Where Is The Crypto Alpha Hiding This Cycle?

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All right, everybody. Super excited today to be joined by some of my favorite allocators in the industry here to talk a bit about where the alpha is in this cautiously optimistic but potentially early bull market that we have going on here. Yeah, why don't we go down the line here? Just feel free to introduce yourself. Yeah, maybe mention your style of fund and what you focus on, and we'll start with you, Arthur.

Hi, I'm Raj. I'm a GP of Framework Ventures, a SF-based investment firm that mostly does early-stage venture and some liquid token investing.

Yeah, I'm Smack. I'm a partner at Compound. We are a thesis-driven, research-centric investment firm, typically early-stage venture, and more recently spending time on public equities and tokens as well. So, generalist fund based in New York, probably a third of the fund is crypto-related.

Awesome. Yeah, why don't we get into where the emerging sectors are and what's interesting. Obviously, the first one is AI. There's obviously been a lot of excitement there over the last year, and starting to see that shift towards excitement in crypto. And obviously, the intersection of AI and crypto, there's a lot of interest and excitement there. So, just love to hear a bit about that specific niche sector, how the three of you are thinking about it, how you're thinking about the alpha there and the opportunity set. Arthur, why don't you go ahead?

Yeah. So I think there's a few things. One is that AI is obviously transforming the way that companies operate. So we're seeing sort of operational leverage that we haven't seen previously, sort of for early-stage companies, where they're able to make a lot more progress without needing to hire a lot more people or potentially spend on headcount. On the crypto side, I think in particular, we've been really excited about financing opportunities. We think crypto is really good for capital formation, and sort of with the whole AI capex buildout, there's lots of different areas that need to be financed. One of our portfolio companies, Usual, is doing like mid-market cluster financing. So if you, you know, want to, if you're a promising startup or even a public company, and you want to buy, you know, $150 million worth of GPUs, you can go to them and potentially get more attractive rates with like less of a down payment relative to what you might see elsewhere.

Yeah. So we've been investing in traditional AI and ML since 2016. And so for us, one of the things that when we look at kind of crypto/AI or where that overlap is happening, a lot of it comes down to like the talent level of the builders there. And so I think what's kind of interesting is we've seen some of the overarching ideals of kind of crypto start to permeate more into these AI systems and this AI kind of narrative, which is a lot around permissionlessness. And so to me, I think we think that if crypto AI is going to compete on efficiency today, that's probably not the place that makes the most sense, at least today. I mean, maybe that's not true in the future, but I think there's a lot of kind of underlying societal trends that make the things behind crypto more appealing. And that's kind of around coordination. I think some of the economic models could be different. And then again, like permissionlessness compared to the, you know, centralized AI and some of the centralized frontier labs and what they're doing.

Yeah, I'm always hesitant when I hear people talk about this idea of, you know, crypto was never, you know, it was never built for humans to utilize. You know, there's this, I don't know if it's just like force-fitted in retrospect, this idea of, okay, crypto is actually going to be used by AI agents into the future. Curious how the three of you think about that premise. Is that just sort of, you know, hindsight bias or is there something there?

I think it's so, I've always thought like crypto is especially good at coordination and then kind of like economic incentives. And as blockchains have got more efficient or more performant, I think there's the argument I would say on the crypto AI side is cool, machine-to-machine transactions and communication. Maybe centralized systems that you use a credit card and you can have agents talk to each other, but there's some minimum floor to actually do those transactions. And I think the argument for crypto AI is, okay, cool, can we smush the actual cost of doing this towards a level that's more competitive that a centralized provider can't compete with? I think that's TBD on if that is actually possible. But to me, it comes back to like coordination more so than anything else. Like that's especially what crypto has been historically good at. And then also like the global nature of the permissionlessness. I think people are, like Arthur said, much more concerned about privacy and kind of like where their data sits and who owns it. And yeah, I think there's definitely an underlying trend of pushback on these kind of frontier labs and AI, like the traditional AI model. So I do think there's like opportunity for crypto somewhere in those wedges.

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Yeah. One idea we've been toying with recently is like sort of with all of these agent swarms that have been out there, the idea of like a distributed, permissionless ledger becomes potentially very interesting. You can imagine, for better or worse, you know, if a bunch of agents need to communicate with each other and need to make sure that their messages are durable or available, blockchains actually might make a lot of sense, whether you're cramming it into something with high data availability, whether you're using persistent file storage. I think it would be a very interesting experiment for somebody to like crawl Arweave or Filecoin and see if like any of these agent swarms are already using it.

I think also just like one other point around this is if you think the future is going to be more local models or smaller models, not everything being done in these like massive kind of frontier models, and more of the work or more of the inference gets done at distributed versions of that. You know, I don't know whether or not there's value to be had there or captured from crypto companies or projects is, I think, an open question, but directionally it's, I think it is again like in the ideals of some of the early kind of core beliefs of crypto around, you know, distributed networks and privacy to some extent. So yeah, I mean, TBD though, the value capture is always like an open question with a lot of these things.

All right. I want to look into privacy, but through the lens of the modern crypto fund allocating towards it and using that as a jumping-off point, because I mean, the three of your funds kind of represent this idea of this barbellness of, you know, you have the venture book, the more illiquid book, and then you also are actively on the liquid side of things. And that's it. It's quite an interesting, you know, when you just look at the form factor of what crypto funds have done well and are still here and are still allocating, it seems like that barbell is a nice place to live at. And then you put that into, you know, this privacy narrative has been something that's really taken hold recently. And what's interesting there is that a lot of the opportunity set there are assets that anybody can go buy in the market. You know, like Zcash has been around for ages. We've seen Nym start to go off. There's obviously, you know, anything related to the zero-knowledge proof world out there. So, you know, those are assets that you can go out there and buy in the market today. But allocating in size is a difficult situation there compared to the allocation through a venture book where you can size into it very easily and not be as worried about liquidity. Obviously, you have to worry about it at the liquidity event. But yeah, using that case study there, I'm curious how the three of you think about why we've ended up in this style that seems to be just, you know, the best way to go in crypto these days. Start with you, Arthur.

Yeah. I mean, the way we look at things is like regardless of whether it's a liquid asset or sort of on the venture side, we are looking for venture-style outcomes for the things that we invest in. And that often means being willing to hold an asset over a very long time horizon and sort of realize some of the volatility and hopefully convexity with the asset. I think, yeah, like sizing into assets is always a challenging thing, especially if the liquidity is not great. The team may or may not be willing to OTC. There's also a lot more crowding these days in the market where things become consensus a little bit more quickly. And I think people or the funds and market participants that are here are a bit more discerning around like what is working, what isn't, what actually makes sense to invest in and what doesn't. So the prices sort of when you get excited about something can move very quickly because it's very likely other people are doing sort of similar homework. So a lot of it is just being comfortable and understanding, at least for us, what the upside case looks like. And similar to Arthur, like, you know, if there's some variance in our entry price, we are okay with that.

Yeah, we've, so historically, we were primarily only kind of private venture, seed and pre-seed. I think there was a point a couple years ago where we said, hey, we're still excited about the asset class and the technology, and we're not meeting enough founders that we could get to a yes on in terms of like early-stage investing. And so we said, hey, we should be spending more time on the liquid side, mostly as a function of wanting exposure to the asset class, which again, if you're kind of periodically only doing private pre-seed and seed stage, like maybe we only do four or five transactions a year. And so it's like the asset class moves faster than that. And so we shifted kind of the belief, and I think part of this is just like the overall market maturing as well, is, okay, I think there's more probably investable assets today than there were five or ten years ago. And because of that, I think shifting how you think about the asset class matters. But on the sizing side, we again, like even when we think of structure, for us, it was very much, cool, what do we think is like the proper size that we could own assets to Raj's point, where our view is these should be venture-style returns, whether they're liquid assets or not. And so like what is the size that we think we could reasonably deploy and generate those type of returns and do it in a way that's not kind of beta, because I think that is the other thing in crypto is like it can just turn into a levered beta asset class, which is, yeah, which is like kind of not as interesting to us. And so our view is like, okay, cool, can we generate alpha still and like what's the size appropriate to do that? And a lot of it does come down to the volume of these things traded, like what assets we actually want to own. And then yeah, the vol is so high that I think there's a little bit of like, okay, if we want to build a position over time, if you have some patience, like you kind of have to believe that the volatility is going to work both ways. But yeah, obviously sometimes you see these assets just trend super hard and you kind of have to be comfortable with that, I think.

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What do you guys think about this? You know, Raj, like what you're saying about this idea of dispersion leads to crowding outness really quickly because there's only a handful of assets that, you know, suddenly everybody latches on to because there's just a plethora of assets out there that, you know, the fundamentals aren't as strong. So intuitively, you would think dispersion is great for active managers because, you know, as long as you're selective and in the right assets, you know, you can go to your LPs and say like, look at this alpha that we're generating. You know, it's not necessarily just levered beta where we're just, you know, everything's going up at the same time. But to your point, the crowding out of it can also be difficult to manage. I'm curious, it feels like this is the first bull cycle that we're going into where there is significantly more dispersion. It's not just everything all up, all down. How are the three of you guys managing that?

Yeah, I can start. I think some of it is like, you know, timing, timing does matter. If everybody has very similar ideas, sort of how you time it probably matters a little bit. Timing comes in a bunch of forms. It comes around like how you think about entry. It comes about like, you know, what your time horizon kind of looks like. There's things that might look really attractive and end up being really consensus and crowded over a short period of time, but over a longer period of time maybe are a little bit less consensus. So I think that's sort of some of how we have looked at it. Yeah, I think we're still sort of seeing how all this is going to evolve. That feels very different than previous cycles. And there's still a lot to learn there.