanding foundation models -- Evaluation methodology -- Evaluate AI systems -- Prompt engineering -- RAG and agents -- Finetuning -- Dataset engineering -- Inference optimization -- AI engineering architecture and user feedback.

"This book provides a framework for adapting foundation models, which include both large language models (LLMs) and large multimodel models (LMMs), to specific applications"--page xii.

"Foundation models have enabled many new AI use cases while lowering the barriers to entry for building AI products. This has transformed AI from an esoteric discipline into a powerful development tool that anyone can use -- including those with no prior AI experience. In this accessible guide, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models, datasets, evaluation benchmarks, and the seemingly infinite number of application patterns. The book also introduces a practical framework for developing an AI application and efficiently deploying it."--Back cover.