AI Engineering: Building Applications with Foundation Models

About the Book – AI Engineering: Building Applications with Foundation Models

AI Engineering: Building Applications with Foundation Models by Chip Huyen is an insightful and practical guide to designing, developing, and deploying applications powered by modern artificial intelligence. The book explores how foundation models, including large language models (LLMs), can be transformed into useful, reliable, and scalable real-world applications.

It covers essential topics such as prompt engineering, retrieval-augmented generation (RAG), fine-tuning, model selection, AI agents, data management, evaluation, and deployment. Readers learn how to build effective AI systems, improve model performance, reduce operational costs, and address challenges related to accuracy, reliability, and scalability.

Combining technical explanations, practical examples, and industry insights, the book provides a structured understanding of the complete AI engineering lifecycle.

An excellent resource for AI engineers, software developers, machine learning practitioners, data scientists, researchers, and technology professionals seeking to develop production-ready applications using foundation models.

About the Author – Chip Huyen

Chip Huyen is a renowned computer scientist, writer, and artificial intelligence specialist known for her contributions to machine learning systems and practical AI development. She graduated from Stanford University, where she also created and taught courses on deep learning and machine learning systems design.

She has previously worked with leading technology organizations, including NVIDIA, Netflix, and Snorkel AI, helping develop tools and infrastructure for building and deploying machine learning applications. She also co-founded Claypot AI, a company focused on real-time machine learning infrastructure.

Chip Huyen is the author of several books, including Designing Machine Learning Systems and AI Engineering: Building Applications with Foundation Models. Her work focuses on making artificial intelligence more accessible and helping developers transform advanced AI research into practical, reliable applications.

She is widely respected for combining technical expertise, research, and real-world industry experience in the fields of artificial intelligence and software engineering.