Nicholas

Uncapped #40 | Vinod Khosla and Keith Rabois from Khosla Ventures

Nicholas

Vinod Khosla and Keith Rabois are Managing Directors at Khosla Ventures. Vinod is an entrepreneur, investor and technologist. In 2004, Vinod formed Khosla Ventures to focus on both for-profit and social impact investments that have included OpenAI, Stripe, DoorDash, Commonwealth Fusion Systems and many more. Vinod previously co-founded Daisy Systems, the first significant computer-aided design system for electrical engineers, which led to an IPO. He later went on to co-found Sun Microsystems in 1982, serving as its first chairman and CEO. After joining Kleiner Perkins Caulfield and Byers (KPCB), Vinod incubated the idea for Juniper Networks to take on Cisco System’s dominance of the router market. Keith is also currently the CEO of OpenStore and led the first institutional investments in DoorDash, Affirm, and Faire, invested early in Stripe, and co-founded Opendoor. While a General Partner at Founders Fund, he led investments in Ramp, Trade Republic, and Aven, and before that made early personal investments in YouTube, Airbnb, Palantir, Lyft, Udemy, and Eventbrite. Keith started his career in leadership roles at PayPal and LinkedIn before becoming COO of Square. --- Timestamps: (0:00) Intro (0:58) The working relationship (4:26) Pie chart on what’s discussed (7:11) Ethos of investors today vs yesterday (10:42) Comparing FF and KV (12:46) What makes a great founder (22:56) Alpha in today’s market (30:05) Themes within AI (38:23) AI companies built differently (46:23) Excitement outside of AI (53:12) Politically active on X (58:24) Evolution of political leanings --- More on Vinod: https://x.com/vkhosla https://www.khoslaventures.com/team/vinod-khosla More on Keith: https://x.com/rabois https://www.khoslaventures.com/team/keith-rabois More on Jack: https://www.altcap.com/ https://x.com/jaltma --- https://linktr.ee/uncappedpod Email: [redacted email]

Published
Published Jan 21, 2026
Uploaded
Uploaded Jun 12, 2026
File type
Podcast
Queried
0

Full transcript

Showing the full transcript for this episode.

AI-generated transcript with timestamped sections.

0:00-1:33

[00:00] I've invested a lot in AI. Yeah, I love your quote about AI and how you'd have done it differently if you hadn't joined the Coastal Ventures. Before I joined KB, I joined KB literally two years ago, basically this week. Yeah. I had invested in zero. Rejoined. Rejoined, yeah. Rejoined. Rejoined. And literally had invested in zero AI companies before. Interesting. Since then, in the last two years, I'd say it's about 70% of my investments are AI. [00:30] think I either missed the whole wave and been completely irrelevant or been reckless. Keith and Vinoda, I'm incredibly excited. I got to do this with each of you individually last year. First thing I wanted to do coming into the year was ask two of you to come on together. So thanks for doing it. Pleasure to be with you. Yeah. Obviously, I follow both of you a lot, you know, sort of on online and watching a lot of podcasts you've done and just knowing you over time. And I've never seen you together in this kind of [00:56] format. And so I was really excited to set this up. One of the first things I want to get into is like how the two of you work together, because I think like it's rare that you have two people who are both super individually accomplished at a venture firm working side by side. You've done it for many years now and you're obviously very different people, but there's like a lot in common. Like I see you as this like Venn diagram with a lot, you know, in the middle, but you also have your own styles. So I guess just to start, like what's the like texture of your day to day working relationship like? Like how do you guys operate together? How do you communicate with [01:26] each other? Like, what does it look like? Just like all the time. You want to start? Sure. Well, we first started working together when Vinod joined the board of Square.

1:33-3:32

[01:33] So, and, you know, I've learned a lot of things. Actually, Sly. Well, we worked together, Sly, but that was more intermediated through Max. And I would hear about these meetings with the node and all these ideas and these grand theories about how we should rewrite the business. But it wasn't like hands on. I actually worked with another one of our partners, David, at Sly very directly. He told me my first revenue model was terrible. And so David's a little bit of acquired taste. Sounds like David. Yeah. He's like, this revenue plan is very mediocre, was the exact quote. That's great. Which turned out to be right. But in any event, while he was on the board of Square... [02:03] He taught me a lot of things, including the most important precept of the team he builds, company build. So when I was considering being a VC, it's a very natural fit because a lot of the contributions that have been owed, how the square resonated with me and I could see the style of KV and how that translated through my brain. And that I felt like it would be a really good pairing. What was it like for you? So like, you know, when you're starting to work with Keith, like, could you tell immediately that stylistically it was like what you like? Like, how did you know? [02:33] It's first principles thinking. If you can do first principles thinking, it's easy to know where you agree and where you disagree. It isn't this hand baby thing. Yeah. A, B, and C. Then we can debate those three factors. And it's worked out very smoothly. It's seldom we grossly disagree. We'll even come down to if X were true, then this is a good decision or a bad decision. Which is incredibly helpful. [03:03] where I couldn't actually decide what to do. It was close to the line, wasn't quite sure. And then Vinod said the key attributes of the founder that really matter for this are one, two, three. And then our junior colleague, John Chu, and I were like, well, on those three dimensions, this founder's AAA. So it made the decision really easy because he was able to isolate the key variables from that particular company. Yeah. Do you guys get into strong debates over ideas or have you mind melded so hard at this point that you don't even need to as often?

3:33-5:03

[03:33] Because it's hard for me to imagine either of you shying away from us. You're obviously both going to say whatever you think all of the time. I think that helps the direct style, which you've talked about for years. [03:43] I've always said I prefer hypocritical. Yeah. Brutal honesty to hypocritical politely. I can't imagine you dancing around a topic with each other. No. And it doesn't matter whether it's internally in the debate or on Twitter. You know, it doesn't matter. Being very direct saves a lot of hassle. Yeah. And once you have that culture, nobody's guessing at what you think. Yeah. And that's worked really well within the partnership. [04:13] ever guessing what you think or why you think that. And then externally, I think one of the reasons why we pair well with really ambitious founders is they appreciate clear communication, succinct and direct communication. They process extraordinarily well. On you two working together, like if you had to sort of like guess, like, I don't know, like the pie chart of the time that you guys are spending talking to each other, how much of it is about existing investments, new companies, operating the firm? [04:39] anything personal so nobody ever discusses operating the firm very much you don't discuss adventures interesting you know it's almost note i would guess it's far less than five percent is that because it's so clear how it works or because it's like yeah maybe around if you include hiring like then there's an allocation to assessing people out of curiosity is that because you think that it's like

5:03-6:54

[05:03] it's already so clear there's nothing left to discuss? Or is it just so much relatively less important than the work of investing itself? [05:10] Well, first, we have a lot more fun investing than managing. And the firm doesn't take much management. Honestly, other than comp, once a year, there really isn't a lot of hiring that we talked about. There isn't much in terms of, I can't remember when we had a strong policy disagreement. It's also, you know, at the end of the day, the node is energized by investing in the future through technology and founders. [05:40] I'm energized by pairing with people who want to change the world, which is roughly similar. And so the management part is a distraction to some extent from those two core activities, which are exciting. So what else then? We spend almost no time with the LPs. Yeah, that's nice. I mean, I – You may have to edit that. I'm just kidding. Look, I don't mind. I – [06:00] I spend less time with Alpayee than almost any other senior partner. And I think that's generally two of all the senior partners at Costa. Well, you're a place where you probably don't need to spend that much. And frankly, entrepreneurs are a lot of fun to work with. Yeah. So are you spending most of your time talking about new companies, existing companies? Is that basically all of them? Actually, both. I mean, we take the current portfolio very seriously. Every single Monday meeting starts with the current portfolio before we ever talk about a new opportunity. [06:28] because we're in the... [06:30] build a company business, you know, sort of that's what we focus on is we're an investor. We're going to be a partner for 10, 20 years. How do we help the company achieve its highest ambition, highest potential? And so we start literally intentionally that way with the portfolio before looking elsewhere. So the funny thing is in 40 years that I've done venture capital, I've not once called myself a venture capitalist or an investor. Always say I'm a

7:00-8:53

[07:00] It is focused on. And that's what we talk about mostly internally. How do we help a company change its trajectory if the potential exists to change it? How different do you see today like the sort of ethos of like new young investors versus like when you were getting started? Because like right now it is such like a thing to. You know, they. [07:20] there's, [07:22] Young and old doesn't matter as much. What matters is, have you built companies and earned the right to advise an entrepreneur? [07:31] I think most people who advise entrepreneurs haven't earned the right to advise an entrepreneur. [07:37] Almost all the senior partners in our firm have earned the right [07:41] by helping build a company, being inside a company, having empathy for the founder. So I think that's a pretty distinctive feature of how we think of our role. A lot of firms just want to be nice to founders, and it hurts the founder. [07:58] because, you know, it's like I say, it's like saying yes to your kids all the time, no matter what they want. You want that they know you love them, but you're trying to get them to be the best they can be. Yeah. That includes pushing them to be the best they can be. And I think we both agree. Our business is much more about helping the entrepreneur build a successful company than about investing. I'm newer to this, obviously, [08:28] moment in time where like the dominant marketing strategy for VC firms flipped towards just like extreme founder friendly whatever that means I don't know if it was 10 years ago or 15 something like that though you guys probably experienced this going through being on one side of it and then the other I kind of always lived in that world but like was there like a moment or like a period of a few years where it just like became the strategy for some reason for VCs to just go full you know

8:53-10:31

[08:53] Or... [08:54] goal has always been what's good for the company. [08:58] not what sounds good or what will get us more referrals for the founder next time they need to refer. So I think this hypocritical politeness, which is pervasive in our business, is really bad for founders. And when a founder selects for that, they're selecting, they're generally a weak founder. Strong founders almost always select for the best feedback they can get. [09:28] And also know how to say, no, thank you. I disagree with you. I think that's a really, really important character. One of my favorites is this. Some founders, I don't know the names. There are two founders did something called founderschoicevc.org or .com. Some survey of founders. Some survey of founders. And what I love is... [09:52] They wanted to avoid the hypocritical politeness, so they said, [09:56] Only the VCs that you've worked with can vote on you, on the VC firm. And you can't say, we have these three investors. They're all great. They forced them to rate them. [10:09] head-to-head like a chess elo rating. And I'm very proud. We're sort of at the top of that list among 400. We see firms in hundreds and hundreds of words. I think it's the most important survey for me to know that in retrospect, our founders prefer us and we prefer companies.

10:31-11:54

[10:31] backing the same founders again and again. Like our LP DAX always have a huge component of how many repeat founders have come back to us to work with us. Keith, I'm actually really curious because like, obviously, Founders Fund is an amazing firm, as well as Kostler. And the ethos is the same in the sense of like, we want to do a threat for the company. But I think like the pathway to get there is like the opposite. [11:01] I think the way we actually practice what we do is very different. Our craft is to be the partner in building the company. Like I look at my role as being the consigliere to the founder. And like sometimes the consigliere tells you that's a bad idea. And sometimes they tell you that's a great idea. Then they help the principal and they're not confused about who's the CEO and who's the consigliere. That's how I think of my role. Founders Fund thinks their role is to provide the capital and get out of the way. And if you have an idea where they might be helpful, I'm going to be able to do that. [11:27] Please call and we'll do everything we can to try to help. Right. Proactive versus reactive. Totally. That's exactly right. Very, very similar goals in betting on really bold ideas, whether they're popular or not, whether they're on trend or not. They've done an incredible job of that. And we like to think we do that also. Yeah, it's almost like you can imagine the conversation would play out like, you know, on one side, it's, well, we should back entrepreneurs that like don't need help.

11:57-13:35

[11:57] even amazing people can still be helped. Of course. Like, I mean, like even the best basketball players have, you know, I knew I was going to sports for, you know, they have shooting coaches, even like they're very dedicated or fitness coaches. Yeah. Like there's almost no profession where the best at what they do doesn't have an advisor, coach, mentor. Yes. Yeah. Look, take somebody, a really strong founder like Max Lovegen. [12:19] I've never been on the board. [12:21] The company's gone public. We've distributed. Great outcome. We are the first investor to this day. [12:29] Max and I do quarterly phone calls because he wants my help and advice and second opinion or something he's thinking about or always looking for areas. I'll prod him in to think harder, like you're ignoring this or that. [12:44] I want to talk about like, so what this clicking into the source of like great founders, great companies, because obviously that's like the center of like the work. I posted this, you know, that I was going to have you guys on the podcast. Somebody said, you know, we want to hear about this. But Keith, you can't say the thing about comparative advantages. And, you know, you're like, but it's true. And I think it is true. But like, I want to try to click in as closely as possible to like what makes a great founder. [13:14] the founder, you might disagree on a market or if there's a business you want to be in, but like, more or less, you think the same thing about if a person is a great founder. Very rarely is there significant diversions on the assessment of the founder. I can probably name two, three examples in like eight years. Yeah. What specifics can you sort of like describe? Well, I'll give you my formula and feel free to, you know,

13:35-15:14

[13:35] So mine is one of two traits. [13:38] Either I meet a founder and on some dimension, [13:42] They're the best I've ever met in my life. [13:44] They can be different. They can be the smartest person. They can be the most tenacious person. They can be the best assessor of people. They can be the most strategic. They can do just like, oh, my God, top one basis point on some dimension. Because what I'm trying to do is we do mostly first institutional capital. We want to be bold and as early as possible. What I'm trying to find out is, is there a non-zero chance that this person can change a vertical or the world? That's really it. One of those two things. Neither the world or at least the legal industry. [14:14] change and reinvent an entire industry, let alone the world. And so it's like, what's, is there some probability? Usually the people who succeeded that have some trait that's just like, oh my God, your ears like perk. The other exception is they have a Venn diagram overlap of traits that you don't see in common. So for example, Max Levchin, I've talked about this before, but literally when I met him in December 2000, Reid Hoffman came up to me and said, you're getting ready for your first one on one with Max. Max is a first rate technologist in a [14:44] mind, there's less than five people in all of Silicon Valley that are that. Reed was dead on 25 years later. It's still true. There's less than five people and Max is one of them. And that's led to his trajectory. So if I see these traits, Jack Dorsey, who we've both worked with, is actually a pretty damn good design mind, pretty good technologist and a very good business strategist. He has three, which is also why he's been very successful. Okay. So you meet somebody that you trust, refer somebody, great, I'm going to meet them. You're in the meeting with them for an hour. Are you trying to pull that out in that meeting?

15:14-17:09

[15:14] Is this work happening outside the meeting? Usually, if it's so strong, it usually shows up in three minutes. Like, literally, you meet someone who's the smartest person ever. [15:23] Like you just feel this energy. Aren't there some less obvious traits than like super smart though? Yes, there are. Like grit or something like that? Yeah, exactly. So for example, one of my favorite Gritty founders told me the story of when he was working at Uber, his team in this foreign country that he just joined, like because he was a launcher, was going to run a triathlon. [15:42] on Saturday. And this is like Thursday. And he's like, I want to be part of this team. Like I want to fit in. I'm going to do it. I haven't trained at all. [15:48] Didn't own a bike. So what did he do? He rented a city bike and ran the track. It did the whatever triathlon on a city bike. That's crazy. That's what was so much crazy. Like, it's like, that's all you need to hear. And then his co-founder, like, finished second in the spelling bee when he was in high school. [16:04] and passed out due to stress. So he didn't quit his senior year. He went back and tried to win it. [16:11] There's a dimension there that you don't hear very often. So to get some of these ones that don't show up in a live meeting, do you have certain things that you're prodding towards? Are you asking more about life than business? No, I actually don't do the Doug Leone, Daniel Gross style thing where tell me about your history and your sibling and that. It does work for the people. It definitely does. Have you tried it? Tell me about your company and why you're doing this company. It just shows up somewhere. There's just a spark. They can't help themselves. [16:41] the Doug Leone thing and it just didn't work for you? I never really tried it. The mechanical... It's like when you assess people. If you know what you interviewed, executive candidates for 30, 40 years for companies, there's a mechanical way of assessing doing an interview where you go experience by experience. Why did you leave? What did you accomplish? What was the biggest challenge? What are people going to say about you? And then there's different ways when you interview people that's a little bit more freeform. I'm definitely in the freeform version of interviewing.

17:11-18:50

[17:11] Is it a whole different thing for a founder? You know, every situation is different. I want to add a couple of other things to what [17:18] I think the most important thing is exceptionality in some dimension, whether they're going to be a good CEO or not. [17:26] But related to that is two things. In the areas where they're not good, [17:32] perfectly [17:33] good to back a founder if they don't know an area. Often it's a professor or something. [17:39] That's where venture assistance comes in that I was talking about, where we can help them be a complete founder. But also the thing I want to emphasize is, [17:50] To me, what's key is the learning rate of the founder, how open-minded they are to new ideas, how good they are at rejecting bad ideas they solicit. Too many founders just take every idea and try and execute. If a person listens to me all the time, I'll almost never invest with them. I know they're not critically examining. I often take positions I don't believe in just to test how the founder's thinking about something. I have a document I put out, [18:20] document on [18:22] how to do an interview. It is very much like it's preformed, but everybody knows what answers to give in an interview. So how do you get past that? I have an internal document I give to only our founders on how to interpret the answers they get. If I put them out publicly, then every candidate would understand how I'm interpreting. So I can't put that publicly. But the first half,

18:52-20:41

[18:52] SS somebody. So I have a pretty clear style. [18:57] And it's usually about putting people in a situation they haven't been in. It's not soft. Tell me about your life history because people know how to storytell. And the best storytellers may not be the best candidates. So you have to get past the obvious answers. Like I did this in that company or I opposed that in retrospect. I think it's very nuanced. So that's a great example. [19:27] and ties back to the team you build. There's a company you build, not the plan you make. Because the right team will evolve the plan to the right thing. And your initial plan is seldom the right plan. But if you can help pick the right team, [19:42] in a new context, which is you're trying to do something bold and different. [19:48] That's a pretty critical part of it. So both part of what we can do to help a founder and why most people are not qualified to even interview candidates. I've seen such bad specs for what the company needs. Most of the time, they're wrong on what a company needs to hire. Well, you have a great example in marketing specifically, where you talk a lot about like [20:12] Yeah. What is that? Yeah, I'm curious. For example, most startups are trying to create a brand. If you've been marketing at Cisco, you know nothing about creating a brand. You know how to incrementally sustain a brand. That's a very different skill set. I was going to say something even worse than that, but yeah. You know how to make this quarter's number look a certain way so that your manager. I was saying if you're at Cisco more than 10 years, you're not qualified for a real job in the entrepreneurial world.

20:42-22:32

[20:42] No, it's generally true. Yeah, it's hard. They're just so different. They have like trying to figure out like they have nothing to do with each other. What's the dimension that leads to successful with a startup needs? Yeah. And then how do you find that trait or that proven ability? Yeah. Make sure there's a Venn diagram overlap there, which purses diagnosis. And then it's like assessment. And, you know, this is the kind of place where venture firms are pretty different. [21:07] We'll agree if somebody can advise somebody on marketing. But if you look at a spec a board will put out, it'll be... [21:16] Cookie cutter, then X business to get somebody from X related businesses. It's just a terrible idea. It's actually a source of a lot of like management mistakes, which is like, it has to like look good on LinkedIn for the board. And that's a disaster. Yeah. And it's really hard if you're like a young founder to like stand up to that. This is the role of a really good advisor, board member. Sometimes just giving... [21:39] the founder confidence. Yeah, permission. You're not wrong. Just saying that when they're getting a lot of pressure from somewhere else, like especially the first time founder, just saying like, [21:49] No. [21:50] You're probably more likely right, actually. And then all their instincts kick in and they have enough confidence to just say no. Outside of this idea of, like, exceptionalism and, like, finding this dimension of special, like, you know, basically what you're saying is, like, if somebody's, like, B-plus at everything – [22:04] That's not a good investment for you. Usually an A plus and either incomplete. Like Vanera likes to term incomplete. Incomplete. I like that better. A plus plus incomplete is really a really good formulation. The rate of growth is hard to tell in your first meeting. That is one of the hardest things because we have one dot. You know, geometry is like you can draw infinite number of lines through one dot. What do you do about that? Do you try to go historically? The best is if you know someone over time. Like reality is. So the easiest, let me interrupt with my favorite example.

22:34-24:15

[22:34] The most important question I can ask the partner who's working with the company is how much have they learned in the last three months? Three months is enough to tell if they have a high learning rate or not. Totally. So I guess in a fast-moving process, all you can do is basically try to get a data point from the past. Yeah. And then once in a while, you can try to get data points from external people. But most people have the wrong prison. They don't – unless you ask the question perfectly and unless you can really retrain their eyes, it doesn't help. Right. Right. [23:03] You know, there's other ways. [23:05] I'd like to say... [23:06] Imagine you were in this business that you're not familiar with. How would you go about it? [23:12] learning X or Y. Let's even see how they would start. Putting them out of context and having them think through, very easy to tell. One of my favorite questions is... [23:25] It doesn't matter whether they're doing a startup or not. [23:27] Let's say they're candidate for a marketing job. If I gave you [23:32] a seed amount of funding to investigate three ideas. Which three would you pick? How would you go about evaluating them over the next six months? That's good. [23:41] It's a pretty simple test. [23:45] You can tell a lot about a person just based on how they answer that question. Yeah, that's good. Are there any things that a founder can't be completely deficient in? Ethics. Ethics? No question. How do you figure that one out? Mostly through references. Even on that point, a lot of people that seem not so friendly are actually very ethical. And I've noticed that a lot of the highly disagreeable, intense founders actually have a very strong moral compass. Yes, that is absolutely true.

24:15-25:36

[24:15] because they believe in their principles. And it like is the source of both. That's interesting. You've seen this in the Valley. We were talking about this earlier. People have changed their political affiliation at a whim. [24:27] not stayed with what they really believe in. Yeah. [24:31] We're definitely coming back to politics in a little bit. I have a lot there. Is there anything around ability to recruit? Anything around like... Ability to recruit is a very important dimension. Can you envision this person? It sounds like they've got to hire a thousand people at some point. Yeah, but can they hire the first 10? Maybe a hundred. It's really critical because those people are going to replicate themselves. Patrick Halson talks about this at length, like the first 10 are going to multiply by 10. Because you could imagine somebody who's really exceptional in some dimension, but you just don't think they could recruit well. Right. [25:01] Harley, whatever it [25:03] unique assets they have into convincing people to work with them. And sometimes they can't actually, even if they're very uneven, it's like, [25:11] Oh, my God. Like they can still or you can help them. You can help them communicate. Like, why is this ambition worth chasing? What kind of people do you want? But their energy or their special secret sauce that comes through. Like, let's say I set you up to interview with one of these great founders. I think you would pick up on this person's kind of unique, even if you couldn't articulate the exact reason. Yeah. You just come out feeling that way. You come out feeling like, wow, that was interesting. At a minimum, that was interesting.

25:41-27:18

[25:41] kind of on some level go to selling everybody around. It's the same person who can convince candidates and investors and customers and kind of all of it. It all kind of does bundle together. Yeah, you definitely have to be able to tell a story, right? At the end of the day, you have to convince people. You haven't proven almost anything usually in the beginning, right? And you've got to convince people to come along on the journey with you. Yeah. Those are investors, early beta alpha customers, employees. You have to retain your employees in a hot market. You're doing some version of that constantly. When you look back at a bunch of the greatest investments over the last, let's say, 15 years [26:11] like a button like and like an airbnb or you know whatever there's like a bunch of companies that were like not hot early and like everybody passed is that still the case do you think or do you think that it has become more like has the consensus become more accurate or is it still the case that like it's random signal i don't think it's random at all by the way go ahead i mean i think for example like [26:33] Let's talk about Airbnb. To me, it was obvious. Three minutes into Brian's monologue, I was like, this is the coolest thing since YouTube literally told him this, told him exactly why. It was so obvious. I needed to meet him, and I didn't like the Airbnb breakfast name that they were using at the time, so I kept referring to the meeting, which is crazy. [26:48] It was a very costly decision for me. Yeah. That's at the end of the day. [26:52] If you met Brian for three minutes, there was no way of missing this. This team was very special. And he was able to convey a couple, three key things he said in the three minutes. That I was like, oh, my God, this is really, really amazing. But you saw it, but most people didn't. Yeah, but I'm saying it's not random. Or like you saw OpenAI, like some of the company we all know. The key investment decision, literally, like if you read our memo, which he sent to the LPs because it was so much of an outlier at the time,

27:22-29:04

[27:22] critical density of research-grade people that could possibly pull off AI. That was the investment hypothesis in like a sentence. Given all the other stuff, like it was a non-profit, you know, there was no product plan, no revenue plan, just this AI capability. It's the only time in the history, 20-year history of Costa Ventures, we sent an apology letter to our LPs when we made [27:52] investment because it was twice the largest investment we'd ever, initial investment we'd ever made. We sent an apology letter. I know it makes no sense, but we're doing it anyway, not asking for permission. It's really that letter is now part of our fundraising deck, but we sent it in 2018. And then here's a good example too of Raider Grove. It did help a lot that [28:19] David [28:20] me and Vinod all knew Sam for a long time, a sustained period of time. So you could see certain lines there and the critical density of talent that he had assembled plus certain traits about Sam specifically led to that investment. [28:35] Do you think that as time has gone on and like more people are in tech and there's more founders and more investors, do you think that there's any increasing, not from, you know, people who can really see it, but from the average reception to investors? Do you think that the consensus hot deal is becoming any more or less likely over time? You know what I'm kind of? I don't think so. You think it's still the case that like these hot seeds are no better than the non-consensus seeds? Personal opinion? I agree totally.

29:05-30:59

[29:05] We're talking about like Rocket Lab was one of the best investments anywhere. No, I mean, I don't think they would have raised money from anybody. Well, it's worth $40 billion now, but you bought a third of the company for $5 million. Yeah. [29:18] Because nobody wanted to invest in space. Or Commonwealth Fusion probably. Or Commonwealth Fusion, or even OpenAI, right? It wasn't, we were the only venture investor in 2018 that committed because it didn't make sense. I think at the seed level, consensus hotbeds are generally around people. [29:43] knock around the idea. Yeah, it's like if you have two people who left, picked your super hot current, two people leave cursor, an engineer and a designer leave cursor tomorrow, what's that going to go at? [29:57] But a seed investment around, let's say, undiscovered people. I think the consensus ones aren't going to outperform the outliers at all. Maybe just talking about themes that you guys are interested in. I know that you're mostly focused on people, but you also care a lot about markets and technologies. Maybe to start with AI and then we can go outside of AI. So obviously AI is like... [30:18] in the midst of playing out. [30:20] I don't know what inning it's in, but it's one of the early ones, probably. You know, I think there have been like a lot of changes to like what, you know, the labs say that they're focused on and maybe like the types of companies that are getting funded is adjusting a little bit if you sort of like just like. [30:32] kind of track every six months or so. I'm curious what you guys see as the lay of the land for like outside the labs where you think most of the opportunity lives, what you're most interested in, what you think is going to be like a big deal in the next year or two. That's such a broad surface. Of course. Sorry. I think I was counting the 30-some startups in our portfolio that are building an AI worker or some sort. Yeah. An AI oncologist, an AI mental health

31:02-32:33

[31:02] I'm a structural engineer. As many professions as there are, there's that many opportunities. Basically to fully do the work. [31:10] Do the work. So one thing we decided a couple of years ago, probably three years ago, we wouldn't do a lot of co-pilots. Co-pilot had just come out and we said... [31:23] Co-pilots, humans get in the way. Let's just do the work. So we love... [31:29] really people doing the work as opposed to helping a human do the work. Now, there's exceptions to that, but mostly that's true. That's a big category. So we haven't invested in any competitor to OpenAI, obviously. And we should come back and talk about it. We are fiercely loyal to our companies. We can talk about loyalty. Well, OpenAI, I think I was the very first one [31:59] to come out and say, we'll fund Sam for whatever he wants to do next. Yeah. Is the loyalty, does that stem from sort of like a business perspective? [32:09] decision or idea or is it stemmed from just like this is how it ought to be like a more ethics kind of thing? This is how it should be. It's about ethics. In [32:19] And if I disagree with Arnold, then my job is to sit down, tell them why and agree that we agree or disagree. Yeah. Before taking the right position publicly. Yeah. If we believe the principles like for the point.

32:33-34:12

[32:33] if you have principles and you believe you're on the right side, [32:36] then we're willing to use our brand capital audience to help. [32:43] But along those, the AI question you were asking, we've invested a bunch in [32:49] in all their other approaches than transformer models that make sense. And we probably have [32:57] More of five different efforts that are [33:01] They don't have to replace transform models, but they're different. Because I think the big labs are doing transform models really well and then doing some other things. So what else do you think is promising? Look, it's too early to have. [33:14] So I think any of us who pretends we know this technique or that neurosymbolic technique, we have a bet on category theory in math. We have a bet on interpretability that leads to different models. We have diffusion models. There's plenty of others. Do you think we're very excited in real world models? Yeah, I was just going to ask you that. [33:38] I think that game hasn't played out yet. It's not clear at all who will win. Yeah. It's very clear what the major labs will do in that area. And at least the major labs all have efforts. But I think it's completely up for grabs. And you have no doubt it's going to work. It's just a matter of how. I have zero doubt it will work and work in place. [34:02] increasingly well. And it'll be embodied robots that are... It'll be embodied and more than that. Understanding the physical world. Yeah. Let me give you an example.

34:12-35:47

[34:12] This is a public clip we showed. Intuition is a very big deal. [34:20] And I don't think current models embody intuition. So we have a company called General Intuition based on gaming data. And I saw a clip of... [34:32] this live feed of Ukrainian soldiers trying to escape Russian attackers. And then we give the AI half the clip and said, replicate the other half. It replicated the intuition of the Ukrainian soldiers trying to escape Russia. [34:51] almost identically. That's intuition. There's many dimensions like that. [34:57] But there's many obvious ones. You know, we all talk about the fact that frontier models hallucinate. And there's probably not a good way to avoid them. There's ways to minimize them. And the labs will do a pretty good job. But you see the hot agent startups like Sierra and Decagon. [35:15] They're completely, I think, missing the point. We've... [35:19] Focused on customer support agents that do not hallucinate. [35:24] If you're a bank, if you're a Visa or MasterCard or insurance, you can't afford to hallucinate an answer. [35:33] even if it's low percentage. We've heard a lot about mental health [35:39] therapy where bots take people down towards bats. Those are all examples. So

35:47-37:18

[35:47] I think the winning customer support thing, [35:50] will be something that does not hallucinate for a class of applications. Some applications, some hallucination is fine. And are you saying that you think that like a company can't just increment its way from hallucinating sometimes to hallucinating never? And you just need to you can't just those companies can't just improve their way to know. It's possible. [36:10] But I think if you architect for low hallucination, know when to use no hallucination when you can afford to, giving somebody's bank balance, you'd... [36:19] Better not ever hallucinate. I think it's pretty important. [36:24] to look beyond normal, [36:27] Lots of people will do the normal. Extensions of LLMs to lots of applications, massive market. Lots of people will do it. Every area will have 10 startups. Keith, are you interested in hard tech as much, or do you invest more in, like, B2B typically? Well, I've invested a lot in AI. Yeah, I love your quote about AI and how you'd have done it differently if you hadn't joined the Coastal Ventures. [36:57] basically this week. - Yeah. - I had invested in zero-- - Rejoined. - Rejoined, yeah. - Rejoined. - Rejoined. And literally had invested in zero AI companies before. - Interesting. - Since then, in the last two years, I'd say it's about 70% of my investments are AI. And had I not rejoined KV, I think I would either have missed the whole wave and been completely irrelevant,

37:18-39:08

[37:18] or been reckless. Neither one's good. Because what I was able to do when I joined is learn by osmosis. So I'd sit in partner meetings, and 80% of the companies that we would discuss in the portfolio of new opportunities would be AI-based, and I would listen and learn. And then B, as I started meeting founders who were interested in AI that fit my normal standards, I could send the DAC to... [37:41] actually three people here, Vinod, Sven, and John Chu, and sometimes actually Kanu too, get feedback, and then actually often have some combination, maybe all four, meet the team. And so when I first started making AI investments, I felt like I had this air cover of like a lot, they could understand how good is the team, B, how smart is their approach, how differentiated is their approach, and then B, is there anything else in the landscape that's even better? [38:11] some taste and some ideas about what works. And then you join the board of the companies and you learn how these companies are built and what works, what doesn't, what are problems, what are not. And so now I basically do almost virtually all AI. Yeah. I'm actually curious on the topic of how the companies are built. And obviously you're super involved with company building. You've built companies yourself a bunch. And it's just something that you talk about a lot. Do you think AI companies are built in any substantially different way? I think fundamentally different. First of all, they are growing at rates that are [38:41] a little bit like, to me, it's like running the four minute mile. Once you see someone runs the four minute mile, then no company should have an excuse for not growing rapidly. It's like, you see all these enterprise companies going from zero to 50 million. You start asking questions, well, why, why can't you, at least what are the limiting factors? And there sometimes are real reasons, but you start with the question of why, why not, you know, why not versus like, oh, that's impossible. Like if you had said, we're going to start a company and have $10 million of revenue in year one from launch, you would have said, all of us would have said 10 years ago,

39:11-40:46

[39:11] It doesn't mean every company should do that, but it's an open question. Then the question is, well, what do you do about that? I think the idea of them borrowing from Peter Fenton here, the idea of PMs does not make sense in a rapidly emerging technology field. What do PMs do? They go talk to customers and they create a sequential roadmap over the next four months. Well, if the field is evolving and the capabilities are evolving, like literally every month, there's papers published. You probably read papers every week, let alone things that are launched live. [39:35] You can't have a 12-month roadmap that makes no sense. And so you have to rethink that. Then also how does sales work with your research team? Like OpenAI actually pairs, as far as I can tell, like the people doing customer acquisition with the research team. And that's a completely different model than how most technology companies were built. Compensation, this is in the public domain. Completely different. Completely different. And people haven't even thought through the implications. Yes, there are so many companies like Meta that can afford because of how they meant money [40:05] to when we were growing up. However, if you're a startup, [40:08] How you can afford that level of cash comp while you're not minting money. Well, you can't, right? But then you still have to compete with people who can. So you have to think... Does that go to your diamonds in the rough type of idea? Either. Well, that's one possible solution. Or you've got to hire people that... [40:24] don't care about short-term cash comp and have a different missionary zeal or different orientation, or you've got to take costs somewhere else. [40:31] A lot of money from somewhere else that you're not paying for. Like, but no one's really, very few people have thought through company building from scratch. If you need research grade talent and you have to compete with a market, how do you reorient the entire P&L of a company? Yeah.

40:46-42:17

[40:46] do you have like well i think it depends what you're trying to do like depending about what market you're in and who you're competing with and how much cutting edge ai talent you have do you need one person do you need a team 10 yeah those are all very different you know financial there's a lot of financial consequences to those yeah how different do you think it is for like let's say like a i don't know somebody who's building like a new like ai centric system of record or something like that like how different is like the first 30 hires look like what or like [41:16] approximately look like? I think it's very different. First, the whole idea of systems of record is going to change pretty dramatically. And it may be the old system of record don't go away, but the operating substrate is wholly different. In fact, most likely that'll be the case. Take ERP, a hot area. [41:38] It's really becoming unbundled. So there's procurement and then there's finance. And then you can go through the various modules in this ERP system. [41:50] If you don't have the right substrate, [41:54] to have it operate under an agentic architecture. [41:58] you're not going to have huge success. [42:02] used to be in an ERP system, it's what features does it have? [42:07] I'm a manufacturer. Do I have... [42:09] manufacturing features. I think now it's about [42:14] How do I reduce the number of people I need in...

42:17-43:53

[42:17] accounting or supply chain or others. Yeah. So one of my favorite examples, we invest in dual entry. [42:24] They have a client called Slash. [42:27] Small business lending, complex business. It's both regulatory complex and credit scoring and all our complex areas. $150 million ARR company with only one person in accounting. That was my reference when we invested. Why? Because the architecture is right. [42:47] And by the way, these aren't founders who are credentialed. I think they're from Venezuela. Really great people. Loved entrepreneurs. That was number one agreement. We loved entrepreneurs, too, loved architecture. [43:00] Three, love the impact. The benefit is very different than a feature list. Another difference is, for example, traditionally when you build an ERP-ish system of record or whatever, you think about your defensibility would be around the number of integrations you would do. Like think Rippling. We have all of these integrations, blah, blah, blah, and creates a big moat. With things like Cognition, Devon. [43:23] Doing 100 integrations is something you could actually feasibly do in a month at very low marginal cost. Totally. Like a company like MuleSoft makes no sense now. Yeah. Well, exactly. So a lot of these incumbents are much more vulnerable, I suspect. So given that you've got all these different intentions for the company, the way success is measured, it's like the building, the way you build a company, like the old playbook to whatever extent those ever were any good or definitely no good now. Have you found that retraining, for lack of a better word, experienced execs who came

43:53-45:48

[43:53] in pre-AI ports over well? Do you have to be more cautious with that? Is he like bringing higher execs into new companies? I think it's fun and challenging. Like, so I'll give you a good example. One of the best companies like ever is going to be Ramp. But Ramp started in the pre-AI era and we're very AI forward. Like we talked about this publicly, there's stats about it. We're leaning in, we're hiring AI native, you know, people constantly. We have incredible, we have the best intern pool on the planet for the last three or four years in a row. But we actually have to rethink the company. [44:23] Because we really started in 2019. And so we have a lot of things that were based on doing the best possible version of a technology company in 2019. And that's changing. And it's an interesting board level conversation that we have of like, wow, should we rip up everything we've learned? Or which pieces should we rip up so that we can be the best company in the next 10 years? [44:43] And if Ramp's doing that, imagine what every other company should be thinking. You know, my way of explaining this, most experts are experts in a previous version of the world, not the one you're trying to create. And so fast learning, and I come back to that, is much more important than lots of experience in this AI world. Even how you do anything. [45:05] computer architecture, system integrations, marketing, customer support, all that is so radically different. You want rapid learners, whether they're experienced or fresh. Yeah. Let me give you a mundane example. So like thick lattice back in a lot of days, [45:22] Right now in enterprise, because of the hype of AI, top-down sales can work extremely well. The CEOs feel pressure from their board to be AI forward. Their executives feel pressure to be leaning into AI. Historically, not the best way to build a company is to depend upon top-down CEO sales. But it actually does work in certain verticals right now extremely well. So the whole go-to-market playbook, you have to rethink too.

45:52-47:14

[45:52] they just want to buy AI. Is it more than what the specific solution is? We have a big budget for AI. In the short term, they have the budget. They may not care about the impact. Long term, it'll harmonize. You have to produce results. Ultimately, we care about that. We evaluate. When we look at application level companies, what is the actual impact you're driving for your customers is a key input. But I assume if you have a founder you love and there's this crazy market pull, even if they haven't worked out all the pieces later, that's a good enough starting point to bet. If they really understand that they need to, [46:22] Revenue? Yeah. [46:23] Outside of AI, you said 70% is AI, so there's other stuff you guys are interested in. I know we've talked about robotics last year. We've talked about... Well, robotics is AI. Yeah, of course. Pretty big on robotics. Yeah. Well, one thing people know less about us, but we've been consistently excellent at across the United Fund, is in financial services. We have this point we make to LP, is that in every single fund we've had, we've returned the fund solely on one, just on one... [46:47] financial services investment. That's a crazy step. So we love things like Square, Stripe, Affirm, just examples in the modern stuff. We're the first investors in all of those, except Stripe, we were second. We have Avon, which is a very excellent company. Yeah. It'll be the next surprise Stripe. Upstart was incredibly successful. We did some of the seed, led the A. Has finance gotten less AI-ified than other areas?

47:17-48:52

[47:17] You think it's because people are like a little scared, like, or like rightfully scared? Because I do feel that the fintech companies of the last era seem more, they seem more insulated from the AI wave and threats. And like, I haven't seen as many like. Well, there's a weird example of, well, some of the hallucination concerns. Yeah. Yeah. [47:38] But even as good example of a company that's deeply using [47:42] AI? [47:43] in every aspect of it. That's why you can get a home equity line of credit and consolidate all your credit cards onto a new credit card that you get that has 10 points lower interest rate. And then they have your credit card. Well, they issue a credit card based on your home equity line of credit. They can get it done in an hour. Normally, that's weeks and weeks. And AI is what makes it possible to go so fast, which makes it fit in the right way [48:13] process. Head ramps using AI very aggressively, but I think it hasn't been quite as transformative across the broad set of legalism. The thing is, there aren't [48:27] too many great fintech companies, I would venture to guess Ramp and Avon will end up being two of the best of the new breed started in the last five years. Yeah, I agree with that. And so that may be true. Like once every so often, there's an amazing fintech opportunity, at least in the United States. There's been like New Bank and company in Germany, Trident Public, they're also Revolut.

48:57-50:35

[48:57] true iconic company. Yeah. They'll get to tens of billions or 50 billion or 100 billion market. Yeah. There's not that often. And so I do think the next generation will use AI in a very significant way. [49:11] So FinTech's a really interesting area. We still do a lot of sustainability stuff. I'm really bullish on energy. We are very, very bullish that that area will keep sustaining. Actually, so maybe this is a good moment to... [49:27] By the way, manufacturing, another area we haven't talked about. Huge interest for us. Defense is another huge interest. What in manufacturing? I think applying AI to completely change the paradigm of how manufacturing is done. [49:45] As part of that, you can onshore stuff that was offshore. [49:49] So it's these two trends colliding. [49:52] Is robotics part of that too? [49:54] It is part of that. [49:56] It's not the most essential part. What's essential? [50:01] Essentially... [50:01] reducing labor costs in other ways. [50:04] Not by a robot do the job, but running a system. [50:08] In a way, an [50:10] iPhone assembly line would have... [50:14] a few thousand manufacturing engineers. If you can do that function with AI, [50:19] Then you have a pretty large advantage manufacturing onshore. How much of the opportunity is that like the points of creation of goods versus like the operations and logistics around a manufacturing company? Both, both.

50:36-52:14

[50:36] We are seeing both. Yeah. [50:37] Supply chain was sort of a minor part of all ERP. We talked about that. There's going to be lots of opportunities to replace supply chain software with new AI software. Yeah. And then in defense, I guess, like, obviously with like, [50:52] Andrel, SpaceX, like, you know, obviously, like, now there's, like, huge... [50:56] inroads here is your guys sense that there's a lot more opportunity for those flavor of companies to be built will those companies dominate in their markets like how do you think about what those markets will play out like i think there's room for lots of new startups i think there's [51:09] I mean, we have big investors in Hermes. Now, that was not started in the current fashion. It was started five years ago. [51:18] to do supersonic aircraft. I think that'll be an important part of national defense, become even more prominent because Russia has used supersonic aircraft missiles in Ukraine and we don't have any. Yeah. [51:35] So that's an important area. We did [51:38] a while ago. There are many other areas. Keith, you can talk about Mark and some of the others. Yeah, so we've been in that, well, we've been concerned, like, [51:48] politically geopolitically about the threat posed by our adversaries the ccp etc they know got involved in hill and valley forum before school one of the first 20 people like when you know setting up to alert by the way under a democratic yeah under a democratic administration because it was common concern because the country needs to take advantage of the best and brightest in technology and the cutting-edge technologies or we are going to sacrifice our way of living to people who do and

52:14-54:00

[52:14] We started investing in things like that ahead of the curve. There's now more interest among VCs because some companies are perceived to be doing quite well. VCs, you know, are always like a herd. But we invested in VARDA, which has a significant, you know, [52:31] Defense component, mock technologies is a very high potential. Rocket Lab, many, many years ago. Yeah, all of these were before was kind of cool. Now, also, the country needs to take advantage of technology. The country has more threats and has more potential adversaries to worry about. It has to do with less money. It has to survive or thrive with less money. Technology is a great magic wand. It has been for consumers for 40 years. It's like magic wand, you get more for less. [53:01] And this administration is and putting people like Emil in place, hopefully to catalyze a new world order where we take advantage of technology and make America better. Yeah, I guess on politics, like both of you are like pretty willing to like get into politics stuff on Twitter and stuff. And you have very different politics, obviously. But I guess my first question is like you both are like willing to just sort of like get into, I don't want to say fights, but like fights on X about politics and stuff like that. [53:31] think. Why spend the cycles on it? Like, why do you? I'll give you my answer. I don't actually know yours. Mine was like, yeah, through technology, I developed a following. And I woke up one day and said, like, look, I don't want to die one day and regret that I didn't use my audience to positize about ideas and things that I find important. So if I can surface new ideas or rebut bad ideas, I want to, you know, finish my life thinking I did the best I could to have influence and I have a platform. So I started using it that way, particularly on like topics

54:01-55:36

[54:01] um and so i was just like i don't want to regret having not tried to change people's opinion are you stressed at all when like when you're like getting into it on x with somebody are you like feeling anything about it or are you just like i'm just saying what i think but i'm well there's times where you should have more time to like research like if i was doing nothing else and i didn't have like a day job yeah you know there's times when like i know how to construct an argument i know where all the evidence is i don't have time to go do that um like my friend david [54:31] to help them. I don't have time to do that. There's times when I happen to know the answer. I used to be very involved in politics. I know a lot of details, but I do wish sometimes that [54:41] if I wasn't doing a real job, [54:43] I would be spending more, more care in marshalling more evidence and probably be more effective. Actually, one other bit that I'm now curious to ask, because I think it's kind of funny, is you're like kind of harsh on Twitter, but you're like really friendly in person. Is that just like how you write? Or like, do you mean to like, well, I also have this crazy idea. This is a dumb idea. Like a decade ago, I was like. [55:03] I'm going to combat every bad idea on the internet. With the worst idea? Like, I was like, well, if someone puts a bad idea or something wrong, nobody responds. People think it's true. Yeah. Like, LLMs are going to pick it up and think it's true. I was like, I'm just going to respond so that at least there's a written record. But, like, there's so many bad ideas. There's so many bad ideas. [55:21] Dumb ideas in the world that this is like the worst idea I've ever had in my life. Yeah. But you get addicted to trying to fix every mistake on the internet. I like the ones where you don't even like explain what's the problem. You're just like wrong. Yeah. Well, that was a funny square joke. That was an old square. We had this critic at Square named Mark Cash.

55:36-57:06

[55:36] And he used to just like causally complain about like Square. Square was never going to be successful and need new payments for 20 years. He's a canonical expert in payments. And so sometimes I'd engage and write back like substantively. But sometimes he'd be like so far off. I just turned wrong. So it became like this internal Square joke to our caps. And it became like a meme. That's good. That's where it started. That's good. Why are you motivated to like get into it online? You know, I don't spend very much time. All of social media, I probably spend less than an hour a week. That's good. [56:06] If I... [56:06] incidentally run into something that is blatantly wrong, then I'll express an opinion. But I won't even have the time to read the replies, I guess. So like if you're if you're like fighting with somebody on X about whatever and you're getting all these replies or you're just like, I can't like you're not like bothered. I'm not bothered. Yeah. But if something's an important idea or something, you know, usually it's some principle somebody is violating. Like this weekend, I happened [56:36] that was sucking up to Trump on capping interest rates at 10%, you know, said, [56:45] So he's sort of recommending that idea and then saying, well, maybe there's a market approach. Hedging the truth is clearly a market person. So I replied to him pretty bluntly. [57:01] I like Bill. He's a good guy. Know him. But...

57:07-58:38

[57:07] I just couldn't let that pass of sucking up to Trump, which on a truly bad idea of capping interest rates, almost like Trump and Trump Harris would have the same idea. Price control. It's like, come on, speak up. Don't be dishonest about your opinion. And he was being dishonest. So when it bothers me, I reply, but I don't spend a lot of time and I don't have a lot of time. [57:37] Yeah, I do mostly like I'm in an Uber. You know, you have these moments where it's really hard to be effective. Yeah. Like I just use it as like snack while I'm like in an Uber ride. I'm not going to be able to schedule a call while I'm in an Uber ride, you know, et cetera. So I kind of like. Get on there and dunk. No, no, you do it when I'm eating, which is a bad habit. Yeah. Like I'm having breakfast. I'm like on Twitter or something. But I started, you know where I started? It was actually a business reason. [57:59] I was kind of famous back in the day at Square. I read every single tweet every single day about Square for years because occasionally you see a jet like either a great story that could be shared or like a positive experience like you helped my life and you have this great anecdote or you'd see like a customer complaint. [58:13] And you could route it directly to someone. Or you'd see a product feature. I literally read every day, started every single day. But then that gets you in this trained habit of like you have to read everything. And, you know, maybe not the best. You were like 10 years ago, maybe let's say you were like sort of like one of the first sort of like vocal conservatives. Maybe the only one. Maybe the only. And I think now you're maybe like one of the only vocal like at least like.

58:38-1:00:18

[58:38] liberal leaning? Maybe that's like too strong. I'm an independent. You're an independent. For the record. I've never been a Democrat. Oh, yeah. So what was the political journey? I used to be a lifelong Republican over fiscal issues and switched to independent over climate issues. And I've stuck with that. [58:56] pretty consistently. [58:59] My... [59:00] And then principles matter. So, you know, my fight against Trump is his values. He has none. Yeah. [59:08] Um, we can disagree or he tries to go to extremes to get his constituency rallied around him. Either way, I don't like the idea that people don't mind lying about things. Yeah. When you watch that and like, so it's like violating your principles, you're seeing like everybody around you. Like what's your, what is your like assessment or read on the situation? Cause like, obviously 10 years ago, this wouldn't have been the dynamic. Clearly people have changed their affiliation to be for convenience. [59:38] Doing things for convenience is a bad idea. Now, I realize... [59:44] Some CEOs... [59:46] have responsibilities to others than themselves. [59:51] But some just will change political affiliations. And if the next president is Bernie Sanders, they'll become liberal again. That I hate. So I agree. By the way, I don't like the convenience. I believe in principles. I think a reasonable fraction of people, I think that's true. And then I think there are some who have watched the evidence of just like there's a lot of things. Let's say the last administration did badly and made decisions.

1:00:18-1:02:07

[1:00:18] jeopardize the country in some ways. And then some things that Trump has done have clearly worked or seem to be working, at least, you know, et cetera. And some of it is fine to change your mind based upon evidence. I would say there's an element of convenience to there's probably a mix. It's hard to sometimes, you know, who's who and what camp and all that stuff. And then there are some who have customers and employees that they have to represent. Absolutely. And, you know, that's an important consideration. Like, so, for example, if you have a significant government contracting revenue, you know, you have you do have to think about like. [1:00:46] you're fueling your families, your employees' families. Like, yeah, you know, there are real responsibilities. There are responsibilities. You see them from a number of companies where they clearly fundamentally haven't changed their principles, but they have to take the responsibility of the role or get out of the role. It's also interesting because it's like it's new for tech to even – [1:01:08] to even be reasonable for tech to care about politics. Like, it just didn't matter in the past. And also, it was, like, not possible. Like, tech was much more monoculture on the left before. And then also, there just, like, weren't, like, government-related tech startups. Some of it is the government has obviously, you know, found it much more interesting what tech's on. Much more interesting. A variety of good and bad reasons, probably. And, you know, you could argue that it was best thing ever was that tech was built mostly on the West Coast, far away from Washington, allowed tech to thrive and, you know, invent itself without a lot of scrutiny. [1:01:38] because generally speaking, government scrutiny early in emerging technologies is not a good thing. I'm like afraid of like AI regulation. I'm like, what are the odds of getting it right? It just seems hard to do. Well, I think that's a real risk with emerging technologies. The government is less likely to be right than wrong on something that's rapidly emerging. Maybe when something stabilizes, the government might have a better predictive accuracy record or something. Yeah. I mean, you obviously need regulation at some point in these journeys. But then you also have to think about the rest of the world. And even though it's probably a

1:02:08-1:04:02

[1:02:08] speaking than I am, [1:02:10] has been very concerned about losing AI to China and what that would mean to this country. And if you have a threat, you have to think very carefully about regulating a new technology. If you know a very serious adversary is putting the pedal down and doesn't, you know, is frustrating itself. They're really good at robotics. They're really good at manufacturing. They're really good at robotics. Look, it's very clear. And three years, four years ago at the Hill Valley Forum, I talked about we are in a techno-economic battle with China. [1:02:40] must do everything to win and everything we can to disadvantage them. It's just the truth. What does that look like? What does need to happen? So I think too much regulation in AI would be a really bad thing. State level regulation is a horrendous idea. Just generally? Because they don't understand the global implications. You know, not everybody abides by American rules. The Chinese for sure don't. So I think we have to [1:03:10] realistic and pragmatic about what battle we are in. Over the next 10, 15 years, economic superiority is up for grabs and we gotta win or we'll [1:03:23] live under President Xi's rules. Yeah, I mean, obviously, you've talked about this a lot, too. Yeah, but it was a bipartisan effort back four or five years ago, and fortunately, the [1:03:35] um it was very effective it started changing people's mind like there was a lot of people that were very naive about the threat yeah um five years ago and i think if we'd waited too long and there's still debate about like should we export this chip or that chip yeah you know what should the restrictions be on different technologies like there's a lot of nuance to this but at least the central idea that we just cannot lose this race yeah for ai is pretty mainstream now yeah it's

1:04:05-1:04:59

[1:04:05] It's really resonant for people. People want to work at those. There is a growing patriotism out of necessity, I think, probably. I have a final question for you, Vinod. Did you see the report that Keith went to Barry's 2,000 times last year? That's an exaggeration. Too many times. It's only 438. You're just trying to get a hold of Keith. He's just like in- The interesting thing about it is, though, literally this morning, I went to Barry's, 7:10 AM, and a founder comes up to me after class, and he says, "Nice to meet you. I [1:04:33] I was like, what do you do? He's like, I run an AI detecting cancer funded by A16Z. And I was like, that's cool. It's interesting. Who knows if one day we'll invest or whatever. But he said, thank you so much. I said, what are you talking about? He's like, I started getting myself in shape by going to Barry's because I read about you doing it. [1:04:49] And so you change someone's life indirectly through that. Like that's actually really rewarding. It's not much, but it's good. No, it's just this morning. That's great. All right. You guys, thank you very much for doing this. I had a great time. Really appreciate it. Thank you a lot.

Want to learn more?