Building with AI feels like magic, but the engineering is a huge challenge. Chip Huyen's "AI Engineering" provides the first real manual for this new era, shifting the focus from building models to adapting them. Here's what you need to know.
In this episode of Beep Beep Boop Boop, your host Baris takes you on a 60-minute deep dive into the groundbreaking book, "AI Engineering: Building Applications with Foundation Models" by Chip Huyen. Forget a simple summary; we're unpacking the core arguments, historical context, and practical applications for today's developers.
What you'll learn in this episode:
The single most important idea from the book: why "adapting" models is the new "building" models.
The spectrum of model adaptation, from simple Prompt Engineering to complex Finetuning.
The architecture of a RAG (Retrieval-Augmented Generation) system and why it's like an "open-book exam" for AI.
How to evaluate subjective AI outputs using the "AI-as-a-judge" method.
A critical analysis: Where the book was right, and what's changed since its publication.
How these ideas apply directly to modern software development and AI.
Chapters
00:00 Introduction to AI Engineering
02:55 Understanding Chip Huyan and the Context of AI Engineering
05:15 The Central Thesis of AI Engineering
08:04 Key Concepts in AI Engineering
12:18 The Challenge of Evaluation in AI
14:36 Inference Optimization Techniques
16:31 Building Robust AI Applications
18:27 Developer's Perspective on AI Engineering
22:44 Conclusion and Key Takeaways
About Beep Beep Boop Boop:
Beep Beep Boop Boop is your weekly deep dive into the books, papers, and ideas shaping technology. Hosted by full-stack developer Baris, this podcast breaks down complex engineering topics into clear, practical insights for builders and the tech-curious.
Connect with us:
https://www.barisbll.com/
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