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Chip Huyen

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2025-10-23

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2025-10-23

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1. “Like a master social media, LinkedIn, Twitter. I don't post a lot, but I keep telling myself that I should do more because I kind of like the conversation with readers. So I'm Shirley Abash to start a sub spec. So I have like a placeholder for subspec right now and I'm thinking of doing it for more system thinking because I think it's a very interesting skill. And so like thinking of doing a YouTube channel on book review, so I'm basically books that help you think better. So I think it's the first book I'm going to review is probably this book because it's like my favorite book growing up and I have been like keep on reading it. So yeah, so how can it be helpful? Like send me books that you like, books that help you have changed the way you think or change you the way you do anything. So I would appreciate it.”

   2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

2. “Very logical, very rational, and just does everything just like very rational. And then the feedback I got is I have a very good friend. And he was like, he's an amazing person. He's a great person. And he was like, I'll be honest with you, I hate that person. So it doesn't matter as a story. It's just like the person is so unlikable. He doesn't want your continuity. So in the second version and makes the person secure a lot more likable, like what how she makes a character more likable is that you put in some vulnerability. Like sometimes, okay, maybe it's a person has setback because sometimes we can relate to it. See, in a lot of ways, it's very interesting. It's like a lot of it is about understanding the emotional bit, like how the users feel, not just of us as a story, but also about the characters.”

   2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

3. “As a story, like we want something in the beginning, right? We want something that's like, we need to have a hook so that people continue reading. But we still don't want too much of drama because we'll get like too tired, right? Like because the emotion exhausted, like because it's like you're being emotionally manipulated like a lot of time. So it gets like emotional journey. Maybe have like some climax or like some something more chill and maybe like I also care about another thing I didn't realize like for me for technical writing you entirely focus on the content like the argument is very impersonal right like it like first of all like people like ML compilers like doesn't matter if they like the person telling them about compiler or not right because it's just like objective like but like four and four novel people care about like character like ability so so like in the first version is my story and makes the characters like a little bit more like very”

   2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

4. “Yeah, so you do a podcast, it's like, okay, what kind of things that the users could find engaging, right? And I find this like a little bit like, and a lot of companies, like you have like launch a product, you have a narrative coming out. It's like, okay, what guide, how do we position this product in a way that users would want, right? So I feel like I have done tedical writing for a while. And I felt like I have had some experience like trying to predict what engineers would want to hear or I care about, but then I don't have an experience like this completely different type of audience. So that's what I want you to like career writing, granting a story. And that's why I was doing a lot of research on my question. I mean, going to research, I enjoyed a lot, like watching a lot of dramas to see what people like. So one thing that I care about is just like, I think I learned this like, well, like emotional journey. That's from my editor, right? So like when we write something, we care about how users would feel like across.”

   2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

5. “A lot of time when we read, we get tripped up by some small things. So I think I want to do crib writing because I just want to go a better writer and it tells us maybe try a different audience, have me become better, like anticipating what this different type of audience would want to hear and what they care about. So it's a way for me to get up. So I think about writing, like even like any kind of like content creations is about like predicting the user's reactions, right? The next token.”

   2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

6. “Can he possibly want at this moment? It just made me real like at the end of life there's nothing that can bring you like material can bring your joy, there's no like money, no product, nothing. And in a way, it's being like, okay, what really do I really care about at the end of the day? So I guess it's like a thing about it. It's like, okay, maybe I fail it, maybe I don't get that contract, maybe the thing is like the end of life. Like, I don't think that I should really matters. So in a way, it's like it's kind of liberating.”

   2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

7. “The sauce wear nihilist, I think the sauce like in the end nothing really matters. Usually think of like in the grand scale or something like in a billionaires nothing will like no one will never be there. I think, okay, some people argue with me about that. So my theories in a billionaires, like none of us will never exist. So like whatever messy things, like crazy things we do or like how bad we do it. I mean, no one would remember wouldn't be there to remember it. And I think in a way it's like itself scary, but it's very liberating because it just allows me, okay, let's just try things out, right? Like, why does it matter? And then there's a story of like recently so have a some family member who passed away recently. And I was talking to my dad because I couldn't be home for that. I was assuming that like, okay, say anything I can do to make the person like something like comfort so that anything you can get that person. And my dad was just like, what?”

   2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

8. “So I watch a lot of movie and TV shows as a research because I working on my first novel and I recently sold it. So I'm interested what makes it a drama. It's not a science fiction or anything that like tech people usually read. So it's very like, I know it's a very level and like very watching TV to see like what kind of stories become popular trying to understand the trope and stuff like that. So I'm not sure if the audience like.”

   2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

9. “Like how to create policies that encourage people to do the right things that is good for the nations. And also talking about foreign affairs, foreign policies, like the liberation of the country with other. So it's a really good book to think about for me it's like system thinking, but like it's a different guy system which is a country which a lot of us don't get a chance to like ever explain in their own life so it's good to learn about that.”

   2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

10. “Consciously, but subconsciously, we do want that. And I said two ways, like one is like via genes, like genes, one is just like one to continue forever. But it's also the two ideas. I think there's something called meme. It's like being able to have some ideas out there and then it's like the last for a long time, it's ongoing to live on. I know it's like it's a little bit like abstract, but it felt very interesting. These are the books I really, really like. It's like from like the book from Singaporean previous. I think he's also gone as a father of Singapore. I'm not sure what's the title of it, but like he did so, he was the one who left Singapore from, he's changed Singapore from a third world country to a full world country within 25 years. And I have never seen any country leaders that spend so much effort into like putting that his thought on how to build a country like that. And as I say, talk a lot of like public police.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

11. “I'm really terrified of book recommendations because I feel like what books or persons should read really depends on what they want and where they're in life and where they want to get you. But I just several books that I do think really changed the way I think and see the world. So one thing is a selfish gene that you understand. It actually helped me with the question like whether I want to have kids or not because it's like understanding more of like a lot of our functions or where we operate is the functions of our genes and genes want you to do one thing was like to procreate. So yes in a little way. But it's not like the book also proposed another thing is like so everyone wants to live forever, right? And maybe it's not like.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

12. “I would like to say that I'm very bullish on using AI, just create like micro tools, it's just something make your life a bit easier”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

13. “Can it be done a different way? So it's not frustrating. And you can talk like people can swap notebooks or teams. And I even see they come on frustrations. Maybe there's something you can think about is just to build something around that. So yeah, so I feel like just like notice how we work, thinking of ways to constantly ask questions, like how can it be better? And then I just build something to like address the frustrations. I think it's a good way to just like learn and adopt AI.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

14. “Should see a lot more, but at the same time, people somehow stop, like they don't know what to build. And I think it's like, maybe it's a lot of had to do with like maybe like society expectations because we have gone through, we have gotten into this phase of like specializations, like people like very highly specialized and people are supposed to do like focus on one thing really well instead of like a big picture and we don't have a big picture of you, it's hard to come up with like ideas of what you build. So I know what like when I work with this company on this hackathon like we do work out like come up with a guideline like how to come up with ideas and usually what we think of is like okay like one tip is like go look from the last week right like for a week just like pay attention to what you do and what frustrates you and when something frustrates you think about like is there anything we can do”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

15. “So, I do work with a few companies that do these things of like they want employees to come up with ideas. So there's a big debate on what is a better way for your strategy, right? Should it be top-down or bottom up? Should executive come up with one or two killer use case and like everyone allocate resource to that? Should you give engineers and PMs and smart people come up with ideas? And I think there's a mixture of both. So some companies, it was like, okay, we hire a bunch of smart people. Like, let's see what they come up with. And they organize hackathons or like internal challenge to get people to build product. And one thing that I noticed is like a lot of people just like don't know what you built. And it shocked me why I feel like we are in some kind of an ideal crisis, right? Now we have all these really cool tools to have you like do everything from scratch. I can have you like design. It can have you like write code. You can have your website. So in theory.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

16. “Of them said like 28, and it's like, okay, three of them in agreement. So the answer should be 42, right? So, like, just people shouldn't share it a bunch of it. Or another thing is like a lot of time reasoning thinking, you just like people should like jerate more thinking tokens. I spend more time thinking before showing the final answers. It's like require more compute, but it's only giving more better offerings. So, yeah, so I think. Different potential answers thinking longer, it can give you much better final answers, but the base model itself does not change. Does it make sense? Yes, that does”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

17. “And also, like since then, he has to spend compute on general influence. When I have a trained and 500 model, now it wants to serve it to users. So I might type questions or prompt and it's like Jared, like, do inference. And Zap requires a compute. And I feel about discussion of like, should I spend more compute on pre-tuning or fine-tuning or inference, right? Because like inference, and people felt I was just like test time compute. So like spending more compute on inference is like code like test time compute, like the strategy of like just allocating more resources, compute resource to Jerry inference when actually bringing better performers and how does that do it? Like let's say you have a math questions, right? And maybe instead of the generic one answer again, you had like four different answers and say, okay, whichever is the best according to some standard or like, okay, have four answers and I maybe like three of them say for it too.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

18. “Help us understand so, um, so 8 years it's like, okay, like, you have a fixed amount compute, right? So you're gonna spend a lot of compute on pre-shading or trading the model pre-trading instead of spend a lot of some compute on like fighting in the ratio of pre-trading genetic post training compute is like crazy varies different between different labs”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

19. “Yeah, I'm sorry why don't you bring back china what you mentioned is about the gas like from anthropic mentioned about the performance improvement. I think there's a big change. I think this difference between a model-based capability. So I'm not talking about like the pre-strained model, right? Versus the perceived performance. So let's say it's just like I'm not sure it thought about like are you familiar with the term test time compute? I don't think so.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

20. “I'm shocked that we don't have better voice assisted at home yet. I think I have been testing out a bunch almost like I keep hoping, oh my God, that could be the one. And then I know how many of them I just like had to get away because they're not that good. I think it's”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

21. “As you think, but it's all not quite like an AI foundation model problem, right? Because like a human interruption detection is actually a classical motioning problem. It's a different framing of like you can be classifier for that or like the question of like let us see a massive engineering challenge, not an AI challenge because there can be an AI challenge because people are trying to build voice to voice model. So instead of having like having to first transcribe the voice from me into text and then get a model various text answer and get another model to like turn from text to speech, you can start to voice your voice directly. So that is something called working on, but it's very hard. Yeah, so yeah, so like even audio, I think of it is like the easiest and video, right? Because video have like board image and voice. It's already pretty hard. So I think there's a lot of challenges in that space.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

22. “In AI and humans, when humans talk to each other, like if I say you try to interrupt me and say, Chip, right, I would like pause and I try to hear you out, right? But sometimes I just say some word, like acknowledge when I shouldn't stop. I should continue. So the question of like foreign interruption and whether it's like should I stop or not? It's a big and what perceived as like national conversations and that's also regulations right because like because like a lot of time people want to build a chatbot, voice chatbots and sound like humans try to like trick users into thinking they're talking to humans but it's also like maybe potential regulation saying like okay you have to disclose to users when you talk if the if the bot is talking to you is human or ai so so i think that's like um there's a whole space i think it's not quite as sole”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

23. “And then text to voice answer, right? So it's like mindable hops and like latency become very important. And there's a question like what does it make to sound natural? So for example, like people think like.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

24. “Improvements we see in the post training phase, in the application building phase. And yes, also I think that's where I feel I would see a lot of improvement there. Also very like interest in like multi-modality. So we've seen a lot of text-based budgetness, a lot of audio videos, use cases that is very, very exciting. And I think audio is not quite as soft as one thing because I do work with like with like a couple of like voice startups and I'm going to talk to you thing about voice is an entirely different list. So let's say you have chatbot, right? We go from a text chatbot to voice chatbot. It's like the conspiracy different because now with voice chatbot, right, we need to think about like latency because I think multiple steps are first like voice to text text to text and text question to text answer and then like”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

25. “I'm also like on the cam of thinking that it has merit is a camp of like, okay, base models, we have probably like not quite max out, but we are unlikely to see like really, really strong, like crazily strong model. So remember when we have like GPT, right? Which is a big step up, like an automatic GPT and then GPT3, which like much mouth bigger than GP4, much, much bigger. And then, of course, on your GPD5, but like it's GP5, like that scale of much bigger, like a step jump compared to the previous. I think it's a debatable, right? So I think that it's like we had disappointment like the base model performance improvement is not going to be mind-blowing and it was in the last three years. So I think there's like a lot of like”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

26. “Is it when you and me, but we haven't really got rid of these functions, right? I follow a lot of things like previous outsourced, for example. Traditionally, it's a business outsourcing this core to them and can be done with not can be in a more systemized. So with that, you can actually use AI to automate a lot of that. And so as a separation, if you're thinking more of like, what is the value of junior engineers or senior engineers? How to restructure engineering for that? So yeah, so I do definitely think that it's one thing to success organization. People are just moving pieces around and thinking about use cases, whether you need to spin out new use cases and who would lead the new effort. And like, yeah, that is one big change. Another thing in terms of like AI, I think there's, I'm not sure how true this is. I guess I'm”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

27. “User behaviors, because you need to know what users care about so that you can write evaluations and reflect what users care about. So all of that you can sort it from different component architectures, place guardrails and stuff. So it's just engineering, but understanding users is like what product, right? So because of like a lot of things and they are extremely important. So like the guy bringed product team and like engineering team even like marketing team like user acquisition like very close to each other. So yeah since in a way so if you go a structuring so there's more communications between like previously very distinct functions. Another thing is just like also see as teams of course I think about like what can be automated in the next few years and what cannot be automated. And I've seen that people already like shedding like actually it's a little bit like scary to think about it but also things it's like the team is like okay”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

28. “I think in a lot organizations they don't move that fast, right? But at the same time, they also move faster than I expected. Because again, I think it's biased. And don't work with dinosaur companies. I think a lot of executives who come to me are very forward-looking. So maybe for me, I'm very biased towards organizations is move fast. So yeah, so I think on big change I see just like in organizational structure. I think there's a lot of value placed in like, so before we have a lot of disjointed team, like we have very clear engineering team product team. But then there's a question of who should write Eva, right? Like who should own the metrics? And it turns out it's like Eva is not a separate problem. It's a system problem, right? Because you need to look into different components, how to interest each other.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

29. “One thing I really dislike about writing books is that it has to defy like this. And I think it's no definitions to be perfect because they always be like edge cases. But yeah, in general, I think it's CIS like gen AI as a service, like Morris as a service, like when somebody builds the models for you and the base model performance is a pretty shock. So it's like it's enabled people to just like, okay, now once you integrate AI into my product, I don't need to learn for Korean designs. even though knowing that could help but but yeah it's like it makes an entry barrier really low for people who want to use ai to build product and at the same time ai capabilities are like so strong because like it's also like increased like the possibilities like the type applications that ai can be used for so i think that yes what both entry barriers like super low and is a demand for like a applications like a lot bigger so it feels it's very very exciting it opens up”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

30. “It doesn't process JavaScript. Well, I don't know, whatever incident didn't work. And it was like, okay, that's it. I'm not just going to read documentation myself and see what's wrong. And it turns out it's like I'm on another tier. Like the fish I want did not is not available in this tier, right? So I feel like, okay, so the issue with chronicles is trying to focus on fixing things from a very a different component versus the issue is from a different component. So I think of like, okay, be understanding how different components work together and where the source of issue might come from. You need to have a holistic view of it. And this made me think it's like, okay, how do we teach AI, my system thinking? Like that, right? I think I have all the human experts, like having write very much on a scaffold. It's just like, okay, fox this guy problem, look into this, look into that, look into that and stuff. So I think that could be one way. But there are so many things like how do you take humans?”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

31. “Fix specific features or like build an app from scratch, right? Like, doesn't have to interact with a large existing code base. But it is something like a little bit more complicated. Maybe it requires interaction with other components and stuff. It's usually not that good. And for example, I was using AI to use, to deploy applications. And it was testing out a new posting service. I was not familiar with. It was like, okay, like usually they for me. So autic AI does give me is like confidence to try new tool. Like before what AI is like trying new tools has really not documentations for the beginning, but AI was like, okay, just try it out and learn. So I was testing out this new hosting service and it kept getting a box. It was very, very annoying. And it was like, okay, I asked Carco was like fix it. And it kept giving me like, it kept changing the way, like maybe change the environment variable, fix the code, maybe I change from the function to this function, maybe change the language.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

32. “Thinking like using like quoting to some actual problem and problem solving will never go away because like what AI can automate more stuff, the problems just get bigger. But as a process of understanding what caused the issue and like how to like design step by step solution to it will always be there. So I think an example of like I actually have a lot of issues with like AI for like in the way of like is debugging. So I'm going to show you use a lot of AI for coding but like something I've noticed.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

33. “I do think that what I mentioned is that loading to architect, I think I grouped that in my system thinking. I do think it's a very important skill because I think AI can help automate a lot of destroyed skills, but like knowing how to utilize the skills together to solve problems is hard. So there's a webinar between Miran Sami, one of my favorite professors. He was a chair of the curriculum as a CS department at Stanford, so he spent a lot of time thinking about CS educations, right? Like what should students learn nowaday in the era of AI quoting? And then the other person is like Andrew, which is, of course, a legend in the AI space. And Neha Sami person like Sami said, very interesting. So like he said, a lot more things at CS is about coding, but it's not. Like coding is just a means to an end. Like CS is about system.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

34. “Once they only need a very small group of like very, very strong engineers to like create like processes and reviewing code to get into production, but like get like AI or like junior engineers to like produce code. But then the question becomes like, how does one become a very strong? Right, that's right. That's right. That's the problem.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

35. “Yeah, I definitely really appreciate as you see companies like we appreciate engineers who have a good understanding of the whole system and be able to have good problem solving skill or thinking holistically instead of like locally locally organized companies have seen the way they work as I said told me we're completely different now and like so they actually restructure the engineering awk so that like they get more senior engineer should be more in the peer review because they like they get like sort of writing guidelines on like what is a good engineering practices what is the process would be like maybe like okay so they've write like a lot of like processes on how to work well and then they and then they have more junior engineers like produce code and and like submit proti engineer more in the reviewing case so i think it might be pre for the future so another company actually told me something very similar so it's like preparing for the future”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

36. “Yeah, so like say give like half of the entire company, but like half for each bucket. Yeah. And then they observe the difference in productivity. I see.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

37. “To like using AI as a tooling because they said it's like, okay, but AI because they are more opinionated and they have very high standards. It's like, okay, but AI code jet sucks. So just like very, very resistant in using that. So I don't know. I haven't quite be able to reconcile very different reports on that yet.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

38. “So I give like half of H growth, like access to cursor. And then he noticed over time, I was like, okay, the something funny, like the group that get the biggest performance boost, in his opinion, so it goes very close to his team. The biggest performance is a senior engine, so the highest performing. So the highest performing engineer get the biggest boost out of it. And then the second group is just like the average performing. So his opinion is like, okay, the highest performing engineers is a normal proactive. They will say no how to solve problems. So I help them solve problem better. Whereas the people who already have the lowest performing, they only don't care much about work, right? So it's easier to just like go on autopilot, get it to like Jerry, like that code and just do it. And I always don't know how to do it. Another company, however, they tell me that's like actually senior engineers are the one most resistant.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

39. “Yeah, so it's tricky, and I think that's like the question of productivity is not Sure, it's like fundamentally that some people are more productive, but it's just like we don't have a good way of measuring productivity improvement. Another thing is also very widely. And I think people do tell me that they notice different buckets of employees, like different reactions to AI assistive tools. Like first of all, I keep going back to quoting because it's big and it's easier to reason somehow. It says like I have different reports. One team would tell me that like one of the people tell me okay among on his engineers he thinks it's like senior engineers would get the most output like would be more productive because like okay so that's that person very interesting so see he actually divided his team to like three buckets but he didn't tell them obviously he was like okay here's more like currently like best performing average performing and lowest performing and then there's a randomized trial”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

40. “Could you rather give everyone on your team very expensive coding agent subscriptions or you get an extra head out right? Let's say it's like maybe like and almost everyone could say the measures could say headcal. But if you ask VP level or like someone who managed a lot of teams, they could say that's like they could want AI assistant tools. And the reason is that people say, okay, because as managers, right, because you are still growing. You're not as a level when you manage hundreds of thousands of people. So for you, like having one HR has account is big. So you want that not for productivity reasons, but because you just want to have more people working for you. Whereas for executive, you care more about the maybe you have more like business metrics that you care about. So you actually think about what actually drive productivity metrics for you.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

41. “The main thing is it's really hard to measure productivity again. So I taught you a lot of people on the first of all harmonic on the sample is coding, right? A lot of companies not using coding agents or coding coding. And I was asking, I was like, I was like, do you think that it helps with your productivity? And a lot of times the question is very hand-wavy. It's like, okay, they were like, okay, I feel like it's been better, right? And I said, okay, because we have more PRs. We see more code and then immediately correct me. Okay, but of course quote number of live code is not a good metric for that, right? So it's really, really tricky. And it's something funny. So I do ask people to ask their managers because I work with like user VP levels. They have like multiple teams. Under them. So I asked them like, okay, do you ask some managers?”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

42. “Adopting, like, giving people chat subscriptions, cursor subscriptions, clock code subscriptions, like to get the employees to be more AI literate. And that's the thing is a lot of the secretary now comes to me and say, okay, we spend a ton of money on this tool link. But then we don't see, because you can see the usage. But people don't seem to use them as much. And what is the issue? So yeah, so I think that is tricky.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

43. “The process of building it is like not that great. Yeah, so it's tricky. For the internal adoptions of toolings or interproductivity, that's where it gets tricky. I would say a lot of companies, was it Thing OI strategy? Think of AS3s have usually have very key aspects, right? It's like use cases. And the second is talent. You might have great data for grid use cases, but you don't have talents and you cannot do it. So a lot of time in the beginning with Gen AI, and it's still, and sometimes I'm really admired a lot of companies for that, it's just like exactly if it was like, okay, we need our employees to be very GNA aware, like very AI literate, right? So what I do is I start like maybe like adopting a bunch of tools for the team to use. They have a lot of upskilling workshops, like they encourage learning. And then it's like a really, really good thing. And it's also willing to spend a lot of money in Chile.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

44. “That is another category pool. And I think that identified customers or external facing tools because people are driven to choose applications with clear outcomes. So the questions of adopting the MasterNet based on whether they see the outcome or not. Of course, it's not perfect because sometimes the outcome can be bad not because the idea or like the application idea sell is bad. It's just because...”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

45. “For my friend, Booker is a process for that. So, a lot of this like having chatbot, internal chatbot to help with internal operations. And another thing, another category is more like customer facing. Partner facing. So product customers about chatbot is a big one. If a hotel chain, you might have like a book in chatbot, which is like somehow massive, like a lot of booking chatbot because I guess it's I do have this theory of like a lot of applications companies pursue because they can measure the concrete outcome. And I feel like booking or a sales chatbot is very clear, right? There was a conversion rate right now with that chatbot with human operators and what could be a conversion rate with the chatbot. And so somehow I think it's like very clear outcomes and companies are easier to buy into this solution. So a lot of companies have that customer facing chatbot. So yeah, so.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

46. “For Gen AI in company, I think there are two types of Gen AI tooling that I have seen. One is to internal productivity, right? Like have coding tools, SlackChatbot, internal knowledge, like a lot of big enterprises have some kind of a rubber a relic model, but like with access, like maybe some different kind of racks that we should, I think we talk about text-based rack level and talk about like Asian tech rack or like Mancy Model rack yet, but it's like, yes, there's a whole very exciting area or rather. Yeah, so like basically it should allow the employees to access internal document. Some way someone asked like, okay, I'm having a baby, what a good piece of maternal paternal policy, right? Or like, am I having these operations goods of health benefit, like cover that? Or like, I want you to interview, I want you to like.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

47. “Say that you have a function, a documentation for is maybe library. As a library say, okay, the output of this one is like maybe talking for like, I know, some crazy term, maybe some temperature or something under grab. It should be like one. Zero or minus one. And as a human expert, maybe understand the scale what one in the scale means, but for AI, I just read it doesn't understand what that means. So I actually have another annotation layer for AI. It's like, okay, good temperatures, you've got one mint like that. It's not like it's an asteroid temperature. It's my associated with the scale over there. So it's just having that all this data processing to make it easier for AI to retrieve the relevant information to answer the questions.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

48. “My summary, metadata, hypothetical questions. Somebody was telling me just like a very big performer. I said, God, is that from rewriting their data in the question answering format? So instead of having like, so they have a podcast, right? Instead of just chunking the podcast, you just like reframe, rewrite it into like, here's a question here's answers, like, and produce a lot of the AKU's AI for that as well. So that's one example of data processing. A lot of examples I see is like for people helping, like using AI to help specific tool news and documentations, right? And we write documentation usually to a lot of documentation today is written for human reading. And AI reading is different because it's different because humans we have like common sense and we kind of know what it is. So on things that are like human for human experts, they have the context that AI doesn't quite have. So somebody told me that like what's a big change they have is like let's”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

49. “So, like, one way is mentioned as in you have chunks of data. So we can think about how big of each chunk should be, right? Because if it's like, so to think about each other context, you want to maximize, maybe you can, it's a very simple example, right? You want to retrieve like a thousand words, right? So if Hung's data is too long, then so if a data channel is long, then it's more likely to contain more relevant metadata. So you can retrieve more. It's too long, like then you have a thousand word and so chang is like a thousand words to get a reach one chunk, so it's not very useful, but it's too short, then you can retrieve more relevant information. Like also, it can retrieve a wider range of documents and chunks, but at the same time, Hung is too small to contain relevant information. So we have very nice chunk design, like how big HUM should be. You add contextual information.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source

50. “Agonizing over what databases to use. We've got very database quite is very important to care about things like latency or if you have very specific access patterns like read heavy or write heavy. Of course it's like it matters. But in terms of like pure quality answers, right? I think the data preparation is just like hands out.”

    2025-10-23 · Lenny's Podcast · Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix) · IDENTIFIED FROM THE TRANSCRIPT · source