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It is a violently competitive landscape.
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I think people are very concerned that it is a globally competitive landscape.
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There's insecurity in that because I think it's a bit narrative [music] breaking as well.
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The belief is like with recursive self-improvement of AI research, models that can improve the models themselves, we are a year or two [music] years away from some sort of exponential intelligence.
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>> [music] >> Sarah, where [music] to begin uh what will hopefully be a really fun conversation.
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I guess because you and I are interested in so many of the same things, I'm just curious what's on your mind today.
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I think we're both feeling a little frenzied and it's been going for a while and it kind of feels like if anything it might get more frenzied and more chaotic both for what you do, but also the world around what you do.
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So, just in the in this moment like what Yeah, what does it feel like?
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What what's on your mind?
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>> An obvious thing for anyone like thinking about how to navigate this period as an investor is just like well, like how does it unfurl and how's it different from the past?
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Um and what do I do if I can't back test, right?
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I was talking to a investor friend last night and the analogy he gave me was like I keep saying I want to press the brakes as hard as I can, but I'm not doing it.
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Um going 90 miles an hour.
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And I do think the question is like do you miss the opportunity on one side or you know, do you make the mistake of every boom bust cycle in technology history?
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I think it's a complex question.
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>> Do you think that we got it right in the profile that we wrote that you're sort of making a specific I think we called it a wager or a bet or positioning, whatever you want to call it.
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>> Yes, I'm a I'm I'm a long. Yeah. >> Yeah.
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That there is a really important fundamental thing happening between a couple of labs in AI and kind of everybody else.
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And that we need to sort of like take up arms to make sure we don't end up in like a very monolithic outcome.
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Do you think about it that way?
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>> I would answer in a maybe different way, which is I I I believe in like the great man and great woman theories of history.
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I just believe that if you have very high agency people in all of these places and they have the correct risk capital or support in the network or environment, like yeah, you change outcomes.
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And so you look at very important questions of what happens to open source models and like US industrial policy.
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You know, if you if you think about the opportunity for the ecosystem in the future, is there going to be a competitive Western open source model?
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Like it actually leads to like did anybody make one?
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Could they like raise the money or were they willing to commit the capital and to gather the talent base and you know, build all the infrastructure and fight for the frontier or not, right?
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And so I definitely think that people can individual people and entrepreneurs can affect the outcome.
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I don't necessarily think of it as a war.
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I am working closely with and co-invest with and have many friends at the labs, uh the big labs and small, but I think it's fair to say the extreme point of view that some folks may have in and outside of those big labs of the owner of one, two, three frontier models consumes the economy.
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I do not want that future. Very clearly.
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And I don't think we are going to end up there.
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>> Do you actively want to be a great woman in this sense of the theory? >> No.
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I think the like and I I don't mean that from like a personal humility perspective.
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It's just like it's not on my set of goals. Right?
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Like I want to be the best investor in the things that I try to do.
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And so it's not out of lack of ambition or even confidence.
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It's I think some people are driven by like I want to be the person that like made this happen.
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And like my realization of I thought I was going to be like a software entrepreneur for the longest time.
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Uh and my decision that like from an identity perspective I was going to be an investor actually had a lot to do with the idea of like I'm I'm deeply curious.
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I like I like to understand things. I like to be right.
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And then I like to I care.
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I'm very motivated by working with extraordinary people.
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And then, you know, if I have a set of skills using those to make them more successful and that looks like a pretty good fit for early stage investing. Right?
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If I want to work with the very best people and I want the companies to have impact like I think the the firm can support a movement and support change we want to see.
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But I don't think it has to be me.
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>> If that's the goal, what what does it take do you think right now to be the best in a very competitive environment?
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What would you describe you've done really well so far?
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What are the things >> We're still very early. >> I know. >> Yeah.
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>> Um but undeniably you've done really well so far.
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I'm curious what it has taken to be that good and what you think it's going to take, you know, in the next year plus to, you know, within horizon to be that good?
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>> I think it's been pretty simple so far, actually. Right?
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We talked about this like my read of the environmental was was the growth of firms and generational transitions that were happening meant that it wasn't the most competitive landscape in early that it has been.
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And you have this massive technology transition happening.
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And if you took the bet on understanding the technology and the community and approach it from first principles, like you might have better access and make better decisions than others who are less focused, right?
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So, all you have to do is like take the risk and be focused.
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And then it's an execution play.
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And I uh that that's one of those things that I think is like pretty simple and it's just hard. It's effort.
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So, that I I think today it's like actually been not that complicated.
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It's more about what your bar is for the people you work with.
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And my partner Mike and I started with like a set of pre-existing relationships and understanding.
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And so, I think that has been useful.
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>> Surely there must be more than just outworking everyone.
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Your partner Mike said something interesting to me a couple weeks ago, which was there's sort of 250-ish people that he thinks about or you you guys think about that are what some combination of entrepreneurs and researchers and you know, >> doing the most interesting things on the frontier.
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>> Yes, just like the people that are actually like showing up in the morning and pushing this whole thing forward.
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And that one of your goals as a firm is to be as close to those people, know them all and be as close to them and support them in as many ways as possible. I really like that idea. It's a cool idea.
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And that's more than just like doing a bunch of meetings with people that are starting companies.
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So, it just feels like from the outside looking in from the cheap seats, it looks like there's more unique stuff going on than just the competitions that was low and we focused more on and we're executing better. >> Yeah.
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>> And so, I'm I'm interested in the like this the ingredients that have been so far a part of um of success.
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I won't I won't name them, but there was there's one well-known LP that does this like survey every year of what all of the other fancy LPs who they most want to invest with.
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And you were either number one or two.
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And so, there like there's there's something going on both with the companies you've invested in with the performance so far with like the market perception, like there's something more than just okay, it was a moment in time we worked really hard.
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And so I'm trying to get at those ingredients.
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That's why I'm pushing on it.
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>> To the point of like perhaps making a bet that others wouldn't.
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Um we thought very carefully about what markets are going to matter and like what what might be different about the founders that we look at at in this era if we are right about capability growth and the breadth of impact that would just be non-obvious to other people, right?
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So like where where's the biggest difference from the status quo and like just how how does the framework change?
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I'll give you two examples.
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One of the things that we were really looking for uh in the first year was application areas, like workflows and professions, um tasks that we thought were a good fit for purpose for the models, which is a very like technology-forward approach.
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Lots of people thought like this is nonsense, right?
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Like you got to think about the customer problem and working from the customer back is the only way.
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I think we do we want to do both.
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Um and if you look at Harvey and the function of the law, like rationally if you think that we can do next token prediction with language and you knew that in late 2022, then law is structured language.
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And I'm I'm not a lawyer, but like from the outside I'm like, "Okay, you need to like read a lot of documents." And we had retrieval.
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And you need to generate text.
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Um and there's a lot of precedent text both inside firms and in common law and history.
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That feels like a really good match.
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When I say focus, it's like we also took a very specific view of what is now possible and then what is valuable within what is possible.
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Um and then who's aligned with us?
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So like Winston and Gabe, they they believed that AI would transform the practice of the law in a very It's like now even cringey to say, but like in a very AI pill way, right?
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They're like we will do enormously complex work with lawyers. I don't know when.
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Could be next year or 5 years from now, but like from the from the kernel of I can look at a landlord-tenant agreement in California and answer a question somewhat trivial um to I can project to doing a Activision Blizzard M&A and doing 85% of the work. Like that's leap, right?
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Um uh and so the thing that appealed to me in that moment was the ambition of what was possible then um and the this like just technical logic of like why it would work.
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And so I don't I think that's the probably just different decision-making framework from how other people were approaching it at that moment.
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12:03
What is that group doing talking about today, the 250 researcher kind of like frontiers group?
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What's the most interesting thing and the most notable difference between today and like 6 months ago or 12 months ago or something?
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>> It's a violently competitive landscape.
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I think that was true 12 months ago, but like even more true than it was 24 and and 36, right?
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I think people are very concerned that it is globally competitive landscape.
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There's insecurity in that because I think it's a bit narrative breaking as well.
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I I'm going to like describe a belief and then, you know, some I'm going to question the belief.
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Uh the belief is like with recursive self-improvement of AI research, models that can improve the models themselves, we are a year or 2 years away from uh some sort of exponential intelligence.
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I think that belief is new within the last 12 months for a lot of researchers.
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But some driver of it, like that that we're 2 years away, um and smarter people than me, Andrej Karpathy will actually in a very self-aware way say like I thought it was 2 years away for about 10 years. >> Yeah. >> Right.
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Um and he thinks it again, to be fair. Um but who can say?
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Um I do think that there is some sense of the major labs are so compute-intensive and so large my head count perspective now that the sense of contribution of like I can move the needle, you know, if if OpenAI has 200 people and there's not that many researchers then the question of like how do we get there is really up to every single person.
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Now if the question is well I need 750 billion dollars of compute spend and and we have many thousands of people working on this problem like I think people feel less ownership of the >> the >> of the outcome.
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>> Oh, that's interesting.
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So it's just like a function of getting compute.
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Like that's the thing that's going to push this thing over the line not our own human efforts.
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>> I definitely think there's a large contingent of researchers who would feel that one of two things is now true.
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Like what I do doesn't matter anyway because the model >> is going to do it. >> is going to do it.
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Or or two, the only thing that matters is compute scale.
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And both of those are somewhat disempowering.
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>> So then what are they doing?
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Like if I believe both of those and I'm a I'm a top five researcher or something or >> So that that says something about your psychology because you want to like do something that matters.
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I think there's also a set of scientists who like they want to work on the thing whether or not it matters that they're working on it. Right?
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I didn't an entrepreneur asked me yesterday would anyone I would not work on the companies if I felt like we couldn't change the outcomes a little bit for them.
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But he he asked me yesterday like would any of the companies that you backed not been backed without you at that round?
15:13
Like would would people just say no?
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Like couple of them, 5%, 10% max.
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Like they're resourceful, really talented people.
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They'll find other investors.
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There are lots of smart investors in the world who want to take that risk.
15:26
Um but, you know, maybe they wouldn't have gone the next hundred million dollars of compute. Right?
15:31
Um and I don't think I don't think every researcher um doing frontier work at these top couple labs right now feels like they're essential to the machine.
15:44
>> What do you think is unhealthiest part of everything going on right now?
15:47
Like what worries you about what people are trying to accomplish and where there are What are the things that you're most worried will inhibit the future that you want to see?
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>> I think compute is one.
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People um I think understand that very well.
16:01
The version of us having enough compute over the next five to ten years.
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And people are like very much thinking about like 2032 at this point at scale.
16:10
Um I was talking to the leader for infrastructure at one of the hyperscalers earlier in the week.
16:17
And he's like, "There is nothing that is going to move the needle for us at sufficient scale before 2030."
16:23
I was like, "Oh, that's depressing."
16:23
Uh it's just, you know, where can we get sufficient natural gas?
16:30
Americans and entrepreneurs have been able to build new technologies and new capabilities very, very quickly in the past.
16:37
And I don't think it is a technology or capability or capitalism problem.
16:43
I think it is a regulatory problem and an alignment problem.
16:45
And I don't mean like AI alignment.
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I mean, if you want to build data centers in New York, you need to convince the people of New York they should want to data centers there.
16:55
Or America should want data centers there.
16:58
Um if you want to make the price of nuclear competitive as base load power, then you need to convince people it's safe.
17:09
And you need to allow enough construction of uh you know, >> If you want to build ours, yeah. Our rest of ours, Yeah.
17:17
Um, in order for the price to come down because we understand like how that cost curve will change in theory.
17:24
I don't think we lack the technical and entrepreneurial capability to build abundant cheap energy for the data centers.
17:31
So, you know, that's that's one.
17:33
The physical supply chain is it's just a tough reality, right?
17:39
Um, that makes me worried that the learning to build things and having the tacit knowledge and the labor and the raw materials, uh, that can't go as fast as software re-invention decision-making.
17:57
But, there's the only way the only way through that is through, right?
17:58
We just have to invest in it.
18:00
Uh, on the investing side of like what worries me, I was talking to one of our founders, several of our founders who are researchers and, uh, explaining that the quality of their storytelling and their ability to make the companies' bets legible to investors is like obviously very important to their success if it's going to be a CapEx intensive um, play up front.
18:28
And, um, the reality of the financial landscape for all of these people is like I'm not a research scientist, you're not a research scientist, and all of the capital is not research scientists, right?
18:40
So, um, uh, like it's on entrepreneurs to go explain their story.
18:45
But, one of the like challenges is there are a lot of people attempting to invest, as they should, in, uh, technology bets.
18:55
And, there's a, you know, it varies how much fundamental understanding there is.
19:00
There's a lot of uh, proxying of judgment to pedigree or to other legible signals like who's invested, you know, like what are the references are always good, but like, you know, who are the referral sources.
19:18
And so, the decision-making is less fundamental, right?
19:22
Like I asked a ex- like extraordinarily good investor friend, like, tell me I like, you know, we had a debate, like you you do.
19:32
And I was like, I don't understand.
19:33
Like, what is this company going to be that would be big? Explain it to me.
19:36
And his explanation uh was essentially like, "Do you know the quality of this person?"
19:45
I'm like, "Yes, I've known the quality of the person for 8 years.
19:48
Um but the busi- like the the technical theory and business don't make sense to me.
19:53
And I'd say like people are making large-scale research bets without any intuition for them or without any opinion on them."
20:01
And I'm like, "It's not all going to work.
20:03
And I may not be any better at like deciding, but like we want to get to that intuition.
20:10
And I think not having it is not having a point of view on the business besides the pedigree of the person is like it's very dangerous."
20:19
>> Who Who is a researcher that has most kind of blown you away, and how did they do so?
20:24
Like, what's something that they did that to you felt extraordinary, you know, back to the great person theory?
20:31
There are a number of these people who I think like the history books will write about a contribution of theirs as a truly extraordinary thing that like, you know, created this kink.
20:40
What's an example of that of a person like that and something that you've seen them do?
20:44
>> My partner Pranav and I um were introduced to Tony Zhao and Chenxi at Sunday Robotics um when they were PhD students at Stanford.
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And they were, you know, they'd worked at Toyota Research and DeepMind and Tesla.
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And so, um they weren't like just academics by any means.
21:02
They're young PhD students, who I think they're like 25. >> Yep.
21:08
>> Um I don't know I think one of them didn't finish.
21:09
They just like started the company.
21:10
What I thought was impressive about them then and then now, I remember looking at their body of work and I was just like, I think took me a while to get oriented, but I think that they have contributed dual-handedly more most of the interesting ideas in robotics AI over the last 4 years, right?
21:30
And it's like that's a pretty weird thing for two very young people to do.
21:35
And then like if I try to characterize the type of ideas, it is uh how can I use um modern AI to solve the robotics generalization and robustness problem in a very practical way.
21:49
It is believed in robotics that if we just had the internet of robotics data, like yeah, we'd have like fully general robots everywhere.
21:57
This is like clearly going to work.
21:58
Um and so one of the big research and practical problems is like where do you get that data?
22:02
And so some of the ideas that Tony and Cheng have worked on is like well, how can you be clever about collecting the data in the cheapest way possible in a way that supports the distribution of like real-world environments and tasks.
22:17
And so I think the creativity of uh thinking about the actual constraints of we don't have the data, we don't have infinite dollars to spend on the data, and we're going to treat it as a technical problem to solve of you know, what is the shape of the data and the collection and how does that interact with the model and how much of these like cheap data collection can we transfer to model learning?
22:42
Like that's super interesting.
22:43
That's very outcomes-driven.
22:45
I was blown away in the first meeting.
22:47
We said yes immediately there, um thankfully.
22:50
And it's just under 2 years that the company has been around.
22:54
Nothing is true until it is shipped, but like this entire team believes that we are going to have general semi-humanoid robots doing things in people's homes like first in beta end of this year.
23:07
Um that is not something that like any of us believed and when like it it blows me away that you can move that quickly from like a bunch of cardboard in a Stanford basement to like we built the full stack saying it is manufactured here.
23:25
Um we have done hundreds of iterations of hardware on model collect uh model data collection and translated it into tasks and tested in all these real world environments and like it's going to work. >> are very cool.
23:40
>> I just I think the I think the entire like the speed of that is mind-boggling.
23:45
Um because the the I still think the broad view, not everyone but like lots of people in robotics are like now it's a question of when not if.
23:54
And it surprised me that the team was like if not this year next year.
23:59
>> I'm very curious about the moments of your investment decisions.
24:00
Like you just said in the first meeting you were sort of like okay we're we're in. >> Yeah.
24:06
>> Is it always like that or are there examples of things where you like hem and haw and you end up doing it and it works?
24:13
Like like I I I would love to hear more about how you and your team make investment decisions like the actual like in the room process for okay this thing is interesting we're going to do it or we're not or we're not we're debating it.
24:24
Like what is that what is that process? What is it like? >> Yeah.
24:27
Um it varies based on company.
24:27
I'm personally like I'm very um I'm very instinctive on people.
24:33
And then um I don't know that this is like the best way to go about it and now describing it but I often I often know I want to do something immediately.
24:43
If I know what somebody has worked on and then I interact with them and I hear the idea and I have some basis like some background in the idea then um I'm like we have a rating scale of um you know, a 1 to 10 scale and I'm like, okay, I'm like immediately an eight or a nine.
25:01
And what I'm then doing between that and a real decision is often figuring out like where the holes in my understanding, where my judgment of like their premise or them is incomplete or wrong. Right? Like what do I not know?
25:18
Because like if you're an investor looking for the most ambitious impactful companies, um you can't know every domain, right?
25:26
We're like we have biology and defense and robotics and law.
25:33
Um and so I'm I'm like spending the next day to few weeks like desperately trying to ground myself and being like, okay, what does everybody else believe about this space?
25:44
Um and are they the people I think they are?
25:47
That's what my process looks like and then I want to get feedback, I want to get like second reads on people.
25:50
I want to understand what the core questions are.
25:54
I'm a memo person, even at the very beginning of the firm when it was like just me, I would like write the full memo.
26:04
Perhaps Greylock style, right?
26:04
And like ship it off to a friend that was an investor who I trusted for their perspective outside of the fund.
26:10
Uh you and I have talked about like what do you value about a partnership?
26:14
And I'm like, I'm comfortable making investment decisions, but I think other people can make me better.
26:18
I want people to like push at the logic and like have me reflect.
26:22
Um and so I used to like take the memo and like send it to John Lilly or Dylan Field or something.
26:26
Um and so, you know, we write a memo, I go see what Bella or uh Pranav or Mike wants to know about the person.
26:35
We try to complete the picture.
26:37
Other people I think are like more even in their decision-making. Right?
26:42
They're like thinking about it and thinking about it and then um like they they climb to conviction versus I kind of start there and then I like work backwards, but I think a similarity between both Mike and I is we will we'll start at a point um and explain like what will move us, right?
27:02
And so I met a really interesting company earlier this week with my um partner Bella, and uh I'm like, "Okay, instinctively I like am positive on it, but I don't I just I don't know enough about the science here, and I have to like go make sure this makes sense."
27:17
Um and so you know, can you really be an eight or a nine if you don't get it? Like, no, right?
27:24
And so that's what I'm like, I could get there.
27:26
Um and that as we were talking about is one of my concerns for this period of time where I'm like, if you if you don't feel like you have any grounded intuition on the on the bet itself what are we doing here? Right?
27:38
Um it's not I'm trying to think about if that's fair cuz I'm like, if Bret Taylor wanted to like >> Yeah, that's like what the most ridiculous thing about >> or do dog streaming or something, I'd be like, yeah, of course, man.
27:49
Um but you know, he wouldn't do that. >> Yeah. >> Yeah.
27:56
>> So so there there is some class there is some version of like, I don't even care if it doesn't compile in my brain, the person is so undeniably good that I would just back them. Bret as an example.
28:08
>> Yes, but I I I feel like these things are so um inextricably like intertwined in my mind. >> Yeah.
28:16
>> Because part of what makes people great, like I was trying to help one of my companies the candidate yesterday, uh and they're like, "Oh, what do you see in these people?"
28:24
And I'm like, "They're just so right." Right?
28:26
That's a very useful He's right all the time.
28:30
Like their industrial logic is impeccable.
28:32
Um you know, they have all these like great character traits, too.
28:35
They're amazing at recruiting, but you know, they have a point of view that I think is going to be right in the world, and they make I've seen them just make repeatedly correct decisions, including when I am wrong.
28:45
And I'm like, I have a lot of respect for that.
28:46
Um and so, when you're when you say like these people are amazing and they're um I'm like part of what I think makes them amazing is I believe in their judgment.
28:56
And so, if I don't understand what they're doing, I can't have an opinion on their judgment, right?
29:02
And I'm like Brett's doing enterprise AI, right?
29:04
Like I I understand what he's doing. >> Yeah.
29:09
If I were to build a pie chart of your time >> Mhm.
29:12
>> now, not not when you started the firm, but but today.
29:15
There's, you know, meeting new companies, there's helping existing companies, there's talking to researchers, there's time with other people, there's talking to candidates.
29:23
Like I've no sense of what it would be. What is it?
29:27
Like if you had to sum it up what are the things that you spend your time on and what's like the percentage allocation?
29:35
>> I think I spend 2/3 3/5 of my time working on portfolio company stuff.
29:43
Um uh and that is recruiting, helping people think through things, trying to influence the outside ecosystem in some way. Then, raising money.
29:55
And then, you know, the next largest piece is looking at companies, right?
29:58
Um but I probably like I don't know if this is right or wrong.
30:05
I get paranoid about it and like move the number, but I probably see four to six new companies a week.
30:11
It's not a very high volume.
30:13
My first couple my old firm, I saw 500 companies. And so, I'm like >> Wow.
30:19
>> Um like now, I feel more calibration where I'm like I I just have much more confidence I can tell. >> Yeah. >> Right?
30:25
Um and then, the balance of my time, I am doing a combination of help one of my partners look at something, meet people that might teach me something about the world.
30:39
And that could to researcher or um if you were a purely early stage in a larger firm, you can you can be very myopic cuz your ecosystem is big enough, right?
30:48
Uh and we are very small firm.
30:50
We're very like ecosystem oriented.
30:50
So, I've learned so much from just like getting to know investors who think differently than I do including different asset classes, right?
30:57
And I'm like, "I never spent that much time with public markets people before."
31:02
And it is very educational how they think about the world, right?
31:05
Uh I spend time with other investors of all scales and asset classes.
31:10
Um I spend time with companies, right?
31:13
Um like right now with a pharma company who is thinking about how AI is going to transform their business.
31:23
And like this is very interesting to me because I've learned a lot about like what they believe about the future.
31:27
I'm doing a lot, but I'm like leaving room in my calendar for like just learning, um feeding curiosity, and then uh you know, there are pieces that are like other parts of bridges to DC.
31:42
Uh external communication.
31:44
>> you doing about raising money?
31:45
>> I stand with the belief that I um advise entrepreneurs with.
31:50
You should understand people's objections to what you are doing and their questions, but you should not tell them what they want to hear, right?
31:58
When I started um the the fund raise for fund one, I knew a lot of LPs over a long period of time already.
32:07
So, it was not very complicated, but I had one of my friends who is a private equity investor who stated like, "You have to have like a very differentiated story for LPs."
32:17
Um and like every part of the funnel should be, you know, the specific thing you're going to do.
32:25
And I'm like, "Let's be honest.
32:26
I don't know yet, but I need to like raise the money so I can go like experiment and figure it out."
32:29
Um and uh so, I never like made slides and told a specific story about all the things that like we attempt to do now.
32:40
Because I I think you don't know until you make contact with the reality and like think about it and you're in the market.
32:44
And I'd say like there were definitely LPs who did not like that.
32:46
Um they're like I I I think I I like gave people a two-pager on my background and investing history and claimed that I was good at identifying extraordinary people and then good at, you know, being useful to set of people and being genuine like supporters and being a genuine supporter of those people and like you combine that with investment judgment and ability to recruit like you got a starting point.
33:16
I mostly said I'm like, "Okay, here's like some things I imagine about firm culture and then we'll go execute like hell and figure it out."
33:25
And it's like, "I can I can see how this is tough from an LP perspective and I like deeply value the people who bet on us early because they go write a memo for their investment committee."
33:34
And they're like, "She's going to execute like hell. We'll find out." Right?
33:38
That's like tough, right?
33:41
Like sometimes um the cleanliness of the story is what people are looking for.
33:45
I can't advise other managers on this because, you know, people have different outcomes.
33:50
But like, you know, if you tell people what you are going to do, life is much simpler and what you actually believe, life is much simpler.
33:57
And for me as an investor, when somebody can convince me that the world works differently than I thought, I'm like immediately incredibly excited, right?
34:05
And so I'm like, "Maybe I'd convince people that this is just like how it actually works."
34:08
I also I've met a lot more investment managers the last 4 years than, you know, I knew a lot of VCs, but like people who are doing creative things.
34:16
people who are doing creative things. I really like entrepreneurial investment managers as you I think do and as you might imagine where I'm like, "I don't want to build the firms that they've built, but the creativity with which like um
34:31
Felipe and Thomas co-two or that Josh at Thrive approach their business um and you know you know the encouragement they have for others to approach their business with like, "Well, you can do new things and you should go express your opinions in your in the form of your investment management firm." I think is amazing. I think is amazing.
34:48
>> What was imprinted on you watching your parents who are both entrepreneurs?
34:53
>> I think this is very helpful to me because there was no um there was no moment of my childhood or being a teenager where I felt like they were not there for me even though they worked all the time, both of them, right?
35:07
Um and then like if you try to resolve these things, like one is like, "Well, I was pretty independent kid where I'm just like that helps me."
35:14
I don't know where I was in the distribution, but I feel like I was pretty independent.
35:18
It helps me to think like your family can make you feel like you are the center of their world.
35:26
But they're whole people with other interests and they want to spend time doing other things, too.
35:29
I think our our family values are very similar to theirs, right?
35:32
Um and I would say there's like integrity.
35:36
There's thinking for yourself.
35:36
It's independence of thought and then there's like focus and like um on family, team spirit in family.
35:44
And um the independence of thought is probably like the least generic one of those.
35:50
I think a lot of people like want to be good, kind, and work hard, and whatever else.
35:54
Um but uh for both my parents, it was a moral issue.
35:59
They were like, "You cannot ever worry about what other people think." >> Mhm.
36:05
>> Uh >> [clears throat] >> I think I'm like you know far too that side of the spectrum, but I do think about it sometimes.
36:12
>> You You do sometimes worry what other people think? >> Yeah.
36:15
>> What do you want them to think that you worry that they don't?
36:18
>> I worry about raising people's competitive hackles in the ecosystem. >> Why?
36:25
>> Because I'm a friendly person.
36:25
I want to be friends with everybody. >> Mhm. Right?
36:29
So, uh but I don't mind competition, but I I think the the um the sometimes pure zero-sum competition stance of traditional Series A firms, Series A Series B firms that says like I'm going to own 18 to 25% of this company and take the board and you're going to own none of it is like is not conducive to like a lot of collaboration.
36:56
There issues with that from an incentives perspective, but the public markets like orientation is people are love to tell you about their best ideas.
37:04
You'll pile in after them.
37:07
And I'm like this is an extraordinary situation, right?
37:08
I would love to talk about why like gaming and entertainment is going to be like totally different and people are um you know, super under-indexed on it.
37:17
Um and and so I think there there's part of that orientation that just appeals to me as very positive sum person.
37:25
>> I'm always interested in sources of inspiration.
37:28
And I'm I'm I'm curious in two ways.
37:31
Overall in your life, who has inspired you the most?
37:32
And also like right now in this very moment, who is inspiring you the most and and why?
37:38
>> I saw my parents build a company.
37:38
I was like this is so cool, right?
37:40
Like it's us against the man and like the man is very big companies.
37:45
The man is trying to kill us and like we can still do it just because the technology is better and the product is better and the customer will want it.
37:53
My like love and ethos goes to like entrepreneurs because I'm like okay, you can make something out of nothing because you see a better future and you can do it really fast, right?
38:03
and these things like have just appealed to me in terms of like what I want to try.
38:07
There's so much courage in that, right? And optimism.
38:12
And I actually like there's there is something like poisonous that bothers me today where I think especially like the post Gen Z entrepreneurial crowd think it's like all marketing and brand is real, and it's like building a network is totally real.
38:26
No one denies that, but um when folks are very cynical about how the world works, how entrepreneurship works, like that it's just nepotism and like Twitter Twitter's useful.
38:40
I think that's nonsense, right?
38:42
I'm like if you focus on value and treating people well, and you work with extraordinary people and the vision is worthwhile, like that works more times than you'd think.
38:55
There's so much cynicism about like playing the game, be it marketing or fundraising, and um I hate that.
39:02
Um I'm inspired by the people who uh um and Pat is like this, I find him very inspiring and uh like Tuhin is like this, I find him very inspiring where he's just like, "If we just do the right thing by the customer, we will win."
39:15
And I'm like feels a lot more complicated than that, right?
39:21
And like I think he's right, and that seems to be working. >> Mhm.
39:24
One of the huge debates right now is what to do about the fact that there are open-source models not American-made, which are competitive at the frontier of performance of AI models, and seem to clearly have been, at least to some degree, based on the work of American models.
39:43
What to do about this, what it means for the future of AI.
39:48
Companies love open-source because they can build their own thing and um you know, Base 10 and others that serve a lot of inference, work with a lot of these models.
39:56
How are you thinking about what's right, what should happen, what will happen, the implications for business.
40:01
This is a big, hard, important, interesting question. >> It's a big question.
40:06
Um I think there is like my point of view on what is healthy for businesses, America, the ecosystem, individuals, and then there's like what's already actually happened. >> Yeah.
40:18
>> Um the reality is we have uh over the last 3 years increasingly competitive open source models from all fronts.
40:24
Uh largely China, but definitely like also, you know, uh the US and Europe um and uh most recently like you know, thinky, poolside, people waiting for reflection, um Nvidia models, Mistral.
40:38
We will have um very powerful and already do have very powerful open source models from Western countries.
40:45
Uh so, I'd say like the cat is out of the bag, and these are uh in use everywhere.
40:52
Even if you have no economic point of view on the labs, and you just say like, "Well, what if you like how is the diffusion of capability going to happen in the economy?"
41:05
There are a huge number of instances where it is too expensive, too sensitive, or too slow to use the like model from the frontier providers today.
41:18
Um and I think that's going to increase as we learn how to do more things with AI because it's actually like quite expensive.
41:25
And so, I'd say like it's objectively true that if the capabilities are more democratized, you will see them used in more ways, right?
41:37
And I like I want to see that happen.
41:37
It would be irresponsible not to understand the safety profile of models as they progress because you just draw the line you're like, you know, we have companies that um uh they use frontier model capability for defensive cybersecurity and for um biology work.
42:03
If it works for those use cases, it obviously also should work in similar ways for the >> offensive purposes, yeah.
42:10
>> use cases or the, you know bio weapons bio security use cases.
42:13
I think like we just need to look at that reality and think about like what are the other ways in which you control this.
42:21
Um but attempting to stop technological progress and openness around it.
42:28
Like if you did um restrict use of open source models in the in the United States, like you'd basically just restrict law-abiding American businesses.
42:39
Um and slow them down or move profits different pockets, prevent certain um uses of them because the actual uh attackers or um people who have adversarial uses of these things are not affected by your restrictions. Right?
42:57
So you're just you're restricting your own people.
43:01
My view would be like there should be testing and understanding of these models at the frontier.
43:07
Um people are very worried about backdoor like behaviors in Chinese models.
43:13
Um and like well, like like the thing to do would actually be like have a very rigorous set of safety testing on that.
43:21
Like let's go find out as much as we can instead of like talking about how there might be this issue in a speculative way where there's not been nearly enough actual research on it. Um and we can do it.
43:31
They're um uh It's not trivial, but we can do it.
43:35
And so I um I think that the future where there is broad access to intelligence too cheap to meter, as Sam put it, like that is coming.
43:50
Um it will be supported by open source.
43:53
Businesses want it to control their own destiny for economics, for capacity.
44:00
Uh and I think that if given those models and the increasing democratization of like the skills to post train these models, build harnesses, use task.
44:08
Like that's how you're going to get it into the The economy is so big, right?
44:12
Every individual has these use cases that are not going to be imagined by a researcher in a frontier lab.
44:21
You can't imagine the diversity of reality.
44:23
Um and it even if you trusted the models to go figure out what to do, they have to get there, right?
44:31
And I think the best way for that to happen is a ecosystem of businesses as we've always had in the economy and um you know, cheap infrastructure.
44:41
>> Do you ever worry that there's a version where uh an alternate version of US history is that there was energy too cheap to meter because we built a thousand AP 1000s or something, much like China is doing now in nuclear and just the set of circumstances happened such that like we just didn't get that and um do you ever worry about that as it relates to intelligence?
45:00
Like it does seem inevitable that we're going to have abundant, accessible, low-cost, valuable intelligence.
45:07
Um can you imagine a world where we don't? >> Yes, absolutely.
45:11
And I also think I can imagine very easily a world where we don't have that in a competitive way um because it is essential to uh economic competitiveness and national security, right?
45:23
Like uh let me posit that there is not a version of the world where we rebuild our industrial base without automation in the United States.
45:34
If we like don't import people and our people are expensive and we lack some of the skills, but we want to produce a lot more goods um and have a more resilient supply chain like >> Just doesn't add up.
45:45
>> Yeah, what are you going to uh who's going to produce this stuff, right?
45:46
Um uh people in the United States do not want to work and should not want to work for $13 an hour doing a very inhuman job.
45:53
Um I don't think it is like the I don't think it is inevitable that we are competitive and I think we need to like make that decision actively.
46:02
The version of it that I think is very possible is that people are um very rationally afraid of the impact of AI on jobs, or dislike the capture of rent by a small number of technology firms, and you know, rejecting the idea of being in the permanent underclass, and then connecting that to like a anti-capitalist orientation.
46:35
Like that contingent of thought um can, you know, slow down build of energy and infrastructure and industrial capacity.
46:46
And like one of the most important inputs is compute.
46:49
If we don't have it, we're naturally not competitive, or we're at least like not independent, right?
46:52
I think we're going to start talking much more about compute independence.
46:58
Um and so that's a that's a big problem.
47:01
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48:47
>> So on this point of compute [music] independence, what does that mean?
48:48
Like what are what are the missing pieces of compute independence?
48:53
Like the most obvious one might be more fab capacity, more leading edge fab capacity here in the US or something like this.
48:59
Um there's all sorts of stuff upstream.
49:01
There's particular kinds of glass, very you know, very important that's controlled by basically one company that TSMC has like a monopoly on the supply of and there's all these, you know, component parts.
49:09
But if you think about compute independence, like if so much boils down to compute, what's to be done about it?
49:14
Like are you trying to invest in companies that are solving that problem? What is the problem?
49:20
Like say say a bit more about what it'll take.
49:22
>> Well, if you just uh work backwards from a data center full of GPUs, cooling, powering, training, and inference, so we can support the use cases.
49:32
All of those inputs, I think it it actually looks a a great deal like um energy independence or something like that.
49:42
Uh all those inputs, there is a global supply chain.
49:44
There are parts of that I've got my TSMC mug with me.
49:46
There are parts of that supply chain that um are like a very thin sieve in a place that is not uh necessarily stable or accessible to the US and allies.
49:56
And so um a like a different version of the world that will take a bunch of investment and national security and energy policy is for example Jacob Helberg is working on something called Paxil and it's like, "Okay, for every part of the supply chain, can we invest in more capacity and figure out what the independent paths are?"
50:20
I don't think that means like it's all got to be created like in the United States.
50:26
Comparative advantage is real, right?
50:28
But uh having more than one source is a position that everyone wants to be in.
50:34
When we think about the components that we've invested in, like we've invested in the labor gap for data centers and robotics, we've invested in nuclear energy, we've invested in alternative chip architectures.
50:48
We like keep looking at people who are essentially like data center builders, solar installer solar and battery installers of some kind because like part of this is like the actual capacity build-out.
51:00
But that's a very operational business, like somewhere between operations, some technology, and real estate. >> Financing, yeah. >> And financing, right? Absolutely.
51:08
That's like probably the dominant thing and um we have not invested in it yet despite looking very closely, but I think it's probably because I'm I'm I'm not opposed to it, but fundamentally I'm a technology investor.
51:22
Like I want to understand what it is that is the um durable product asset people are building.
51:29
>> Uh what are the biggest debates inside of conviction?
51:31
You've got such an interesting team.
51:32
Uh Mike, your partner is is a very technical, incredibly technical person, amazing engineer.
51:37
The young talent in your firm brings really interesting perspectives.
51:42
So I'm imagining great lively debates about things that matter, etc.
51:46
What what are the big debates today?
51:49
>> A lot and I have a podcast called No Priors.
51:51
Like this premise of some of the things you believed, especially about markets of the past, are like no longer true.
51:58
Um is an interesting one.
51:58
Uh and uh regularly we look at companies in domains that are not traditional software domains.
52:09
Not even traditional software domains, but like can you make money in this market at all?
52:16
Like venture investing in semis companies, Lip-Bu Tan aside, was like a godawful business for the longest time, right?
52:25
The returns >> Everyone told me this. >> Yes. It was really bad.
52:27
But I think that's like an example of um uh Bella, a partner on our team, you know, started looking at a bunch of these companies and it's obvious that the demand is there.
52:40
And so now I think we have arrived at the conclusion that others are as well, which is well, the market is different today, right?
52:49
We are seeing um consolidated at scale demand for accelerators or um uh even supply chain independence because, you know, the big buyers of it want it, too.
53:03
Um we can't all be like stuck on one line at TSMC.
53:06
Like who, you know, like um all of that is very, very valuable and that changes the risk equation for these companies.
53:16
And so we start with like pretty aligned beliefs about um the direction of travel or the problems that are worth working on.
53:23
And then a lot of the debates are like is the market friendly to a venture-backed company or not?
53:28
Or even if it's not you know, space is not a friendly market to a venture-backed company, but is it possible?
53:34
And like is the is the distribution of outcomes worth betting on?
53:37
Um and so that could be true in solar and batteries and nuclear in turbine manufacturing in robotics and biology.
53:48
Like these are not your favorite software markets from 10 years ago.
53:54
Um so each of them is a new debate.
53:56
And like like biology is an interesting one where um by virtue of seeing the data empirically, I have now strongly moved to one side of the debate. >> What side is that?
54:06
>> You can um create and capture enormous value with um models in biology.
54:10
Um and there could be different like AI software in biology.
54:16
We're the first check in a company called Chai Discovery.
54:20
Um and Chai is working with a number of um top 10 pharma companies in really significant ways to accelerate some part of the R&D process.
54:30
And the answer is like you know, the the traditional the conventional wisdom uh when we invest in this company and I've been looking at like computational biology companies of different sorts for five plus years at that point.
54:42
Um the conventional wisdom was like the only way you make money in biotech or serving pharma is um by >> making a drug.
54:54
>> Make a drug and then like get biobucks deals and then decide how far along that risk path you want to take and what that means for the capital structure of the company.
55:01
It's like okay, the great traditional biotech firms, they like find these principal investigators and they own 40% of the company and they're kind of assembling these things and like turning them into candidates and but most of it doesn't work.
55:13
So it's just like a very different distribution of outcomes and structure and way to invest in businesses.
55:17
And so like dumb software investors, like you can't make money selling software to pharma.
55:24
Um or build platform businesses in pharma.
55:27
And so um the debate is like does it change with models?
55:31
And it's like I I strongly yes now.
55:34
You know, we still have a question to solve on regulatory and like the there's the speed of the physical world and um safety is not something you can overcome easily, but I think we should see a massive acceleration in cures. >> Mhm.
55:50
>> Um and like part of the value creation will come from young companies and then we are excited to invest in them.
55:56
>> What flipped that for you?
55:56
What bit of evidence did you see from we don't know yet to like this is clear like a >> Well, we invested when we didn't know yet. >> Understood. >> Yeah.
56:04
Um so I'd say like you know, that's part of the fun adventure.
56:06
We were like it is possible and it is worth trying. There's no genius here.
56:10
I'm like that's a $10 million contract, you know?
56:12
Um and I think the other piece is actually you just talk to the scientist at the customer or somebody who leads, you know, a division.
56:23
Yeah, the user of the tool or you see um you know, they're also like end user adopted tools like product led growth tools that are working in the space.
56:33
And um you know, I'm like well, the customer knows if it's valuable or not.
56:38
Um I think the the the like lightbulb moment for the industry is when we will have a new indication or a new drug that like clearly the trajectory of the thing was changed created by AI.
56:52
And then I I I think like we should see a huge wave investment and rightfully so, but it's it's going to happen.
56:59
Um I uh I'm like very impressed by the speed with which pharma and health care overall has said like yes, this is going to make a difference and we actually think it's going to change the business.
57:14
>> Why did you call it conviction? >> It's aspirational. Right?
57:16
The most traditional form of early stage investing is you like you know, start early with a company, you have a significant position, you never sell the position, and you work on the company until it works or it's sold or dies, right?
57:30
And I think that there's like wonderful um alignment and simplicity to that.
57:35
Um uh Mike and I have both had the benefit of being part of the journey for some companies where it like took a minute to begin to work or it's like not obvious at the beginning.
57:46
And so, you know, Figma, Notion, Rippling, like you wouldn't bet on a company like hoping that it's going to take 4 or 5 years to like find the thing, right?
57:57
Um but I think everybody is a product of their own experiences, including investing experiences.
58:04
And so, um you know, the first couple years at Base 10 were like very non-obvious as well.
58:15
Um and so, the ability to like take a point of view that is not obvious in the market um because the market or because the people's backgrounds um or whatever reason, and then just you know, suspend doubt and act with full belief until it's true or not.
58:33
Like I feel like that's a great way to be a partner to somebody building a business.
58:40
Um and trying to build a partnership.
58:40
Um and I deeply believe in like this is a team sport.
58:44
But I also um I was talking to a friend who runs a another investing firm where he is like, "We don't have individual ownership of our investments."
58:52
And I'm like, "That is nonsense to me.
58:54
How could you run a a business that way?"
58:56
Because somebody has to own the decision, right?
58:57
And so, I um uh I don't know if this is right or wrong, but I don't know any other way to invest by saying like, "Patrick, you must make the decision." Like, "Do you believe? Convince us.
59:09
How can we help you make that decision?"
59:11
And so, I I think it's like all inputs to a single person. >> Good.
59:16
What have you learned about risk-taking?
59:19
And behind conviction, it sounds like there's often a leap of faith of some sort.
59:23
Like, obviously, if you knew everything and it was obvious, like that would be priced in and there'd be no return opportunity. >> Yeah.
59:29
>> So, is there always a leap of faith?
59:29
Is that risk-taking by another name?
59:33
You've been doing this enough You've made enough investments now.
59:36
>> Unlike my good friends at Founders Fund, I don't have an instinct to be like contrarian, but I do think it is like so fundamental to decide what you think and not worry too much about what other people think, right?
59:51
Other people is like uh the dominant narratives of the period or even what, you know, different players in the ecosystem that are really important declare one way or another.
1:00:01
Um I think you like just need to find the truth.
1:00:06
Um and the way I would relate that to risk-taking is like, well, if you find the truth and it is wrongly priced and you hold on to that, like you're in a good position, right?
1:00:15
You want asymmetric information and then the confidence to like hold the opinion when other people haven't come around to it yet.
1:00:22
Um and so I I think a lot about how to make sure we have the information that is better than other people's and then protect ourselves from like noise.
1:00:30
>> Describe that in one more level of detail.
1:00:31
Like that That's a great way of asking like what conviction looks like today.
1:00:35
You're building that, that shell.
1:00:37
What are the keys to doing those two things well, both having the having the truth and protecting yourself from the noise?
1:00:42
>> Yeah, I like want to spend my time when I'm learning about the world from somebody who is making it happen, like our portfolio founders or the many founders who are doing amazing things outside of portfolio, who like but are doing something that surprises me or advances the frontier or like really smart believe something I don't, right?
1:01:03
These are like three different categories.
1:01:04
And I'll give you an example.
1:01:06
Um uh Mikey Shulman at Suno is building an amazing business doing music generation.
1:01:12
And like uh shame on me, I knew Mikey, a mutual friend of ours who was an investor, like asked me to like invest and I stupidly said no.
1:01:18
But I was just like, ah [gasps] like I don't think that how many people want to make music. I make music, right?
1:01:25
Um but, like, is that like can you turn into a social network?
1:01:29
How much consumption is there going to be? A lot of questions."
1:01:30
And like my my intuition is just wrong.
1:01:32
It's been actually somewhat wrong because I I have underestimated the amount of expression or entertainment and creation for a lot of AI tools, right?
1:01:42
And I'm like, "Oh, I learned something here by talking to Mikey about his business and what people are trying to do.
1:01:48
And so, if it is um like founders who have companies that are creating a behavior you don't understand, somebody working on a research in an interesting direction, um businesses that like are like here is my plan for AI.
1:02:03
Um all of that is super educational.
1:02:06
I think the uh circular logic sometimes of like what do people believe about the big lab strategy today?
1:02:18
And it's like what what like, you know, how can any of the applications live?
1:02:22
It's actually not that instructive for your decision-making.
1:02:26
Um the way I think of it is any organization has a couple of key priorities.
1:02:34
Let's assume the priority for OpenAI and Anthropic and DeepMind is AGI, right?
1:02:36
Or ASI, um in a safe way where they capture a lot of profit.
1:02:43
Um uh the priorities that ladder into that probably look like ChatGPT ads coding, and then like maybe there's an expansion after that.
1:02:54
Um co-work, like the ability to, you know, get different types of users to uh do richer tasks in my interfaces.
1:03:05
Like um I think you have to judge the actual uh competitiveness of any of those efforts, the reasonable scope of them, and then look at them relative to each of our companies or opportunities that we're looking at, but like coming up with some grand strategic framework for like what layer is going to win here, I think it's like not useful to me.
1:03:27
And I feel like people spend so much of their investing energies thinking about that.
1:03:33
Um versus I want to spend my energy like figuring out like, okay, like if we're 1% of the way in, what is the next 99% of diffusion?
1:03:40
Um so, I like that's that's where we try to direct our energy.
1:03:49
>> For fun, as we wind down here, understanding this is like a purely speculative question and it's meant more fun than like raw prediction.
1:03:53
What are some things you think are true a year from now?
1:03:57
Based on all these incredible people that you're close with, the research community, the entrepreneurs like like the Sunday founders, you know, you add it all up. Things are moving fast.
1:04:07
A year is a long time and it's like reverse dog years now.
1:04:11
Um what do you think is notably different about the world of technology a year from now?
1:04:18
>> I'm hopeful that a year from now we see we see Jevons paradox in practice as we have agents and products that do more of the mundane more effectively in all the domains of our lives.
1:04:32
It should look like the transformation that has happened in software engineering, right?
1:04:38
Like you have companies, I have companies where they're like we are just going way faster.
1:04:42
And I expect that some analogy like that will happen. >> Everywhere else?
1:04:51
>> Everywhere else, right?
1:04:51
And we see it in our companies where I'm thinking about like um in one of our portfolio companies the marketing department is like a person and a half. >> Right.
1:05:07
>> This is a company that serves lots of customers and like they need to do very traditional things like sales enablement content, right?
1:05:13
And like what happened was the guy in charge of marketing is very interested in like creating leverage for himself.
1:05:22
And he's like, "I made I made an autonomous marketing department for us, the company.
1:05:27
And so I think in every function, as you learn faster, do less of the mundane, um you will repurpose that time somehow, right?
1:05:41
Do you work less now that you are more productive with the AI?
1:05:45
Yeah, I work more, right?
1:05:47
And I think this is like a core wisdom of Gen Z's, which is just like we're all we're all going to be more employed.
1:05:55
Um and we need to make sure that people are given access and education to the tooling that will allow that to happen.
1:06:02
>> Well, what you built is incredible.
1:06:02
Um we've loved through the Colossus side getting to know just like your whole world.
1:06:07
I think it's so distinctive.
1:06:07
I think you you are a great example of that there's always room for great.
1:06:14
Meaning there was plenty of early stage investment firms when you started Conviction, and yet here we are, 4 years later or whatever, and if you ask the people you've worked with, you've made a real huge difference in their lives.
1:06:25
Like there's just always room for great.
1:06:26
I think that's like a great awesome lesson, especially because I love how you described the early pitch was not like here's how we're differentiated every level of the funnel, just like we're just going to run at this thing.
1:06:35
>> By the end I got so frustrated I was just like, "It's an execution game. It really is." Like >> Yeah, totally.
1:06:41
Um I ask everyone the same traditional closing question.
1:06:43
What is the kindest thing that anyone's ever done for you? >> I love this question.
1:06:46
I'm going to give like a collective answer.
1:06:48
I think there are so many people who are um extraordinarily accomplished in Silicon Valley, um uh who care very little for pedigree.
1:07:01
Uh as soon as they have a conversation with you, and they're like, "Maybe you can help me or you have an interesting idea or like maybe I just think you're promising."
1:07:12
Um and uh like the the dominant factor in their own willingness to invest in a relationship or a person is just their assessment of the idea and the person. I think that's amazing.
1:07:24
That is not how most ecosystems work.
1:07:28
Um and so, you know, Asheem Chandna and Aneel Bhusri and Joseph Ansanelli and Reid Hoffman who hired me at Greylock, like I started when I was 23.
1:07:35
People love to make fun of like young VCs where they're like, "Ah, what a barnacle on the ecosystem?
1:07:41
Is it a terrible experience for entrepreneurs?
1:07:43
They don't know anything.
1:07:44
They're trying to advise people.
1:07:45
Who gave this kid money?"
1:07:45
And I'm like, "Well, one, my job was just to make other people successful at the time. Um and like learn."
1:07:55
And you can you can take any task in any job and just like try to be great at that task with mimicry and first principles thinking, right?
1:08:02
Um and so I, you know, we hire earlier career people at my firm.
1:08:06
But I do think like, "Oh my goodness, like, you know, thank you for taking a shot on some random person um and then investing the time to like teach me how to be an investor."
1:08:18
I think there were few people who gave me advice starting the firm who I think they would think of this is like entirely trivial.
1:08:30
They were like, "I'm just giving you my opinion."
1:08:31
But you know, um Ravi Gupta who's now CEO of a new thing called Ethica, like Dylan Field and Elena Nadolinski, um John Lilly who's been a long-time partner and friend.
1:08:43
There were few folks who were just like, "You can definitely do it, right?"
1:08:46
Um and I was going to do it either way, but like having the encouragement of people who believed that there was room to be great um and including our like some of our first uh LPs, like I I will be forever grateful to I guess the people who took risk with me.
1:09:05
>> It's beautiful the world runs on faith, belief without evidence yet.
1:09:09
And and still conviction in someone's ability to do something. Pretty cool.
1:09:13
>> Yeah, and I think it's it's faith in people, right?
1:09:14
We talked a lot about how, you know, people's ideas and um, you know, our opinions of them are intertwined.
1:09:21
But I think that's a like a beautiful thing, right?
1:09:23
Because you don't need any particular advantage to have an idea. >> Yeah.
1:09:28
>> Um, and so, like, you know, the fact that folks will evaluate that and put faith in us, like, I could not be more grateful.
1:09:36
>> I've learned a lot watching you operate and talking to you.
1:09:38
Uh, this has [music] been really fun. Thanks for having me. >> Thanks.
1:09:46
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