Ejaaz: Okay, we have an incredibly special episode for you guys today.
Ejaaz: You're about to hear from one of the most well-researched strategic investors
Ejaaz: in frontier technologies.
Ejaaz: If you don't believe me, these guys raised $1 million, just one,
Ejaaz: back in early 2019 for their first fund and turned that into over 10 figures
Ejaaz: in value in a year and a half. You want to know what's even crazier?
Ejaaz: The original $1 million that they raised was on credit card debt and loans.
Ejaaz: So we know that these guys go all in when they have conviction in something.
Ejaaz: What I'm really excited about is over the last two years, they've been dialing
Ejaaz: in to all the stuff going on in AI, and I'm really excited to get into their
Ejaaz: heads about what trends they think are exciting and what they're excited about investing in.
Ejaaz: Anil, Jan, Jose, it's great to have you guys on. How are you guys doing today?
Anil: Yeah, thanks for having us. Amazing intro.
Jose: Yeah, I appreciate that.
Ejaaz: Great to be here. Let's go. Okay, so from a lot of our listeners that tune into
Ejaaz: the show, they've probably never heard of you guys.
Ejaaz: And so maybe you guys can spend a few minutes painting a picture of who you
Ejaaz: are. And now maybe you can kick us off.
Anil: Yeah, for sure. So yeah, we're all co-founders of Delphi. The Delphi that everyone
Anil: knows of today has like three main companies, right?
Anil: Delphi Research, Delphi Ventures, Delphi Labs.
Anil: Jan heads up the ventures, he's managing partner there. Jose heads up labs,
Anil: and I mostly focus on research and ventures.
Anil: Essentially, what Delphi does is we're very research focused,
Anil: right? We started back in 2018 with research embedded in our DNA.
Anil: Jan and I and a couple of our other co-founders all met at our first job out
Anil: of college at Bloomberg.
Anil: We did a lot of like TradFi there with research and did leverage finance at Deutsche Bank.
Anil: Essentially, it fell down the crypto rabbit hole when we realized that maybe
Anil: the future that TradFi promised wasn't all that great.
Anil: And yeah, just kind of like fell in love with kind of the promise that crypto provided.
Anil: We put our jobs in 2018, started Delphi as a research firm. And like,
Anil: you know, first few years, basically, no one really paid us for research because
Anil: like there weren't that many fundamental investors in the space.
Anil: You know, shout out like Multicorin and Hash. They were kind of like our first
Anil: two, you know, real paying customers.
Anil: But where we really bootshopped was actually helping design and kind of consulting
Anil: a lot of these protocols.
Anil: A lot of what you saw in DeFi and work with like protocols like Aave,
Anil: Lido very early on. And then especially with gaming as well,
Anil: with, you know, projects like Axie and Yield Guild.
Anil: Over the years, Delphi has kind of morphed into this like, you know,
Anil: three kind of like pronged layer where we build, we research and we invest.
Anil: Right. And I think these three different perspectives work really well together
Anil: because it lets us have, you know, as many like different hands on the elephant as possible.
Anil: So we can really feel what crypto is and where it's going and,
Anil: you know, have a really good pulse of it.
Ejaaz: It sounds like Delphi was extremely focused on the Web3 crypto world,
Ejaaz: right? And that's been your bread and butter since you guys have been incepted.
Ejaaz: And then over the last two years, you've been like dialing in very much on AI. I'm curious, like,
Ejaaz: like, what kind of like parallels run between the two technologies?
Ejaaz: Like, do you just see the AI stuff happening and thought like,
Ejaaz: huh, I just want to kind of like peek over the fence?
Ejaaz: And then did you get kind of like more involved in that? Like,
Ejaaz: what made you more interested?
Anil: Yeah, definitely. I'd say that like, you know, when we first fell down the crypto
Anil: rabbit hole, it was almost it wasn't even just obvious to us.
Anil: It was just like, you know, what else could we work on or spend our time doing
Anil: other than this, right? It felt like nothing else mattered.
Anil: And I think over the past two years, you know, shout out Tom,
Anil: one of our other venture partners and co-founders.
Anil: He really was early to the AI trend and everything like that.
Anil: And a lot of people within the hive mind that dealt by got nerds signed by AI
Anil: and it felt we had that same feeling
Anil: where it was like, how can we not be infatuated and obsessed with this?
Anil: And yeah, I think there are a bunch of parallels. I mean, obviously the speed
Anil: of innovation, just like when we entered crypto, just like today,
Anil: even with a team of almost 100, right?
Anil: We have around 88 people across three companies at Delphi.
Anil: There's just no way we can kind of, you know, keep up with every single thing happening in crypto.
Anil: I think that's the same thing that we see in AI and why we think,
Anil: you know, we'll get into this later, why we think it's really important to have
Anil: a team focused on it and kind of like separate the signal from the noise.
Yan: Yeah. No, in terms of parallels, I think just when you see something that,
Yan: looks so glaringly obvious in terms of, you know, its growth and application,
Yan: but at the same time, there isn't really any widespread adoption of it or it's
Yan: still, you know, orders of magnitude away from what it'll eventually be.
Yan: Your eyes tend to light up because you start to think about all the possibilities
Yan: on the growth building and investing side.
Yan: And so I think what we saw that with crypto, you tend to see here with AI.
Yan: And then there definitely overlaps the two in terms of implementation and where
Yan: they can be synergistic.
Yan: But I think, you know, holistically, you tend to, I think that positioning is
Yan: really what gets you excited at first, because, and you know,
Yan: for and all the reasons you're bullish on it are,
Yan: you know, fundamental reasons, and then kind of put that against a backdrop
Yan: of the fact that it's still barely permeated, and there's still very minimal adoption of it is.
Yan: And I think that position is what really excited us about it in the first place.
Ejaaz: Well, I think what something that's really interesting is your focus on kind
Ejaaz: of crypto and web three for the initial fund.
Ejaaz: Crypto is an incredibly fast changing technology, right?
Ejaaz: And the whole point around it is it's meant to rebuild a ton of different sectors,
Ejaaz: finance, media, you know, you name it.
Ejaaz: AI is exactly that as well. So I'm not, I can't say I'm exactly surprised that
Ejaaz: you guys are marrying both technologies together.
Ejaaz: You're doing a ton of stuff in this space. So you just mentioned a few arms,
Ejaaz: Anil, You're doing the research side, the investing side, and also the incubating side.
Ejaaz: I saw that you guys are incubating a bunch of AI companies.
Ejaaz: Maybe you guys can speak more to that. Jose, maybe I can pass this to you.
Jose: Yeah, very similar to these guys. I had my crypto-pilled moment in 2017 with
Jose: Ethereum and pretty much had the same experience last year, actually,
Jose: a bit later than I think some of the other people at Delphi when I read situational awareness.
Jose: I'd been playing with MidJourney, obviously, and ChatGPT, but I was just so
Jose: busy and kind out of deep into crypto that, that, uh,
Jose: I think I didn't realize just how momentous this thing was.
Jose: And then, yeah, last year, once I read Situational Awareness,
Jose: it really clicked into place.
Jose: And we pretty soon decided with labs that we had to start doing some stuff in AI.
Jose: So we put together our thesis on crypto AI, spent a lot of time on that,
Jose: just figuring out where the good places for overlap was, and then ended up partnering up with Nir.
Jose: Ilya is obviously an OG in AI. He's one of the original authors of Transformers paper.
Jose: And yeah we we partnered with them to run our
Jose: first accelerator in ai which was really really great
Jose: had some insanely uh strong founders that applied just through ilia's network
Jose: um and then did a second one uh about finished about two months ago with with
Jose: the cyber fund guys which was also awesome um yeah we always think that the
Jose: best way to i mean like anil said the the old
Jose: elephant groping metaphor that Anil likes.
Jose: We like having a lot of hands on the elephant.
Jose: And I think researching is awesome and we're all kind of researchers in, is it our core?
Jose: But building, you get a really unique perspective. And that happened for us in crypto too.
Jose: Like there was things we learned by building protocols and being really deeply
Jose: involved that we really couldn't have learned any other way.
Jose: And it's been the same exact thing with AI. So it's just been really interesting.
Jose: And also it's similar to crypto. It's an entirely new paradigm.
Jose: Like crypto building is like very different
Jose: from web2 building like you have this these smart contracts they're
Jose: immutable well uh they used to be anyway nowadays protocols
Jose: take a slightly different approach but still a lot of them are immutable and so
Jose: it ends up being more like hardware like you have to be really careful
Jose: you have to spend a lot of time researching um and then
Jose: writing like uh it's less of an iterative approach
Jose: and more of uh you know once this is out there it's it's out
Jose: there for anyone to exploit and ai is like a different paradigm still
Jose: where these things unlike like most
Jose: of software before it aren't deterministic they're
Jose: probabilistic and so it's really hard to ensure
Jose: like a uniform user experience and like they're not even standards for like
Jose: unit tests or anything like that um i really think the the metaphor of it being
Jose: a new kind of computer is great so it's just been really useful diving in and
Jose: and learning um like with our hands in the yeah with just just just getting stuck in and building so
Ejaaz: There's a lot going on in AI right now, new frontier models are being released
Ejaaz: like every week at this point.
Ejaaz: Billions of dollars are being spent to train these things. There are numerous
Ejaaz: consumer applications that are out there.
Ejaaz: And I can't help but think that this is like an incredibly expensive game to play.
Ejaaz: So I'm kind of curious, what's your unique edge when it comes to investing in AI?
Ejaaz: How do you view the market right now? And where do you think you guys can make
Ejaaz: the biggest impact with what you're doing?
Ejaaz: You obviously have the whole Web3 crypto background, and maybe it's something
Ejaaz: to do along with those kind of principles of investing that you had with that fund.
Ejaaz: But I'm curious whether there's anything new you guys are seeing in the market right now.
Jose: I don't think we have an edge right now. I think we're sort of
Jose: hoping to build our edge over time. We've definitely made a lot of investments
Jose: in crypto AI. I think we have edge there.
Jose: We've made a couple of investments in AI, but I think we all sort of recognize
Jose: that we're sort of paying tuition right now and getting to know the industry,
Jose: getting to know as many founders as possible and kind of building our edge over time.
Jose: That's the goal of intelligence really. Same as when we started in crypto,
Jose: you guys didn't want to start a fund straight away, wanted to kind of build
Jose: your edge, build your knowledge, and then go for that.
Jose: And I think it's similar here, except now we have some capital behind us.
Jose: So it makes sense to invest and start building that.
Jose: So yeah, the hope is that we build the brand with Delphi Intelligence,
Jose: get some really tough researchers on.
Jose: And then we're also doing a couple of other things. Like we've been investing
Jose: in young fund managers in AI, sort of looking to, like when we started Delphi
Jose: Ventures seven years ago, it was really hard to raise.
Jose: And we know firsthand both how hard it is to be a first-time fund manager raising
Jose: and also how much edge you can have as a first-time manager.
Jose: And so we're kind of looking to find those people that were in the same position
Jose: we were in seven years ago in AI and back them and then kind of benefit from
Jose: that deal flow and that learning.
Jose: And I think the way we're thinking about it internally is we would like to aim
Jose: to have edge and to really start accelerating our investment pace.
Jose: 12 to 24 months from now, something like that. So yeah, this whole thing is
Jose: sort of us aiming to build that edge.
Anil: I think like even when we first got started and we were writing reports,
Anil: you know, if we put out a report on say, synthetics or something like that,
Anil: people would always message us afterwards and say, damn, you guys really knew
Anil: synthetics really well.
Anil: That's why the report came out. So, you know, great or anything like that.
Anil: It's quite the opposite, right? Like we learn about, you know,
Anil: whatever we're researching when we're putting together of this report that we
Anil: know is going to get like, you know, picked apart on places like crypto Twitter
Anil: or by the team or by competitors. Right.
Anil: So that's why we really do love having research embedded into our DNA,
Anil: because like it almost provides like this check and kind of this like,
Anil: you know, high bar that anything we publish, we know is going to be looked at
Anil: by, you know, people either building the space or other investors in the space, et cetera.
Anil: So we want to make sure that the research is not just really good for us to
Anil: use and build conviction, but also meets this bar where it won't get ripped apart.
Anil: And that kind of fear or intimidation, I think, is really powerful.
Jose: Yeah.
Yan: If I had to pick an edge, just to give you some answer to that question,
Yan: I'd say it comes from a few areas.
Yan: One, just from investing for however many years we've been doing it,
Yan: and granted, that's an edge that's kind of consistent across anyone who's been
Yan: doing it, So it's not necessarily a big one.
Yan: I think we do have a decent variety of backgrounds and ways of thinking as well.
Yan: And that's been an edge for us in crypto and should continue to be one here.
Yan: And I think just being able to operate as a group is a big edge where we're
Yan: able to take a variety of learnings that each of us are doing,
Yan: bring them to the table and get kind of immediate feedback and have just a variety
Yan: of points of view. I think that that's probably one of the bigger ones.
Yan: And then patience, I think is another one that we've kind of learned over time
Yan: in crypto in particular.
Yan: And so here we realize we don't really have an edge and we're trying to understand
Yan: is where the best opportunity is, right?
Yan: Is it early stage or does early stage really take too long to get a proper payback?
Yan: Is it makes sense to kind of invest in some of these growth-stage higher value or higher.
Yan: Valuation but lower risk type plays where you have a pretty kind of cemented
Yan: path to becoming a large company. And so that's still something we're exploring.
Yan: I don't think we have really have an answer there yet, but I think it's just the patience.
Yan: And I think what's helped with crypto is that you go through so many cycles so quickly.
Yan: And I think you can draw parallels to kind of other online experiences versus
Yan: physical ones. So if you think about like,
Yan: online poker guys have have seen an insane amount of hands right and so they
Yan: have a lot more experience than someone who plays live despite you know having
Yan: a long-term career so i think you know there is some benefit uh in terms of
Yan: taking that from crypto and understanding those cycles and trying to uh draw parallels there.
Jose: Yeah i think we all agree i definitely
Jose: agree with jan i think being a venture investor is like a skill that's sort
Jose: of generalizable across sectors like a lot of it dating founders
Jose: understand it but you you kind of need to understand the sector to be
Jose: able to properly do diligence the founder and not get bamboozled
Jose: by a high by a charismatic um you know sort of charlatan i guess um and so i
Jose: think what we all agree with is that uh we all agree that this is going to be
Jose: i think the biggest bubble that that like humanity has ever seen i think just
Jose: like all the ingredients are there isn't it like already
Ejaaz: A bubble this this was being said like last year and it's just been up only
Ejaaz: i think what nvidia crossed like four trillion in market cap this week.
Ejaaz: I feel like how big do you think this boat was going to go?
Ejaaz: Because I agree with you, charismatic founders are super important,
Ejaaz: but I see a bunch of these VC investors talk about theses for decades,
Ejaaz: right? The next 30 years is going to look like this.
Ejaaz: AGI, we're going to achieve it in whatever, 2027, or they're arguing about that.
Ejaaz: How important is the founder when it comes to all of these kinds of things?
Ejaaz: I'm guessing quite a lot. Yeah.
Jose: To me, we have different I think focuses even as investors.
Jose: To me, the founder is the most important thing, especially at the stage that
Jose: we invest in, which is normally seed or pre-seed.
Jose: The idea is going to change a lot.
Jose: And you're really betting on
Jose: a founder and you want someone that is just exceptional and has a history.
Jose: And exceptional people leave breadcrumbs. You can sort of look at their past
Jose: and be able to see some evidence of exceptional behavior before.
Jose: And ideally, you're looking for the things that are like, he was insane at a
Jose: video game or something in their youth, some sporting thing,
Jose: those things are generally better because they're not as priced in as someone
Jose: having done a successful startup and exited it or whatever.
Jose: And you're really looking for these kind of freaks, basically,
Jose: that are insanely motivated, that are able to...
Jose: Go through walls to achieve what they want. And so that pattern of like,
Jose: we've seen a few with ventures over the years, and those have been our big winners.
Jose: And we're just looking for more kind of an AI.
Jose: And then on the bubble comment, I don't think so.
Jose: I mean, I think when you look at where, I look at 2000 as my mainly,
Jose: like, maybe the biggest comp, like the price to earnings ratios of the Mag7
Jose: equivalent, we're still like, you know, two to three EX what they are now.
Jose: And then And I think in the private markets, there's definitely a few bubbly
Jose: things, but there's also like insane growth and fundamentals,
Jose: you know, like CatcherPT is the fastest company ever to a hundred billion in
Jose: revenue, to a billion in revenue, to 10 billion in revenue.
Jose: Cursor, I think was the fastest actually company ever to half a billion in revenue.
Jose: And you're seeing multiples of these, right? With DAUs, like actual revenue.
Jose: I do think there's some bubbly behavior and some stuff that's kind of reminiscent
Jose: of 2000 with these valuations, but I do think there's just a long way to go
Jose: just because, first of all,
Jose: you have the most profitable companies in the history of the world that are
Jose: stuck in this game-theoretic arms race where they're incentivized to spend every
Jose: single dollar of free cash flow into training better AI models because otherwise
Jose: they might miss AGI and have their company destroyed.
Jose: And that's a dynamic that's just going to be a constant tailwind to making these models better.
Jose: And every startup in the ecosystem benefits from better models. So there's that.
Jose: And then I think there's just the fact that this stuff, like the internet was
Jose: kind of like, people got really excited in 2000, but there was all this infrastructure
Jose: that still needed to be built for the killer apps that people imagined in 2000 to work, right?
Jose: You needed people to have mobile phones to build Uber. You needed payment rails.
Jose: You needed like GPS working. You needed all these different enabling technologies.
Jose: And with AI, it really feels like you don't. like everyone
Jose: has a smartphone everyone has a has a computer fast
Jose: internet like um it there's nothing
Jose: in the way of this thing just scaling like
Jose: it's really limited just by the quality of applications uh for people to use
Jose: and there's so much talent going into it there's so much compute going in there's
Jose: so much like spending uh happening that i just think it's it's gonna stay extremely
Jose: uh it's gonna keep moving extremely fast uh yeah so i don't think this is the bubble the bubble yet.
Yan: Yeah. And on the bubble point, I think you can kind of think of it in multiple phases, right?
Yan: So right now you have this kind of scenario where the markets are.
Yan: Really giving credit for just capex. So, so margins are coming down on some
Yan: of these bigger players and, and it doesn't matter because they need to spend
Yan: and, and spend and spend and just get to this point where, um.
Yan: The, like the next kind of wave is proving out that the spend is actually valuable.
Yan: And I think you're, you're starting to see elements of that,
Yan: but the, the market is kind of very forgiving right now.
Yan: And, and so, um, you, you know, for the first time in a while you have this
Yan: technology that can improve efficiency by an order of magnitude.
Yan: And it just gets captured in so many ways, right?
Yan: You'll have the big guys who leverage their distribution to just improve margins
Yan: because they need to reduce headcount or just become more efficient.
Yan: On the startup side, you have these smaller teams that can get to unicorn status
Yan: without really needing these longer term cash raises.
Yan: And so I think the fact that it's kind of happening across multiple areas is
Yan: what'll give it legs for quite some time.
Yan: But yeah, in the interim, you have basically this massive spend phase and that
Yan: doesn't seem like it's going to be slowing down anytime soon once we're starting
Yan: to see that there are actual improvements to be made to the base models, right?
Yan: There was that concern up front where, okay, it was actually kind of solved.
Yan: And then when there were these big breakthroughs, then everyone,
Yan: you know, the CapEx got turned back on again.
Yan: And so it doesn't seem like that's really going to slow down anytime soon.
Yan: But at the same time, you're having real efficiency gains at the early stage.
Yan: And so, yeah, I think that the trickiest part is probably the very late stage
Yan: investing side in the world where they don't necessarily need to bring on that capital.
Anil: Yeah. The one thing I'd add here too is like, Bubble has this very like negative
Anil: connotation to it, right?
Anil: I think like one reason we're really excited is because we actually do exactly what Jan said.
Anil: We think they're going to be insane efficiency gains. We think there's going
Anil: to be this huge period of abundance, right?
Anil: Obviously with this new innovation. And I think I think like,
Anil: you know, one thing that we think about and we were talking about just this
Anil: past week at our founders retreat is like, you know, there's this like the churn
Anil: rate of Forbes 500, the Fortune 500 company every decade has just been going up and up and up. Right.
Anil: So even if you use the churn rate from like the last decade,
Anil: I think, you know, probably half of the companies would be kind of churned in
Anil: the next like 10 years. Right.
Anil: We actually think, or this is at least my stance, I think that churn rate is
Anil: going to increase exponentially because of AI.
Anil: And I think you may even see 350 to 400 of the top 500 companies get churned
Anil: out in the next decade, which what does that mean?
Anil: That just means there's immense value creation happening in other areas of the
Anil: market and capturing even a little bit of that upside. I think it's just going
Anil: to be the craziest thing that you could have ever hoped for as an investor, right?
Anil: So yeah, I think we are excited for some of these big companies that already do exist.
Anil: Obviously, like the Max 7, Fang, they're obviously fighting very hard to hold
Anil: on to their spots, and there will be a lot of efficiency gains there.
Anil: But I think more excitingly and obviously going to be much harder to figure
Anil: out are the companies that will go from zero to some of these top 500 companies
Anil: in areas all across the map.
Anil: So yeah, honestly, we're just super excited. But yeah, I think it's going to
Anil: be challenging, but that's why we're kind of pumped.
Ejaaz: Yeah. So one of these words that I keep hearing all three of you mention is the word edge.
Ejaaz: And it's like looking to find the edge. And what I want to ask,
Ejaaz: because I think this is what I'm personally interested in, a lot of people who
Ejaaz: are listening, is what the process looks like in finding an edge and what type
Ejaaz: of topics you guys are interested in pursuing where you can find that.
Ejaaz: Because a lot of times there are episodes, we're interested in just exploring
Ejaaz: different frontiers, but there's a lot of different pillars in the world of
Ejaaz: AI. There's so many different industries and categories.
Ejaaz: Is there a particular spot you're excited about?
Ejaaz: And within that spot, how do you go about finding an edge and getting an advantage?
Jose: It's honestly like a lot of trial and error and being very honest with yourself about where you sit.
Jose: I think that's something crypto really gives you like to survive and thrive
Jose: in crypto. You need to be very honest about whether you have edge or not and where you have edge.
Jose: And in AI, I think for us, it's just been a process of, I think,
Jose: first of all, we started looking at, obviously, we did crypto AI where we thought,
Jose: you know, there's an overlap here with crypto, we have an existing brand.
Jose: The sector is exciting here. I think it's pretty clear that we can have edge,
Jose: like we're very early to it.
Jose: And then we started trying to do more AI direct investments. And I
Jose: Uh, the, the bigger challenge. We were, we were like, some of the stuff was
Jose: hard for us to get our head around.
Jose: Um, but also it was unclear to us, um, like whether we had edge and that's always
Jose: like a bad sign. Like you should, you should kind of know.
Jose: Um, I guess we know the feeling of, of having edge to some extent.
Jose: And I think it's a mixture of, um, there's like some reason,
Jose: something that other people aren't seeing here, which I definitely think we're,
Jose: we're like more bullish on AI than the average person, but probably not than the average VC. Right.
Jose: So then we thought, okay, I think this direct investment, there's some negative
Jose: selection happening here, like the deals that we're seeing are potentially not the best ones.
Jose: And so we started to look at, I mean, first of all, we started to look at fund
Jose: managers, which I think was an interesting one where we saw,
Jose: okay, there's these fund managers raising small funds,
Jose: first-time fund managers, they're really struggling too, because no one wants
Jose: to back a first-time fund manager generally, and the fund of funds are very risk averse.
Jose: And so, and we started seeing, wow, there's some guys here who are super plugged
Jose: in, insanely well-networked and
Jose: hungry, and really remind us of kind of ourselves seven years ago in AI.
Jose: And this could be a way that we can have some edge, like not only will these
Jose: guys perform, but also the deal flow that we get through them is going to be
Jose: like pre-vetted and give us some access that kind of overcomes that negative selection problem.
Jose: So we've been kind of digging into that now, and we think that there's edge there for us.
Jose: We're also looking at China, like we've been looking at China for a while,
Jose: one of our, actually, both our members of the investment team spend a lot of
Jose: their time, of the intelligence team spend a lot of their time in China.
Jose: I believe China is producing like over half of AI engineers.
Jose: And also the, it's much, the rounds are much cheaper there because there's just
Jose: less capital, like the US investors are
Jose: really able to invest in China, like institutionals. And there's obviously concerns
Jose: like geopolitical concerns and stuff like that.
Jose: So you've kind of been looking there and figuring out whether there's a way
Jose: for us to have edge there and to add some value in helping kind of these founders go global.
Jose: So I think for me, I'm curious what the other guys think actually.
Jose: And then we're also looking at kind of these secondaries of the big names,
Jose: the Anthropics, the the groks um the
Jose: the open ais and kind of figuring out you know
Jose: whether we have edge there because i think there we're more just trying to capture
Jose: the the beta versus have a lot of edge but um yeah for me it's a trial it's
Jose: a trial and error process of like thinking through things going in doing some
Jose: research and then figuring out being very honest with ourselves if we if we think we have edge or not
Yan: Yeah no i think the the honesty is is the important one um edge comes in many forms, right?
Yan: It's selection edge, it's timing edge, it's some informational edge.
Yan: And then there's some that comes with experience in terms of bet sizing and everything else.
Yan: And so for us, what we're in the process of doing now is basically trying to
Yan: understand where we can have an edge.
Yan: And I think even that on its own is very valuable or it could even be considered
Yan: an edge and now we're like using this in a very nebulous way but so you know
Yan: timing wise it's it's it's on the early side for sure right so i i think that's
Yan: certainly one having the luxury to commit a.
Yan: To look at this without necessarily needing to generate a return immediately,
Yan: I think is a huge benefit, right?
Yan: Where to some extent, other managers as part of their job, they're forced to deploy, right?
Yan: And so that I think comes with a disadvantage where you might be deploying in
Yan: areas you don't necessarily want to.
Yan: So I think the patience itself is a huge benefit and should give us the opportunity
Yan: to find those unique plays.
Yan: I think one of the biggest things, and and this is another learning in crypto,
Yan: is so much of it comes down to bet sizing, right?
Yan: And it's like, it's really knowing what the opportunity is and whether you're
Yan: allocating one, five, 10, 50% to a position is really what makes or breaks a
Yan: lot of these or what really drives, I think, the outperformance.
Ejaaz: How do you personally figure that out though, Jan? I know you say that and that's
Ejaaz: what all the investors say, but I want to get inside your head.
Ejaaz: What's the difference between you being like, you know what,
Ejaaz: I'm going to give you around $1 to $5 million.
Ejaaz: And then you're going, you know what, I'm going to pump in $20 million into
Ejaaz: your thing, which is not something you guys are unknown to, right?
Ejaaz: So what is that difference?
Anil: Jan is a great person to ask this question to be honest.
Yan: The big one is just risk. And so it's understanding, you know,
Yan: how can this go wrong? And realistically, what is my downside?
Yan: And then I think sometimes, you know, when things are going well,
Yan: it's also knowing when to, like on paper, you should be taking position down.
Yan: But I think there's an edge in understanding the position outside of it relative
Yan: to the rest of your portfolio, right?
Yan: And saying, sure, by the book, I should probably be downsizing,
Yan: but it's more about how is this position relative to the rest of the market?
Yan: Is everyone else underexposed?
Yan: Will there be a lot of money coming in. And so I think that ends up really,
Yan: it's like, it's understanding that your winners are winners and they should
Yan: remain that way. And so you're either doubling down or leaving them as is.
Yan: And so it's not often that you get really convicted and it's kind of in those
Yan: scenarios where a lot of those edges line up, right?
Yan: I happen to be down this rabbit hole and I found this, it's going to be a lot
Yan: harder to get access to this in the future.
Yan: I think it's de-risked more than people actually think.
Yan: And so it's when the stars align in those scenarios that you really need to just kind of have...
Jose: You're talking about optronic here?
Yan: That's one of them. Yeah. And where you just have a lot of...
Yan: And I think the risk tolerance is a big one too, where thankfully from crypto,
Yan: you kind of get numb to the volatility.
Yan: And I think that ends up being a huge edge as well, where you're just able to
Yan: tolerate swings where if it goes wrong, it goes wrong.
Yan: But ultimately, more often than night, it will go right. And you really want
Yan: to be able to capitalize on those opportunities.
Jose: Yeah, I think that Jan's really good at this. It's probably one of his biggest strengths.
Jose: And we definitely have a lot of experience just from, in fund one,
Jose: we started with one position in the fund just by virtue of our size.
Jose: And the rest of the cycle was us just selling that position to buy others.
Jose: And so we just, you really, from that, like understand deeply,
Jose: like the importance of bet sizing.
Jose: And you also naturally have this like hurdle rate, right? Like,
Jose: is this thing going to outperform DoorChain?
Jose: Which was our position at the time. But I think the sizing, that's,
Jose: yeah, Yeah, one of the biggest things is also one of the biggest things I look
Jose: for in fund managers, like people who are going to be concentrated and not afraid to take big swings.
Jose: And it's also one of the biggest mistakes early fund managers make.
Jose: They want to kind of, and like, concentration just drives all the right behaviors.
Jose: Like it forces you to think about whether this founder is going to be able to
Jose: return the fund for you, whether this is someone you want to spend a lot of time with.
Jose: It forces you to actually add value to the founder. It forces you away from
Jose: like indexing and just following in to around because Sequoia is in or whatever.
Jose: So, and then the other thing is just like conviction is, it's like a feeling, right?
Jose: That you build through research and speaking to someone and thinking about it.
Jose: But when you have it, it's really important to recognize it because conviction,
Jose: at least for me, it's not like you can have sort of 10x more conviction in something
Jose: than you have on anything else.
Jose: And a lot of people will feel that and size them equally anyway,
Jose: right? Or like I have to have 10 positions or whatever.
Jose: But actually if you're conviction, if you have 10X more conviction in something
Jose: else, you should size it appropriately because those things don't come along that often.
Jose: You know, there's only probably three to five, if you're lucky,
Jose: spots a year where you really find that kind of conviction where the stars line up.
Jose: And when you find it, it's really important to size things correctly.
Jose: And it's kind of the biggest difference, I think, in performance for people.
Anil: That's why we wanted to build this research team build this conviction right is like
Anil: we think we feel confident in our ability to see these opportunities.
Anil: But if you don't have the conviction, you may not take the swing at the right size.
Anil: Right. And I think that's going to be really important for us.
Anil: And then, you know, going back to Josh's question about, you know,
Anil: obviously, we've been using the word edge a lot.
Anil: I'll say that, like, you know, EJ started it. So
Anil: not totally our fault. But the only thing I'd add to what these guys said is
Anil: like, For me, I think one of the biggest edges that we founded with Delphi is
Anil: just different perspectives.
Anil: And I think that's what we're going to seek out with Delphi Intelligence as well.
Anil: And I think that's not even just within our team, which we really do like building
Anil: those perspectives and insights within the team.
Anil: But I think more so just within our trusted network.
Anil: Within crypto, we lean on our network all the time. And that really helps scale
Anil: the amount and, you know, the speed at which we learn.
Anil: That's definitely going to be something we lean on, you know,
Anil: within other areas that we're trying to explore and learn about.
Ejaaz: Yeah. So as you guys move into the world of AI, I'm curious if Delphi,
Ejaaz: as a company, if you individually, you have a framework or a structure of how
Ejaaz: you think about these opportunities.
Ejaaz: Because AI is divided into a lot of big categories.
Ejaaz: I mean, on the show, we like to talk about it as a layer cake almost where you
Ejaaz: have the chips layer, then you have foundation models and you have dev tools
Ejaaz: and like infrastructure. and then the top's the application layer.
Ejaaz: And there's all these different worlds that you could explore,
Ejaaz: I guess, to get that edge.
Ejaaz: And I'm curious if any of you or if there's a company-wide kind of tooling or
Ejaaz: a way that you explore these opportunities and find order in the chaos when
Ejaaz: you're evaluating everything.
Jose: I definitely think we have, different people have different perspectives on this.
Jose: We've looked at things across the layer cake.
Jose: I think personally, I'm most interested in the top and the bottom.
Jose: Um i just think that's like
Jose: um those are the places that tend to be
Jose: the most defensible so we've looked at a couple of we haven't actually pulled
Jose: the trigger on any although i actually made a mistake on one of them but we've
Jose: looked at a bunch of chip startups and and and people doing new new architectures
Jose: and stuff which have been really interesting um and then for me i'm really bullish
Jose: on the application layer like i think i think chat gpt rapper is
Jose: uh people use it as a as sort of
Jose: you know to throw shade but i think chachapati wrappers
Jose: are going to be insanely valuable and you're kind of already seeing it with
Jose: with cursor you know and and others like it and to me ai the capabilities that
Jose: it has already it could do um probably like 100x more than what people are using
Jose: it for right now and that gap to me is the product opportunity
Jose: of creating like verticalized applications
Jose: with really clean products,
Jose: with really smooth like context engineering and to solve like particular pain points.
Jose: And I think you're going to have those across every single vertical and they're
Jose: going to be, yeah, really, really, really big opportunities.
Jose: So that's one I'm really excited about.
Jose: But yeah, we look at stuff all across the stack, I think just to,
Jose: at this point, just to kind of build knowledge. I mean, actually,
Jose: in the crypto AI area, we did look at a lot of data stuff, too.
Jose: We kind of had an intuition that that would be somewhere that crypto would have
Jose: a particular advantage, like being able to, it's always been kind of a crypto
Jose: thesis, right? Initially, it was this idea of Web3 Social where everyone would
Jose: own their own data and you'd get paid for it.
Jose: But I think the idea of coordinating a bunch of humans to provide valuable data
Jose: to train AIs always was like an obvious or seemed like an obvious crypto AI idea.
Jose: So we did make a lot of bets there too.
Jose: I think we're a little bit more cautious now just given where things are going
Jose: with synthetic data and just RL and we're being a bit more cautious there.
Jose: But yeah, those are two that kind of came to mind.
Ejaaz: So you mentioned that you're bullish ChatGPT wrappers.
Ejaaz: Can you just give us the bull case for them?
Ejaaz: Because I, like you, have seen so many people shit on them, basically.
Ejaaz: Yeah. Why are you so bullish?
Jose: The sort of precondition for me being bullish on a ChatGPT wrapper is the founders,
Jose: or the app gets better as the models improve, right?
Jose: So it actually becomes more useful as the models get better.
Jose: And there's a lot of examples where that's the case. There was a lot of examples
Jose: initially to be where you're just building some scaffolding on ChatGPT to do
Jose: code or therapy or something.
Jose: And that's not interesting. All that stuff will get picked off by the models.
Jose: What is interesting is just verticalized applications, which improve as the models get better.
Jose: And some of them, I think even the more interesting ones or the most interesting
Jose: ones are the ones which actually don't work right now.
Jose: They're actually just betting on the models improving enough that one day they'll work well.
Jose: And there was a bunch of examples of that initially, but I think there's There's
Jose: some interesting ones now too.
Jose: But to me, the bull case is just, yeah, kind of what I said earlier,
Jose: what i said before that to get the most out of
Jose: out of models is actually hard work like you need pretty
Jose: good system prompts for whatever uh vertical you're
Jose: using it for right like if you're using a model for for therapy it needs to
Jose: not be so agreeable uh it needs to actually like tell you hard truths and stuff
Jose: like this whereas if you're using the model to write you uh i don't know a twitter
Jose: or shill post or something then maybe you want it to be persuasive and and stuff
Jose: like this um if you're using a model for investment due diligence you needed
Jose: to have access to all your investment notes.
Jose: You needed to know what the thesis is behind your firm.
Jose: So there's all this, people call it prompt engineering. I like context engineering,
Jose: which is a combination of meta-prompt and context.
Jose: And that stuff is actually really hard.
Jose: It's hard to get the most out of a model. And there's going to be applications
Jose: that optimize that process for a specific vertical and just give users really
Jose: refined experiences for it. Cursor is a great example, I think.
Ejaaz: But also Anthropic just released Claude Code recently, right?
Ejaaz: And so I'm curious about your thought around how much of the application layer
Ejaaz: you think the model makers can actually kind of take, right?
Ejaaz: So I'll give you another example.
Ejaaz: XAI just launched GROC 4 and they have this huge distribution network, right? Which is X.
Ejaaz: And granted, Elon is a very unique case because he's just buying everything.
Ejaaz: He's probably going to be influencing the chip sector at some point as well.
Ejaaz: He's putting chips into our brain, blah, blah, blah.
Ejaaz: And he's building up a massive competitor in terms of data centers.
Ejaaz: What edge do you think application builders that either you're investing in
Ejaaz: right now or that you're looking for right now have over what model producers
Ejaaz: can just kind of replicate themselves?
Ejaaz: Is it in the context engineering that you're talking about, Jose?
Ejaaz: Is it the fact that these founders can basically and intuitively describe how
Ejaaz: an app should behave? Because a lot of this is just around social behavior.
Ejaaz: The thing that makes an app successful is if you go on it and a bunch of people
Ejaaz: like it and really vibe with it. That's it.
Ejaaz: OpenAI just launched their agent yesterday.
Ejaaz: And the number one bit of feedback I've seen was, this is cool,
Ejaaz: but what am I going to use it for?
Ejaaz: And if you have your potential target market saying, what am I going to use it for?
Ejaaz: You haven't nailed the application there. So I'm wondering whether like there
Ejaaz: is like, you know, maybe just a list of items that you think separates kind
Ejaaz: of like founders that are building applications in AI versus like model producers
Ejaaz: that are just going to like steal their stuff eventually.
Jose: I think it's a great question. It's kind of the golden question if you're investing
Jose: in AI applications, like is this something that the models can do?
Jose: I think coding is an interesting one where, like, if, I think if Claude turns
Jose: out to be the best coding model for everything, it's going to be hard for,
Jose: for Cursor to, to win, right? Right.
Jose: If it's just literally a Claude wrapper, although there's still like cool stuff
Jose: that Cursor's built, like the, the rules, you know, which are,
Jose: which I think is a really interesting primitive.
Jose: I don't know if you guys have used cursor much, but it's a very interesting
Jose: UX framework that they've built and there's other stuff like that.
Jose: And I think there's definitely advantages to being laser focused on just pretty
Jose: much user experience and not having to build your own models.
Jose: It's hard to answer in the abstract and in the general. I think you have to
Jose: go kind of like application by application.
Yan: Yeah, user experience is a big one in the sense. I think one parallel is looking at Gemini, right?
Yan: And how underutilized it is because it's just the UX is tough, right?
Yan: And so it's kind of clunky. It doesn't really, it's not as widely used as you'd
Yan: expect it to be considering how many people are using Gmail and all of that.
Yan: And so I do think, you know, the UX is a big component.
Yan: And so it depends on how much of the value is just in the raw processing ability
Yan: of the model versus how much of the value in the product is in building out
Yan: everything else around it and making the experience fluid.
Jose: There's a lot, for instance, Harvey's an interesting one where they've just
Jose: built a lot of scaffolding, as I understand it, a lot of scaffolding to make
Jose: the document creation for lawyers extremely fast and seamless.
Ejaaz: So Harvey AI, just for context for the listeners is like ChatGPT for lawyers. Is that right, Jose?
Jose: Yeah, basically, for creating memos and stuff like this. And you want to be able to have your firm's
Jose: standard boilerplate stuff and like whatever the style
Jose: is that your firm writes in the key
Jose: documents and you want to go document by document because this isn't
Jose: this is like very high uh fake stuff that
Jose: you don't want to get wrong and and i think that's going to be the case for
Jose: like almost every vertical is going to have this uh and because like reliability
Jose: is also a huge thing kind of talked about that before but these these models
Jose: are not uh they're getting more and more but they still have hallucinations
Jose: and not super consistent um that that's another thing that the
Jose: kind of verticalized applications can can help fix with really good scaffolding
Jose: and system prompts and stuff um but yeah i think harvey and cursor probably
Jose: the two biggest examples of ones so far that i think have have built cool stuff
Jose: on top of um like a basic wrapper nice
Anil: Yeah i do also think customization is going to be a big key and i'm you know
Anil: i wanted to jump in after you because I think like, this is something I go back
Anil: and forth on a lot is a lot of these model creators obviously have a lot of
Anil: data on, you know, who is paying for compute,
Anil: how much they're paying and, you know, can very quickly figure out why,
Anil: you know, if this person is paying, they're obviously building something that
Anil: is valuable. Let's go copy and paste that.
Anil: And yeah, to Ejaz's point, obviously a lot of, you know, these guys are all
Anil: going towards this agent space, towards like creating something that is scalable
Anil: to, you know, the masses.
Anil: I think, you know, the last decade was very much about, you know,
Anil: there's an app for that. and I think
Anil: upcoming decade will be very much like there's an app for you,
Anil: right? So very like custom app.
Anil: Maybe Jose, like, I don't know if you want to leak or share some of the conversations
Anil: we were having this week about like, something labs is building for Delphi itself.
Anil: I don't know if you want to go into that. But like, I think that's a great example
Anil: of like something that, you know, yes, we know a lot of these model creators
Anil: will have something that will probably accomplish 70 to 80%,
Anil: if not, maybe even more, you know, in the future for us.
Anil: But it's something that, you know, So I think Louds wanted to roll up their
Anil: sleeves, get their hands dirty and build something custom fit for us that would
Anil: be, you know, fulfill basically 100% of our needs.
Jose: There's like Delphi, we operate, we like to call it like the hive mind,
Jose: right? It's also the name of our pod.
Jose: And it really operates that way where there's a bunch of people in different
Jose: divisions, some doing research, some building stuff, some investing that are
Jose: having a bunch of interesting calls.
Jose: And right now it's the sort of bandwidth between surfacing the interesting conversations
Jose: for the whole firm to benefit from is really slow.
Jose: Like we have to schedule these like bi-weekly calls. And then by the time that's
Jose: happened, people have forgotten about it.
Jose: And so I think the initial sort of vision is for it to be sort of an organizational
Jose: knowledge base, or like we call it, you know, Delphi OS or Hivemind OS,
Jose: which can just, first of all, like have all the conversations that people are
Jose: having across the firms in a retrievable and like queryable format and then
Jose: building like intelligence on top of that.
Jose: So this thing can, for instance, generate IC memos really easily.
Jose: Like I have a bunch of calls of the project and then it has our IC memo format.
Jose: Maybe I can put in podcasts that the founder's done and then I can answer some
Jose: questions to the AI and then it can just generate an IC memo format,
Jose: you know, something that takes me kind of hours to do.
Jose: You might have the same with research. Or for instance, if we want to have a
Jose: kind of CRM of all the companies that we've ever spoken to, we can see all the
Jose: conversations people have had with people at this company and also all the conversations
Jose: people have had about this company, right?
Jose: We can sort of search this and see, oh, this founder actually leaked to Malifaux.
Jose: Like these guys are not performing well. They ended up using a different service provider or whatever.
Jose: Like, and we want to have, and I think every company will basically have this in the future.
Jose: Like it'll all the knowledge of the company will feed into this to this uh central
Jose: like memory knowledge base whatever you want to call it and then there'll be
Jose: various kinds of agents you can run on it that both help the company operate
Jose: better and just automate and augment its people to be able to to be able to do more you
Anil: Know you could kind of see this getting kind of crazier as time goes on right
Anil: like recently we just had this big founders retreat and we always like to like
Anil: kind of like share a book that we all read and stuff like that and this book
Anil: for this last week was Essentialism by Greg McCohen, right?
Anil: And you could see us using all this data that this knowledge base like fills
Anil: and then in our chat add an agent that is based off Greg McCohen who like kind
Anil: of follows our calls and then kind of shits on us whenever we're drifting away
Anil: from, you know, what the thesis of his book is.
Anil: So it's not like us holding each other accountable, but this agent almost holding
Anil: us accountable to the decisions we're making at an org level.
Anil: So yeah, I think we're super excited to play around with it.
Anil: And I think it will be super useful for other companies.
Anil: And at the same time, to answer your question, do I think this is something
Anil: that like the big models like OpenAI, Anthropic, et cetera, you know,
Anil: Crop are not going to build in?
Anil: No, of course, they're obviously building it right now, as we've seen with all
Anil: these recent announcements.
Anil: But I think the customization is something that's really special.
Anil: I think will be like, you know, again, what I said earlier, an app for everyone
Anil: rather than here's an app for, you know, you.
Ejaaz: Yeah, this is a super interesting point, right? Because you were able to build
Ejaaz: Delphi OS using AI, and that would previously have been something that you'd
Ejaaz: have to go to a larger company or use a lot of resources in-house to develop.
Ejaaz: It's become much easier.
Ejaaz: And then you mentioned that, well, Grok is probably going to integrate this.
Ejaaz: ChatGPT will probably see these types of tools in. I'm curious where you see
Ejaaz: the most forming, because a lot of the new innovations tend to become commoditized fairly quickly.
Ejaaz: And I think one of the most that we've seen perform the best,
Ejaaz: at least in the consumer world, which is what a lot of the people who are listening
Ejaaz: to. are involved in, is ChatGPT's memory function.
Ejaaz: And memory is amazing because it includes all the context of previous conversations
Ejaaz: you've had, and it really locks people into that platform.
Ejaaz: But outside of memory, I haven't really seen many other moats that make me want to use a model.
Ejaaz: So I'm curious what your takes on moats are, if they're possible to capture
Ejaaz: a large amount of a user base, or is it just going to be commoditized software
Ejaaz: all the way up, all the models get better, they all kind of copy everyone's features.
Ejaaz: Is there any moats that you guys are excited about?
Yan: One funny one is there's a big moat to the brand and what kind of gets normalized, right?
Yan: So as we kind of all agreed on earlier, we are using a very,
Yan: very small fraction of the potential of these, right?
Yan: And so if you think about the earliest adopters of this tech,
Yan: which, you know, ChatGPT has an insane amount of users, but the penetration is still pretty low.
Yan: And that's why it's so valuable. And so the first cohort is going to be kind
Yan: of the most diligent about figuring out, okay, this one is better for this.
Yan: This one is better for this.
Yan: But each incremental onboarder is going to be less particular.
Yan: And at the same time, all of the models will keep getting better.
Yan: So what that basically means is each one will continue to use less and less incremental.
Yan: Of the potential of this thing and and and they're all going
Yan: to be relatively commoditized for their use case and so what
Yan: it'll boil down to is what gets normalized you
Yan: know uh going back to you know use xerox
Yan: uh like for copying then google everywhere you google it and then now like chad
Yan: gpt has has won that so far right that's just kind of the one that comes into
Yan: mind for anyone who's looking to start dabbling in this and i think you know
Yan: that as an onboarding tool and as a customer acquisition tool can't really be slept on?
Jose: In general, AI stuff has less of a network effect than the web two giants did, right?
Jose: Like social media and ad based stuff has way bigger network effect where it's
Jose: just much harder to disrupt.
Jose: But I think, I mean, the moat in AI, there's some things that have a data moat, right?
Jose: Someone like Tesla that has like so many hours of driving data and there's other
Jose: like robotics companies that we've looked at where that's a moat.
Jose: I think OpenAI in itself, the amount of chats that they have and the ability
Jose: to use that for training and things like this is also somewhat of a moat.
Jose: But I do think in AI that the main moat is just going to be UX and speed,
Jose: the team that is the best at constantly shifting to where the meta is and building the next thing.
Jose: Ideally, you don't want your memory to sit with ChatGPT or whoever.
Jose: And this is, I think, pretty visceral for people when they're sharing.
Jose: I've shared some pretty personal stuff with ChatGPT.
Jose: I think we all have. Yeah, like more personal than I ever thought I would have.
Jose: So I think ideally, remember, we would actually sit and we have a project that
Jose: we're incubating that's actually building this.
Jose: Ideally, you would have private memory built on TE or ideally FHE once that works.
Jose: And then you would give in sort of a cursor like UX, you'd be able to choose
Jose: which model you want to give permission to access certain parts of that context
Jose: to answer a query, right?
Jose: I mean, the ideal ideal would just be you have a model that runs locally,
Jose: but I think that's going to be
Jose: super tough um so i think
Jose: that's like one interesting area but i agree in
Jose: general like the moats and that's why we've also been looking at
Jose: deep tech stuff i do think the moats sort of end up also moving to like hardware
Jose: to ip um to just things that in the past were seen as not sexy you know like
Jose: uh it's not software it's it's too hard but i think those things will actually
Jose: have like some of the most persistent moats in an era of of uh of ai and just insanely
Jose: deflated cost of software.
Anil: Yeah. I'd say that like on the memory front, I really hope that's not a moat, right?
Anil: Like I, if memory is a moat, that just means that you're kind of like stuck
Anil: into the, one of these ecosystems and you're really relying on that one builder
Anil: to build every, you know, the best app of everything.
Anil: Whereas like, you know, um, yeah. So, you know, to Jose's point,
Anil: yeah, we are incubating a project that is, you know, based off this thesis that
Anil: memory won't be locked in in one place and won't be disemoted.
Ejaaz: So I feel like this whole memory term is just like another term to describe data, right?
Ejaaz: And that's what all the top social media technology platforms have nailed so
Ejaaz: far, right? They just aggregate the most amount of data.
Ejaaz: I mean, Jose, you just mentioned that you use so much personal stuff or you
Ejaaz: say so much personal stuff to ChatGPT.
Ejaaz: I am talking to this thing for hours on end, right?
Ejaaz: So at this point, I'm just like naturally inclined to use ChatGPT,
Ejaaz: even though there's like another model that comes out. I really hope the portability
Ejaaz: gets figured out Anil, to your point I just don't know what the incentives would
Ejaaz: be for some of the bigger model producers
Jose: It's sort of different from social media though because in social media it's
Jose: not just the data it's the fact that all your friends are on there so you don't
Jose: just have to port over your data you have to get all your friends to sign up
Jose: to whatever new thing whatever web through social media thing you're using whereas here,
Jose: portability you actually have access to all your chatchipity chats and it's
Jose: not that heavy no matter how much you've talked to it It's text data,
Jose: you know, it fits on any computer.
Jose: So I do think if someone builds a great user experience here,
Jose: it's something where it can actually win because it's a better product,
Jose: like fundamentally. It just has to work really well.
Anil: I also think, Ejaz, you put out this tweet, I don't even know if it was today
Anil: or yesterday, it's been a long week,
Anil: but you talk about the different personalities of these models, right?
Anil: I think that's an interesting way to think about Emote as well, right?
Anil: The conversations I have with Rock are way different than the conversations
Anil: I have with like O3, right?
Anil: So yeah, I think that's an interesting way to think about it as well.
Ejaaz: No, that's a good point. For those of you who are wondering what this tweet
Ejaaz: said, I basically described all the top models as having different personalities.
Ejaaz: So I said, Grok was kind of like, whatever, naughty and rude and extremely horny, just to be frank.
Ejaaz: And then ChadGBT was like kind of this incredibly agreeable personality.
Ejaaz: Claude was kind of like, yeah, there you go. There you go. It's much more human,
Ejaaz: right? It's much more intuitive.
Ejaaz: Anyway, they have a bunch of different personalities and it kind of like attracts
Ejaaz: a certain type of audience or it kind of like secretly molds you into being
Ejaaz: some one type of a user, right?
Ejaaz: You end up saying information to one model that you went to another.
Ejaaz: And it just kind of like Chris's weird kind of sociodynamics that I think are interesting.
Ejaaz: But kind of moving on, guys, I remember when you first started your fund in
Ejaaz: 2019, the stuff that you guys were investing in, I thought you guys were insane.
Ejaaz: And this is coming from someone that like worked in the space, right?
Ejaaz: And then of course, years passed, and it turns out that you guys nailed it.
Ejaaz: So my natural question now that you're focusing on AI and investing so much
Ejaaz: in AI is, and I'm going to put each of you in the hot seat, so prep your answer,
Ejaaz: is what is one emerging contrarian trend in AI right now that you think everyone is missing,
Ejaaz: but they should 100% focus on because it's going to become a big thing over
Ejaaz: the next couple of years?
Jose: I guess one thing I'd say is I don't think you necessarily have to be contrarian in venture, actually.
Jose: I think you have to be right, but not necessarily contrarian.
Jose: Although it helps for sure. Like it definitely is helpful when you're looking
Jose: at something and you're really bullish on it and no one else happens to be.
Jose: But I do think just, yeah.
Jose: I mean, the area I'd say is the one I already spoke about, which is like GPT wrappers.
Jose: I think a lot of people are sleeping on them and I think they're going to be
Jose: absolutely like giant kind of businesses.
Ejaaz: What's a GPT wrapper that isn't like a coding wrapper that you think people
Ejaaz: should focus on or pay attention to?
Jose: Um, I mean, this, this application that, that we're building internally,
Jose: and there's a couple of teams that we've spoken to that are, that are building it.
Jose: Uh, one of them is, is Den. It's like a YC company.
Jose: So it's kind of like, think about it as cursor for, for work,
Jose: right? It ingests like all your work data, your emails, your memos, your calls.
Jose: Um, and, and, and then you're able to use any model to like run on that data.
Jose: They also built a Slack clone, which I think is really interesting because the
Jose: idea being that you're chatting with these models anyway, and actually in the future.
Jose: And so you can open these chat groups with a model and your team in them.
Jose: And you can all chat to the model together in these groups and have different
Jose: models in the different chats, which I think is really interesting.
Jose: The idea that you're chatting already, why not have a chat app where you can
Jose: have group chats with the models and they can be on calls and stuff like this.
Jose: I think various versions of those, I think you'll have a new Slack.
Jose: I think all the company CRM stuff that Salesforce does right now is going to be rebuilt around AI.
Jose: I have to think of more some more examples of good rap. Those are the ones I've mainly been focused on.
Jose: But I think in hiring, for instance, you're definitely going to have something
Jose: like that that's just going to know exactly what kind of person you're looking for.
Jose: It can do the interviews for you, sort candidates for you.
Jose: In every vertical you can think of, AI is going to have, you're going to want
Jose: AI to do a huge percentage of the work
Jose: and there's going to be an app that facilitates that workflow, I think.
Anil: You're giving more high-level ideas, though. I feel like Ejaz wanted specific,
Ejaaz: Right? I want specific. A specific company. Yeah, exactly. Yeah, yeah, yeah.
Ejaaz: And the crazier, the better, honestly. Yeah, the crazier, the better. Just lean in.
Anil: Mine aren't going to be crazy, and I hope Jan and Jose will make up for that.
Anil: But going off of what Jose said, which is the contrarian part,
Anil: I think, is over-indexed.
Anil: And I think in crypto venture, it definitely worked out really well for us.
Anil: But also, I think nowadays in crypto, there's not much stuff that is contrarian.
Anil: Every conversation you have, people are bullish, hype or pump or something like that.
Anil: But I think, you know, when it comes to, you know, just generally AI,
Anil: I think for us, we thought the contrarian thing was, we thought even the most
Anil: bullish people were going to be underexposed, right? So for us,
Anil: we just want to be underexposed.
Anil: And, you know, the thing that I go back and forth on, you know,
Anil: to Jan's point is like, I think finding alpha here is going to be extremely difficult.
Anil: Obviously, we're up for the challenge, but I think it's going to be extremely difficult. difficult.
Anil: So for me, what I've been kind of pushing internally, and I think,
Anil: you know, this is open to kind of like any anyone inside or outside of Delphi
Anil: is, you know, capture a lot of this beta exposure.
Anil: I think sometimes like investors and people just like to work very hard to,
Anil: you know, to feel like they're smart.
Anil: But I think almost like, you know, you can capture, you know,
Anil: a nice index of, you know, open AI, Anthropic, like Andurl, Neuralink,
Anil: all this stuff, and capture a lot of this beta upside in a lot of these like
Anil: sectors that you think are going to be massive, right?
Anil: Even in the public equities, I think like companies like Google,
Anil: you know, maybe Tesla and stuff like that, I think are worth like looking at.
Anil: You know, I'm super bullish Google, for example, even though people maybe,
Anil: you know, are dancing on their graves because they're thinking that,
Anil: you know, their big search is going to be like cannibalized by AI, right?
Anil: Or open AI is launching this browser, which is going to like kill Chrome or
Anil: something like that. Um, so yeah, I think, you know, again, definitely not contrarian, right?
Anil: I'm literally fucking talking about Google and, uh, you know,
Anil: open AI and stuff, but I do think that people will mid curve it and say,
Anil: you know, that's too easy or, oh, these things have run away.
Anil: Like maybe the 10 X is behind me or a hundred X is behind me or something like
Anil: that. So let me try and find that
Anil: a hundred X and then probably invest in things that go to zero instead.
Anil: Right. Um, so that's my kind of answer, but, um, and then, you know,
Anil: more in Jose's vein of like giving, broad ideas and not specific names.
Anil: I think one idea that I think will be massive in the next, I don't know,
Anil: 12 to 18 months is I think...
Anil: If you're using Twitter nowadays, you kind of get really annoyed at all these
Anil: bots, right? And these agents that are like, in your replies, they're really bad.
Anil: And so a lot of people are kind of like looking for a social network that is
Anil: like, you know, people only, right? Maybe you do this world corner, whatever the fuck.
Anil: I think actually the opposite is even more interesting where it's like a one
Anil: on, you know, one where it's like you entering a social network where it's all agents, right?
Anil: And you basically can kind of like get these agents to have a conversation about
Anil: whatever you want based on personalities that you actually do follow, right?
Anil: Instead of, you know, people listen to all in podcasts, and you're waiting for,
Anil: you know, the topics that they're talking about, hoping to talk about a topic
Anil: that is maybe relevant to you, you can kind of create your own podcast of those
Anil: personalities, personalities you
Anil: do want to follow talking about the exact topic you want to talk about.
Anil: So I think something like that will be really cool. And I think will kind of
Anil: exist in the next like 12 to 18 months.
Anil: I don't know if the company exists yeah but um that's something that
Ejaaz: I i think like meta is that's that part
Ejaaz: of their strategy is just to kind of create a bunch of ai companions grok
Ejaaz: is launching them as well and i wonder i wish i
Ejaaz: could somehow track how much time each human user spends with some of these
Ejaaz: ai agents and companions as they go live i bet you like it's going to be incredibly
Ejaaz: sticky and what's really interesting about that anil um is that it's basically
Ejaaz: going to be a reflection of the person to an extent, right?
Ejaaz: And it depends on how much you dial up the sycophancy trait or if you dial it
Ejaaz: down and it becomes kind of like your mentor that kind of like abuses you every
Ejaaz: now and then and says like, no, you need to work harder or whatever that might
Ejaaz: be. All right, Jan, you're up next.
Yan: So one area I've spent a decent amount of time looking into and I'm super excited
Yan: about is the humanoid space.
Yan: So I think, you know, us speaking to a bunch of emerging managers and early
Yan: stage investors, It seems as if most of them are kind of fading it to some degree,
Yan: or they think it'll be more of a application-specific form factor that makes
Yan: more sense from a cost perspective, from a utility perspective.
Yan: Part of it is them talking their book, naturally, because building out the humanoid
Yan: component is very difficult and expensive.
Yan: And if you're doing early stage investing, it makes more sense to do these targeted
Yan: use cases that can get to market a lot more quickly and start to generate revenue.
Yan: And so I think there's a massive world where those make a lot of sense, right?
Yan: The unit economics can be very predictable because most of the tech already exists.
Yan: And I agree, there's a huge market for those.
Yan: But I think fading the humanoid side doesn't make much sense.
Yan: And the way to think about it is the market for the humanoid form factor is insanely huge.
Yan: I'm very aligned with the idea that there will be billions of these in probably
Yan: two decades just because of the amount of time it takes to build them.
Yan: But I think there will be a massive just supply crunch for them within the next
Yan: three to five years, realistically.
Yan: Um the the the the human
Yan: form factor makes a lot of sense because it can easily slot into everyday life
Yan: now i think uh the cost component is
Yan: starting to really get close to achievable so the the human form factor uh business
Yan: model usually fell off in the transition from uh prototype to scalable model
Yan: and and that makes a lot of sense right you have these insanely expensive robots that can breakdance,
Yan: but that's not really valuable from a business perspective.
Yan: Ultimately, what you want is reliability. So you're paying for hours worked, right?
Yan: That's kind of what really drives the value prop here.
Yan: And so I don't think there's a winner take all in this market because the demand,
Yan: I think, is nearly infinite, right?
Yan: And as they get better, the surface area for deployment and implementation only grows.
Yan: They all kind of gather within, you know, they all learn together,
Yan: which is, I think, something that isn't really appreciated enough where whatever
Yan: it's learning in one factory, it gets to apply everywhere else.
Yan: And so, and then, and you also, I think one of the things that gets faded on
Yan: the humanoid side is the fact that people think there will be kind of a societal
Yan: uprising, right? They're taking our jobs.
Yan: But for the foreseeable future, it just kind of amplifies productivity, right?
Yan: If you zoom out and think about demographics in terms of the population that
Yan: wants to do some of these roles, that's only going to decrease.
Yan: So cost of labor will increase. On the other hand, you have electricity costs
Yan: will come down, production costs will come down, reliability,
Yan: these things will come down.
Yan: And these businesses become pretty profitable pretty quickly,
Yan: especially when you think about their creative kind of forms of financing so i
Yan: think that space isn't really um as
Yan: as as appreciated and so realistically in the
Yan: u.s there are basically three major players for it
Yan: right you have tesla as the leader with optimus uh figure
Yan: is second in line they just did a val they did a raise at 40 billion that's
Yan: kind of getting wrapped up and then i think eptronic is the clear third and
Yan: um that that's they're trying to do another race soon and that's the one uh
Yan: we're really excited about internally because we see a lot of value there we um.
Yan: We think what they excel in is the actuator side, which is basically the joint of the robot.
Yan: And that's something they've been building for quite some time.
Yan: And I think there is a moat in that because of how that contributes to the dollar
Yan: spend per hour's worked formula and in terms of what it does for reliability.
Yan: And then on the other hand, they're partnering with Google and plugging in Gemini, right?
Yan: So you have the physical humanoid and then the model and the two needs to work
Yan: in tandem. And so you can try and build the model from scratch,
Yan: which is what Figur is doing after their kind of separation from open AI.
Yan: But I think partnering with someone and focusing on your strength makes a lot of sense.
Yan: And so, yeah, it turned into an electronic shell.
Ejaaz: That point around the actuator, Jan, is such a crazy thing to think about.
Ejaaz: Can you imagine in the Industrial Revolution when humans were just working at
Ejaaz: factories, that they were each graded by their ability to move their elbow or
Ejaaz: whatever at a 90-degree angle? That's just insane.
Ejaaz: The fact that you can program economics into these things is crazy.
Ejaaz: And I think you're right.
Ejaaz: Being able to picture and visualize these robots as actual, not some otherworldly
Ejaaz: creature, but just functioning humans and then monetizing that is just,
Ejaaz: it's just a new model to kind of like wrap yourself around.
Ejaaz: It's just insane.
Jose: I think humanoid is a really good one because you can kind of like,
Jose: I think being in crypto so long, you can kind of identify what things cause a bubble.
Jose: And I think obviously the thing has to have very strong narrative potential, right?
Jose: Like humanoid robots replacing all physical labor has that. And then you also
Jose: have to have a lot of hate.
Jose: Like you kind of need, because it both forces people to talk about it and also
Jose: creates like these really hated rallies.
Jose: And I think humanoid robots actually has a decent amount of hate from like smart
Jose: people who just think that specialized robots are gonna win out.
Jose: So it's a very, I think, good contestant for that. I'd give you two names that
Jose: I think are interesting, maybe contrarian.
Jose: I think Anthropic is really valuable.
Jose: It's like the least valuable of the model companies. I think you could get it
Jose: at like 60 bill when I last looked a month or two ago versus three to 400 billion
Jose: for OpenAI and 150 billion or so for Grok or for XAI now.
Jose: And they're clearly the winners in coding. Like they have been over and over again.
Jose: I think they have a lot of market share in coding, like every dev and any dev
Jose: you speak to is using CodeCode.
Jose: I think that's insanely valuable. If you think software has eaten the world,
Jose: is going to continue to eat the world, and you are literally the world's software
Jose: factory, where everyone is going to produce software, I think it's insanely valuable.
Jose: It's also one of the things that's easiest to train on because you have these
Jose: easy kind of RL loops that you can do. It's formally verifiable and stuff.
Jose: So I think they're actually in a really strong position. And
Jose: it's tough because they don't have their own users i think
Jose: a lot of people use it via api and that's generally
Jose: not a not a great place to be but i think if they win coding that's
Jose: like i think tens of trillions of of
Jose: dollars like use case like i think it's only going
Jose: to get get bigger um and then the other one the one we're speaking about at
Jose: a dinner is just it's in a hated sector it's not to do with ai but it's it's
Jose: epic games um so those guys they're doing like six billion in revenue and um
Jose: i haven't found supply for it yet,
Jose: but it trades at something like 15 billion,
Jose: which, you know, it's a very depressed multiple and just because gaming is not hard at all right now.
Jose: Gaming is in kind of a secular decline for the last two years.
Jose: Sort of the time people have spent, not just crypto gaming, but time people
Jose: have spent gaming has gone down for two years straight, which no one really thought was possible.
Jose: No one knows the reason either. A lot of people speculate it's literally just
Jose: TikTok eating your leisure time that people used to be spending gaming.
Jose: And people talked a lot about the metaverse in crypto.
Jose: Fortnite has actually built the metaverse. It's not VR like most people expected,
Jose: but they have the closest thing to a metaverse in terms of
Jose: Just different worlds that are player created, all the different maps that are
Jose: player created, like 500 million users.
Jose: They're having concurrent players maps with like thousands of players and just
Jose: a really thoughtful CO and I think like everything is going to be leveraged
Jose: by AI and I think they will be too just in the speed of what they can do.
Jose: I think it's an interesting one that like it's always interesting to look at
Jose: sectors that people aren't excited about at all and I think gaming is one of them right now.
Ejaaz: Awesome. Before we round up guys you made a big announcement this week around
Ejaaz: something called Delphi Intelligence.
Ejaaz: And you gave Josh and I access to the platform beforehand. And we have to say,
Ejaaz: like, we were super impressed.
Ejaaz: Maybe you could tell us a little more about what this is and why it's important
Ejaaz: towards what you guys are doing.
Anil: Yeah, definitely. Yeah, so obviously, we've talked about this a lot on the pod
Anil: already. But like, research is just at the heart of everything we do.
Anil: And to be honest, like, any decision we make, we kind of want to go in with
Anil: conviction and as much like insight and knowledge as possible.
Anil: So we know we're not only making the right decision, but when we are making
Anil: that decision, can size it properly, right? And I think for us,
Anil: you know right basically you know jose right after he
Anil: he kind of like passed around the situational witness paper um
Anil: which he actually read on a you know week off which is like
Anil: probably when we get the most work done it's like our weeks off um
Anil: to actually like read and think about you know the future of delphi and everything
Anil: like that i think that's when we really you know probably nine ten months ago
Anil: at this point realized that um you know this was like a no not an option for
Anil: us right we think to be the best uh investors builders researchers in crypto
Anil: and honestly any area, you kind of need to start building expertise in AI.
Anil: So that's when we really started, you know, rolling up recipes and doing the
Anil: hard work of building out a team and building out kind of like an MO,
Anil: which is just publish a lot of like great work on in areas that we're interested about.
Anil: So we can kind of build conviction and build expertise in this area to help
Anil: us make these decisions. So that's what Delphi Intelligence is.
Anil: It's a research platform, free to access for all. So you can,
Anil: you know, go on delphiintelligence.io right now, put your email in and you'll
Anil: get all of our research, you know, basically bi-weekly free.
Anil: We already have two reports out, you know, one on just like AI in the era of
Anil: entertainment, and then one on video generation models.
Anil: Both are like great. We have another one coming out next week on AI powered
Anil: browsers, which I think is going to be like really top of mind for a lot of people.
Anil: And essentially like, you know, it's us open sourcing our learning to the world.
Anil: And what's cool about it too, is it's not just going to be our team.
Anil: We're going to be curating a lot of great reads from within our network and
Anil: people we respect, including some of the fund managers that Jose brought up.
Anil: So yeah, I mean, if you're interested, please subscribe, follow us on Twitter
Anil: and everything like that. But we're really excited about it.
Ejaaz: Awesome. Well, thank you all for spending time with Josh and I and kind of going
Ejaaz: through your thoughts on the AI market.
Ejaaz: As you can imagine, there's just so much going on and our Twitter feeds or rather
Ejaaz: our X feeds are off the hook. We are talking to like five different AI models
Ejaaz: for various different things a day.
Ejaaz: And it's just not easy to think strategically and long term and have conviction
Ejaaz: around investments, right? Investments are such a hard thing to kind of nail.
Ejaaz: So, you know, hearing your perspectives has been hugely informative for us and
Ejaaz: I'm sure for our audience as well.
Ejaaz: For the Limitless listeners, thank you so much for joining us for another episode.
Ejaaz: As you know, Josh and I are trying out something new, which is just put out
Ejaaz: loads of content as and when it comes live, as and when the topic is trending.
Ejaaz: So we appreciate you and your feedback.
Ejaaz: The main bit of feedback that we've got so far is that you love the guest episodes
Ejaaz: and we want to get more interesting guests on.
Ejaaz: We hope you see this as one of those pushes towards that.
Ejaaz: And again, if you have any friends or colleagues or whatever that might be interested
Ejaaz: in this thing, we appreciate you sharing, liking and subscribing.
Ejaaz: Thanks, folks, and we'll see you on the next one. See you guys. Thanks.