AI Engineering: Building Applications with Foundation Models

Very detailed and well explained! Anyone with basic knowledge of Computer Science can read this book. I just finished the first chapter. This book gives a high level overview of AI application development.

A great book that gives you a comprehensive overview of the GenAI tech in an easy to digest format. A great starting point for all seriously involved in AI tech.

It's always daunting to pick up a technical book that's over 500 pages long or 21 hours long. However, this book did not disappoint. Not every section, of course, addressed my particular needs. However, the entire treatise was clearly communicated with a broader technical audience in mind. That should be no surprise because Chip Huyen, besides being an AI expert, taught graduate school classes in AI at Stanford and writes science fiction as a side hobby. This book is simply the best technical introduction I've encountered to date. The book starts with high-level concepts about AI, which would be accessible to all sorts of scientific folks. Then it focuses on technical topics that are of most interest to engineers. It does an excellent job of centering around concepts first and not being wedded to particular technologies which will soon change. I valued the insights so much that, after listening to the audiobook, I even bought a paper copy to have for a reference. I plan to continue to read about AI engineering, but given that I haven't taken formal coursework in the topic, this book served as an equivalent to a graduate school class to give me confidence to dive deeper. Although some math were presented, the audiobook was incredibly accessible, unlike with some technical books. For those who spend time commuting in cars, I recommend listening to the text if you don't have time to flip through a paper book. Overall, this book raised my game significantly about AI. Where other books obscure with technical jargon, this book enlightens with clear concepts. I still need to brush up on a few focused topics to ready myself for a project, but I'm much more fluent about the ideas than before. I highly recommend this in-depth introduction, at least for the next few years until the field outpaces our knowledge once again.

A bit pricey to what I usually buy, but I can confidently say "You get what you pay for"! I am so jealous of the author's clarity and easy tone that somehow manages to convey an impressive amount of information. In technical writing, if it looks easy, it certainly wasn't! If I survive the technopocalypse, I look forward to reading more of Chip's books!

Very informative. The audio version could use a little polishing like reading a table is not very conducive to the understanding and should be skipped

Can't describe in words how important this book is in today's tech landscape. It covers all required ground required to learn GenAI concepts in detail with ease.

A great resource for anyone looking to enter the field of AI engineering. The book assumes some prior experience with basic ML and AI concepts, which allows it to dive deeper into practical and relevant topics without spending too much time on fundamentals. Highly recommended if you have that foundation and want to take the next step.

This book isn’t that deep and doesn’t require extensive thinking, but it gives a great overview and a deeper dive into AI engineering. I’ll take the lessons learned here and may refer back to the book while building real applications at my company.

Probably the best book on the topic

Chip is master at explaining complex concepts in an easy to understand words, with lots of practical examples! I was not expecting less after reading her first book tho!

The book had exactly the level of depth I needed. I’m coming from the data engineering side and needed some complete overview of AI Engineering. The book gave a complete coverage of the key topics while still going with some details (but avoiding the non-necessary technicalities). The reference are really valuable and worth the de-tour while reading.

If you feel like the ground is shifting beneath your feet as an engineer, you aren't imagining it and Chip Huyen’s AI Engineering is one of the best guides to make sense of the chaos. Our February 2026 Data & AI Book Club recently dissected this book, and the consensus was clear; it’s a manual for the new reality of software development. Whether you are a seasoned architect or a developer just starting to integrate agentic workflows, this book provides the framework to stay relevant. It’s not just about learning tools; it’s about understanding the shift in economics and strategy that defines the current year. AI is a fast evolving space and so much has already happened since the book was published. We look forward to a second edition that includes AI engineering with vibe coding, AI platforms and multi agent systems.

A solid introduction to LLMs and AI engineering. The book explains key concepts well and gives a good overview of how modern AI systems are built and used. Some parts may feel a bit challenging for non-technical readers, but it’s still approachable and worth the read if you’re interested in the field.