Prashant’s entrepreneur calling
First blood tasted for entrepreneurship at Facebook
India’s entrepreneurship environment’s evolution
Identifying problems and start building solutions piece by piece
Heru Finance’s nique architecture
The Signal to Noise Ratio
The changes that are essential to evolve the algorithmic stablecoins scene
The emphasis on understanding how to create a scalable model
Ultimately, This Is How Things Will Be
Read the best-effort transcript below (This technology is still not as good as they say it is…):
Prashant Malik 0:03
Hi, this is Michael Waitze and welcome back to the India GameChanger. Today we are joined by Prashant Malik. Did I get that right that I get your name, right? You’re the founder and the CEO at Heru Finance and the Founder general partner at Tykhe Ventures was like a minefield for me to even try to pronounce things. I hope I got it right. Anyway. Prashant, thank you so much for coming on the show today. I really appreciate it. How are you doing?
I’m doing awesome. I am doing super. And I’ll tell you, I find these days like this is my third or fourth recording today. And I find these days when I record I get into this groove. And I love doing it. Because I get to learn from some of the smartest people in the world. I mean that and I feel like super lucky that that’s actually the case.
Michael Waitze 0:44
Anyway, before we get to the main part of this conversation, can I get some of your background, just for some context,
Prashant Malik 0:52
I am a guy who was born and brought up in Delhi, in India, from my teenage times, I was very academically inclined, mostly a topper in the school and that kind of guy, then I went to one of the top institutes in India, IIT Delhi, computer science was out of there in 1995. And then after a short stint in India, I went actually to the US was at Microsoft, Redmond campus, basically, in the court systems group where actually my computer science running started. That’s where I learned a lot of the tricks of the trade and how to actually write good code and work with some of the who’s who, when the technology Well, that was actually when I initially went there, it was when NASDAQ was kind of going up and up. And then that dirt crash kind of happened. What year was that? So this was the 97th, that I went to Microsoft, and then 2000, I saw the peak and the crash, and everybody was getting laid off from all places and joining Microsoft, because that was the only stable place where you could be. So that was good, in a sense, because a lot of great minds kind of came there. And we built a lot of good stuff was granted a number of patrons there. But there was always this thing that was in my mind to kind of go into a startup or go into a small company make it big, and which startup I should go to and things like that. So I actually made a list of startups that I wanted to join in the US or in India, in the US Go ahead. And then at the top of my list was YouTube, second was f5 networks. And third was actually Facebook. And I got through all three, and ultimately ended up joining Facebook, because YouTube was already acquired by Google, right. And I thought was a more infrastructure company in that sense. And Facebook, after talking to Mark, I couldn’t stop myself but join phase. So this was very early days at Facebook, and I it was 2006, less than 3040 people were there initially started building the search algorithms for them. And then actually, there was a huge problem at Facebook, which was about data. So somebody had to take that up and start building a new kind of database so that new applications could be built. Yeah, that’s what I did. I took up that hard problem and started building something called Cassandra. Yeah. And then was not sure whether it will ever be built. Because it was a very, very hard problem. And even though I had confidence in it, nobody around me had confidence in
what does that mean, though? Nobody else had confidence in it.
People were like, Yeah, I mean, you should try this out. I mean, you might be able to build it. But it’s really hard. And only Google has something called big table that’s also built by PhDs from who have done this in Database, Data and database. And I was like, Okay, let’s just try to see how we can go about it. Luckily, I was joined by another friend of mine from Amazon, who had worked on something similar, which was dynamo, and we married your ideas together, and ultimately ended up building Cassandra, which was hugely successful, clearly. Then we open sourced it and I had really no idea that it’s gonna get so big. And every Tom, Dick and Harry kind of I’m onto that bandwagon started contributing into the code. today. It is like almost ubiquitous database out there. Used by the likes of Netflix, Instagram is completely built on it, Apple cloud runs on it, even in India to kind of uses it in there. So that was my claim to fame in the technology world. And I also started believing that I could create great things. That gave me a lot of confidence, actually, and it actually changed my personality in multiple ways, too.
Can I ask you this when you back in 1997 It doesn’t feel that long ago to me and maybe it doesn’t you either, but I’m super curious about this. You graduated from IIT Delhi, right? You’ve always said like you are academically inclined. It’s weird, right? Like going through the early part of your life kind of knowing you’re super smart. It’s an interesting thing and you don’t have to respond to that but just like that is what it is. Right. But back then a lot of your peers did go to through the IoT system and then say, now I can go to the Redmond campus and work at Microsoft. Now I can go back then nobody wanted to work at Apple, because it was almost going bankrupt in 1997. But you went there instead of staying in India to work for a big technology company there. And I feel like that bit has flipped. But there are two things that I want to ask you, because I want you to get to that in a second. But the first is when you got to Redmond, you said, Now I really knew how to do computer science and write computer programming. What was the adjustment like for you? You know, because being in Delhi and being in Redmond, it’s like, night and day back then? No, what was that? Like?
Yeah, that was my first time out of the country. I was very, very protected kind of guy who because my home was also Delhi and my college was also Delhi. So I never really been out to that was a big change for me, in all respects, both personal and in terms of professional too. So I had joined something here in Bangalore, which was also a tech company called Siemens, which was probably the one of the very, very few tech companies building technology in India. But Microsoft was totally another ballgame. I mean, it was like, actually, you got to know how what software engineering is? Yeah, there is one thing about writing code learning to write code, we’re there and building stuff. But there is software engineering is a totally different ballgame. When you actually kind of need to understand how you work in teams, how you write stable code, how you make sure that your code doesn’t crash? How do you make sure that when your code is put into a system, which is used by billions of people is still working? What are the repercussions if it doesn’t, and those are the kinds of things that you kind of learn, especially at a company like at the scale that Microsoft used to operate there. So I mean, I build very challenging product projects, even at my my school, or the college time, and even even in the company that I was working in India, but this kind of thing I was not really ready for or had seen. So that was, I think, the big eye opener or big learning for me as to how to really write code that people use.
Yeah. Were you surprised by the scepticism at Facebook? You know, when they were 40 or 50? People there, right? All of them should have been super smart. But were you surprised by the scepticism like hey, I can build this thing called Cassandra, I can do this thing. And it was it like, I won’t say the first time in your life, but like, Was it one of the first times where people were like, yeah, maybe you can? Maybe you can’t? Let’s see, do you know what I mean? And then having to react to that?
Yeah. So actually, I wouldn’t say that, that I was surprised or anything, because the problem itself was huge. And even in big companies like Microsoft, it would have taken a team of hundreds of engineers to kind of build something like that. Okay. So actually, it was a very, very good environment in a way, because I don’t think I could have built it in any other company, apart from Facebook, because there were so many smart people around. And even though there was scepticism, there was this always that belief, because not only I was doing this kind of project, but there were other people doing projects, which were kind of impossible in nature, in building things like two people team trying to build the entire New Street project are two people trying to build the entire data platform for storing all analytics and all that stuff. So that was kind of the norm there. And that was actually a big change for me, because so far, I had worked in a company like Microsoft, where everything was very organised, right? There was a product manager, there were test engineers. There were 20 people team, there will be discussion, there will be papers written and then you actually get to code that what you are here, it was like one building.
But does this inform the way you think about building your own businesses? Right, because one of the things you said was, it changed the way you were as a person, I completely understand this. Like, as I said earlier, like you grew up as a kid, you’re always smart. You go to it, like these expectations, and probably been on you your whole life, right? But then you go to the US, you get to Facebook, and they’re like, Cassandra, you go through all this thing, you build this thing that ends up being huge. You’re like, Okay, wait a second, I can do big things. Like I always thought I could. But now I actually did. So what else can I do? That’s really big. Like, do you have these thoughts? You know what I mean? Yeah, I
think that was my first blood tested for entrepreneurship. Really? Yeah. Where, where it is, like you’re building something from scratch, and you take it out and it gets big. That is ultimately what entrepreneurship is, right? You start building something. And people kind of are sceptical about it. But ultimately, it gets built and then it gets popular, right? That is ultimately the pleasure of entrepreneurship or startup at the end of the day. And that was my first blood tasted at Facebook, and I never went back after that. So after that, I’ve always been an entrepreneur. So at Facebook after the Khazanah thing, I was leading one of the largest teams there which actually will The entire backend for messenger chat functionality and all that. And then close to the IPO I caught out. It was all about doing something of my own
right. Yeah. I mean, once you figure it out, you have all these ideas. And you’re like, I want to implement my own ideas. Yeah. So that’s awesome. I asked you earlier, and I want to just re address this, this idea of when you were a kid, right? The idea was to get educated go to the US. And I said that that bit had flipped, isn’t it? Now, I don’t know if this is the right way to say this. But now it’s so exciting to be in India, be educated in India, and then build in India as well. Is that fair?
You’re absolutely right. I see all these kids coming out of the IDS now, and I feel a little bit jealous. And also, I feel that these guys are so fortunate. There are so many opportunities in India today. In fact, much better, I will say that I’m going to the US. And they are doing great hair. I mean, in terms of entrepreneurships in terms of the kinds of things they can work on. In my days, there were just one or two companies that also you would always be thinking, Did I make a compromise, saying things like that, right. But in today’s India, I mean, it is actually a compromise to kind of go to the US in a certain way or the other. I mean, if you want higher education or something us is still a good option. But if you want to get into the entrepreneurship world, I think India is a much better option today than it was. And I would make
the case that technical education that you get at it Atelier it, Mumbai or any of the it is right is equivalent to what you get at Stanford at Berkeley or at MIT. Like I don’t think that that’s an argument anymore. And here’s the thing, too, I don’t know what your family was like. But when you were a kid, and kids like you that were growing up with you, they probably had to convince their parents like, Oh, I just want to go to California. I just want to go to Boston, I just want to go to Chicago. And now the parents don’t even have to convince the kids to stay home.
Right? Yeah. Yeah. No, that’s That’s very true. Very true. And yeah, I mean, I think India’s India’s doing great in terms of developing Thailand in terms of developing new kinds of companies, lot of good startups are also coming out of India. No, so yeah, I think it’s only it’s only going to get bigger and better for him.
I think so. So what are the two things you’re working on right now. And then maybe you can tell me how they’re related to each other.
So actually, the two things are one thing only two hander. So I will tell you about first, the goal is please, all this relationship kind of happened. Part of the goal that we are working towards is what we saw is that there is a huge gap in especially the tokenized world where we have seen companies that have been built on the trading platform like Coinbase, coin switch, Bonanza, all these guys are trying to build one pillar of this financial system called trading, then there have been companies that have built the lending and borrowing and those that kind of pillar, which is done mostly by the protocols like eBay, and Goldman Sachs is also big time into it. Then there is this whole stable coin things which is which is done by circle and all these companies. But there is nobody is thinking about the serious money that is about to flow into the tokenized world. If you look at the traditional world, a lot of the wealth that actually gets invested. And since you have been in Morgan Stanley, and Goldman Sachs, you can vote for it, that it goes through wealth managers, wealth managers are the guys who actually do the investing, serious investor actually gives their money to the wealth manager. And the wealth manager is the guy who’s actually really interesting, this thing is not yet happened in the tokenized world, they are going and trading, you are going and doing trades. Nobody does trades directly. Nobody buys stocks directly or creates a portfolio or things. When you have serious money, or to be invested, you rely on somebody to do that for you. You rely on a fund manager, you rely on mutual funds, you rely on hedge funds, you rely on wealth managers to do that. That entire piece is kind of missing in the token as well. And as more and more money flows into this ecosystem. That is what would be needed. Yeah.
So let’s back up a little bit, right, you can go all the way back probably to the 1950s or 1960s. And say, like back then the stock market in the United States, and let’s just use the stock market as an investment view as a proxy, right for just like investing at scale, even though there are plenty of other things in which you can invest, including real estate and futures and options and a whole bunch of other things, right. But when Vanguard were started, the idea was most people don’t know how to invest at all. Let’s just invest in the Dow Jones Industrial Index, give them access to that, and then we’ll take care of it for them. And then if the index changes, we can do index inclusions and exclusions, like we can do all this stuff for them. And as that started happening, you got this massive development of the financial system, which in a way didn’t exist, there were banks, because Glass Steagall said that by banks could not make investments, investment banks had to do that all this stuff was separated. That changed in the 90s. under Clinton, but we can get to that too. But I feel like what’s happening in the crypto and in the tokenized world, which is probably a better way to describe this is happening all at once. I think you’re right, right. So everything that we saw happened in the financial system now says tokenization, is going to financialized. Is that the right word? Everything? Is that fair? First, it’s just an assumption.
Yeah, that is actually our first assumption, that is very luncheon that we are making, everything that is out there is going to get tokenized, including the real estate, including the art, including the museums, including even buy buy parts of aeroplanes or whatever. I mean, everything is going to get tokenized.
Yeah, I mean, I used to look at the financial system and think, I didn’t realise that airlines didn’t buy the planes that they just leased them from somebody who bought them from Airbus and Boeing. And I thought, how can I but there’s no way for me to invest in that. But now we can
use that as the kind of things that will be available to the investor. I mean, all these things that have uniquely been out there for maybe institutions to get into will be out there for investors to invest because of tokenization. So when
you tell me is you’re trying to build a vertically integrated, almost like financial institution that handles the front to back for something that is almost exists, right? In other words, we know, because we’re involved, but like the rest of the world doesn’t understand what tokenization is going to be. Maybe you can talk about that a little bit. For people that don’t understand, do you know what I mean? Because you already mentioned stable coins, we can talk about that, too. But I want to talk about this idea of what does it mean when something gets tokenized? And why does it matter? Right?
So let’s say there is something out there, let’s take our typical stock. Okay. Let’s say it’s the Apple stock, which is available at $2,000. And you can go and buy that. But what if you wanted to invest 10 rupees into an Apple stock? How would you be able to do it? The only way you can do it is if I were to create tokens, or or or split the Apple stock into small small pieces, and be able to give it to the user and that is nothing but tokenization. Similarly, for real estate, right? What if I wanted to buy a big flat in Manhattan? And now there is no way for me to do unless I have $50 million or, or more. But what if I know that Manhattan is going to triple or goof 10 times or whatever, I believe in that real estate, but I want to invest? How do I invest? So if I can invest $50,000 $10,000 $20,000 into Manhattan’s Real Estate, that is where tokenization can get us by splitting things into small small things, and giving the ownership to the users. And this is not just for for for the sake of investment. But so we have recently invested in a company, which actually tokenize these songs or makes NFT use out of them, for example. Let’s keep it as tokenization. So small singers who used to raise money used to find it very difficult to raise money from big music labels. But now they can say, Hey, guys, by my token, if I get popular, you get benefits. So it’s an easy way to raise money. So things like that, get a label.
I’m just thinking I’m not ignoring you. Right. And you did this. I thought it was super interesting. You said let’s not talk about NF T’s let’s just talk about tokens. And you know this right, but maybe the listeners might not mean NF T the T in the NF T stands for token. Funny, right? But tokenization also allows access, right? So this is really important to me in that, like you said, just as synthesise what you’re saying here, this idea that like, if I don’t have $50 million, I can’t buy an apartment or a condo in Manhattan. But if I have $50,000, that I know it’s going to or I think it’s going to triple in value, I should be able to take advantage of it. I shouldn’t be left out, right. So there’s this whole concept of financial inclusion and financial literacy that tokenization allows as well. Right. And even if you don’t look at just India, but you just look at the whole world, there’s a whole bunch of people out there that don’t have access to these investments, because they haven’t had enough money to be able to do it. But this democratisation that tokenization allows, to me is one of the most important things right, but you have to start somewhere. Is that Is that fair? Right? You can’t start with everybody. Yeah. So what exactly like where are you starting? And where is it going? If that’s okay to ask.
Your. So where we are starting is we talked to a lot of people out there. And everybody gave us similar answers. But Sal, I want to invest in digital assets. Everybody said that. I don’t know how where to invest? I don’t know and how to do it. I don’t know. The only thing I see is these videos on YouTube or ads telling me to buy some crypto coins, right? I don’t want to take that risk. Because I don’t know what’s going to invest in it. Want to be a millionaire overnight, but I want to do solid investment, I want to put my serious money into this asset class. And that is not available today. And even the infrastructure that is there has not been built for it. So to be able to build these kind of structured products doesn’t exist today, for example, how do you build a mutual fund of crypto coin? Yeah, I mean, doesn’t exist. How do you build a hedge fund of crypto coins and make it available to the users doesn’t exist? How do you make a index fund of fund which takes him let’s say you want to we want to buy one cryptocoins short, another one call on another aliqua, you have been into this kind of stuff. So you might not call into another covered call into the third one can’t do it. So those are the things that are not possible even to do because of the lack of infrastructure, and some of those things we have to pay.
So how complicated is it to build the software? And this is interesting for you, right? Because your whole life has been around building and architecting software? That was impossible. Right? Yeah. So how complicated does it look to you to build something that end to build the software stack? Really, because it’s more than just a piece of software? Right, that will allow this to happen at scale? You don’t? I mean, how hard is that? Yeah.
So the way we are, we have picturised, where we have grown pictures on the board and kind of architect this whole system, what we have kind of figured out is that there are a lot of missing pieces in the entire infrastructure. And we have to start building it piece by piece. So there are some things that are purely blockchain in nature, there are some things or when I say pod blockchain, I mean decentralised, finance, or defy the word that is being called out today. And then there is the centralised finance, which wants to get into the tokenized stuff, if there is absolutely nothing out there, which kind of helps them get in there except for the exchanges. But even the exchanges are just trading systems. But to be able to aggregate and create structured products, these are the things that you need this software stack for. And that’s what we are, we are kind of starting to build. In fact, we have been part of this also the value of building these kinds of structure products, you need a lot of the trading the LOI Signal to Noise kind of conversions, or you get data from all these various data points like discord, the Twitter’s of the world, and so on. And you need to make sense out of that, you need to use machine to be able to make make sense. And then the human intervention happens to take kind of trading decision, those things are also missing from this entire ecosystem. So we want to bring all that to the table really like a platform where you can just go easily, and you have everything available to be able to build these structures.
So we ran automated trading systems, right? And I’m, like I told you before we started recording, like I’ve worked on a portfolio trading desk, and I also worked in an automated, what’s the right word? Give me a second. Yeah, like programmatic trading. So we would build programming, we would build models that would just go out and trade for us, we built on all these back testing models that we build, is there enough data out to things really? Yes? And the answer is probably no, but it’s coming. Right. But is there enough data out there today in just the assets that are already trading on crypto exchanges to be able to do valid back testing? And is there enough liquidity to take advantage of it at scale?
Yes, we’re certainly haven’t can only come from somebody who has been in this kind of field. So, I think both are valid questions, and the data is building up for some of the tokens it is out there, if you look at Bitcoin and Aetherium they have had enough of the history and have seen all the ups and downs and you can really build good models on top of the data that is available for question these two coin and for others, it is of course building up and the liquidity again, that has been a problem because most of the liquidity that is there is on the Etherium chain, okay, whereas most of the opportunities that arise are on alternate chain. So that is another problem that needs to be solved. And we are solving. So how do you use the liquidity on Aetherium chains to and be able to do trading on other chains? How does that work? And that’s an interesting tech problem also. And for that you need to build these underlying protocol where no matter where the liquidity is, or where the money is, you should be able to use that liquidity on any of the alternate chains that is out there. I won’t get into the details of this because that gets too deep. And also a lot of the things that we are planning and things that we are doing. That’s the crux of the issue that needs to be solved. But what
can you talk about here, right, because it almost sounds like you’re building an operating system for trading or an operating system for the tokenization or just Just being able to take advantage of the information out there because in a decentralised world, right, so here’s the thing. In the old days, if I’m trading Japanese stocks, I just go to the Ts, the Tokyo Stock Exchange, I can get all the feeds from the TSE. And I pretty much know everything. Now. Yeah, there were ADRs that were trading in the United States. And maybe you’d have to look at that arbitrage opportunity. Sure. But today, I think a hybrid model is going to emerge, for sure, right? Where machines say all this stuff, and then humans make final decisions, and vice versa. But it’s so decentralised, like, how, what needs to get built to be able to do this? And can multiple companies do it? Or is there going to be like two or three companies build these operating systems? And then everybody else uses that?
Yeah, absolutely. So login grid coaching. So I think there will be two or three companies that will build this protocol, or the platform that I’m talking about. And a lot of the companies will use it. And we have already seen this happen in kind of the trading world. So uni swap has become kind of the top protocol for doing doing the swaps, or the trading Ave has become the de facto protocol kind of for doing the lending and borrowing. Similarly, there will be a wealth management protocol that will be there to do Wealth Management in a certain way. How does that look? Is the question,
how does it look? Do you know? And you’re just not saying or what do you think? Because, yeah, here’s the thing that I can’t get out of my head. When you were at Facebook. In these early days, you had this massive data problem you had to solve? Yeah. And I’ll say this, like, I don’t think the problems are different. Maybe Maybe it is this idea of like, they just rhyme right? In the sense that you just have to solve this massive data problem, again, with different sources of data, different depth of data, and all this other stuff. But at the end of the day, it almost seems like you’re solving a similar problem. Yeah. So
that I have seen actually happen in computer science again, and again. Yeah, it’s the old wine in the new bottle kind of thing. Maybe the problems kind of seem very similar in nature, but they present themselves in different forms. Yeah, I think it is. So you are right there that it does have a lot of deja vu about things that are done in the past. And the way I will say is to when I was building Cassandra, Cassandra was probably the only system out there which had no master, it was a new architecture in place, although it was in a centralised, for the cloud or to be in a cloud environment. But all the nodes were equal. There was no master, there was no special node. All database nodes were absolutely. So the algorithms used in Cassandra was such that you always had to vote things to kind of design. And whenever you have to spread out information, you have to use protocols like gossip, or to kind of say, Go and tell this to all my nodes and similar things. Are there in the decentralised world? Yeah, there is, there is no special note, there are nodes that are all equal in nature. So you need to kind of use algorithms, which are very similar, like the same problems presenting themselves, but at a much larger scale,
it must have been super interesting for you as well, because like one of the things we didn’t talk about was companies like Facebook actually went out and just what’s the right word? Again, they disambiguated their own servers, right. So they basically said, we can’t use an existing architecture to manage all of the data and all of the speed and all of the access that we need for what we have, and what we have is so specialised, we’re gonna have to rebuild this architecture on our own and run our own data centres. We can’t just like lean on somebody else to do this, because what we have is different. And you must be able to lean on some of that experience to now build what you’re building at Heru for everybody else, right? It’s very different, obviously. But just the experience of doing that has to lead to what you’re doing today. Yeah,
absolutely. That’s kind of what I was kind of hinting towards. Yeah, a lot of these things with the data, the way the nodes are structured, the way the algorithms were built to kind of manage the humongous data while at Facebook are very similar to what’s happening with the blockchain world. And in fact, it’s a lot more complex here because it’s not just one flavour or it’s not being done in a closed environment. Everything is there out in the open to you can create your own blockchains and each of them has different flavours, and each of them has different properties. So how do you merge these things together? How do you build things that can pan all these kinds of different things? That makes the problem even more interesting?
You must love doing this, don’t you? Oh, yeah, absolutely. I mean, I can just tell by the look on your face like you don’t look at this as a as like a what’s the right word? Not problem, but you don’t look at this as like a pain. You look at this as like, oh my god, I can’t believe I get to solve this gigantic problem every day. Right? I don’t know. I just tell by the way you’re talking about it. I want to ask you this, like, you talked about this signal to noise ratio, which I talked about a lot. And I’ll tell you why. When I was on the trading desk at Goldman Sachs, we actually started hiring engineers like not guys that had just studied finance, but we started hiring computer science people and also electrical Engineers. And one of the things the guys said to me was because I didn’t understand like, why would an engineer be good at trading? I didn’t understand it at the time. And he said to me, Well, what’s an engineers job? We’re trying to minimise noise and find signals. And I was like, Well, that’s what a trader does. Okay, I get that now, right. And that’s why I think it’s interesting when you talk about the computer science, understanding the way all this stuff works, being able to apply that to trading. And I think that’s something that a lot of people still haven’t figured out yet. But it’s neat that that that’s the way you think about this. But here’s the other thing when you look at what’s happened this year, right, with Terra Luna. And they’re different, right? Because the Terra Luna thing had big problems with like the underlying value of the algorithmic stable coin. And what’s happening in FTX is different. And obviously dou Quan is different than Sam bank been freed for sure. But how do you see these things as impacting the sort of mainstreaming of what’s happening in the crypto and let’s just call it a wealth management world as it relates to cryptocurrencies?
Yeah, yeah, absolutely. It’s a new infrastructure, given that everything about this is kind of getting built from scratch. Yeah, there are things that are happening where people are jumping the gun, right. So for example, for me, Lulu debacle or algorithmic stable coin is somebody jumping the gun. I absolutely believe that algorithmic stable coins are the future. And they will, at some point, or the other be the way you actually implement this table. But today, we are not there yet. The kind of algorithms needed, the kind of things that are needed to kind of make a stable coin out of algorithms is, the technology is not yet up there. And you’d have to jump the gun and start building a company on top of it and do everything on top of that it is going to crumble down at some point or the other. That’s what kind of happened with Lulu, in my opinion.
Yeah, I mean, look, part of the lunar problem was that it was so reflexive in the sense that, you know, Luna was supposed to equal one stable coin. But then if this didn’t, if the value of this was not understood, then how do you get this value. And then also, if I get out of this, you have to create more of these, like it was just a nightmarish circle that got created, and a death spiral as well. What has to change, to make algorithmic stable coins, the future
the amount of research that is already happening, in fact, it’s one of the cutting edge research in this field, where people are coming up with different kinds of algorithms to be able to build those cryptographic ways in which stable coins can be implemented in an algorithmic way. And we have to go there, we have not reached there yet. These papers that are published are silly little fancy says results have to be tested data has to be out there, somebody has to go there, Prove these things are all that things needs to happen. And technology needs to get there before you can actually start building and saying yes, this is the way to kind of build a stable coin.
So is this and I just thought about this, right? But is this sort of analogous to the gold standard and the dollar, where the US government had agreed before they went off the gold standard that like, if you gave us this much gold, we will always give you this many dollars and vice versa? And then Nixon was just basically like, yeah, we’re not doing that anymore. But we’re backing it with the full faith and whatever of the US government. And then currency started free floating, and at the beginning was just like a little bit of a nightmare, like where does anything trade and every now and then you do have a run on the pound or run on the Brazilian Real or whatever. But at the end of the day, the FX markets are relatively well understood. Is this the same thing that’s gonna happen through algorithmic stable coins in the crypto world? Yeah,
I think so clearly, this is going to mature because ultimately, as we go into the or we look into the future, gold cannot remain the facto standard on which you kind of back currencies, it has to get into compute, it has to get into how hard something is to compute, which becomes the basis of your point. See, even before gold money was when it was there, people used to use sheep, people used to use trees in the village or whatever, that were really dear to them, or hard to them, or reproduce and those kinds of things well as a backing for the money. And now as we look into the future, it has to be something that is really compute oriented to be able to scale because if you just rely on the metals on are like, gold, for that matter, that’s not going to be a very scalable model in the future.
Why does it rely on Compute like I get the gold thing to me like the idea that gold is the backer of money? I don’t know. We can argue with people about this until we’re blue in the face, right? But I don’t get it. But the computing I kind of understand, right? But can you just dig a little bit deeper into why it has to be the compute?
Yeah, so because in Compute I can make let’s I can devise a cryptographic algorithm with Make something to generate something very, very hard. Yep. Now it is up to me to control how hard that is. And the harder it is to be able to generate something and produce something, the better it is for me to use that as a backing so that it cannot be reproduced by anybody else. So if you have 10 things which are really hard to produce,
that’s why so that’s why because it creates a creates scarcity. So this is the idea. And this is why I think it’s hard to explain to people in the old days, right like gold and diamonds felt scarce, because they were hard to take out of the ground. But we know how to do that. And diamonds to be fair aren’t scarce. One family controls them globally. And we know how to mined gold. Right? And I think that’s why mining is maybe a good example of this. But the idea that we can create scarcity through the difficulty of understanding it is why now that compute is where the value is, that’s a different way to look at this. No. Exactly, exactly. And that changes the way I think now about cryptocurrency super interesting.
So from this line, this is how I will kind of taking this whole lunar debate call that yes, they kind of were early movers into this space, but ultimately this is how things will will be maybe the distant future, if not the near future,
Michael Waitze 36:15
probably the near future not too distant future super interesting. Prashant, you have to come back. I want to have like an ongoing conversation with you if you don’t mind. But this was really, really interesting. Prashant Malik, the Founder and CEO to Heru Finance and the Founder and general partner in Tykhe ventures. This was so interesting and so awesome. I really appreciate your time.
Prashant Malik 36:33
Thank you so much. I had a I had a lot of fun.
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