Tarun Chitra - De-Risking DeFi Through Automated Governance: Why Applying AI Will Change Blockchains Forever

Full transcript: Tarun Chitra on London Real

2:37 This is London Real. I am Brian Rose. My guest today is Tarun Chitra, the mathematician, blockchain technologist and decentralized finance thought leader.

2:56 You started your career in 2011 at the global investment fund D. E. Shaw, known for developing complicated mathematical models and sophisticated computer programs to profit from anomalies in the financial markets. Then in 2018 you became the founder and CEO of Gauntlet, a simulation platform for crypto networks that helps developers de-risk DeFi to better understand the importance of security, governance and consensus mechanisms. Gauntlet provides cutting-edge real-time analytics to DeFi platforms like Aave, SushiSwap and THORChain to help make their products perform better, mitigate risk and allow for scalability.

3:30 Tarun, welcome to London Real. Great, great to be here. Thanks for having me. Thanks for being here. I tried to kind of out dress you with colors today, but clearly I’ve failed.

3:39 You usually win on that one. I saw you on stage at the Token2049 conference. I think you were next to Stani Kulechov and you guys had a great conversation, so I’m really looking forward to this. I have to start by confessing that I couldn’t get a job at D. E.

3:53 Shaw when I tried. I was at MIT and I tried to get a summer internship there, I think in ’92, and they sent me a rejection letter. But later I went to Bankers Trust and worked on Wall Street and got a kind of probably a different type of vibe than I would have had there. Obviously, I think Jeff Bezos famously worked there before he started Amazon in ’94. So much to talk about, Tarun, and I’d love to start off a little bit maybe with your first five years on Wall Street, because when I look at Gauntlet it seems like a strange combination of everything you learned at Cornell and maybe some of the things you picked up at D.

4:26 E. Shaw and then, you know, all the other things combined. So maybe we start there. What do you remember from those days on Wall Street, and was D. E.

4:34 Shaw an important part of your career? Yeah, for sure. I think maybe the way I will color this is I’ll give it a history of how I got into crypto and then along the way, like, I’ll give a little bit about of kind of the finance type of stuff that was. Sounds good. Kind of there.

4:54 So I was working at D. E. Shaw Research where we were actually building ASICs and custom hardware for a bunch of different reasons, not for mining but for a totally different use case. And basically what happened in 2011 is we had this 25 million chip order and basically we gave 25 million dollars to a supplier and then they ghosted us for six months, and then of course they came back six months later and we’re like, hey, we’ll give you a 10% discount. And of course, maybe slightly more politely than this, we said, why did you have to tell us what happened?

5:36 You know, like where is this, where did our money go? And you know, they were kind of reticent to tell us what really happened, but after, you know, twisting their arm a bunch, they told us it was like someone doing cryptocurrency mining. And in 2011 that was just like unheard of, like that someone would be going to the process of building hardware to do mining. So that had me starting to mine a bit, which I, you know, I took all the coins I earned then and sold them at the bottom in 2013.

6:14 But it definitely got me into the space a lot. And I think what happened in sort of like 2015 and 2016 the academic research on cryptocurrencies got a lot better. So I think when I was at D. E. Shaw and also when I was in high frequency trading, most people I worked with were people with sort of like traditional distributed systems backgrounds.

6:40 And one thing that’s interesting about, you know, Bitcoin or the early days of Bitcoin is that basically no one in distributed systems believed it was really working until it, like, existed for like four or five years. And one of the reasons for that is that A, there’s a lot of like incorrect math in the original white paper and it doesn’t really kind of prove the claims that are made, but then also B, there’s just a lot of, there’s a lot of like existing sort of theory for like how distributed systems work, like what, you know, how distributed systems, that’s like in a data center run by Google or Apple, like how all the computers that talk to each other, a lot of those properties only hold in sort of like a probabilistic way for cryptocurrencies, and until basically 2015 no one actually gave a very good description of why or how that occurred.

7:37 So I think once that started getting a lot better, like the academic re- there started to be like, hey, there’s actually like a way of, you know, wrapping your head around these things. I started, you know, reading a lot of papers on new protocols, especially like proof of stake protocols, and one thing I thought that was interesting was that a lot of the stuff was written by cryptographers and they would focus on, hey, like, does this cryptographic assumption break? Like, does some mathematical property not hold?

8:09 Whereas, you know, when you’re coming from finance you think of things in terms of like what is the likelihood of this event happening, or what’s the likelihood of users, traders, market makers, whatever, changing their behavior and then suddenly the system breaks because, you know, there’s no one there or, like, you know, someone’s doing something malicious. And I kind of noticed that these papers, the security models they used were really focused on these kind of like cryptographic assumptions and not user behavior assumptions, right? And that led me down the rabbit hole of trying to take a finance lens to these different protocols and sort of try to understand if there are like financial attacks that would basically cause all the users to sort of like leave in some sense or take over the network.

9:06 So that’s maybe a longer one that helps. Do you think you got that perspective from like being at D. E. Shaw, where, you know, understanding risk and capital at risk and markets was so important? Because, you know, at Cornell you’re studying mathematics and physics and it’s again like you said, it’s very easy to go down that cryptography rabbit hole and go analyze it that way, but the perspective from a risk management perspective is one that it’s not obvious to a lot of people unless maybe you’ve worked in a firm that lives and dies by P&L and risk.

9:36 For sure. I don’t think I, so I think D. E. Shaw helped me more on the like understanding cryptocurrency research side of things, because they’re much more focused on sort of the rigorous research aspect of, you know, how they think about both risk and modeling things, etc. But I think when I worked in high frequency trading, that’s where I got the real sort of idea, the sort of kernel of like, oh, actually we should be thinking about these cryptocurrency systems the way high frequency traders think about risk.

10:09 It’s like much closer to that, where, you know, HFT is extremely adversarial, it’s like very zero-sum. You know, you have like, you know, 10 firms and then, you know, a whale makes a big trade and everyone is fighting to kind of like be the one providing liquidity around it, right? And that is very similar to like, oh, how a lot of cryptocurrency networks behave. And so I think thinking about it the way traders think about it, and I really mean much closer to automated high frequency traders, less like the sort of D.

10:43 E. Shaw, most of the stuff D. E. Shaw does or like these bigger asset managers, Renaissance, etc. They don’t do super high frequency stuff, it’s sort of like medium frequency and very large size, like they have, you know, billion dollar portfolio and they rotate it into different assets every week or something like that, right?

11:00 Whereas in high frequency trading it’s much more like, you know, you do a quick trade and you don’t have that much capital at risk, but you like, you know, you’re sort of like attacking the system in some way that looks more like what cryptocurrency attacks look like. So I would say I learned more about thinking of this type of stuff from HFT than from sort of like D. E. Shaw. Can you give everybody here kind of like high frequency trading like 101 in like a couple minutes, because you mentioned some interesting things about it.

11:31 Again, it probably gets a really bad rap in the market and people probably don’t understand what it is and what you can learn from it. But how do you kind of explain like what it is to most people? Yeah, so I mean, I think the simplest way to think about it is, in a market, you know, if prices are really stale, if there hasn’t been a trade in a while, then it’s really hard for people to trade a lot of size because there’s sort of uncertainty, like, oh, like no one has really wanted this asset for a while, so maybe it’s worthless.

12:06 So in order to actually ensure that, you know, markets have very recent pricing, you need people who are posting liquidity, who are adding buy and remove orders, almost like wholesalers, like, hey, I’m willing to sell you this crate of grapes at a dollar and I’ll buy a crate of grapes at 99 cents, right? They’re sort of like the middlemen who kind of provide inventory. And one important thing is like you want your inventory to be adjusting as fast as possible, because like if you don’t adjust your inventory, let’s say the price of oranges crashes 10 now you’re stuck holding a bunch of them and, like, you’re getting out of them at a huge loss.

12:49 So high frequency trading really is about inventory management at a really fast scale, so that prices are incorporating as much information about supply and demand as possible. The reason, I guess, people have a negative view towards it is everyone thinks they’re sort of like, you know, being front run. But the thing is, it’s an extremely competitive game, so to the point that it has, you know, the fees and sort of profits from it have, like, shrunk quite dramatically over the last 10 years per trade.

13:24 But it’s basically a way of people doing inventory management that you could think of it really like they’re a wholesaler, but they’re a wholesaler for this like asset that exists and, you know, that they’re adjusting the prices of really quickly. The reason I say it’s, you know, the HFT mindset is closer to the mindset to think of for security and blockchains is because in, you know, most trading is, you know, fully autonomous. There’s sort of, you know, you have these algorithms that are sort of competing with each other, and most of the way that people interact with doing different trades is that they maybe interact with multiple venues.

14:10 So maybe there’s an asset in New York, or well, really New Jersey, on NYSE that’s supposed to be correlated to an asset in Chicago, in Aurora, it’s the CME. Well, then the high frequency trader, you know, sort of has two computers on both sides, they see one price change and they go and update their price on the other exchange. In blockchains you have a lot of that because there’s tons of exchanges and there’s also tons of chains, and so you have liquidity sources that are on chain and your liquid resources off chain and you have to synchronize all of those to get, you know, kind of like the best information into pricing.

14:50 And in that sense it’s much closer to HFT than something like statistical arbitrage, where you’re like, I just want to buy, you know, Pepsi just went up 10%, I just want to go buy a bunch of Coke. You’re not actually, like, saying how much you care about the price as much as you’re saying, I know these two things are correlated and when Pepsi goes up, Coke’s stock price goes up, so I’d want to buy as much as possible, right? It’s not so sensitive to, like, the little like, hey, the price of this moved one cent here, I need to move the price one cent there.

15:24 It’s a little less fine-grained, and blockchains have a lot more of the latter than they do with the former. Okay, that makes sense. So that was probably some of your best preparation for what you do today, is the high frequency stuff, because it probably taught you more about what’s going on in the blockchain. Most people don’t come from that background, so they don’t look at it maybe through that lens. Yeah, and one of the biggest things is that the way you measure risk, and this is true for standard places like D.

15:49 E. Shaw as well as high frequency, but it’s way more, you live and die by this in high frequency, is backtesting and simulation, so stress testing your strategies against historical market data. But then also, and this is something you do in HFT and not as much, not really at all in stat arb, is you make models of other parties who are either trying to compete with you or are like, you know, the whales who are trading, and then you run simulations where you, like, look at how well, how, you know, when these two bots are sort of competing, like, which one wins, your bot or the other one, and then you try to adjust your strategy to beat the other one.

16:27 And that is a very like blockchain security mindset in a lot of ways. Okay, that makes sense. So that’s why thinking about, yeah, right. So your cons, it’s just game, like game theory and game playing against what could happen and scenario analysis and the other people out there that might be doing the same thing you’re trying to do with arbing. And I guess that’s why you started Gauntlet, because you could look at then all of these blockchain platforms from that lens and do all the things that none of these developers were maybe thinking about because they were trying to build a platform, and you were thinking, well, I can do all this risk analysis and do all these simulations.

17:03 And I guess that’s what Gauntlet brings to the table to all these big DeFi platforms, is that right? Yeah, yeah, exactly. I mean, one other thing to that I thought was cool and that kind of made me want to leave trading for this space is that all of the data is public, A, and B, all of the identities are public. So in HFT, when I was talking about, hey, we’re simulating the game theory and I model my strategy and I model the opponent’s strategy and then I run these simulations, I don’t actually know the opponent’s strategy, I’m guessing.

17:38 I’m trying to think as if I was them, right? So it’s like, you know, trading in the 1970s, I have two parties and I have one person trying to think how the other person thinks about something and then try to be before or after them. Trading in the, you know, 2000s, like, I have a bot, you have a bot, I have to think about how you would have written the algorithm for your bot and, like, what type of math tools you might be good at or might be bad at, and then try to make my bot identify that and then compete.

18:09 In some sense, that’s, you’re still guessing a lot in traditional finance because you don’t have the data of the other person’s strategy. You just, like, you go out and you trade and then you see, like, the results, and based on the results you say, okay, like, they’re probably doing this strategy, they probably wrote this algorithm because it seems very similar to what I see in simulation, what you see in production. In blockchains you don’t have to do as much guessing because the data is actually fully transparent, at least for on-chain things, not centralized exchanges.

18:42 So there’s less of this statistical inference problem and more of a, like, how well can you replicate their strategy exactly, like, you know, exactly to the T. And so that’s what we really focus on, is making sure that our simulations, our models of these agents, replicate people’s behaviors in practice as well as possible. And one other difference I think that’s important to bring up in DeFi is that in traditional finance you have these counterparts that you trust.

19:14 You trust the exchange, you trust the CME, you trust the NYSE, the New York Stock Exchange, you trust, you know, your bank, but to some extent. But here you don’t. In fact, you rely on arbitrage and people like liquidators to, you know, be able to earn a profit in the system to do the function that the centralized entity would do. So like, if I go on the CME and I trade ES, and then which is like the S&P 500 future, and I get liquidated, so like I took too much leverage, you know, my position’s underwater, the CME does the liquidation, right?

19:53 Or FTX, the centralized exchange, does the liquidation. But in DeFi what you have to do is you have to incentivize people, you say, hey, here’s some profit, people compete to do the liquidation to make the system safe again. And that part is quite unique in trading. When you’re simulating things you’re really modeling you know, little traders, medium-sized traders and big size traders. You’re not modeling the counterparty risk of the CME, you’re kind of like, the CME, I will sue them if they mess up, right, or something like that, right?

20:24 Here you’re modeling many different types of users. You’re modeling the traders, the lenders, the borrowers and the liquidators, arbitrageurs, people who are keeping the system safe, and so it’s way more complex because of that, even though the data is more transparent. So yeah, look, this is a super important point. And, you know, so I’ve got about 500 students that are in my DeFi Academy and I push them in to experimenting with these DeFi protocols. So they have to, you know, do a swap on, you know, a protocol like Aave, they have to execute a liquidity pool so they can at least have a sense of what’s happening.

21:00 And when they look at something like Aave you don’t see all those risks that you’re talking about, right? They see I can lend Ethereum or borrow Ethereum, etc., but you’re not going to be able to tell, like you said, all of those risks out there that are almost unquantifiable. When I trade on Wall Street, like you said, when I did a contract with the Board of Trade, the Mercantile Exchanges merged later, that was pretty good credit risk, right? They were good at what they did, they would do margin calls, you knew they would be there.

21:25 When it came to the trades we did OTC, we would post nothing, there was no information out there because that’s how we made our money, but also the counterparties were highly reliable because they were all banks, double A rated, single A rated banks, and of course the Fed’s watching everybody. We got risk committees that are coming down trying to watch us, you know, they do a pretty good job until something comes along like a black swan event and then it goes out the window. And but now you’ve got DeFi, where you’ve got markets that look similar, but like you said, there are all these different risks out there and very few people even understand what those risks are, and maybe that’s where you come in.

22:01 Yeah, yeah, exactly. Like the idea of using simulation in high frequency trading, one other thing that’s actually an a thing that it’s very useful for is giving you some notion of interpretability. So you might make a strategy that’s sort of this abstract math strategy, you take some signals, you like construct some, you know, prediction based on the signal, and then if the prediction says very high probability of something happening, you go do a trade.

22:29 That’s very abstract, you don’t know what the economic reason it’s doing something might look like, but if you run many simulations then you start looking on average, like, oh, it tends to be that this algorithm I wrote is really capturing the fact that there is a bunch of, like, there are a bunch of ETFs that are actually buying around the times I’m trading, and you can, like, go back and get some interpretability for what is actually happening. And so that is actually one of the more powerful things I think of, like, if you design these systems correctly, is you can get a lot of interpretability for the risks, you can actually, like, have a better handle on what the intuition is, and that’s sort of what we’re really focused on, those using simulation to make those things crystal clear.

23:12 But one other thing is it’s not just mitigating risk, it goes both ways. So the other way it can go is improving capital efficiency. So when the market is actually not super volatile, you know, if you’re an exchange like an FTX or CME you will basically say, hey, we’ll let you put less collateral up, right? DeFi protocols have to somehow adjust to that, right? And that’s the other side of the risk coin, is when it’s not risky you can actually offer better loans or better sort of forms of leverage in these systems.

23:50 And that’s clearly one of the things that DeFi is lagging in, and, you know, I think that’s what we’re focused on, helping people do that in a way that is safe, because, like, you can do that and then completely blow up. And we’ve seen, I don’t even know, tens, 50, hundreds of incidents where, you know, at the expense of risk people gave you good capital efficiency. Yeah. And one of my students asked me tonight, he said, well, if I’m letting my coin out on Aave, then, you know, at one point does it get liquidated, or how much collateral do I have to hold?

24:22 And I kept thinking, well, you know, Tarun usually comes up with that number, you know, because you’ve done all the risk analysis, simulation, and if you go to your website you can see kind of your, I think real-time look on a protocol like Aave or Compound, and you can see each kind of instrument, recommended levels of collateral and versus what they’re doing. And like you said, it’s not always about being too safe, because then you’re not maximizing liquidity or capital efficiency. And that’s what you guys do.

24:51 Can you walk me through even, like, a use case of something you’ve done for Aave or Compound where you could explain it to someone, like, for example, we looked at this and we found out that this was this and then we recommended they do this. Is that a good way to explain to people more of what you do? Yeah, sure. I think the simplest examples are things actually that are revenue related, which is, in these protocols, these protocols do collect some revenue for the DAOs.

25:20 So they collect some fees based on borrow demand. Now, one question you might ask is, what are protocols supposed to do with these fees? Well, they sort of act as a capital buffer or sort of like pseudo insurance. I wouldn’t call it totally like insurance, but that revenue that the protocol generates is sort of value generated for token holders. And one kind of important thing is that we make recommendations of how do you improve the capital buffer, how do you increase the revenue for the protocol without reducing borrow.

25:53 And there’s a couple levers for doing that. One is changing the collateralization ratio and the amount of interest collected. So maybe you increase the, you say, hey, you can take a riskier loan, you can put up less collateral, but the protocol is going to take a higher percentage of interest as a capital buffer, again to kind of control for liquidations or control in the situation where you have sort of like cascading liquidations. And you know, I think in a bunch of different cases we’ve been able to, like, increase the revenue for these protocols by, you know, like single digit plus millions, hopefully over time like that increases quite a bit.

26:36 And the idea is that once you’re really like increasing the revenue the protocol has and also over time improving its like insurance buffer, its capital buffer, then you can start offering more risky sort of parameterizations. But that’s the type of thing that, you know, we spend an inordinate amount of time really anal, like, you know, we have the platform that sort of ingests data from, you know, many different blockchains as well as centralized exchanges, tries to analyze and categorize different borrowers and look at, like, hey, this like really risky borrower just joined the protocol, like given that they joined, like under the current settings, like what’s the likelihood that if they defaulted they would cause a bunch of other people to default, to things like that.

27:21 We have this like sort of automatically triggered watching the blockchain, running the simulations, and then when there’s something more adverse go and send out the proposal. But you know, I think, yeah, building the infrastructure for that and making sure you can do all the monitoring, automatically run these simulations, you know, running tens of thousands to hundreds of thousands of simulations a day, and then you know from running those trying to say, like, under these different parameters, like, hey, if we increase the collateral factor by ten percent, or and then reduce the sort of revenue taken, earned by the protocol, what’s the expected sort of safety, value at risk and stuff like that. And so that’s the type of stuff we spend a lot of time doing in a way that is similar to how people in high frequency trading optimize their strategies, except we think of the DeFi protocol as doing a strategy.

28:14 It is a trader, right? It’s trying to execute some type of strategy. Yes, it’s trying to be delta neutral or trying to have certain types of risk properties, but it’s a strategy that needs to be optimized as a function of market data, user data, et cetera. And what’s been your biggest, I guess, learning or surprise, say, in the last 12 months? I mean, obviously these markets have rapidly accelerated since, I guess, like DeFi summer of 2020.

28:41 Well, you know, maybe walk me through that and even maybe the last, you know, three years since you started, because the market’s changed massively. Yeah, I mean, so when we started it was, you know, basically almost about to be the bottom of bear markets, like 2018, and the interesting thing was back then I really, really, really thought it would be proof of stake protocols that really had this financial risk, because that was how I sort of fell into this part. Part of the reason for that is that, you know, if you were to try to execute an attack on a proof-of-stake proof-of-work protocol like Bitcoin, where you try to basically borrow people’s miners in aggregate over the whole world, you would have to effectively corner the electricity market for it to be profitable, because you would basically need to go to every miner and be like, hey, we’re gonna sell you this derivative where you deliver hash power to us at some future time, but we will give you cheaper electricity, whether that means, you know, we sold you oil or we sold you a bunch of futures, things like that.

29:52 But in proof of stake that’s less true, the market for it is much more centralized in the sense that there’s a small number of venues. You know, the stakers want to earn yield, that’s why there’s this crazy explosion in staking derivatives, which, you know, I think I maybe wrote a paper on it a little too early before it kind of like became super popular, but like they, I think this idea that stakers really want leverage and yield means that they’re more easy to coordinate to do an attack. And in some sense that was how I got into this.

30:26 I think the thing that really changed my mind and needed me to warp my finance brain was Uniswap first, because, you know, I think to someone who worked in trading, especially, especially in, you know, more adversarial trading like high frequency trading, you know, Uniswap liquidity providers naively, it seems like they’re getting a terrible deal, right, on every trade. They are giving up the asset that’s going up in value for the asset that’s going down in value, and they don’t, like, adjust their strategy, they take a tiny fee, but like, hey, maybe it doesn’t work. But seeing that work in practice and seeing liquidity providers actually keep their liquidity there for a long time when we were analyzing their data in 2019 is what led us to sort of write, you know, probably the most cited academic paper in DeFi right now, which is on why Uniswap works.

31:19 But I think the, that was like the first surprise to me, but it, you know, it made me realize there’s this huge demand for passive investment products, kind of like there was in, like, the right after the financial crisis where, like, ETFs grew from like sub 100 billion dollars to like this like multi-trillion dollar asset class. And like watching the evolution of that, of like, hey, people really do actually want these passive products, like staking products. Staking products are kind of like the new ETFs.

31:54 They’re like Gen Z’s ETF in my mind in some weird indirect manner, and that part has been super interesting to see. In terms of, like, the non-DeFi stuff, I, you know, I I, you know, I’ll be the first to admit I don’t totally understand profile pic NFTs. It’s just not something I have a great understanding for, but I do think this idea that you know, NFTs serving as a form of sort of pseudo identity, not like strong identity, be it some form of identity, will interact with a lot more of DeFi and sort of bring us different types of products that might be more risky, but like, you know, you’re able to offer them because you have some kind of identity wrapper around someone.

32:44 Yeah, on that same note, I was speaking with Yat Siu of Animoca Brands, who’s in Hong Kong, and I was talking about, I think last week, and he actually credited DeFi with the explosion of the metaverse because he said if it wasn’t for the DeFi and all the borrowing lending protocols, then they wouldn’t have the liquidity or the demand that they have, and I was very surprised to hear someone in the metaverse say that. Do you agree with that? Do you think the will also come around and change the DeFi markets?

33:13 That part I’m not totally sure yet, but I would say the first part about DeFi kind of leading to the NFT boom is a hundred percent true. So I think a lot of people who made money during DeFi summer rotated a lot of that capital into NFTs, and pretty aggressively I would say, like a lot of the run-up, the first run-up, sort of like the NBA Top Shots post DeFi summer run-up in NFTs was driven by people who were kind of successful at DeFi summer. And then I think the second run-up in February was started more by DeFi off Ethereum on Polygon and Solana and Avax.

33:57 I think Avalanche may be a little later actually, but definitely Polygon, Solana early, and then Avalanche later. But like there, that led to another kind of wealth effect of people got rich off of that and then put it back into NFTs. So like I feel like there is, there’s this like, there’s a cycle of like something has a, people make a lot of money on it and then they recycle that money to the next thing, and then they’re sort of the next generation of people who kind of made money on the next thing and they recycle it, and there’s this kind of like weird capital wealth effect thing.

34:32 And I think one thing that’s interesting is in these communities, you know, if you can, one of the stickiest things for developers is basically you and make a protocol that kind of gets all the developers who are the first developers on their super rich, and then they stay, they quit their day job and then they start a protocol and then they stay in your ecosystem pretty captively because they got rich there. And I think that’s something that, you know, differentiates maybe like Solana and Avalanche from, say, Cosmos and Near, because there are just not as many people who on Tezos, like there’s just not as many people who kind of got squad wealth or whatever the current phrases out of that, and that doesn’t like lead to your ecosystem growing and then there’s this huge cycle.

35:27 But yeah, I think DeFi led to NFTs, which led to sort of DeFi on other chains, which led to like the bigger NFT boom that we saw. And while we’re on NFTs, I’ll just, I guess I’ll finish out with that. I mean, you’re right about who owns, I mean, we had Stani Kulechov in the studio and he has like 2,000 NFTs and he was showing me on his phone and he’s like, I’ve never sold one. And he said, Brian, we want to finance these some days the same way we finance fungible tokens, and you know, it’s a pretty bold aim.

35:57 Do you see that happening any time in the future? Will you be doing analysis with NFTs, or is by definition what you do have to be with something highly liquid like a fungible token? Yeah, I mean, so one of the reasons actually, so I, you know, I run this sort of small fund with Robert Leshner called Robot Ventures. One of the reasons actually we were sort of the first investor in a company called Fractional, which does fractionalized NFTs, is that I do think that the borrowing and lending markets for this for the NFT world will be quite different than the purely fungible world, but fractionalization is sort of a nice bridge because it allows you to kind of use the existing mechanics as long provided there’s like enough liquidity from the fractions.

36:50 And I think fractionalization will be kind of an interesting tool over time, as especially as we’ve seen people have these like collective ownership of NFTs, and that I think will actually be able to get into risk products. I think the other type of product will be a little more like a derivative, like a pure derivative rather than fractionalization. But yeah, I think financing NFTs is very similar to, you know, real life, you know, construction financing and large project financing, so it is the thing that resembles the majority of, you know, capital work that happens in the real world, because, you know, yes, over-collateralized lending like Compound, Compound and Aave is very popular in the real world, right, like home equity loans or like, you know, people borrowing against their real estate, but it’s not that big as a percentage of the market, right?

37:48 It’s like sub 5%, something like that. If you add securities loans it probably goes up to like 15%, but, you know, the rest of the market is really things like bonds, things that are like more unsecured credit, things like that, and I think NFT finance gives you the promise of you know, bridging the gap of the other 85% but for digital goods. Okay, that’s a really good perspective on that. You mentioned Uniswap, and maybe we should spend a little time on the phenomenon of Uniswap, and like you said, when you first looked at it you were not necessarily convinced that the small amount of premium you get as a liquidity provider would allow that platform to thrive, and it has.

38:30 I mean, it’s probably changed everything and I don’t know if anybody saw that coming in 2019. Maybe you did, but it’s something I try to explain to my students, you know, the cost of liquidity, and it’s really hard. When I was at Bankers Trust my job was to quote, you know, fixed floating swaps to these institutions that were speaking with our sales team, and I was going down to four decimal places on a swap. So again, it was fixed floating and it was a six year term and your rate is 5.64 31%, and if I was off I got nailed, and that’s what happens to market makers, you get nailed if you’re off and you take the hit, but of course you make the bid offer when you’re not.

39:09 And the closest thing I saw was when I go to visit Chicago and I’d see the 300-pound football, American football size player guys screaming in a pit who were creating liquidity for the market. That doesn’t really exist anymore in a physical sense, but they were being paid to basically make two-way markets even though big whales were coming in and the funds were coming in and Goldman Sachs was over here, they saw the information, but they only made that bid offer. And it was really hard to quantify the value of the liquidity, and that’s why when I saw what was happening in DeFi I was like, wow, they found a way to actually pay you for liquidity.

39:43 It was kind of mind-blowing to me because this never existed in the traditional financial markets, and maybe you can expand on that a little bit. And like you said, it’s not about theory, it’s really about practice and do people do it and does it work. So tell me your thoughts on that, and yeah, do you agree or disagree with any of that? Yeah, I agree. I mean, there, you, the adverse selection cost you’re describing is like very much a real thing when you’re doing trading, right?

40:11 At the same time, you know, it took me a while to realize that there’s, you know, the LP shares are more like ETFs than they are like liquidity provision. On Uniswap it’s a little bit more like an ETF than it is like I’m a market maker. And I think like from a sort of profit standpoint, and it took us about a year to prove like the mathematical formalism for like how you get to that and like how you can write the math out to show that it looks like an ETF.

40:42 But because of that, if you flip your mindset to something where it’s like, oh, I actually just want exposure to these two assets and I know I’m going to pay some holding costs, but I also don’t really want to think about which direction I’m holding, at the end I just want, no, I probably want both of them in some proportion, like the Uniswap, Balancer model actually just does kind of make some sense. I think the other thing that’s important to note is that there’s just, there are a lot of people who are more sophisticated liquidity providers, especially nowadays, and they really do migrate their capital from pool to pool trying to optimize the old, and I think that there’s the fact that there’s like a spectrum between the like super professional and the people who just want the passive exposure like an ETF.

41:40 It does resemble the normal market in, again, in a very similar way to how high frequency trading kind of like flatlined while ETFs bloomed, even though ETFs in some sense are kind of a money-losing asset to hold. There are a lot of ETFs that you can go find that don’t track the index, the thing they’re supposed to be matched to, they don’t track, because like every time they make a trade you know there’s like five hedge funds that know, like, have some model of like how to predict when that ETF rebalances and they front run them, right? That happens all the time.

42:14 Like I guarantee you that’s like 50% of like large hedge funds that do that type of stuff. And yet there’s just so much demand for that because there’s a ton of retail demand that’s like, I just want to own these assets and I don’t care that I’m paying more of this cost, because to me I’m like thinking on a long enough time horizon it doesn’t matter, and somehow that the LP mindset is somehow a little bit closer to that. So another thing we do, so we, you know, we have, we talked about risk products, but another thing we do at Gauntlet is incentive management, and what that means is, you know, how much should different protocols pay for liquidity incentives, like SushiSwap for instance pays rewards for different pools, and so for instance we help them manage like how much should they put in each pool.

43:02 Like you don’t want to give a ton of incentive to a pool that has no volume and there’s a random coin, whereas you do want to give a lot of incentive to certain pools, but not so much that there’s just a ton of capital sitting there relative to the trading volume. So we help them save like two, 300 million dollars of like spend because they spend a lot of money on attracting liquidity. And the cool thing from that is one of the things we’ve learned is there really are these like different types of liquidity providers.

43:32 There’s really like the never touches, they put it in and they, you know, they haven’t thought, they haven’t done the interaction in their wallet for a year, and then of course there are people who have made these sort of farming funds that are constantly churning through, and there’s a spectrum between those. And I think, you know, this is why I think the types of things are like simulating the users in these systems to understand, you know, what the incentive should be or what the risk render should be is kind of powerful, but it also kind of says something about the nature of these LP shares, which is that they really do have this like passive to active spectrum. That is, you know, I think that that’s something that exists in the normal finance world and is one of the reasons, right, like, you know, there are a lot of hedge funds who make more money than high frequency trading firms by just doing this ETF front running, right?

44:30 Is there, I saw a video that I think on Finematics about they were calling it DeFi 2.0, where you see a lot of new platforms coming in with kind of maybe second order ideas on how to incentivize DeFi protocols, whereas, you know, DeFi summer we saw some amazing things happen and obviously, you know, providing token incentives for different LPs and certain pieces, but now it seems like we’re seeing a whole brand new group of platforms that are almost offering, you know, offering completely new and very complex ways of incentivizing that even link back to their own monetary policy and burning coins and things. Tell me, first of all, what are you seeing out there, and do you think that this model will have to evolve? So the current version of, like, you know, an Aave or a Compound or SushiSwap will have to get more complex with more complex systems of rewarding to stay competitive with some of the new protocols?

45:24 I think one of the ways, you know, I don’t know if I like buy the meme that this is a version change that’s 2.0, but I appreciate there is a difference in some ways, which is a lot of the new protocols utilize their treasuries of governance tokens much more, you know, they take more risk with them, and there are a bunch of different meme names for the same thing that people say for this, like protocol controlled value and stuff like that. What all it really means is that there is a pool of capital denominated in potentially multiple tokens that the DAO controls, but the DAO is doing more aggressive things with them. So for instance, in the case of something like OHM, you could think of as, I’m going to ignore the OHM bond piece, but let’s just say it’s I actually, I’ll give sort of like the spectrum for them.

46:22 So OHM has sort of three ways of earning yield, real, real, realistically it’s more like two, two and a half, but we’ll, you’ll see why in a second. So one is you take the OHM token, you stake it and you just earn OHM inflation. The second is you provide liquidity in the OHM-ETH pool, and the third is what’s called a bond, where you basically say, I am willing to provide this much liquidity to this pool for a certain amount of time, and if I do so then I get some reward.

46:51 And the OHM mechanism is sort of, you know, right now kind of manual, but I think, you know, using, you know, things like, you know, things like what we do, you could imagine a system where you’re kind of, you have something that’s like dynamically switching between how much it incentivizes for each of those three to meet some objective. And OHM sort of does that manually, MIM does that manually, they all kind of have a bunch of this flavor. But there is some actual sort of unifying theory to this, which is that they’re using their treasuries more actively, right?

47:25 They’re using their treasuries to adjust these incentives and adjust risk parameters. Well, I mean, none of them are saying it that way, like if you read the docs, they, there’s a whole, like, you need to understand their vocabulary for, like, how they’re describing these things, but if you squint enough and read the code it really is this kind of, they’re using their treasuries more actively to adjust, you know, sort of incentives to different users, which the Aave, Compound, Sushi, Uni era protocols don’t quite do, like they don’t take risk with their treasury right now for the most part. Do you, and do you think they will have to to compete going forward, or is the jury still out?

48:07 Yeah, I mean, the thing is there’s different protocols for different risk levels, right? You’re going to have people further on the risk spectrum who, that these protocols will be, and then you’re going to have protocols that, you know, want to attract traditional capital from traditional finance, and they probably don’t want to be taking some of those risks, right? And, you know, it’s just like bonds, right? Like there’s tons of junk bonds, there’s tons of really great bonds, but there’s clearly a market for both sides of that.

48:37 And so I think they’ll coexist. I just don’t really get the point of calling it 2.0 as it’s not really that Aave or Compound or SushiSwap or Uniswap can’t do that, I think it’s that they don’t want to, like, actively, right, because it will add a ton of risk to their system and they’re trying to attract more conservative users, right, versus the DeFi 2.0 is really truly like the degen squared you know, user. So let’s talk about what you just said, is they’re trying to attract more conservative users, because this is a really important point and one that I get asked about a lot.

49:11 I was at the DeFi Live conference on stage talking about how to get institutions into these markets, and I’ll tell you true, and I kind of have two camps of people that have been on my show. I’ve got the Stanis and the Roberts of the world that say it’s all about liquidity, show that the liquidity is there and then the institutions will come, and then I got the, you know, Alex Mashinsky’s at Celsius that say show the KYC and the AML, and that’s the way that the banks and liquidity will come. I’m wondering what your thoughts are on this also.

49:40 I’m meant to ask this one question, you know, if SushiSwap didn’t call you up or Stani didn’t know who you are, I’m wondering if some of these systems, you know, would have the best handle on the risk management, whereas back in the days in a bank there was always a committee, the Fed was watching it. I’m not saying they did the best job, but at least there were people, it was a history of watching risk and understanding risk management, whereas in this space, I don’t agree with Gary again, so I don’t think it’s the Wild West, but there are protocols that start up that you probably see massive amounts of liquidity that aren’t even having these conversations. I’m sure you see that all the time, and it is that kind of weird that that can even exist, and will it all ultimately end in tears when one of them breaks and will we learn something from it?

50:23 So there’s a bunch of questions there, feel free to answer them. Yeah, you know, and however they come up. Well, you know, I think a little bit about you know, Mark Cuban losing money in the algo stablecoin Titan. Yeah, the Iron Finance. Explain what happened there, because Mark was kind of touting it, it was an algo-based stablecoin and then it all crashed one night, right?

50:52 Yeah, I mean, basically the liquidity dried up and like people couldn’t make money from arbitrage and then the price crashed, like at a very, these kind of system, systematic collapses oftentimes have this problem, which is one of the interesting things I think that the OHM, you know, OHM brand itself is a stablecoin, but obviously if you look at the price chart there’s no way any of the tokens associated are stablecoin, but the thing that’s interesting is it has this dynamic thing where it’s using its treasury to, like, adjust incentives. You know, is there a ton of risk? Of course.

51:27 I mean, you can just see that from, like, oh, you know, you can look at the data and it’s certainly much riskier than like putting your money in Compound, right? You can see that. And I guess you probably could, could you see Iron Finance from a mile away? Could you see that going on? I mean, the crazy thing to me was that they forked a code base that already had that happen, called Gaia, just like on a smaller scale.

51:50 Okay. But then they like of course did kind of better marketing, plus it was on Matic, so they like could attract more new degens, right? Well, because this space is a lot about marketing, PR, you know, some influencers and then boom, right? And very few people like you are running the numbers and even looking at the blockchain, which is public information, but most people don’t do that, right? For sure, but I do think that’s for a lot of the protocols that will in the long run attract sort of sophisticated capital over time, they will have to think a lot about this sort of risk and incentive management.

52:31 And you know, there’s two camps of viewing this. One is you start doing that at the onset, but then you kind of grow more slowly with liquidity, you have like guarded launches, you like make sure everything is sort of safe, and the other is the own model of get as much liquidity in the door as possible and then fix it afterwards. And you know, I think there’s both sides to that argument, like, you know, I think they both are valid ways of growing. I think it’s more about understanding your user base in that case and, like, what you’re thinking through who your user base will be in the future and I think that’s sort of one thing we’ll see more of.

53:14 I suspect there will be some crashes, but you know, I think, you know, I’m sure more people will talk to us because of that. But yeah, I’m excited for the DeFi 2.0 stuff though. I actually was kind of trying to write out some math for it this week and I, you know, I think there’s like a lot of good ideas there, they’re just like shrouded in like kind of mysterious vocabulary, and like if you get through that you can map it to things that exist in traditional finance and get a little more like, okay, I see why this is kind of working.

53:50 Behavior. So you know, to the Omi’s out there watching, you know, I think you guys figured out one or two things that a lot of the algo stablecoins did not. Yeah, I agree. When I first saw it I thought, hmm, probably can’t ignore these ideas because they seem like there’s some merit, but like you said, you know, vocabulary and language is everything, and in the beginning it’s hard to know what it is exactly, how it works and then how it actually works in practice too.

54:21 But yeah, I think there’s something there. What about the institutions coming in? I mean, you’ve worked on that side as well and so you kind of know how they think. Do you have any thoughts, any predictions? They are definitely coming in.

54:32 I mean, so for instance, D. E. Shaw, like, historically has always hated, like David, like the founder, always hated cryptocurrency and was pretty against it, and they are trading crypto. Okay, why did he hate it? You know, it gets back to this academic point I was making about, like, the you know, when the Bitcoin paper came out, like I think most people in distributed systems just didn’t view it as a viable thing because the there were a lot of errors in it and it didn’t, like, the paper and the code base are actually quite different for Bitcoin too, and a lot of the stuff that went into, like, actually getting it working in practice is what kind of helped it more than like the theory side of things.

55:22 But like, to distributed systems people it just sounded kind of like a crackpot paper, because there were at that time also there were a lot of like people who were, you know, making new databases and saying like, hey, my database, like, achieves like X million transactions per second, like almost a little bit like blockchain advertising now. But at that time, like, that was around kind of the, like Web 2, I guess, boom of like e-commerce companies, social media platforms, whatever. And one of the things that, you know, people were always like, you know, people wanted to build sort of enterprise SaaS companies at the time for was like building databases that had way better redundancy, more transactions per second, didn’t require a schema, like all these kinds of features that, you know, if you squint enough you can’t get all of them for free, like you’re definitely trading something off, but like venture investors didn’t really care, they were just like, yeah, everyone’s launching a social network, it’s gonna have 10 million users, so they like need a better database than Postgres at that time.

56:28 And so you had this kind of weird explosion, and a lot of academics, people like David, right, he was a professor at Columbia before, were very much skeptical of these types of databases because a lot of those turned out to not work in practice, right? And like they’d raise like 100 million dollars from venture investors and then crash, and so like academics tended to view those skeptically, and Bitcoin was in that camp. But I think, like, you know, the DeFi was really the thing that, for lack of a better phrase, killed a lot of the traditional finance people.

57:10 You know, I think Jump obviously was quite early, but I would say like people like HRT, even I’ve heard rumors of like Citadel are like really FOMO-ing in right now. Like HRT has a job description that honestly right now is one of the most hilarious job descriptions I’ve ever seen, because it basically asks for someone who is an expert in DAOs and DeFi who also knows hardware programming and then also, like, knows a lot of like data science, and it’s like very clear that they’re scrambling to hire anyone and they like made this ridiculous like unicorn job description, which, you know, there’s probably like two people in the world who fit that, who would never be working for them now. So I think there’s definitely a lot of institutions, but the institutions are more on the trading side and less on the brokerage side, right?

58:02 I think there’s also kind of, to your point, Reid Gensler, there’s this like old, older crowd, I guess, what I’d say, who are like the Fidelities and like the Gentlers who are like, Bitcoin is the only thing that will ever survive, and they’re gonna die on that hill, and that does mean that like, hey, it’s Fidelity and Vanguard, they’re going to be very slow about, you know, making funds, although I do think you know, they are like, you know, LPs in a bunch of funds that are investing in crypto stuff. I think the question is at what point are they willing to be like, hey, look, we don’t want to spend 20% on your performance fee and, like, we’ll do it ourselves. And I don’t know when that happens.

58:51 I do think they’re coming though, like way more than last time, like DeFi, you know, every fintech company is trying to put capital into DeFi, right, because they have to offer yield to their users, right? And they have no other, like, where else are they gonna get yield? Yeah, yeah, let’s talk about Gary Gensler, because you know, he called what, stablecoins the poker chips in the Wild West, you know, they’re threatening to regulate the lending of stablecoins, and yet you know, right now I’m 20 hours into a course he taught at MIT Sloan School in 2018 on blockchain, and Gary really understands, he’s one of the smarter guys that I’ve ever heard talk about this stuff, and he was working with Silvio Micali there and was quoting him on his cryptography, and he really explains it well.

59:38 This is before, I think, he was even at the CFTC and obviously before he was at the SEC, and so it’s very interesting to see him kind of agnostically talk about what blockchain was doing back in ’18. And yet now when he talks, well, he feels like a politician because I guess he is kind of a politician. It feels like he’s got a blunt instrument, a department that lacks funds, and he’s trying to do enough to scare people not to abuse maybe coin offerings, but also trying to keep the innovation going and maybe failing at both.

1:00:10 What do you see that maybe I don’t see in Gensler or the SEC, and even regulation as part of a cycle you’ve talked about before of bull and bear runs? So what are your thoughts? Yeah, I don’t, with Gensler I don’t exactly know what to make of it, kind of for the same reasons you do, of like he’s clearly spent a lot of time thinking about crypto stuff, but, you know, I certainly hope never to work in government, but so I don’t understand the pressures of actually working government.

1:00:43 I think it, I’m sure there’s, it’s more complicated socially, especially politically, socio-dynamically than any of us can see on the outside. That being said, I do find the stablecoins or poker chips thing kind of crazy, a little bit, because, you know, I saw a funny comparison where someone looked at like stablecoin volatility relative to like muni bond volatility for US municipals, and it was like they’re like way safer than some of these like triple A rated bonds, right? In terms of, like, you know, so I don’t really have a great understanding on of like why there’s this kind of push, other than, you know, the US sees a ton of capital moving into something and can’t tax it.

1:01:34 But you know, I don’t really know where we go with regulation, like I I do think one of the more interesting things, and we’ve written a bunch of papers on this recently, is, you know, what does privacy actually mean in DeFi? So one of the big questions hidden in all this regulation stuff is like where does privacy stand? So of course you’ve seen with Zcash and Monero, right, regulators really heavy-handedly killed them, where they like went to every exchange and were like, travel rule, you cannot list this, you cannot do this, and, right, and like they have really crimped the growth of those networks.

1:02:10 On the other hand, there’s a sense in which people do want, realize that right now DeFi is sort of weird, in that there’s absolutely no privacy, there’s like no privacy at all in any of your transactions, which is in some ways what government should want, you know, for their sort of poker chip monitoring software. But I do think there’s this bigger question of like what amount of privacy will governments tolerate in these types of systems, and this feels like the beginning of the war on that and at the beginning of like the war that will come for that, that, you know, we haven’t quite hit on the technical side yet, but in the next five years, like two to five years, I think we will, regulators will be much more, have to face that question much more seriously.

1:03:05 Do you think Gary’s saying these things about stablecoins because they see a stablecoin success competing with the digital dollar, which now will have to compete with the digital yuan, which according to Alex Mashinsky is the next World War Three, is a currency war of, you know, digital coins between the US and China? That sounds, you know, a little, every war since the 1700s is a currency war. That’s what I, I will make that claim. I love that claim. Can you talk more about that, expand on that?

1:03:35 Well, you know, the history of debt in the Western world is very much tied to wars, where different European countries would like borrow from each other to basically fund their war, their local wars, and I think the British were actually quite successful at being sort of the mercantilist lenders, and which kind of, I would say, to in part because they, you know, could tax far parts of the British Empire and then lend out that money to European people trying to fight wars. So I think there’s a very intertwined history. I’m trying to remember which book I read that was like it was this like historian that wrote this book about like how debts either caused or funded wars and the debts were all just like between these different countries, right?

1:04:26 And so you know, if you take a squint from that angle, and you know, everything kind of does sort of seem like, you know, it’s a currency war just in a, you know, slightly different form, right, and including US, China, right? It ultimately is, right, currency war, war. For sure. So I do think I could see, I could see the digital currency thing being that, but I don’t know how to say this in a somewhat polite way, but I feel like the people working in DeFi and like AI stuff are like a million times more competent than the people working on CBDCs and digital dollars, like just like the level of talent, the disparity between the level of talent between the two is so large that it’s really hard for me to imagine these government currencies really taking off.

1:05:17 Like it’s truly mind-boggling how much worse the talent that’s working on like the central bank digital currency type of stuff is. And I, there’s some obvious reasons for that, but there’s also just this fact of like I it does, this doesn’t seem like an appealing job for someone smart. Yeah, I mean, has the government or the US government you know ever executed anything with any degree of efficiency? No, probably you want a private company doing that in almost all well they’re going to subcontract it, you know, to like Microsoft or Amazon or whatever, right?

1:05:52 Like it’s not going to be that different than that. I think they’re going to try to do some stuff on their own and then they’ll end up just contracting out, but that’ll be true for China too. It’s just more like I don’t, I trust the crypto market, it’s ruthless, like ruthless lately progression to be to like outstrip the government efforts for a long time. I mean, eventually maybe they’ll converge in some way, but I just like the talent, like the developer talent and like talent that is going into crypto and AI stuff to some extent is just leaps and bounds better than the talent I think going into the government focused efforts.

1:06:34 And you’re saying lately you were impressed with how that’s progressing, or what did you mean by that, or how it’s moving? Well, I think like the fact that we’ve had this crazy long cycle since DeFi summer has just brought in way more talent into crypto than, you know, last cycle. So like as a barometer, you know, people who kind of win these like really like high prestige contests in high school, like the Math Olympiad, the Informatics Olympiad stuff like that, Physics Olympiad, you know, last cycle there were a couple people who came in from that side.

1:07:11 You know, of course there was some, you know, Vitalik is famous as being an IOI medalist, but you know, there are definitely a bunch of people who have existed in crypto and from that talent pool, and but like usually that talent pool goes to high frequency trading, becomes a professor, does AI. Like if I were to roughly hit them into three things, and this cycle I’ve seen many more people instead of go to either academia or AI, like go to crypto, and so that has been like a very interesting shift, and that’s what I mean by like the talent that’s coming in in the last six months to a year is like kind of, it really is like a big shift. 2017 there was a lot of people who are like, well, you know, I like trading coins, so I’ll do it as a side hobby, but I’m not quitting my job at DeepMind, right?

1:08:02 Whereas like this cycle is like way more like, oh wow, actually I see that there is a future here, and that’s because of maybe financial incentives with going with these companies, or the future is so bright, or the value locked of DeFi summer just showed everybody beyond a doubt. I think 50% is financial, but the other 50% is people seeing that there’s a lot of things that aren’t scams, right? You know, like again this gets back to this risk spectrum thing, there’s a lot of really smart people though who would in crypto land be the most conservative possible user ever, right, and they look at Aave and Compound and Uniswap and they’re like, okay, that’s safe, right, and they look at A, how much value is in there, B, how many people are using those products, which you know it’s not a lot by Web 2 standards, but it’s way more than every other crypto thing.

1:08:58 And I think like that, you know, then they see things like academic papers we write, or like research that’s like some of what Gauntlet does or other people who are doing research in a similar vein, and they’re like, oh wow, this is actually real. It’s kind of like the AI cycle in the 2010s when it like went from being like, oh, we’re never gonna actually implement these things in practice, to like, oh, oh, it’s actually possible. Yeah, and so I think that there’s also this vision thing of like it’s not just all like Ponzi schemes.

1:09:32 Yeah, and I hear a lot of that from, well, even the guests I have on the show, they all have their journey, you know, whether you started in ’11 or they heard about it, and I first heard about it in ’13. Max Keiser was on my show, he was screaming about Bitcoin and I bought some and then I didn’t, you know, do much else, and then Andreas Antonopoulos was here in 2015, ’17 and ’19 and he talked about the future, money, internet money, incredible ideas, but there was no DeFi yet per se and I didn’t really, it didn’t really hit. And everyone I’ve spoken to almost has that journey, but in the last 18 months so many people now are, they’re crystallized with the vision like you said and they’re ready to change careers, change everything, much more than 2017.

1:10:13 You know, I feel like me switching in 2017, all my, everyone I worked with in trading was like, you’re dumb, or like, oh, like why are you going into that scam industry? And so it’s kind of interesting to see that, like, this cycle people are much more you know, they’ve changed their tune. You know, like all these people who are like, ah, it’s a scam, why are you doing this, are like, hey, how are you doing, like, can we talk? Tell me your thoughts on the layer one wars that maybe we’re currently seeing.

1:10:40 I know you just were at the Solana conference in Portugal, everyone said it was completely off the hook and just so much excitement and development projects. We had Emin Gun Sirer here of Avax, former, you know, a fellow Cornell graduate like you. I had Micali on last week of Algorand, obviously we see what Cardano’s doing, we’re running out of Ethereum co-founders at this point, we see what DOT’s doing and a lot of their, you know, parachain auctions and stuff.

1:11:07 How do you see this playing out? Do you think this is now going to be a battle between, you know, less than 10 layer one solutions, and is one of them going to prevail sometime next year, or do you see it differently? Because this directly affects a lot of the companies you advise. Yeah, for sure. And so we, you know, we do, we’re on multiple chains now, so we support lenders on Polkadot as well as on Avalanche, and hopefully Solana soon, a little more engineering work than the other chains, so unfortunately that will take a little longer, but I would say that, you know, the interesting thing is going to be the like sets of trade-offs that each layer one specializes in.

1:11:51 So a one thing is like how good is the bridge and, you know, how well can I go across chains. There’s sort of this thing of like there’ll be different qualities of service, like if I want to do a bunch of low value transactions, like 100 transactions that I want to just like go between Matic or Polygon and Solana really fast because they both have low fees or something, I don’t need that much security so I’m going to use kind of maybe a cheaper bridge, but I want to send like 10 million of Bitcoin to another chain, I’m gonna use a much more secure bridge, might be way slower, might be more inefficient, I pay more fees, something like that, right? I think the bridges will dictate how usage exists on these chains to some extent.

1:12:40 I think like each of them will have their own things they’re especially good at, like better chain for NFT gaming, better chain for whatever, you know, but how good the bridges are to them and how close the liquidity is to sort of the applications on that chain will dominate everything, and it’s still sort of, I would say the, you know, it’s not clear that there’s like a very concentrated end state for this. It could be quite diffuse over these chains. I think the real question is what developers want in the long run, like do they want something where it’s really hard to develop for, like Solana, but the UX for the end users snappy, even though, you know, let’s ignore the decentralization piece, let’s just think about it from a product standpoint first, obviously they all have very different trade-offs in that spectrum.

1:13:39 Yeah. Or will it be, hey, they want to just be able to jump from each chain to each chain to each chain, so it needs to be some EVM compatible thing that has a really fast bridge, so maybe that’s Avalanche or Polygon to some extent. Or is it going to be a privacy thing, like people, the highest value transactions want, are willing to pay for privacy, so there’s like a side chain that’s focused on that. But yeah, I don’t know if I would say it’s clear, like you, you know, I think the best developer experience of any chain, period, is probably Near, and I’d say like sort of Polkadot’s probably second in a lot of ways, and yet sort of you know, it’s not clear that like those two are, that’s like the dominant thing that people care about, like in the Solana case it’s like people care about the allah, people building on Solana, you know, certainly they got rich from SOL price going up, so that’s why they’re attached to the ecosystem, but the second thing I think they do care about is the fact that, like, in the Phantom wallet, have you ever used Phantom?

1:14:45 I haven’t actually used Phantom, I’ve heard the UX on Solana is really good, but I haven’t used Phantom wallet yet. You should try. I mean, it will feel like you’re using like Square Cash or Venmo or something. It is, is actually Venmo’s slower than Phantom, like Phantom does actually feel almost like it’s, you know, a very fast app. Okay.

1:15:06 Of course, you know, again, you’re trading off some decentralization, yada yada, there’s caveats, but it is interesting that, like, you know, a lot of the developers focus on the fact that the user’s UX is great even though the developer’s UX sucks, and there’s now this like trade-off surface there. So I don’t, I don’t actually have a super strong opinion on whether it’ll be you know a small number take all the win, or sort of win, or whether it’s sort of going to be this extremely diffuse thing, but I do think the bridges are going to be the most important thing because they are the way that liquidity will be able to move throughout this ecosystem more efficiently, right? Yeah, those bridges are interesting because I mean you, you know, you deal with a lot of companies that are bridges to a certain extent, not between chains but, you know, between different types of users and each other, so you kind of see that there’s not very good bridge technology out there right now between these chains, are there?

1:16:08 I mean, trying to move things, I think the Avalanche bridge is interesting, it makes a decentralization or sort of not even decentralization but more like a security trade-off because it uses Intel SGX, but it has really good UX because of that. I think in Solana’s case the bridges are always going to kind of be worse than other chains for a couple of reasons, just like their choice of virtual machine makes it a little bit like annoying, also being at really high latency or low latency means that it might be hard to like synchronize like the really slow chain with a really fast chain, for a bunch of different reasons, and like the UX won’t feel the same necessarily for the end user. And I guess like, yeah, one interesting thing about bridges is that it’s very clear that right now the bridge UX can be more valuable to the end user than the yield, because a lot of people have had bad experiences on bridges, like they sent a transaction and stuck for 30 minutes, they’re like, this, I’m like gonna go somewhere else, right?

1:17:17 So yeah, I think like that’s going to be an interesting way that players build moats for themselves, which is really having excellent bridge UX. Yeah, the UX might be more valuable than the yield, like up to some point, like obviously. Yeah, that’s really well said. Yeah, and again, I mean, I’m putting a lot of students for the first time on some of these, you know, DeFi protocols and dapps and I see their experiences and I see them obviously complain about gas fees and I can see exactly what you’re talking about, whereas they would give up a lot of things consciously or subconsciously for a good UX.

1:17:55 Google did that famous study where they found out that the faster their returns were for searches the more people said they, they didn’t realize it was the speed, they just said they liked the search better, but it was actually the speed that it was the only thing that changed and they didn’t know that. It’s like when you watch a movie with bad sound you stop watching it, you know, but if it’s got really good sound you might give it a little more time. So yeah, these are good things for developers to remember when they’re trying to do so many things at once.

1:18:25 I mean, you must bump into people out there that are trying to do so many things, they’re trying to innovate, build the developer experience, the user experience, trying to get traction, trying to get liquidity, trying to make sure they don’t get hacked, and then you’re trying to convince them but also you have to look at your risk metrics. I mean, it’s a space that’s going very, very fast. I think bear markets and corrections are always very good for this type of stuff.

1:18:47 Okay. You know, I think we’re gonna, the best products, if we think about the products that are the most copied, the most copied smart contracts on Ethereum, Uniswap v2 and the Synthetix minter contract, so the Synthetix minter contract with the liquidity provider rewards contract, which you know, you become a liquidity provider and then you stake it into this pool and now you can earn rewards from the, those are the two most copied things and on every EVM chain. And you know, they were both built at the bottom of the bear market, the Synthetix minter contract came out like peak COVID, like March 2020, April 2020, and that was like very much bear market time for crypto, and so I think that that tells you something about like a lot of the new products were kind of derivatives of the stuff built in the bear market.

1:19:43 There are certainly some that are fully new, but I would say like the majority are more like derivative products right now, and I think a little bit of a correction, I’m not saying like, you know, we don’t need to go through a full cycle again, with a little bit of a correction would go a long way to cutting the noise and like, you know, getting people to like really kind of focus on on building good products. All right, and so when’s that going to happen and what does it look like in your opinion? I walked into that one, didn’t I?

1:20:13 I was going to ask you, I was going to ask you guys because you’re one of the few people that frankly talks about this, and of course you started your company in a real bear market, so, but you do talk about this quite often, so, you know, and it’s a good thing to talk about. I like to see corrections in markets. Yeah, I think like even historically in tech companies, you know, if you look at a lot of big tech companies, a lot of them were started during like recessionary downturn times.

1:20:37 So there’s a lot of benefit talent-wise, sort of like competition-wise, noise-wise, like there’s, you know, it’s actually just easier to kind of like make a brand, whereas, you know, right now if I’m XYZ DEX 599, like I don’t, like, you know, there’s like so many random DEXes at this point and none of them seem to be very differentiated, right? But I guess I kind of think A, the US law, the final form of it certainly will probably affect people, mainly LPs, right? Like I think like LPs and these funds will like redeem and stuff like that if the tax laws are changed in a certain way that’s not favorable to them.

1:21:30 I think some regulatory things, but it’s not very clear which ones will also be kind of in that boat. Okay. But I don’t think it’s going to be I think it’s going to be more nuanced than last time, where it was just like, oh okay, like SEC is going after Telegram. I think it’s going to be much more like a very nuanced type of enforcement that will maybe cause some causal correction, but the tax stuff seems more likely to be the first mover. Okay, and does that also mean markets correct by 50, 60, 70% and that stays down for six months?

1:22:19 I mean, is that what this looks like as well, or I hope it’s a six month thing, but it really depends on interest rates, like if the Fed just suddenly like does get out of the zero interest rate world, I mean I don’t think we know how to respond just like as a species collectively to that event after having just been, you know, been what’s the phrase I want to use, like a boy duck, like a force-fed duck, you know, right, all of a sudden you’re like let off the hook, you know, I don’t, I think that that’s kind of the chickens are going to be running headless not knowing what to do when the interest rates go up, right, because we’re not ready for hard times anymore because we haven’t experienced them in a long time. Yeah, exactly. And also, like, I don’t even think people, like, people also shifted all their products and, like, businesses away from assuming that that would happen, right?

1:23:18 Like those things take time to recalibrate, right? A couple final questions, you know, you also invest in, you know, Robot Ventures with Robert Leshner. How do you look at investing, what do you like to invest in, how do you have the bandwidth for investing is another question. Yeah, you can speak on that. Yeah, I mean, the nice thing about being in crypto and kind of doing what we’re doing, right, you can think of it as like we’re already kind of doing due diligence on a lot of things, so it’s kind of very natural to think in terms of investing.

1:23:52 I honestly, the number one investment thesis I have is a very boring one, but it’s one that I think is, you know, is important, which is I will always invest in the MakerDAO mafia. You know how they like, there’s like the PayPal mafia. Yeah, I think the developers from MakerDAO who start things on their own are really, really good at building things in the space, and that has been one of the main things. I think the other thing is like, hey, if it’s a cool new mechanism and there’s a sense in which the team is compelling in terms of development talent, that’d be great, but right now it’s like extremely frothy.

1:24:42 I like this really does feel like 2017 frothy right now, because there’s a lot of teams raising money that have like, you know, basically no technical talent, kind of derivative idea, and yet can like go raise a round. So we’ll see. I’m, you know, it does feel like a lot, it does feel a little bit like late 2017 in that regard. Okay, I appreciate that insight. You mentioned MakerDAO, I mean, do you think in the future we’re going to see a lot of these, you know, these blockchain protocols move into DAOs and be completely autonomous, and again that’s a lot of what you do is this whole concept of, you know, governance and them ultimately making decisions.

1:25:27 I mean, we’ve really never seen this done in practice for years on end. Just any thoughts on how that happens if that happens, and I guess how you guys help make that happen? Yeah, I mean, I think at some level we’re still just at a point in this market, and I think this will be true for a long time, where you really do need to do a bunch of off-chain orchestration, analysis, logic that can drive sort of on-chain behaviors. I think over time as there’s more chains and there’s more bandwidth, you know, in terms of like block space that can be used for this type of stuff, you can start incrementally building more complicated mechanisms, and these mechanisms, you know, can be, you can think of them a little bit like a controller that, like, a robot has, where, like, hey, you throw something at the robot and then it like has to like figure out, it like, you know, the robot arm will like do some tiny amount of measurements and then based on that figure out how to position itself to say like grab a ball, something like that.

1:26:27 And these DeFi systems will look a lot more like controllers, where they’re able to like take data from other contracts and then try to adjust themselves, and we see a little bit of that, right, but none of those are really secure and battle tested yet, and also there’s just not that much computational bandwidth and storage bandwidth. So you know, I’d say we’re still a long way off from like the fully, fully autonomous vehicle, let’s say. Okay, but it feels much more like in this world I’m much more bullish on fully autonomous entities in crypto than I am in, say, autonomous vehicles.

1:27:06 My co-founder, for instance, used to work in autonomous vehicles like at Uber, so he can also attest to this, that there’s a lot more hype there than reality, whereas I think here you know, the progress made has actually been quite astounding in terms of, like, even just getting to the point of having governance, getting to the point of like automating a lot of features of things in finance that quite frankly normally are done by lawyers and manual. Yeah, I’ve heard you talk about before, all these innovations are basically just getting rid of layers of lawyers throughout time and replacing them with tech. I mean, maybe besides currency wars, that’s all innovation is, maybe getting rid of lawyers.

1:27:52 Yeah, yeah, in some ways it’s capital triumphing over labor in some indirect manner. Last question, what’s your biggest challenge right now as the CEO of Gauntlet? You know, is it recruiting, is it bandwidth, is it the next bear market, like what are your challenges? Yeah, I think it’s just like scaling, you know, kind of like growing to taking on as many customers as possible and building out some new sets of products. You know, in the long run I really think that hopefully, you know, by establishing a lot of the standards for measuring risk that, you know, we can over time start really helping ensure these protocols in a way that’s more, you know, closer to what people are used to in terms of that type of protection.

1:28:45 So really scaling and making sure that we can get to that goal of, hey, are we like, you know, do we have enough research tools and risk tools to get to the point where, you know, DeFi, you know, we’re able to cover a bunch of different types of risks in, you know, tens to hundreds of protocols and then also, you know, provide, figure out how to provide the right capital buffers. Do you have to turn business down all the time? That’s that’s what I figured.

1:29:22 So because like you said, I mean, you know, you go do some work for SushiSwap and it’s like, we’re, you know, saving you 200 million dollars, it’s like, you can, it’s real world applications and it’s in real tokens and real value and real user behavior, and now there’s all these new layer one solutions, like you said, all these new protocols, and not all of them know they need your help, but I’m guessing a lot of them call you. Yeah, yeah, yeah, for sure. And you know, the cool thing about crypto, you know, is that, you know, when I was, you know, graduating college like the cool thing was always to go into AI stuff, and you know, everyone at the time was like, oh, like there are these AI companies, they’ll like do tons of awesome research, but like they’ll productize it and find a way to be a viable business.

1:30:12 And you know, if we look back 10 years, right, DeepMind, OpenAI, places like that did not figure out how to monetize, they had to basically get added to like one of these big companies. But you know, my dream is that we find, you know, we’re one of those but with a business model because it’s crypto. Yeah, well, you’re, it’s already quantifiable, isn’t it? That’s what makes this like fascinating. Well, look, it’s a really interesting industry.

1:30:36 Any other final thoughts or anything we didn’t cover, or for people that are tuning in that might be new to a lot of these concepts, any thoughts for them? Yeah, I think the best thing to do is actually to follow a lot of the developer podcasts because I think it cuts through a lot of the noise. And so I think like podcasts like the Zero Knowledge Podcast, highly recommend, especially if you want to understand the privacy side of things, because I think, you know, I think, in my mind, you know, right now the current thing is like DAOs, of course, because of gals buying real world assets has been like a big thing, but I do think we’ll get back to privacy.

1:31:16 You know, I think privacy in the next year or two will be the meme du jour. So okay, super helpful, and I appreciate you talking about some of those trade-offs between, you know, centralization, user experience, speed, it’s all going to become very interesting in the next 12 months, to say the least. Tarun, how can people get a hold of you and find out more about Gauntlet? What’s the best way, Twitter or website? Twitter, Twitter.

1:31:39 My name, Tarun Chitra, T-A-R, U-N-C-H-I-T-R-A, sorry, not anon or cool, because I made my Twitter 10 years ago, and Gauntlet’s Gauntlet Network on Twitter, but gauntlet.network. But definitely happy to chat and looking forward to talking to anyone who found us through the show. And you don’t have an NFT as your profile picture on and, well, it is an NFT, but it’s not, it’s not a like it’s not one of the big collections, it’s actually this artist who makes profile pictures based on you, but makes a pixelated version of them and then they turn it into NFT.

1:32:17 So oh nice, yeah, it looks pretty cool. So you have to hit me up with that artist, maybe you can do something with my profile picture. So look, Tarun, I really appreciate you, appreciate the work you’re doing, it’s really important and really next level stuff, and I know a lot of people in my academy will find this stuff really helpful when it comes to understanding these protocols, and I have too. So thank you so much. Follow this man on Twitter and check out his website, and hopefully he’ll return your call because I know you’re super busy.

1:32:41 But thanks so much, and next time let’s do this in London in the studio, and wishing you all the best. That’s good. All right, great. Thanks, everybody, at London Real. Stay with me here, we’ll see you all next time.

1:32:50 Take care, have a good weekend.