AI Engineering

Building Applications with Foundation Models

Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models.

The book starts with an overview of AI engineering, explaining how it differs from traditional ML engineering and discussing the new AI stack. The more AI is used, the more opportunities there are for catastrophic failures, and therefore, the more important evaluation becomes. This book discusses different approaches to evaluating open-ended models, including the rapidly growing AI-as-a-judge approach.

AI application developers will discover how to navigate the AI landscape, including models, datasets, evaluation benchmarks, and the seemingly infinite number of use cases and application patterns. You'll learn a framework for developing an AI application, starting with simple techniques and progressing toward more sophisticated methods, and discover how to efficiently deploy these applications.

PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.

©2025 Developer Experience Advisory LLC (P)2025 Ascent Audio

Awesome!

You've given me lots to think about. I look forward to re-listening to it again and again
: )

The narrator pronounces jargon incorrectly

Pretty comprehensive current state of the art for generative AI applications.

Narrative pronounced A/B as “A slash B” and other glaring jargon mispronunciations. Distracting and hard to listen to.

Excellent broad overview

I am new to AI engineering and this book was an excellent deep dive into a broad number of topics to consider. I especially like that topics covered range from AI model selection, prompting, training, and hardware considerations to a recommended architecture for production environments. This foundation gives me a good starting point to building my own AI assisted workflows.

The accompanying PDF includes many graphs, code examples, tables and images to help listeners quantify and visualize topics and research findings discussed.

I went from knowing little more than basic prompting, to having a solid initial understanding of a broad range of relevant topics in just over 20 hours.

The indepth insights and technical concepts explained

The inability to see the images or figures referenced in the book. Probably some pictorial features should be included

One of the best AI technical books I’ve read

Very well done. Thorough detailed and clear. I learned a ton. Highly recommend. Critical for anyone in technology.