Most Venture Funds Are Playing Momentum Games | Michael Dempsey

 Join José as he hosts another episode of the Emerging Manager series on the Delphi Podcast, sitting down with Michael Dempsey, managing partner of Compound. Michael makes the case that most venture funds being raised today are playing momentum games that won't survive contact with a real cycle, and explains why Compound has become known as one of the slowest-deploying seed funds in the US. They dive into the fallacy of founder legibility, why paying up at seed doesn't improve outcomes, and how the firm's research edge decayed the moment anyone could drop an academic paper into ChatGPT. Michael shares Compound's portfolio construction math, the thesis behind their public markets fund and the coming decade of market cap destruction, where he's investing across bio, materials, and robotics, and why the humanoid narrative is far more fragile than the market believes. 

Timestamps
00:00 Intro
01:24 Why Momentum Investing Fails in Venture
05:05 Price, Legibility, and the Myth of the Obvious Founder
15:10 Research as Edge and the Problem With Obviousness
32:31 Portfolio Construction and Shots on Goal
39:04 Bio, Materials, and the Commoditization of Intelligence
43:44 Public Markets, Software Margins, and the Short Side
56:58 Meta, Google, and the Mag 7
1:06:45 Crypto, Robotics, and Drone Warfare
1:21:38 Therapy, Psychedelics, and Writing


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This podcast is strictly informational and educational and is not investment advice or a solicitation to buy or sell any tokens or securities or to make any financial decisions. Do not trade or invest in any project, tokens, or securities based upon this podcast episode. The host and members at Delphi Ventures may personally own tokens or art that are mentioned on the podcast. Our current show features paid sponsorships which may be featured at the start, middle, and/or the end of the episode. These sponsorships are for informational purposes only and are not a solicitation to use any product, service or token.

Transcript

SPEAKER_00 0:00

I don't I don't know if most I think that a a lot of venture funds uh are playing momentum games and I think momentum games are not durable. Uh and so simplistically I think like all risk asset classes are really bad relative to buying the index of, you know, the Nasdaq or S ⁇ P over the past decade and you need to be top decile and I think momentum is a hard place to be top decile in. And so yeah, I think like, you know, uh investing is really hard and it's looks easy in certain 36-month windows, and usually you find out it's hard in 48 plus months.

SPEAKER_01 0:38

Hello guys, and welcome to another episode of the Delphi Podcast, the Emerging Manager series. I'm your host, Jose, and today I'm thrilled to have with me Michael Dempsey, who's the managing partner of Compound, and probably the clearest example I know of research as an actual edge in venture. Michael is a pretty rare thing in venture, a truly thesis-driven, high-conviction original thinker who's obsessed with the with the craft of investing and kind of staying in his lane. He's he was early into runway and wave, which are some of the best seed investments of the last decade. And he also runs what he's called maybe the slowest deploying seed fund in the United States. He sat out most of 2021, 2022 while most people were spraying, which earned him a lot of trust with LPs. Michael, I've I've been reading your stuff for years. Really excited to have you on the pod and talk about some of this stuff.

SPEAKER_00 1:23

Thanks for having me. What an intro. Wow, love it.

SPEAKER_01 1:25

So I wanted to start with the thesis of this episode, which is you've you've written that most venture funds being raised today are going to end badly, and the people running them won't fight out until the tide goes out. So make the case for that.

SPEAKER_00 1:38

I don't I don't know if most I think that a lot of venture funds uh are playing momentum games, and I think momentum games are not durable. Uh and so simplistically, I think like all risk asset classes are really bad relative to buying the index of you know the Nasdaq or S ⁇ P over the past decade, and you need to be top decile, and I think momentum is a hard place to be top decile in. And so, yeah, I think like you know, the investing is really hard and it's looks easy in certain 36 month windows, and usually you find out it's hard in 48 plus months.

SPEAKER_01 2:16

Why why is momentum the wrong strategy in in venture, I guess? Because yeah, it's it's kind of like an age-old, I feel like it's an age-old debate in investing generally, just like you you could trace it back to like the SAROS reflexivity, right, versus the the Buffett like value thing. Um why is why doesn't momentum what could like why isn't momentum a good strategy in venture? And maybe define momentum as well, like how what you see it, how you see it.

SPEAKER_00 2:40

Yeah, I think I think um maybe defining it first, I think like momentum is doing something that you are doing because you know that there are um marginal buyers at at uh incremental price increases in the near term, not because you believe that long term it's durable. I think the complexity of the investors that you mentioned are largely ones who have dealt in public markets, not in uh private. And the complexity with momentum is that in public markets, when uh momentum starts to slow, there is still a bid, and that bid in most cases, obviously there can be pure, you know, uh crashes, but in most cases that bid will come down slowly. It might come down 10% in a given day, it might come down 15, it might come down 20. In venture, there's no liquidity, um, there's no scaled liquidity, and uh thus you and there's dilution, uh constant dilution, and preference stacks that emerge. And thus, like when the bid starts to soften, it doesn't soften 10 or 20%, it softens 100%. Um and so I think that that creates some complexity. Uh again, I think that momentum is different than um maybe the more invoked strategy at growth, which is buying the best assets and believing that they have more terminal value than the market does. We could call that like the Thrive strategy. That I think is a good strategy. That is a strategy that is inherently an economies of scale or assets of scale strategy and a um yeah, the ability to like write the big check type strategy. Uh, and that's a highly access constrained one. And that actually might be one of the most durable strategies in all of venture uh from the past five to ten years. Um so yeah, I don't know, that's that's a high level. Um but happy to talk through it more.

SPEAKER_01 4:23

I agree with that. So the difference is that in in momentum you don't you you you're sort of betting on future flows, whereas you know, if if you're just paying expensive prices for things that you think are the winners, you're just sort of doing um yeah, because because I think people use the term momentum to refer to both of those strategies to some extent. Right. And like there's there's there's also a strategy that's emerged, I guess, earlier stage at the seed and pre-seed, which is kind of like an access and winning strategy of just being in the best names and paying like a hundred million dollar seeds or or even you know more expensive than that in some cases, which you know t sometimes gets like looped into momentum. What what do you think of of that strategy? Because I think that's something you guys avoid as well.

SPEAKER_00 5:05

Uh yeah, I think that it's a fallacy to believe that the highest priced things are the best things at the early stage. Um I think that that's just quantitatively not true. I think that like again, the highest price assets, once they start to compound in a durable way, which again, like with AI, you can debate what is or is not durable, but that is that might be actually quite that's like a you are underwriting in a different form. Um I don't believe that the loss ratios of high-priced seed investments are meaningfully different than the loss ratios of low-priced seed investments. And if you were to look at a bunch of data around like where top uh decile exits come from, it actually is pretty evenly split across uh valuations at seed. Um basically the data shows that everything but the bottom quartile of valuations creates the same distribution of outcomes. And so I do believe that like you shouldn't be trying to go and you know be value investing at seed, but I actually don't think that that quality is correlated at all to terminal outcome uh within the like you know top 50% of price ranges at seed.

SPEAKER_01 6:13

Interesting. Because I guess the theory would be that the best founders um or the best companies in general are sort of priced, right? It's hard to find these like diamonds in the rough, or at least it's hard to make a whole fund of that. And I think we've seen some people be pretty successful with this kind of like polarized sort of strategy where you're you're going for the you're hunting in the backwaters for the for the founders at you know eight mil post or or or something like this, um, and you you're making a fund that's like half of those, and then maybe half of like the the flapping airplanes, you know, seed round, which is already, I think, 100 mil or something like this, and companies of that stature where the founders are clearly like incredible. Um what do you what do you think of that?

SPEAKER_00 6:52

Because I just don't like I think I just and again you we one can debate this, and I I think we'll see on the data. I just like don't believe that like the most legible founders are the best ones. Like I just don't fundamentally care if you're like an amazing 20-year-old person who went to Stanford. Like, I don't believe that your ability to build a multi-billion dollar company is 10x more or even you know 5x more likely than another really talented founder. And so I think actually what we're just doing is we're correlating like on-paper legibility, um, which then creates like some subset of minimum price, uh, and then like in meeting legibility, which creates a multiple on the minimum price, to quality. And I like if I were to look at our you know two largest uh companies today, like neither of those are founders that even today would be considered super legible in the runway team or the wave founder. And so um I yeah, I just like have seen enough, and even some of our more successful newer companies, I'd say that's the same. Uh and so yeah, I just don't um I just don't buy it. And I I think that the all of this, all of this is actually crescendoing at a time in which we all are saying the best, like the barrier to creation is falling because of AI, right? Everyone's like, well, I don't want to do software because the barrier to creation is falling. And so if we were to believe that we have a fundamental shift of the ability to create companies, technology, whatever it is, and the momentum viable level of intelligence is going up because we have these frontier models at our disposal, it feels very strange to me that the talent will actually narrow in where it comes from. And I don't know any other paradigm in which barrier to entry has come down and uh and like talent has not been higher dispersion.

SPEAKER_01 8:39

I I don't think uh I think the the Stanford thing is a bit of a straw man though, right? Like I don't think that's what the the the the people are saying the the really legible founders are necessarily. Uh I think that was sort of the thing for sure at some point, but maybe maybe now there's like this this more sophisticated, like hummingbird-inspired vision of of what a legible of what like a truly extraordinary talent is, which maybe is you know, the guy who came from some difficult upbringing and and like was a genius that did the math Olympiad, got a goal to the math Olympiad, and then like graduated from universities early and built accompl whatever all these like accomplishments that you can name off that that are that are what I would say like that that's I think what like legibility looks like right now versus the the the Stanford thing, right? Things that get really priced. Do you still think that's the case for for those that you can't predict or at least yeah?

SPEAKER_00 9:30

I don't think that they create meaningfully higher outcomes. Um you might be you might have like there are certain pools of talent. I don't think the ones you described are, but I do think there are certain pools of talent that do create um floors for for windows of time, right? We saw this uh during the rise of mobile, where if you were a very talented mobile engineer, you had a floor in your company because Facebook and other companies were acquiring mobile engineers like 10 million an engineer. We saw this in self-driving, where if you had a background in self-driving from one of five places, or if you participated in like the DARPA Grand Challenge, you were generally taken out at between five to fifteen million dollars per team member. Um, we see this now in AI, mostly this with like the Neolabs and some of these other areas. Um, whether or not the investors get hosed on that is still to be determined in some of these instances. I don't I think you then can go and you can look at a few other things, right? You can look at what's the success rate of second-time founders in building venture-backed businesses versus first-time founders. Data is like pretty much not no correlation. Um, you could look at uh um the math olympia thing is like an interesting pool of talent that is like clearly super high intellect, and maybe in certain high intellect problems these people are able to accumulate capital. There is some like self-fulfilling prophecy here, which is the next order question that people probably would want to understand is like, do you believe that king making is actually possible within venture capital or not? That is probably the question that matters most in the legibility conversation, because yeah, it doesn't matter if I believe this or not, if like being legible allows companies to have excess capital advantages, like Elon is the best example of that.

SPEAKER_01 11:04

Yeah, anecdotally, it does seem like this math mafia, whatever you know, the the Olympiad or um was it the it wasn't the Citadel like intern class, right, that has like the the hyperliquid founder and Alexander Wang and uh the cognition founders does seem like there's some anecdotally thing there, or is it something you just think is is sort of like overhyped right now and actually won't be a predictor?

SPEAKER_00 11:28

I think that like there are pockets of talent that sometimes birth really interesting people, and maybe that interesting people is three of eight hundred instead of one of eight hundred or something. I think orienting a strategy of building a firm around either that or trying to continually understand what that looks like at a like at a um cohort level feels very not durable to me. I think like the hummingbird thing is a little different, which is like they believe they have a different view on what what just like spiky people look like, which is actually far more horizontal than um maybe something that is like I hang out with 19-year-olds who are really smart and you know in a few pockets of places. And again, like networks do sometimes compound in interesting ways. There are moments in time where networks are really interesting and good. I think that these things uh to orient a strategy around like a certain type of network, you might be able to make money. It's not how I will make money. And I don't believe that like the legible side of it is what creates um like it's almost like a lagging indicator in some ways.

SPEAKER_01 12:44

So with your hummingbird comment, I guess you said earlier you said you don't buy that, right? That you can that you can build a fund around, but but maybe you don't is it that you don't buy that for you? But you you think it can be done? Okay, you don't buy that for you, but you think it can be done to sort of identify, have this horizontal skill of identifying, I guess not legible though, like by by definition, like it's legible to you, but not to anyone else. But there is a way to hone that skill of finding these these the these sort of talents.

SPEAKER_00 13:12

Yeah, for sure. I mean, I think like if you look if you talk to most of the people who have been at Hummingbird, left Hummingbird, are there like they all source in very unique ways. They all think about how they find talent in very unique ways. And whether like the percentage of that that comes from the machine versus comes from the fact that they recruit very well into the machine is like also uncertain. But like there is a commonality between how they think about sorting humans in the world that again, I think is not is not like them being like this cohort of people is interesting, but actually here are the flavors of people that we think will create possible asymmetry. And uh then the the other thing is like historically those people have been illegible and they have actually also been uh very low priced. Now that is not the case because they people are starting to try to orient more towards them, and also like there might be a bunch of other reasons why. Um but yeah, I think that like that's a strategy in the same way that like I think what Thrive does is like a very differentiated strategy, which is like they believe there are certain types of assets that are really great, and they believe that the outcomes of those assets are more much larger than a lot of other people believe, and that they will compound for much longer. And like that's the original lesson we learned with the Mag 7 companies for a decade plus, is like they compound at much larger scale for a longer period of time than most people ever thought. And it turns out, like, even post Mark Andreessen writing software is eating the world, and everyone thought, like, okay, we all understand this idea of scaled compounding more. There was like a whole other tier of that. Um, and even believing that is like a very interesting way in which you view the world and underwrite companies, underwrite skills, and like looking at category by category what you think the number one asset is and wanting to own it is like a very unique skill.

SPEAKER_01 15:00

Okay. So you're saying like that this is uh this is the way someone can make money, right? Just just being more bullish than everyone else, or just having this sort of people radar that's that's that's very well honed, uh, but it's not how you make money. And you you I think you're you're someone that I really respect for the way you kind of like stick to your uh or seem like very disciplined about sticking to your craft. And maybe you could tell me like how is it that you see like that compound makes money? Like where does your alpha come from?

SPEAKER_00 15:28

I think our view is uh in a similar way that some people have some beliefs about terminal outcomes. We have a belief that like we call what we do research-centric thesis-driven investing. We have a belief that we get very deep in understanding like the closest to the metal academic andor, you know, uh RD group research. We then say um what is possible or what is like inevitable. And um, maybe the last thing we'll say is uh uh we think that like having a prescriptive view on the world and where it will go and the first, second, and third order effects of how science and technology cascades through the world matters a lot. And for 10 years, everybody in venture has told me the same thing, which is like you cannot predict the future, you should not try to. That is not the job of an investor, you should let the founder show you the future. And our view is like we are best suited to partner with founders and understand investing in other areas like public markets, if we have very reasoned views, and that is only going to become more important as there's much more volatility and much more replacement rate of companies in shorter periods of time.

SPEAKER_01 16:40

How do you think because you wrote this post I really like called On Humanity and Human Beings, where you you you coined this world first thinking, right? The idea that the tech builds a beautiful model of the future and slots the human beings in last. Um, but the volatile thing in any model is the human beings, right? So isn't that exactly what you just described as your sort of investment philosophy in some sense? Like a world first.

SPEAKER_00 17:04

I think we uh actually have like a lot of debates around like this meritocratically or like technologically might make sense, but actually from a human perspective it won't. And like actually, I'd say one of the things where we often disagree with people in Silicon Valley or um even sometimes controlling the team is like the way people think technology will just like do like progress because that's the way it should, because like that's how technology wins, is actually just like removing the human side. It's like kind of like the you know Tyler Cowan view of like AI is not going to diffuse nearly as aggressively as all these 30% plus GDP people think, because like humans just like don't want it to and take a long time and are like slower, and then the SF people are like, it doesn't matter what humans want, like the AIs do it all. Um and so I would argue like we probably have much more of a bend uh uh towards like integrating like the the the both like the beauty and the like the uh complexity of humans in how we think about technology changes, which is also why like you can you can like think about this on like the early stage side, and then if you look at like public market side, like a lot of people have a very simplistic view of like, oh that thing's dead because software's dead. And it's like, well, actually that's not really how like these things work with humans making decisions and how we value ourselves.

SPEAKER_01 18:23

Yeah, I like that. And on the maybe maybe going back to momentum a little bit, or it's sort of an offshoot for momentum, like how how important do you think it is to be contrarian in in venture? Because I think you guys are pr pretty contrarian almost almost but by definition, right? In in some of the way. I know you don't like you don't like the word contrarian, um, but you you said um you said something like I think it was in in 2024 was the podcast where AI is at its maximally obvious point today. And anytime I see that, that typically means it's probably time for compound to observe and not deploy too much money, right? If if it was like if it was maximally obvious in 2004, it's definitely like sort of maybe 2x that now. Um and how do you think about like why is it that something being obvious by definition makes it uninvestable? You know, because you you like sort of the the investability is is sort of like a risk reward thing, right? So it's like the price you pay and how big this thing can be. You could conceivably think of something where they're like there isn't enough money in venture to like price in how big this thing is, right? I I don't know an example now, but maybe something that like extends life or makes you live forever, whatever it might be. So why is just the very fact that it's obvious sort of something that that makes you not want to invest?

SPEAKER_00 19:39

I'll say a bunch of disconnected things that maybe hopefully will form a picture. Uh one, venture is the lowest conviction asset class in finance. And so because of that, when things become obvious, um, similar to how like when capital you know disappears and that illiquidity drops something down to zero, um, things don't scale like linearly on price or on risk on like risk adjusted return. They scale like exponentially because everyone moves there because nobody, yeah, there's a lot of lack of consensus. Um two, I think like, what is it that compound believes we're good at? Um we think we're pretty good at like looking at N of 1 style things and saying, okay, this is possible that this could be really, really valuable. Um in times of maximum obviousness, two things happen. One, um, there's a lot of similar things that are built at the same time. So you have like a lot of competition of companies that all look identical. And like our job, like in theory, part of our job could be to pick the best one, but at the seed stage, it's just like not where we have edge or alpha. Like it's not what we're best at. And so I'm not gonna try to pretend it is. And then I think too, like, uh there is like model collapse during these times in tech. As tech has become much more uh concentrated in a bunch of ways and much more dogmatic around like what does and doesn't matter, um, you just see talent start to flow into a singular place. And so I I like, I know I ask people this all the time. Like, if you look in traditional AI, there are actually very few ideas that I've heard in the past three years where I'm like, wow, I never could have thought of that. Like I never would have imagined a company shape would look like this. Like AI for legal is like the I've people have been talking about for 30 years. Like every business looks quite similar. And so there is high model collapse, and like again, that doesn't allow us to operate in the best way. I think there are some people that can operate in these maximally obvious times. Um the last thing I would say is we operate on like 10 year time horizons, right? And so if something is like abundantly clear today and a bunch of procurement decisions are going to happen, you can do one of two things. You can say so much money is gonna flow into these companies, they're gonna go zero to 400 million. And like my job is just get the thing public as soon as possible so I can get out of this because dispersion will happen. Second or final movers will come afterwards in years five through ten, and like that's a real problem. Or you can say, like, I think that this is going to be the enduring business for the next 15 years. First mover advantage wins, or like maybe like you know, middle mover advantage in some of these AI things. Um I I don't know how to do that. That's like again, not not what I do, and not what I think our firm is best at. And like I think so much adventure is just understanding like what is your singular advantage and just pushing on that advantage over and over again, not like trying to make sure that you're like playing the game LPs kind of want you to play, but it's like slightly outside of your sphere of influence, but like it'll make LPs happy to know that you're doing that thing. And so I don't know, I think like we're just fine doing the things that we think we're good at. And um, we tell founders all the time like, make the decisions that if your company fails, you can sleep at night, um, having made, and we're the same. Like, make the decisions if we like lose all the money, we're like, we made the decisions we thought we should make.

SPEAKER_01 22:56

So I I guess when a sector becomes too obvious, the skills that are required to win, right? Which is I guess picking the best team in an obvious category are not the things that you're that you're best at.

SPEAKER_00 23:08

And that's sort of why you you you want to avoid that style of or it becomes like paying highest price, or it becomes floie grinding the company because you need to you have three companies that are all raising tons of money, like for legal is the best example. Like it can be it kind of like they all kind of like layer on each other, and it just all of them increasingly go against what we are best at, I think.

SPEAKER_01 23:29

Yeah. And how do you think about that? Like the discipline of staying uh sort of staying focused on what you're good at versus adapting and learning a new skill. Because that's something I've uh I feel like we came up at at Delphi investing in in crypto, and we really didn't invest outside of crypto for the first like six years of the of the firm or five years. And at some point I I sort of stopped uh I sort of got nerd snapped by I and I wanted to start investing outside outside of crypto, started learning about deep tech and stuff like that. And as I started investing, I realized like holy shit, I just really don't have a edge here. Like uh these these these kids are all like hungrier than me. They're willing to move to SF, to foire gras the founders, to go to the house parties, to to, you know, uh be in the pollicules, whatever whatever it might, whatever the edge might be. And I'm just like not uh, you know, I'm just not. And so there was some amount like the part of doing the the fund of funds for me was like learning from from really smart managers like you about how you do it and sort of also piggybacking on some of the on some of the picking. Um but but it has been like a lot of reinvention uh versus like sticking to what we were good at, which was which which was crypto, where we we kind of learned uh a lot of bad habits for for traditional investing. And I'm I'm curious, yeah, how do you think about that? Like have you consciously added new competencies that that you think are needed or or yeah?

SPEAKER_00 24:48

Yeah, I'm my default view is that all venture firms are constantly decaying, and so actually you have to fight back against the decay. And I think for us, like if you were to think about compound 1.0, which we'll call like 2016 to 2022, was predicated on this idea of like we could spend a bunch of time in academic research, understand it, and then figure out like what are these interesting teams that are building hard technology that people don't really want to underwrite yet at seed and go and do that. And just the understanding component was like pretty big edge. Now any person in the world can take an academic paper, put it in Chat GPT, and say, explain this to me like I'm 16. And so like that edge is gone. It's not like it hasn't decayed, it's largely gone. Um, there are certain things you can do around understanding how these papers compound upon each other, how you know what the differences are, um, the just understanding some networks, what principles of founders you've been able to apply to research organizations are that you learn. There was tacit knowledge that accumulates. But I think then a lot of the things that we talked about internally was okay, now that that edge is like clearly deteriorating and we felt it deteriorating, and now that more capital is coming in, um, what are the next order things we need to do? And it started to become a lot more of this thing of first, second, third order effects. Like how do these things continue to move over time? Like, how do we make sure that we don't just form a view of this technology is possible and if it works, it'll be bought or it'll be valuable? But instead, if it works and there's competition, and there's like who are the early customers, how does this compound? Uh, what other adjacent businesses could exist? Is this the best way to play this like version of the future we believe in or not? Um and so I think it it kind of has evolved to much more prescriptiveness and treating research as even more of a first-class citizen in the org than um, you know, kind of saying like we believe that creative AI is going to be a thing because we've read some of the early generative adversarial network papers in 2016. Like that's a pretty high-level thesis that is detailed relative to most, but not nearly as detailed as we would be today.

SPEAKER_01 26:52

And why can't AI do that, actually? Like the second and and third order thinking on on yeah.

SPEAKER_00 26:58

Uh I think because and we we do a lot to try to get AI to do this, and it's uh I think there's a few things. One, I have seen like nothing that shows me that AI is able to think outside of distribution. So you're you're like by definition, through an AI model, getting like the maximally obvious or maximally viable ideas, right? And we've even experimented with like can we embed a bunch of things um and then like hopefully the embedding space will flatten a bunch of ideas. Um and and that that should remove some of that maximal viability. Um I also think there is just some like like to the point of you're you're you're thinking through a lot of types of companies, types of buyers, types of people, like we just haven't seen AI able to do that. Maybe sometime they will. Um, but we've definitely tried and it hasn't quite yet. Uh and again, I think there will probably be some other new thing that we'll have to think about over the next few years in both sides of the markets. I think like an obvious one today is how do narratives impact multiples in like public companies, right? Like that's something that the models are horrible at understanding, and um, that's something we spend a lot of time thinking about. And uh I think the the other thing that is related to that on the private side is like how do narratives impact later stage flows and later stage investors and their level of confidence or conviction. Um, and that's why we spend a lot of time publishing our writing and our research.

SPEAKER_01 28:20

And and what do you think, like on this topic of of AI and and and the way it sort of um I guess commodifies certain certain skills, what do you think that does to to founders? I had an interesting chat with one of our managers, Abishek for grad capital. Like he he basically invests in like the smartest Indian kids from the IITs and stuff like this. And he was telling me that he thinks there's like one year left of like investing in nerds and and that like they these these like Olympiad and like hyper-technical nerds like skills are just being uh like entirely commodified by AI. And he and he's sort of trying to think of what the next like what he's gonna do next, like what's he gonna invest in in next? And I'm curious, like, how do you think about that in terms of founders, like archetypes?

SPEAKER_00 29:03

Yeah, I mean, I think it's never been that the smartest founders are the best ones. Like, I think you have had to be pretty smart, but like I'm sure there are people smarter than some of these best founders. Um, I would imagine that some of it starts to come down to um some of the stuff that you know I've I've written about recently around like how people how people feel about like working at an organization and thus the leader of that organization. Like, what do they morally stand for? What are their personality traits they believe in? What is the future that they believe in? How do they believe they want to impact the world? Um, I think that could come back into vogue in a in a much larger way. I do think there is like minimum viable intelligence that is being brought up because of the models, but I don't know, man. I'm I'm like so pro-human that like I think humans are so unmodelable that I think we have a while a while to run before we commoditize like humanity through AI models.

SPEAKER_01 29:56

It's it's just it like I don't know, one example is like the in the neo cloud space or whatever, there's there's like these together AI teams that are like super smart on the on the kernel optimization and all this like really complex stuff. Um and and like then there is the teams that they're more sort of aggressive, uh like like fluid stack, I don't know, like a bunch of like super aggressive guys moved to Texas and secured like allegedly like five to ten gigawatts. I don't know. I'm I'm not an investor. And and that's much more valuable now, right? Like the fact that you actually have like powered land is much more valuable than your algos because because that stuff is like very much optimizable by by AI, you know. So I don't know. I have this I think maybe I think it's always been important for for founders to be like charismatic and kind of like savages, like in the sense of being able to to really get shit done, get get deals done, and be hyper intense, but maybe it like overweights even more that way now. I don't know. Um in the sense that it seems like yeah, smart generalist that has like a lot of that charisma can can go a lot further than they could than they could before in a lot more different fields.

SPEAKER_00 31:02

Yeah, I think I think every again, we uh we have a belief that is somewhat uh um in conflict with some of the best investors, which is like we don't believe there's just like these things called great founders. We think there are great founders for certain types of businesses, and like each type of business has different things that necessit that is necessitated from the founders. And so, yeah, if you're working in a supply-constrained, long duration, like highly business development-oriented space, you for sure need to be more of a savage. If you're working on something that is um super heads down, like I think like attention and like commitment is gonna be something that is incredibly rare on a go-forward basis. And so maybe just the ability to like not get distracted doing random shit on the side is like the main thing people should be looking at for founders. Like that that might be the way this goes. And so I don't um I don't know, but I I do think that every every company type has some weird nuance to what the founder should be.

SPEAKER_01 32:02

I like that, and that kind of goes into your portfolio construction, right? To some extent. Like you've you told me once that you know you think you need like 30 seed bets to really catch like one or two good ones, right? Where there's a lot more uh or at least there's more of a meme now around like concentration, like doing these these big bets. Like I think, I think, you know, uh the Hummingbird and Fondomo and some of these funds have done really well with this this this strategy, and and and I think there there's some others too. Yeah, I'm curious how you is how you think about that.

SPEAKER_00 32:30

I think like our I I've told our LPs this, which is like our portfolio should feel riskier and riskier as time goes on. And if it doesn't, it probably means we're not doing our job well. And that that is twofold. One, it's it should be riskier to them because that means like like the world is changing quite quickly, and LPs are not exactly leading indicators for understanding where the world is going all the time. And so it should feel kind of crazy. Um, and if it doesn't, then like what are we doing here? And then two, I do think like because of that, and that's where we think asymmetry will come from, um, we need a certain number of uh yeah, shots on goal to do that. And I think if we look at our data and we look at the data for you know some firms that are like us, we would say like one out of every 12 times we make like a pretty good decision, and one out of every 20 times we make like an incredible decision. And I kind of just want to make sure as a firm we like have that framework in place because venture is so much about the inputs without having any understanding of the outputs for so long that if you really believe in the inputs that you've set up, you should feel really comfortable just continuing to do the thing. And I think what gets a lot of people tied up is they're like year five of their career or year six, and they're like wondering if they're good or not, and the inputs that like weren't really high conviction, they were just kind of doing the things they thought they were supposed to be doing. Maybe they changed a bunch of things of how they behaved, and so there's no consistency, and they don't quite have the output data yet, and that creates so much volatility. And as you know better than anyone, like you can't come to a high-risk game that is like played at very high stakes with like tons of fear and uncertainty internally. And so I think a way to remove that is one, you reduce noise, and two, you like have an input system that you like very deeply believe in, and you are basically saying, like, this is pseudo-religion with with some bands of understanding, like sometimes you know, you have sins around religion, but like generally you keep it within a band. And that's kind of like where we've settled. And I think um we've been a little bit more concentrated over the years, we've had a little fewer companies because we only get excited so often. Uh, but generally we know that like we're not gonna hit a we're not like certainly gonna hit a multi-billion dollar company out of 10. And um if it's the 11th investment and you're like dogmatic that you you want to be hyper-concentrated and do 10, you know, you're gonna be unemployed in five years instead.

SPEAKER_01 34:48

How do you think about the the heuristics with that? Because it whenever I hear you talk about investing, I'm always struck by you're very sort of uh analytical, and also you you you have a lot of data backing some of these decisions, like whether it's the type of founder or the portfolio companies or something like this, um, and even like how many investments you want to have per fund, and and there's a lot of like uh I think like data-backed heuristics. And I've yeah, I've historically really struggled with with heuristics. I'm kind of like undisciplined, and I I tend to well, it's it's kind of a weird type of lack of discipline, but it's like I I like to break the rules and to see, and I think heuristics are really useful to like keep you out of trouble, but sometimes like greatness comes from when like something doesn't fit into any of the heuristics. Maybe it's a very broad question, but like heuristics kind of like shape your view, right? Like if you if you even like in martial arts, the thing that I do, like if you approach uh a position with like knowing its name, you kind of like go in with a certain view, right? It's like the Wittgenstein like language games thing, like you just see what the language tells you. And if you sort of invert the language or you don't apply, or you try not to apply language, which is like almost impossible, but like you can you can see like different things, right? And I I'm I'm yeah, I don't know if there's anything there that you want to p pick on, but i uh I'm curious how you think about it.

SPEAKER_00 36:04

I think like it depends what your goal is, right? Like I think that our goal, like what our stated goal is to our investors, is to be like consistently great. And like how we define consistently great is we want to have consistent top decile funds and have the ability to have top five or one percent funds. Um and so far, we I think we're doing a good job at that. And I think that uh there are some people that are like, there are moments in time, and like my moment in time is I'm gonna go for it. And you talk to some LPs and they're like, look, if you 10x fun one and then you 2x fun two and 2x fun three, we're super pumped. Like over those three equal commitments, like that's that's a great return. And I'm kind of like, that's not the strategy I want to run. I want to be able to know what I can consistently do with the opportunity to be to be like very, very, very great. Um, and again, I think even that is like incredibly hard. And so that's kind of how we've oriented it, and that's why we have some of these heuristics that um yeah, it's kind of like the uh the idea of like choosing when to sell, right? Like, do you sell when you believe you're at the top, or do you sell on the way up? Or you know, in public markets, you talk to a bunch of people who are in super high growth um names, and their view is I sell once it falls 25% and I get invalidated. Uh and again, we've like looked at a bunch of that stuff, and like it's pretty interesting if you look at like on these hyper-reflexive names, if you actually sell at like all-time high like next 12 months uh revenue multiples versus like once it retraces 25%, how do you do? And like actually you do pretty well if you sell the all-time high of next 12 month sales multiples, not on the 25% drawdown. But um, you might miss like the leg three years later. I I don't know. And so um we like consistently making money, and like maybe that uh does mean that like we won't have that crazy volatility as much, but I also just think venture is like so uh random and like cyclical, and so much uh randomness built into even these moments that like as much as you can control, I think it actually gives you a lot more ability to um operate for like a dec multi-decade time horizon, which is kind of everything we do is kind of also oriented around like the mental state of how we invest.

SPEAKER_01 38:23

That's all great. That that makes a lot of sense, actually. I think I don't optimize enough around that, actually. Um yeah. Um yeah, I definitely want to get to public markets because I think it's gonna be super interesting chat. I'm also curious just what you're looking at, maybe before we move on to there, what because there's some areas that you think are just like hot, obvious, obviously AI is is is one of them. Um and you've always been really good at finding these obscure corners of the of the internet where interesting things are are are happening, both in crypto and outside of it. What what are the most interesting areas right now that you're looking at? I know you're doing a lot in bio, which a bunch of ice smart investors are are doing.

SPEAKER_00 39:02

Yeah, curious what what others you're yeah, I'd say bio is where we've invested the most heavily the past three years. Um if we look at our our second fund, which is deployed from 21 until uh through the end of this year, like it's a lot of bio, it's a little bit of AI, um, material science. Uh I think probably the thing I'm most excited about is is that material science side and like just being able to build more full stack businesses built around synthesizing novel materials and shipping an end product. Um, orbital materials is like the case study for that for us. That's one of our biggest investments in our second fund. Foundation model built around chemistry, uh, state of the art in in chemical synthesis, and like one of the things that they did is they have a material, but they shipped it as a full product, which is for cooling next generation GPUs. It's like a modular data center product. Um we think that is like a very interesting shape of business that there will be many others in. Um, we also are looking at like some of the more, I would say, like I would say consensus areas, but trying to understand if we assume this like next few years of build is very consensus in how they're done, like energy. Um uh that's like another kind of adjacent area that we've been spending more time in. Uh but I would I would bet that a lot of our investing still will sit within bio. And then like I think there's going to be a really interesting time to invest in AI in like 2028, 20 to 2030, once we see dust settling dynamics of like um maximally viable, incredibly cheap intelligence. And like the commoditization of everything but the fat furthest frontier intelligence should create a lot of like really interesting companies, and I would argue we probably will be well suited to invest there.

SPEAKER_01 40:41

What do you think of that commoditization um of AI? Because you said it, I actually found a tweet of yours in 2023, right? We routinely underestimate the commodities commoditization curve of AI. I feel like I was on this train too, and it's kind of surprised me how like uncommoditized it is in the sense of just like how good and how frontier intelligence has just managed to stay like ahead and for how long. Um yeah, do you think it will eventually like commoditize?

SPEAKER_00 41:11

I think that there is a subset of tasks that we have enough intelligence and current models that will become effectively free if not able to run locally in the next 24 to 36 months. And you might need to post-train them, you might need to like there might be some innovation or like maybe like operational execution has to happen to make those things truly production ready. But I think that is like undoubtedly going to be true. I think there are certain areas that will be incredibly economically valuable that will require frontier intelligence for the next, I don't know, five to ten years. Um, and there will be a small number of people that have the compute resources to do that. Uh the complexity I have is like in these types of market structures, you only need one player who is not economically motivated by the core monetization of the core thing to really drive the price down. And um everyone hates Google right now, but like I think like that's a pretty stupid thing to do. And so I think like Google sitting there with um the fact that like people value their debt as less risky than the US Treasuries is like one of the most interesting things in the world to me. And um that creates a lot of uncertainty. And so whether it's a commodity or not, I don't know. Um, but uh I think the dynamics of like of call it 90% of intelligence that exists in the world will undoubtedly hit some sort of multi-tiered, like oligobalistic commodity, which again you might have some settling price that is low enough, but um it's definitely not gonna be like a premium asset.

SPEAKER_01 42:38

Google seems to be to some extent betting on commoditization, right? By sort of leaning into cloud and and I mean maybe giving up on the model layer is too is is too like hyperbolic, just like Twitter stuff, but yeah. But maybe actually let's I'll let you respond to that, but then I wanna uh yeah, and then I want to move to Publix.

SPEAKER_00 42:56

Yeah, I mean I think I think Google is not giving up on the model layer. I think they ship some of the best performant, fast, and cheap models, and there's a I think they probably maybe are looking at this saying like they've definitely messed up, they definitely had a bunch of problems on the pre-training, post-training side, um, and talent was an issue. Um I think there's a lot of structural advantages, and um yeah, I'm I'm I'm quite bullish on on Google.

SPEAKER_01 43:19

Not financial advice. All right, let's let's let's move to publics on on this one because I think it's it's a good segue. Yeah, you have this, uh, and I'm sorry to keep quoting you back to you, but I love it and how how easy it is to do this with AI as well nowadays. It makes you look really smart. Um you said the things that the thing that destroys all venture funds and maybe people in venture is scope creep. Right. And if this is the case, why do a public markets fund or a liquid fund alongside your venture fund?

SPEAKER_00 43:45

I think this is like the fairest criticism that anyone can have of compound outside of uh the fact that like we might just be a really like overpaid research organization that never monetizes. Um so I think like those those two things are. Yeah, but you know, you never know. Um we have a lot of things that we see in the early stages of technology that we for a long time had no way to action um at all. And I think uh if you care about over time building highly durable businesses in the private markets, you actually have to understand the entire flow and stage of all of technology companies, especially because in tech, the most innovative companies are the largest ones. Um interesting enough, in bio, the largest ones are not necessarily the most innovative, though. Lily, I think, is starting to change that. And I think as we spent more time and as we managed an internal portfolio, uh, we just started to see that like be like meaningfully true, and we started to say like the things that we need to understand are directly monetizable, and it makes us a better investor in both ways. Um, understanding what Tempest is doing on the diagnostic side allows us to understand what uh other earlier stage companies are doing as well and like should be doing, should not be doing, how they can monetize the customers they can go after, etc. Um and there's a million examples across the board of that in our portfolio. And so um we have like no desire to scale to be you know full stack private fund. We don't think that um venture, we think like the only performance-oriented asset classes in technology investing is early stage venture and public markets at this point, and like that's where we like to compete. And so if we believe we have like meaningful edge that we think makes us better in both ways, uh we we're like really excited to to try and continue to push that hypothesis.

SPEAKER_01 45:37

And how how do you what's the thesis? Is it is it sort of yeah, what's the thesis for the for the public's fund and how do you run it?

SPEAKER_00 45:45

Is it it's a long short, and maybe how many positions just yeah, um the thesis is uh thesis-driven research-centric investing creates an understanding of businesses that um either are uh going to accelerate or decelerate earnings in a way that is poorly understood by the rest of the market. Um and that allows us to be long and short. Uh, it allows us to have uh a lot of time preference. The vehicle's not like an annual, it's a closed-end vehicle, so all the money is locked up for many years. Um and uh yeah, I think we we run relatively concentrated on the long side and on the short side, um far more uh smaller positions and a little more breadth than depth.

SPEAKER_01 46:31

And on the on the long side, I'm curious, like what are you what are you most excited about right now, if you can talk about it?

SPEAKER_00 46:37

Yeah, um I uh a lot of the same themes that we've talked about around bio, around um maybe like next order uh energy things, um, and then also candidly some like simplistic views around where we think technology is overly um hated because of AI. Um so it it it Okay, uh yeah, it looks it looks like uh a mix of like things that one would believe are um very obvious for us to own, some things that aren't. And then there's also some like really random super small cap stuff because our funds uh able to traffic in a lot of different types of um assets that are international and maybe you know sub $300 million market cap even.

SPEAKER_01 47:24

And and so are are you are you like able to buy things like I mean I'm I'm sure you are, but like Mag 7 or like a Google or an Nvidia or yeah, things like this, or does it have to be yeah?

SPEAKER_00 47:35

No, yeah, we can we can buy basically anything we want in the fund. Um, but uh we like our our goal is to have similar IRR to our venture funds, and so um however one you know can can do that is is up to them. But um most of the stuff we own uh is not like the standard Mag 7 for for right now. I don't you know things could change.

SPEAKER_01 47:58

Okay. Interesting. And are there like um are there specific names you said in software? I guess that's like become really hated um area. What what do you look for to make a software business? Yeah, I mean, people thought all SaaS was dead, right? This was the narrative on Twitter at the beginning of this year, and now software is at a great a great year. And from from there, um what do you look for in the in the software businesses that that win? Is it as simple as like API agent usage, basically?

SPEAKER_00 48:28

I think there's some stuff which is like, yeah, can can they actually see like uh can they transition into this usage-based model that allows them to expand revenue and probably have margin compression in the short term, but margin expansion in the long term if they're thoughtful about it. Um that's interesting to us, and I actually think that creates dislocations because the market can look at margin compression in the short term and say, I hate this on a quarter by quarter basis. And we can look at it and say, like, actually, this this shows that like inference into the like inference is picking up within the organization. Um, I think you have to understand management within the organization like spending as in their own spending on inference? No, within the sorry, within like the customers that that pay the organization. Yeah. Um and that reduces margins. Why? Because usually you're you're passing like you're going if you're running a traditional software business in some of the areas, like you're looking looking at a traditional business that might run at like 80 to 90 percent gross margin. And if you're running like passing through AI inference that you have to you know pay Claude or you have to pay insert API, you might run at like 50 to 60. Um and so if you look at like blended, um, as as those things start to come closer, you're gonna see margin compression. But then you look at like other things, which is like um the Pinterest CEO, um, right? I'm sure you saw this. Like Pinterest CEO last quarter during earnings talked about how they've been using a bunch of first party models and like they now have fine-tunes of open source models, they've been very dogmatic about this, people have generally hated this. Um, Pinterest has performed not great. And he says like they they ran a uh like cost comparison in their costs versus using the frontier APIs as 8% of the cost. And like that's pretty incredible, especially because now they're starting to see some of the um like ROI on the AI usage. Um and so again, like you can imagine a world kind of to the prior point of if AI continues to make its way through, it continues to fall in cost, but have performance increases, um, you could see reacceleration of margin expansion. Um, I think maybe related to that, like you have to understand management and their ability to actually understand what's going on in the AI world. Uh, I think if you're like totally blind to it, or if you have some of these CEOs that are like, this whole thing's a sham, it doesn't actually work, it doesn't actually matter, like we probably wouldn't want to invest with that management team. Um there are some businesses that that might violate that. Um and then there are also certain things that uh we believe like again we'll see meaningful like mid-term uh acceleration of of revenue, and we're basically looking for like short-term dislocations to like layer into those. Um and again, our our time horizon is like five years in the public side. So it's uh we have time.

SPEAKER_01 51:03

That's really cool. And in in bio, what what are the most interesting things happening in in public markets? It's been a great year for for for bio. I think people are starting to wake up to it. Um yeah, curious what what you what you like there, what you think is most interesting.

SPEAKER_00 51:17

I think there's a subset of companies that are um sitting on data assets that are like meaningfully undervalued and will be able to monetize their data assets far sooner and at far larger scale than any analyst covering those stocks appreciates. Um I also think there's also just a long tail of companies that nobody covers because they're small and um have been left for dead that are like also could become quite valuable. Um and so a lot of it looks a lot of the stuff we own looks either like things playing into a re-acceleration of or and things we will own, I think, will will be things that play into a re-acceleration of experimentation and biomanufacturing, and then certain platforms, and then uh certain data asset type businesses. Um we don't we don't do like single asset like trading on clinical trial releases. Like that's not something that we have any edge in.

SPEAKER_01 52:11

And on the short side, you said uh the next decade is about market cap destruction, which was ominous. Um I'm curious what you what you mean by it and and yeah, how how you're playing the short side.

SPEAKER_00 52:23

I think that there are as markets become more narrative driven, the companies that accumulate the uh a lot of short-term flows are those that s can sell very great narratives, and those companies often are deep tech businesses. Um historically they are deep tech businesses that went public via SFACs, but now they are all sorts of different types of deep tech businesses. Um these companies we meet when they're fundraising, and we've met them, you know, years prior, and now they're public, and like we had a view that they weren't good investments then, and we have a view they're not good investments now. Um others are just so grossly over overvalued that um we believe there's like a near-term catalyst that will show uh that these businesses are not nearly as strong or nearly as high growth as they're projecting. Um and there's others that are just like existentially we don't we don't think that they will exist in insert time horizon of two to four years. Um for shorting, our view is you always need to have a clear understanding of what the catalyst is. Um you always want to be able to express the short in multiple ways. You never want to like layer on factors that are like uh too highly correlated if you're gonna short a bunch of different things around a singular theme. Um but I think there is an like an infinite opportunity of companies, especially now that like flows and these types of things jump so quickly. Um that like the the first sign of invalidation again doesn't send the thing down five or ten percent. It can send it down like 40 to 60 percent in four to six weeks. Um, and so that uh those are the things that we often traffic in more.

SPEAKER_01 54:01

And how do you think about the conviction side in in public markets? Because I think in private markets I heard you say something like, if you believe in it and it hasn't worked yet, you should keep trying for like five to ten years, which I think does work in in private markets, uh assuming you have you have the time, you know, your LPs give you the time to do that. In in public markets, how do you think about like invalidation of the of the thesis and you know when you'll sort of buy back cover a short, when you'll sell a long?

SPEAKER_00 54:27

Uh we have like really tight risk controls on short side. So like typically if we're pretty wrong on a short, it it just gets closed out. Um like we don't yeah, we're we don't try to be heroes shorting things over and over again. Um and and and we also have small maximum position size on any individual short. On the long side, I do think there are like a lot of the things that we do when we write memos on on the long side public positions is understand like what are the quantitative and qualitative things that would invalidate. And like if for whatever reason the price is invalidated but none of the thesis is, like what where would we like what what would we have to see to cut or what would we have to see to double the position? And so like we have like those kind of bands set up going into any um position. Um again, I do think that like we we think about sizing not as like, hey, we're gonna equally size 12 positions and you know the same amount. We do have varying degrees based off of where we think like there's reflexivity, where there is downside risk. Um there's certain things that like we feel we are pretty certain we want to own in the near term, but we think there actually might be a short-term reason why it could go down 10, 20 percent. In that case, like you could probably try to play this with options, but also you might just say, hey, um, this is like my fully sized position, and maybe I'll layer into it. Uh uh, I do think that like you cannot you cannot underestimate the fact though that like some companies just will never catch a bid in markets even if they continue to execute. And like the you have to understand like of the four quadrants of you know businesses that look cheap but you know actually are expensive, businesses that look expensive and actually are cheap, and then you know the other two, like where where you think the thing is and where it actually is. Um Smack is gonna actually publish something on this pretty soon that's that's quite interesting that we've thought a lot about.

SPEAKER_01 56:14

Then maybe on the big names, I remember when I met with you, you were you were you were pretty excited about Meta. Um and I'm curious how you think they've done and where where you where you where you see them here. Because I've been uh I've also been a meta bull, I've held it for a long time. Um I've been surprised like with how bad their execution has been on the AI side, like on the on the on the model side. I would have expected uh a lot more. Yeah, I'm I'm also surprised by stuff like just WhatsApp just not being like monetized in any way, like just like a send money feature on on WhatsApp seems like it would be like so great. Uh it feels like leading into stable coins, like now would finally be the time for them to do that. It just seems like there's a lot of surface area that's that's being underutilized. But um, yeah, I'm curious how you how you see Meta.

SPEAKER_00 56:59

Um, yeah, not not financial advice, all the things. Um I um I think Meta is uh the company that is probably best positioned to monetize AI regardless of if they build on the frontier or not. And I think we continually see that. Um they also have been pretty pretty ahead and maybe slightly less aggressive now on the compute side, and so if they want to spin up that side of the business, that's like a pretty interesting possible growth trajectory for them. I never really had strong views that they would be pushing the frontier on AI, if I'm being honest. I just think that they can monetize it at with so much ease on so much surface area that every time the market uh gets annoyed that Zuckerberg has this, like, I'll just burn the whole thing down and until I'm you know, until I don't, um uh the company struggles. And I personally think that like people really continually underrate uh just how like deeply embedded their products are. There's an open question that like maybe they're this is the last turn for them, but um I don't know. I think even like how they've like how Reels has gone in the past 18 months has been pretty good. So like I I just don't I don't feel the existential dread of like if you're not pushing the frontier models, you're a dead-on arrival company as a Mag 7 business.

SPEAKER_01 58:19

And how do you feel about the Mag 7 generally? Like I I'm I'm curious, are there names that you're uh Google? It sounds like you're also pretty pretty bullish on. Is that just sort of GCP and and TPUs and like just owning the stack that again the half surface area to monetize or just so much structur, so much structural advantage, yeah.

SPEAKER_00 58:35

Like uh GCP has just been an incredible, like even the Gemini Flash series, I think, is like a pretty incredible set of models. I know that the that everyone's waiting for you know Gemini Pro 4 and all these other things, and then they shelved 3.5 and all the talent's lost and all that stuff, but like they just have a lot of structural advantages that I think will continue to um just continue to compound for like a really, really long time. Um I don't like I admittedly like some of these other uh companies I don't like have strong views on. Like those are the two that I actually have strong views on, and then Apple I think is also incredibly well positioned, and you know, people have noticed that over the past 16 months. Um I think it's very possible that the same thing we saw of like longing tech beta for whatever the past decade like might continue in some form. I think the replacement and the destruction that I talk about is actually a tier below in scale. Um yeah, and so uh and and again I like some of the more hyper hyped things I like in NVIDIA or um or like the memory stuff, like I I I'm just less high conviction in either way, and so I just kind of stay away from that. Same with the neo clouds? Uh there's some that I really like and there's some that I hate, actually. Yeah. I think the next generation of neo clouds, uh like these these set of companies, um, is gonna show that like uh there is actual like motes of competence and execution that like will really matter over the next five years. And I think that you will see dispersion in those um both by their ability to execute and maybe to your point their ability to uh build the right relationships with the right people who want to finance them, backstop them, work with them, and then maybe how much each of them opts to verticalize over time.

SPEAKER_01 1:00:31

Yeah, that's been my biggest uh sorry, that's been my biggest uh sector that I think I think they're like sort of very misunderstood still. Although that yeah, I'm I'll be curious to ask you, maybe off air, which ones you're you you hate and which ones you like um to to compare notes. And and on markets generally, like there's this, you know, Barry's Michael Barry is pretty is short and bearish as he as he likes as he tends to be. Um there's a lot of like Ray Dalio and and Jeremy Grantham are doing the same thing they do, and they're they're pretty bearish. Um like there's the signs of a bubble, you know, brewing or whatever. My my view has been that there will be a bubble, but it'll be like much higher than here, and I don't I don't see like that much cause for concern with like forward earnings and stuff like this. I'm curious where where you sit with that.

SPEAKER_00 1:01:20

Um I think I'm probably in the like um maybe like the rolling bubbles theory, which is like there are going to be perpetual rolling bubbles um and there it's just gonna be like a lot of volatility. I think like there is no strong semblance of what a like 2028 earnings will actually look like for most of these businesses, and like how how like does earnings per share actually look as good as everyone thinks on a go-forward basis? Do margins really change? Like, like I think there's so much uncertainty that there will just be continual whiplash. I mean, like, um, I don't know, you you see it with the neo clouds, right? Like, and you can say that that's you know, started by Leopold and situational awareness and was it value aligned and some of these other funds that were like super levered on the same factor and over and over again, and everyone's like, yeah, they got blown up and liquidated, and then everyone went long again. But I also think it's just like it's a collapse of confidence, and like the collapse of confidence, confidence is kind of what we talked about before, which is like when do you sell? I sell when it draws down 20%. And if everyone has a view that you sell when it draws down 20%, like it's not gonna draw down 20%, it's gonna draw down a lot more, and like uh core weave went to 79 and now is back over 100, and like like Palo Alto drew down 40 plus percent on a random Mythos announcement and now is back towards all-time highs. Like these things just are happening so fast that I think we just will continually see, yeah, rolling ups and downs, and I don't have I'm not a good enough like macroeconomist to move the other side.

SPEAKER_01 1:02:56

Yeah, Corey went to like 60, I think, at some point. At least I I I I saw it at 60 at some point. Yeah. Um and and in terms of indexes, like, do you still think because I've I have this uh view, I guess, that like I think you can kind of see the cross correlation among the constituents of the indices. Is it like all-time lows, right? There's like if it feels like it's once it's a stock pickers market again, or like the long, short hedge funds, I think will be able to do really well. Um do you think, yeah. How do you think about that? Like if you're uh maybe I'm you for for for selfishly, like I'm I'm trying to um like I have a liquid book that is like my part-time job, and I've been stock picking with it. Um and like I did well in the first year, and now I'm like underperforming the the index as as one is you know as one would expect. But I I'm I I'm also like very hesitant to index because I'm I I have a very specific view on AI that I feel like it's it's more consensus now, but not not that consensus. Um and so yeah, I'm curious how you how you how how you'd think about it.

SPEAKER_00 1:03:59

I mean my I don't know, my selfish belief is like I think active management has been hated for like a decade now and it's it should come back. Um but also yeah, like sitting and not having to think about literally anything and owning the Nasdaq like pretty nice. Yeah, I do think that there is um I in 2024 I tweeted this out. Um in 2024 I made this like basket, I called it the AI obvious basket, and it was basically like 30 names, pretty equal weighted. And it was like if you were incredibly obvious around AI, and it's like had some ASML, had some micron, it had some of the hyperscalers, Alibaba, like a bunch of these things. Um and like that thing has just murdered every like it is just so drastically outperformed, and I literally haven't changed it in two years. Um, and so there are times where I'm like, can you just structurally understand the theme? Uh, and should you be able to build these like longer baskets around the theme that you think will uh uh but like be a high beta to the market? Um and it's tough, yeah. It's really tough. But I don't know, we we look at it a lot in uh in terms of like within a given basket, how are we outperforming with the specific names? And um I do think that like Citrini is kind of like the middle of this, right? It builds these like massive indexes of themes, and maybe that's like the future um for a lot of investors, and that's the that's the future of active management.

SPEAKER_01 1:05:24

It does feel like that actually. Um I met a guy the other day who's building a company. I don't know if I can share his name right now, but he's a very good investor, like very good track record in liquids, and that is his view that sort of um AI like collapses the cost of asset management generally. Like you need way less analysts, you need way less of this of the scale, like the the sort of fidelity, you know, having a bunch of PMs and then a bunch of analysts under them, like you don't need that anymore. You can like extend your taste uh pretty costlessly if you're like an experienced investor, and so that the the end game for that is just like a bunch of indices uh that different people construct that you can sort of like uh investment. invest in and and that's kind of like what he's building uh index of like what he views as the 20 best companies in the world or whatever but with very low you know management fee which I thought was super interesting.

SPEAKER_00 1:06:09

I mean ARC has been the the greatest accumulator of capital basically in this thesis. They've also lost more money than anyone in human history but like I think that like that's basically what ARC was, right? It's like doing that with the yeah I don't so hopefully AI is better than them. I don't know. I got I got nothing.

SPEAKER_01 1:06:27

And speaking of that what what are you what do you um what do you think of crypto? Speaking of destroying uh the most money in in in human history um how do you feel about crypto? I remember when you first uh talked about your liquid fund I think it was going to be most of of what you did. Is is that I I imagine that's not the case now.

SPEAKER_00 1:06:44

Maybe maybe it is we still do we still do long short crypto in the fund. Okay. I think we are how would I describe it? We are still bullish on a small subset of of uh projects that will be able to ascribe fees to the tokens and we think will compound um and have similar dynamics to what we've seen in technology which is like you will have far more power law looking things in crypto over time um from a like an application layer or however you call it non non-money basically um I think that we still on the venture side don't have a flow of talent that is uh like aggressively coming but I don't know my hope my hope is that will change and I do think that the things that underpin crypto still matter and like the ideas of like accumulating and organizing long-term capital for uh call it like strange andor non obviously large ideas I think is actually quite interesting. Um so I don't know that's kind of like uh where we are and I'm still yeah still a Bitcoin bull and still think there's a bunch of interesting stuff that we will own in the fund over time.

SPEAKER_01 1:08:03

So you're bullish like the hyperliquids and lighters and and like uh things like this that are that are generating fees maybe like ether phys or I think there's some stuff that generates fees some stuff that we think will uh like will generate fees that's much smaller.

SPEAKER_00 1:08:17

Like our uh yeah like our purview is it can be really venture looking even in this it just has to be a liquid asset um uh but it's largely yeah call it d5 d pin um some DSI and then uh yeah um maybe a few other protocols that are built on top of these L1s.

SPEAKER_01 1:08:39

It's just so tough with the with the generating fees back to the token because raising a a token round for anything is just like much harder than raising an equity round these days I feel like it's like it's like reversed right it used to be if you slap a token on it you get like a 3x premium now it's like it's like half or less. And and so why do people and and and then launching a token is such a ball ache you know with with token holders yelling at you and and all the shenanigans that that that come with that I guess why do uh why do you think that category sort of persists in the and there's things like Metalex that we incubated and others that are trying to like give more like equity like characteristics to to tokens and even like redeemability to equity I think which is like super interesting. But yeah what what do you think like makes that cat category persist?

SPEAKER_00 1:09:24

I think that like on a long-term time horizon public equities and crypto tokens look like the exact same asset. Yeah like and I I don't know in the same way that I think like private companies should go public and allow their stock to be traded and report to shareholders and have responsibility to more than a small subset of price makers and buyers like I think that's good for the world and is actually better for the companies. And it allows you to access capital in more interesting ways. And I get it.

SPEAKER_01 1:10:00

Yeah I don't know yeah I'm a fan of of uh hair doll my my I actually found them other than I I briefly was paranoid that I was losing my hair and went down the the the rabbit hole of that um and found them they're they're like just like insanely crack team to like how silly it looks from the outside ratio. It's it's it's yeah I love when you find that there's crypto's like the industry where you find that the most it's like one of the things I I love about crypto just like so good at uh like no one is better than crypto people at making fun of crypto people. Yeah like uh you know which you can't which like AI is like the opposite they're just like the most they take themselves the most seriously out of out of out of anyone.

SPEAKER_00 1:10:38

It's true. It's very true. I think that like again even to this point of like we are bringing up the the the bottom or like the floor of intelligence and floor of sophistication like that is actually should be significantly value more valuable for crypto I actually think than any other area because it allows people who maybe don't have the traditional communities education whatever it is to go build like durable companies with the help of like frontier intelligence alongside of them versus like a discord of DGens who are yelling at them. And I think that like that that also is quite interesting again long term. I think right now we still have a lot of weirdness in regulatory and just low statusness in the industry that's um hurts.

SPEAKER_01 1:11:28

On thematics you said like robotics was your your biggest miss. Tell me about that.

SPEAKER_00 1:11:32

I think it's I think we well I don't know if the big it's it's biggest miss we've invested in. Like I definitely I my biggest thing I was just wrong about was VR like I love VR and it just like never came from yeah like I still play VR golf with one friend and I love it and it's like amazing but it didn't work. I play Population one yeah I'm I'm a fan. Yeah and like that was great. I think on the robotic side um I think we we made some investments in 2016, 1718 expecting the AI like the deep learning models to be good at uh on policy learning and be more generalizable and that was a in my mind incorrect and wrong thesis. I think we were just a little early we were early both in terms of how the customers think about integrating robots around humans most importantly and then two just on like actual performance scaling um I think we made some investments that uh were mechanical engineering oriented that were good. Hyphen is an example of that they they're focused in the food space um uh there was a company that was enabling like uh agriculture robots and agriculture um farms called Spark AI that John Deere acquired that was a decent outcome but I think we kind of like just missed timed the market and um I think the thing that changed that was frustrating and and is frustrating with how we invest is that you uh at times things go from like totally dead to super super hot and that happened in robotics and so a lot of the relationships we built over many years ended up being some of the most important people in robotics and um that was awesome to see but then when they left they started companies and they raised it like $500 million seed rounds and so that's just like you know we couldn't invest it's a bummer. Um now I think we've seen uh enough and we are continuing to invest in the space because we think that like this time is really different and everything we're seeing on the performance side would suggest so both for vertically specific robots and more generalizable um models but uh yeah you know we were probably 10 I mean by definition eight to ten years too early.

SPEAKER_01 1:13:46

And on on the general models you you said that like the Kang sat in that chair right Andrew Kang of Robo Strategy who I know you have strong strong uh strong thoughts on yeah and he said that humanoids are like a zero to to decatrillion opportunity which which I think I've heard you call insane. Why why is he wrong?

SPEAKER_00 1:14:04

I look I don't know if humanoids like on 50 year time horizon like sure there will be a humanoid company that makes a lot of money I don't know um I think that like humanoids I think make sense in areas in which the thing that you are replacing and that is being paid for is not the cost of the labor is the cost of the human life. And that would thus suggest the thing where you deploy humanoids should be either military or industrial. Military you are paying for a cost of a life lost there's a lot of money that you could put on that price. Industrial a life destroyed in some form due to physical labor. Problem with industrial is it is the heavily most heavily penetrated area for robotics in the world. And so I guess like um I think there will be a very large robotics company that is built. We have an investment in a robotics frontier lab that we're super excited by. It is a very weird approach and you know we think they're gonna be great. I think that the way people talk about these things should be slightly more measured. And I think uh he in particular is running a playbook that we've seen many times uh time and time again um especially if your incentive is to draw people to buy your basket of companies.

SPEAKER_01 1:15:23

And and so what what areas are you most bullish on in in in robotics? Like is it there because you said you said specialized robots and some general platforms what are the general platforms that you're that you're excited about?

SPEAKER_00 1:15:35

Yeah so um like we back to uh as of stealth ish lab now um that is is building kind of like a new learning approach for training generalized models um they're fully vertically integrated with hardware as well um our main thesis there was like can you scale your internal data faster than anyone and can you train models super sample efficiently um and look in a very low cost way um they believe they can and we believe they can I think there's a ton of really interesting vertical specific robot companies to be built um we're investors in a company called Alquist that focuses on a few different like for deployed enterprise use cases one being retail but actually others in like the data center space and the semiconductor space and they basically have built a platform that that has like many different skill sets um not fully generalizable not fully able to like do anything but um the main difference is is like the thing can operate around humans in an unstructured environment it has never seen before and do a bunch of different tasks um and built around that there's also a bunch of software that um both like helps the company in the immediate as well as in the longer term with analysis for certain things. And I think there's a bunch of areas like that. Like I think that hospitals will have a bunch of vertical specific robots. Like I don't think that's going to be humans. I think that the cost curves of these things are coming down meaningfully that you can build like awesome robots that can move, manipulate solve a small subset of tasks and you can probably build them for sub 5k and like that cost will only go down as compute goes down. And they will enable humans to do different jobs and they will just give leverage to humans right like that's like the the biggest thing in the in the short term. Yeah so I again I think that there's I think we will probably make multiple robotics companies over investments over the next five years. But other than that um yeah we just haven't made as many yet. Dovetailing on the military side what are your thoughts on on drones and like the the drone defense space generally I think there's like some actually really amazing public companies that are um yeah could be like really really large that are not today. And I think that my simplistic understanding of the space um is that there's a lot of budget to be allocated there. We looked at drone defense yeah we looked at drone defense a lot we we don't I think it's probably helpful if you can detect and you know catch and disin uh disengage them but we don't have a strong view there. We don't have any investments there.

SPEAKER_01 1:18:24

Yeah drones seem like one of the most um sort of I mean it it is kind of obvious I I don't think just people are talking enough about it. Like how how crazy it is like what's happening in Ukraine for instance, you know where like the the the ways they're able to strike sort of like 3,000 kilometers deep into Russia and strike refineries and cause like tens of billions of dollars of damage at like a few orders of magnitude you know cost um magnitudes and it it does seem like the world hasn't really like grucked like what this means for just like warfare. Like the the the fact that like the front line in the Ukraine there's just like barely any humans there right it's just like UGVs and and drones and and and a bunch of pilots and engineers. Yeah it it just seems like it's not fully priced in. You know you have like the three trillion or whatever annual military budgets and I know like by by my estimates it's like one percent is is drones right now. It seems like that should rise to to a lot more than that and and that's like a tailwind for the entire industry.

SPEAKER_00 1:19:26

It feels like I actually this is a like super stupid thing to say but I actually think it's because there's not a lot of prior art around futures where of military drones. I think there's tons of prior art of like humanoid robots fighting in battlefields and there's a bunch of like drone delivery art. Like that is something that has existed in the lexicon of society for a long time. Sci-fi people don't write about like one-way drone strikes very often and like so much of these things actually I I really do think are like art imitates life which imitates art and like I I actually think like that's just not in the lexicon.

SPEAKER_01 1:20:00

That's really that's a really interesting take yeah I've been that that's sort of the area I'm probably most excited about in terms of a sector um that that I found to have like because it it does feel like it could have sort of like a super cycle type of thing you know where it's just like the this rising tide it's lifting all boats. There and it it is very hard to figure out like how it how it like um what the winning strategy is because it feels like these companies kind of have to solve three problems at once like the autonomy the fleet software stuff and then like mass manufacturing and you know there's people I think focusing on on on each one of them people trying to go for all three of them and there's like a bunch of risks of like local maxima and and stuff like this that's like hard to it's hard to predict but it it does seem to me like the market is also it's one of these where like the market's much bigger than people think like I I I imagine tankers eventually will have like either drones or anti-drone stuff and like you know some a bunch of private people will have it. Yeah I don't know I it it's it it's it's surprising to me how for how little people talk about it actually. There's only so many things people can be excited about at once. It's true. And there's a lot of interesting companies out of Ukraine too I don't know if you've spoken to any of the any of the companies like this iron cluster.

SPEAKER_00 1:21:10

I've heard of this company I have not spoken I I don't okay yeah I I I haven't um I there's this guy who wrote this 300 page essay thing on basically like the front lines of using drones in Ukraine for the past whatever number of years and it's he mentions a bunch of different companies of which like half of them I've heard of um I'll send it to you it's pretty interesting.

SPEAKER_01 1:21:29

Awesome last few uh questions on on more personal note um we we have to touch on introspection right this was like all the rage in in tech a while ago yeah uh you you strike me as someone who's who's done a good amount of work on on on themselves uh you've talked openly about like therapy and psychedelic journeys um and in general like a certain sort of seeking which which I definitely identify with I've done the the the therapy and the and the psychedelic journeys too over the last few years. And I'm curious how uh has it made you like a better, happier person, first of all because I think there's a lot of there's a lot of people that are a lot of the hate is like oh you're just gonna be neurotic and obsessed with yourself and and and like it doesn't lead anywhere. And then has it made you a better investor?

SPEAKER_00 1:22:11

It's definitely made me a better person. I think like yeah I think I'm I'm a person who definitely feels the feelings um and then sometimes you need to like uh figure out how do you like explain the feelings to those around you which is you know equally as important and um uh and understand like what are the the feelings to continue to feel and not. So I think it's definitely made me a better person. And um I think so much of these things is about like um how do you just like continue to understand the edges of your life experiences and like touch the things that might push up against those edges. And sometimes I and I wrote about this like sometimes it's psychedelics right you do a mushroom trip or something and you touch the edge of that experience and it's like a very interesting moment. Other times it's just like seeing how people move through life, right? Like you know, I I was close to someone who was incredibly environmentally aware to a what to a point that like I never had seen before. And like just seeing someone move through the world that way is like a very it might not fully change all of your behaviors, but it like helps you understand that there's like a plane of existence that people operate on that is different than yours and just knowing it exists is like very helpful. And I think it keeps you as like a well-rounded person that to the point on maybe investing like I think it allows you to understand this like humanity part of like what are like how do human how will humans actually progress and like what are the complexities of humans that can manifest themselves versus like the maximally autist um highly like structured obviously intellectual way in which humans will move through the world um so yeah I I think it's I think it's maybe a better investor. I also think like um it's maybe a better like firm builder like I think that I'm uh as a as a person you know when when I started um you know helping build compound I was 25 years old and like I think I was like like many 25 year old guys like I was so like intellectually oriented and like not emotionally oriented in the same way. And I think that um building like a team and building a firm that hopefully everyone else on the team continues to like own the firm and helps build the firm with you requires you to also be like incredibly emotionally aware. And it makes you like a better board member makes you a better like partner to founders and so um yeah I think it's important. And I think it's like a lifelong craft. I don't think it's like a snap the fingers do the thing and you're done.

SPEAKER_01 1:24:35

And it hasn't taken your your hung has it taken your hunger in some way because I think this is what like Mark Andrewson was kind of like uh hinting at right that there's a risk that this thing just like one shots you and takes your hunger and you go live in a in a yurt or whatever.

SPEAKER_00 1:24:48

Yeah uh no certainly not um I I I also like I'm I'm yeah I'm uh uh I think if anything you need to operate from a place of calmness but like calm obsessiveness or calmness with a like a long-term obsessiveness and I think otherwise you're like burn yourself out and that's where really bad investing mistakes happen.

SPEAKER_01 1:25:13

And I I'm curious you keep circling like this uh moral thread as well in some of your writings like that we should be more morally motivated than we are right now uh and you you asked your friends you know why why aren't we doing more um like and then you had this recent post as well on how tech underinvests in in legitimacy and and like the philanthropy the differences between the philanthropy of the East Coast and the West Coast are also found pretty interesting. What what do you and you and you also did your Reverie grants which I guess is like maybe related to this what do what do you think we we should be doing more of like and how how do you think about that in your life?

SPEAKER_00 1:25:45

I mean I think there's like I think that we and a bunch of friends and other people are in like uh immense places of privilege where we get to spend a lot of time thinking about the world. We get to spend a lot of time talking to people who are have immense influence on the world and um uh we have a front row seat to benefit from some of that change. Um and I think that like over the past few years everyone many people in my life have felt similar things of like man like this is so broken and wrong and I but like ah and then it stops and I'm like well okay but maybe we can we can like try to like we're all relatively smart people with some bandwidth and resources and whatever like if anyone can do it you know someone someone like us should um and so I think like everyone has their own battles they want to fight and I actually think that um mostly it's just like we shouldn't lose sight of the fact that like none of this matters if we're not able to like I don't know live lives that are meaningful for both our loved ones and the extended people we're around and I think it's very easy to convince ourselves that like we will do that thing later or after. And I think at some point over the past few years I just started to feel like I don't want myself or my friends or my loved ones to like have this view of well when we're like 50 and 60 is when we'll think about taking care of the world. And right now we're like executing. Like I just don't think those things should be in direct conflict um in the same way that like you know when you're younger you uh think about at least I thought about my career as like well I just need to like I just need to get to this point and then I can like you know relax. And um I think that like actually it's much healthier to just view life as an infinite game and try and figure out what are the things that you are are most morally attuned to and passionate about. And I have felt that technology as an industry has become more insular and more of like actually like fuck everybody else but us. Like that's like what that's most important because they just don't get it or they hate us for some reason or you know they're overly negative. And like that's not where change happens.

SPEAKER_01 1:27:59

Yeah. I think it's been like uh an interesting moment for for l at least some people in tech where you've kind of seen this these like tech heroes uh just just like pandering in like an insane uh in a way that you would you would you would sort of not have expected. Um and and I also think like at least I'm starting to see strands of this in people's thought where like I think a lot of us were were like very capitalist, you know, growing up in venture and the great man theory of adventure and the Elons and the Ayn Rands and all that stuff. And I think like the the sort of acceleration and and seeing some of the stuff Trump's done is is in some sense like um challenging that for for for some of us, I would say, and making you think like, you know, maybe there maybe like economic efficiency like isn't the only, you know, isn't the only like objective and and it and not a justification in itself. Um and I've definitely seen a bit that bit of that with with with you, but yeah.

SPEAKER_00 1:28:53

It's yeah, it's a it's a strange time and it's um uh it's a very highly emotionally uh conflicting thing to to feel. Um and uh yeah, I don't think there's a right answer, but I think everyone should just give it more brain space.

SPEAKER_01 1:29:07

Last one. Um on writing, like uh you you you write a lot about about a lot of stuff, not just tech. Um and you you had this line I really liked about how precision, like I really identified with that, like the pursuit of precision in writing and really trying to like describe things clearly, pull these thoughts out of your head in like a very structured way and like put them out into the world. Um, and you said that you can spend hours finding the exact right word and never once risk being seen a perfect sentence that despite having all the right words actually reveals nothing. Um, like maybe for me, uh, I I really struggle with writing about stuff that isn't in that precision mode of like, you know, trying to map something out and and understand something and make myself understood. Like whenever I I try and write in another way, I sort of feel pretentious and and and have to and I get like icky and have to and have to stop. Do you have any any advice for how to like you know write in a more yeah, how to have this relationship with writing that you seem to have that's like yeah, super cool.

SPEAKER_00 1:30:02

You should default feel like everything you read from your past self is embarrassing in some way. And if it's not, then it probably means you're not like progressing enough. And if you have that first order view of your writing, it really relaxes a lot of the constraints around like what will everyone think um and what will I think of myself. Um and I just think like at a much simpler level, like the people around all of us just want to know what's going on in our heads more. Like, all they want is like, and you like I'm sure in your friendships, your relationships, your whatever everything, like people are just like they just are like looking to get like a little more resolution always, because like the the translation from here to here is like so low resolution, and you can do therapy to make it better, you can read a lot and you can talk a lot, and you can there's all sorts of things you can try, but like sometimes the things that bounce around in your head can only come out on like a page because there's no one there to like stare at you and react to it. And I also think that is like um something that's like in just an infinite life experience for me. Um, that I think also can be a crutch, to be clear. I think that there are some people that like can write incredibly well and then speak with no emotion. Um, and I think that's a different, a different problem. But for sure, yeah. I don't know.

SPEAKER_01 1:31:22

That's that's that's the best best advice I've got. And so I I I want to end it here. Um, because it's been it's been it's been awesome and I've we've already gone gone on a long time. Last one, has it ever been like a problem for you? Like the the overly because because sometimes you can like overly try and verbalize, or like you're living something and you're immediately thinking about how to write about it. Um, you know, you're sort of narracing in your own head in some sense.

SPEAKER_00 1:31:45

Yeah, I think that that can be a problem. Um I think that historically in my life, though I have not uh as a younger person, I did not do as good a job putting things out, uh, like putting things so that the people that I cared most about uh had as much resolution as I thought they did. And so um I do think that there is some balance of like understanding when to be in the moment and like let the moment sit versus yeah, thinking that every single thought that spills through your head should be written and verbalized.

SPEAKER_01 1:32:17

Um I again, lifelong pursuits. Awesome, man. Thank you so much for the time. This was a great chat. And uh yeah, anything you want people to know before before we end it?

SPEAKER_00 1:32:27

Uh Twitter, M H D M C a lot of chaos on there. Um come, uh enjoy it. Uh yeah, thank you.

SPEAKER_01 1:32:33

Thank you, man.