Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix)
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What is the main topic discussed in this episode?
One question that got asked a lot and a lot is how do we keep up to date with the latest AI news? Why why do you need to keep up to date with the latest AI news? If you talk to the users and understand what they want, what they don't want, look into the feedback, then you can actually improve the application way, way, way more.
A lot of companies are building AI products. A lot of companies are not having a good time building AI products.
We are in an ideal crisis. Now we have all this really cool tool to have do everything from scratch. It can have your design, it can have your write code, it can have your website. So in theory we should see a lot more. But at the same time, it will like somehow stop. They don't know what to build.
All is AI hype, the data is actually showing most companies try it, doesn't do a lot, they stop. What do you think is the gap here?
It's really hard to measure productivity. So I do ask people to ask their managers, would you rather have give everyone a team very expensive coding agent subscriptions? Or you get an extra headcal? Almost everyone, the managers could say headcal. But if you ask VP level or someone who manages a lot of teams, they could say one AI assistant. Because as managers, you are still growing. So for you, having one extra headcalf is big. executive, maybe you have more business metrics that you you care about. So you actually need to think about what actually drive productivity metrics for you.
Today, my guest is Chip Huen. Unlike a lot of people who share insights into building great AI products and where things are heading, Chip has built multiple successful AI products, platforms, tools. Chip was a core developer on NVIDIA's Nemo platform, an AI researcher at Netflix. She taught machine learning at Stanford. She's also a two-time founder and the author of two of the most popular books in the world of AI, including her most recent book called AI. Engineering, which has been the most read book on the O'Reilly platform since its launch. She's also gotten to work with a lot of enterprises on their AI strategies, and so she gets to see what's actually happening on the ground inside a lot of different companies.
In our conversation, Chip explains a lot of the basics, like what exactly does pre-training and post-training look like? What is RAG? What is reinforcement learning? What is RLHF? We also get into everything she's learned. About how to build great AI products, including what people think it takes and what it actually takes. We talk about the most common pitfalls that companies run into, where she's seeing the most productivity gains, and so much more. This episode is quite technical, more technical than most conversations I've had, and is meant for anyone looking for a more in-depth conversation about AI. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube.
And if you become an annual subscriber of my Newsletter, you get a year free of 16 incredible products, including Devin, Lovable, Replic Bolt, NADN, Linear, Superhuman, D Script, Whisperflow, Gamma, Perplexity, Warp, Granola, Magic Patterns, Recast, Jack PRD, and Mobbin. Head on over to Lenny's Newsletter.com and click Product Pass. With that, I bring you Chip Gwen, after a short word from our sponsors. This episode is brought to you by DScout. Design teams today are expected to move fast, but also to get it right. That's where DScout comes in. D Scout is the all-in-one research platform built for modern product and design teams. Whether you're running usability tests, interviews, surveys, or in the wild field work, DScout makes it easy to connect with real users and get real insights fast.
You can even test your Figma prototypes directly. Inside the platform. No juggling tools, no chasing ghost participants. And with the industry's most trusted panel, plus AI-powered analysis, your team gets clarity and confidence to build better without slowing down. So if you're ready to streamline your research, speed of decisions, and design with impact, head to dscout.com to learn more.
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Chapters
8 chapters
1
What is the main topic discussed in this episode?
0:00–4:48
2
What does Chip Huyen’s viral LinkedIn post reveal about what really improves AI applications?
4:48–13:49
3
How do pre‑training, post‑training and fine‑tuning differ and why is fine‑tuning a last resort?
13:49–26:38
4
What is Reinforcement Learning from Human Feedback (RLHF) and how does it work in practice?
26:38–39:19
5
Why does data quality matter more than choosing a specific vector database?
39:19–51:55
6
How can evaluation (eval) frameworks make AI products smarter and more reliable?
51:55–1:05:18
7
What is Retrieval‑Augmented Generation (RAG) and when should you use it?
1:05:18–1:16:44
8
Why do high‑performing engineers see the biggest productivity gains from AI coding tools?
1:16:44–1:22:31
Speakers
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