Uncapped #48 | Tarek Mansour from Kalshi

Tarek Mansour is the co-founder and CEO of Kalshi. Kalshi is a regulated prediction market exchange valued at $22B in 2026 where people trade on the outcomes of real-world events – things like inflation prints, Fed decisions, elections, or weather events. Instead of betting against a house, users trade against each other in a market, and prices reflect the collective probability of an outcome happening. Before starting Kalshi, Tarek worked as a quantitative trader at Goldman Sachs as a structured credit and equities analyst and at Citadel as a global macro trader. During his time at these firms, he realized a common thread: a lot of trading stemmed from an opinion on a future event. We covered the idea behind prediction markets and how they offer a more direct way to trade on beliefs about the future. The conversation follows the long, difficult path to building a regulated exchange in the U. S., from early skepticism to ultimately winning a landmark legal battle. We also discuss how these markets can improve forecasting, enable new forms of hedging, and change how information gets priced. --- Timestamps: (0:00) Intro (0:23) Kalshi’s genesis (5:05) Regulation-focused from inception (11:06) Suing the government (18:02) Gambling vs. financial markets (20:58) Defining insider trading (25:38) Incentive structure of the system (32:40) Investing vs. trading (35:31) Hedging use cases (41:38) Scaling a lean team (44:02) Defining Kalshi’s culture --- Links: https://x.com/jaltma https://x.com/mansourtarek_ https://kalshi.com/ https://uncappedpod.com/ --- [email protected]

• 0:00Speaker 00

  We decide to sue. All the kind of bad things that were predicted happen. All the little things like, oh, we're not gonna let you do this. We're gonna delay this. We're gonna kill you on this. We're gonna, the audit that was supposed to be two weeks now is like 18 months.

• 0:11Speaker 01

  Oh, my God.

• 0:12Speaker 00

  It's like a nonstop, just like knife after knife. But the most important thing is we won.

• 0:17Speaker 01

  All right. I'm really excited to be here with Tarek, CEO of Kalshi. Thanks for doing this. I've been looking forward to it.

• 0:22Speaker 00

  Thanks for having me.

• 0:22Speaker 01

  I want to start with the history of Kalshi. So can you kind of take me through the genesis, how the idea came together, how the company got started?

• 0:29Speaker 00

  A little bit background before that. So I grew up in Lebanon. I was born in California. I grew up in Lebanon. And, you know, Lebanon was kind of a, it's called like rough terrain to grow up in. It's like super volatile, a lot of uncertainty. You know, I kind of found refuge in math, you know, kind of a mix of different things. Like I grew up with a single mom. My mom was like, I wanted you to be successful. Maybe math is the thing to like get you back to America. And, and so I got really into math. And then it was like, a lot of my decisions at that point were like, what are the like best, like, smart math people do, basically. And it's like, oh, they went, they're going to MIT. So that's what I need to get into. And got into MIT and then the next kind of stage was the same question. And the answer was finance. And I started spending time in finance. I worked at Goldman. I worked at Citadel. I worked at some small prop shops.

• 1:14Speaker 00

  The one that did Bridgewater and Citadel as well. And the, there was kind of a pattern that was emerging in a lot of these places, especially in, you know, the example I always love to give is, is in 2016 at Goldman, I was working on this desk and there were like, two questions that were like bothering everybody in Wall Street. And like this is, those are the two questions that like people were figuring out how to like trade on these questions. Like, will Brexit happen? And then will Trump win the 2016 election? People wanted to have like the Trump hedge or the Trump trade. And, and then the thing that really like stuck with me was that, so Brexit happened and it was a shock.

• 1:48Speaker 01

  Yep.

• 1:48Speaker 00

  People were like really sort of completely shocked that, you know, the polls were saying this is not going to happen. And, and people had all these smart trades about how to hedge against Brexit. But then a bunch of desks on Wall Street blew up and they lost money and all the bad stuff. When it came to Trump, there was kind of a very similar thing happened. Like, the trade that we sold at Goldman, the very common trade was like, the, the Trump trade was you short the S and P because if he's going to win, the S and P is gonna go down. Right? Like everyone bought that trade. That was the trade. And it was a horrible trade because Trump won. And the S and P actually like it was a, I think it was the sort of single like biggest rally in the S and P's history like ever essentially. It's like worst trade.

• 2:32Speaker 01

  The exact wrong way to trade the idea.

• 2:34Speaker 00

  Exactly, is actually.

• 2:35Speaker 01

  Which is a shame because it's like what you were trying to trade was this underlying thing that you got right and then you expressed it backwards.

• 2:41Speaker 00

  They were right about the prediction and they lost money.

• 2:43Speaker 01

  Yeah, this kind of is like when, you know, like a company has quarterly earnings and people are like, oh, it's going to beat earnings.

• 2:49Speaker 00

  Yes.

• 2:49Speaker 01

  And so I'm going to try to buy the stock.

• 2:51Speaker 00

  Yes.

• 2:51Speaker 01

  And then it beats earnings and the stock goes down.

• 2:53Speaker 00

  And they're all smart in retrospect. Like if you actually trace the plot of like whether the stock went up or down after earnings beat. I think it's like fifty fifty, pretty much. It's mostly priced in. Two things kind of like I realized, like actually a lot of some of the smartest kind of like traders and institutions. A lot of their trading ideas or like the things that they're trying to do originate from a simple like human view about the future. I think Trump is going to win. I think there's going to be like some change in diplomatic relationship between these two countries. I think COVID is going to come back. What they thought they were trading on with traditional market is the event, but they were, what they're really trading on is this sort of reaction function is how the market was going to react to an event.

• 3:34Speaker 01

  Yeah.

• 3:35Speaker 00

  They weren't trading on whether Trump was going to win. They were actually trading on how the S and P was going to react to Trump, which in retrospect, and now like, like we can't really predict. It's so kind of impossible to predict. It was kind of a very exciting idea because it's like, okay, what if we just build this marketplace? Where what you're trading is like.

• 3:53Speaker 01

  The specific thing that you're thinking about.

• 3:55Speaker 00

  Yeah, it's just things that people care about, you know, whether politics or economics or weather or really any of topics that just people naturally walk around the street and think about. Because people don't think about like, you know, what is Cisco going to print? Like what are their financials next quarter? Like they don't think about that. They just think about, you know, the Fed might raise interest rates or things are more simple. And so that is exciting because like the TAM could be much larger because like a larger number of people would care.

• 4:17Speaker 01

  Yeah.

• 4:18Speaker 00

  Right? The second thing that was really interesting is like if you, there's kind of. If you believe in markets, what markets really do is they aggregate information, right? They are a very good weighing function. So they can figure out how to get information from a bunch of people, aggregate it and get a single price. And it's like, what if we apply that to questions about the future? Like all these kind of specific events or questions about the future. Then in theory, we should get a smarter or more accurate answer.

• 4:42Speaker 01

  Yeah.

• 4:43Speaker 00

  Or a market-based answer about all these questions. And that got me really, really excited because at the time we were thinking about if we could get a little bit smarter about the future, this is a very worthwhile product to build.

• 4:53Speaker 01

  Hmm.

• 4:54Speaker 00

  Right? You don't need to be like a hundred percent smart. Even if you get 10% smart about the future, that's more than enough. And that's how I got like into the prediction market. We can talk about that, but into a whole history on prediction markets and all of that. And I got really obsessed.

• 5:05Speaker 01

  So when you got started with the company, what was the first year? What were the first couple of years of building? Like, what did you do when you got started?

• 5:11Speaker 00

  I was actually gonna go work at Citadel. Because I had kind of spent time somewhere there and I actually loved it. It was one of those situations where like once I started talking about it and you know, the idea was just bothering me. Like I could not get it like I have a little bit of like, you know, I'm a little bit OCD and I get like obsessed with things, but I couldn't get it off my like brain. It was like so, so like, you know, I was like gonna go. Because you know, one thing I always say is we were not like entrepreneurs that were like trying to figure out what product to build to build a company. That was not how Kashi started.

• 5:41Speaker 01

  You just had this one idea.

• 5:43Speaker 00

  Like the idea kind of forced itself on us.

• 5:44Speaker 01

  Yeah.

• 5:45Speaker 00

  Like I was talking about it like, no, no, like forget about that. It's just like not, you know, let me just go Citadel paying me all this money like and. But then I remember that we had a friend who was like going to this YC hackathon. I don't know if they still do them, but they used to do these like hackathon and bring a bunch of builders. And, and he was like, oh, I'm going to this thing like you should come. I think the deadline has passed. And we're like, well, deadline's passed. And he's like, no, you should just like email the guy. And we emailed, I forgot who the organizer was at the time. I don't know, we emailed something like, hey, like we, we were trying to figure out flights or something and like. He's like, yeah, fine, you should, you can just come. So we're like, okay, well, we should just go. And it's funny, we did this hackathon, we put together like a front end for what the V1 of. It was like a bunch of questions and like a list format. With yes, no, and then like some probability.

• 6:27Speaker 00

  And it was like an order book, like literally we just copy pasted what the New York Stock Exchange order book would look like. And it's funny because we had judges like that were gonna judge the different teams and then pick the finalists. And our judges were Michael Seibert and Christina from Vanta. I don't know if she had started Vanta at the time or she was in the early innings of it.

• 6:42Speaker 01

  When was it?

• 6:42Speaker 00

  It was October twenty eighteen.

• 6:45Speaker 01

  I think she had started.

• 6:47Speaker 00

  She had started?

• 6:47Speaker 01

  I think so.

• 6:48Speaker 00

  You know, we started pitching the idea and then it's great, like I remember like Michael was like, oh, you know, everything is great about this idea, except for the fact that it's like totally not allowed in the US. And like, you know, this has like absolutely no way of existing in any way, shape or form. And you know, we walk up like, look, we tried, you know, move on. I remember like I drank a bunch of beers in that hackathon, like we're done. And then this guy like ends up picking us to be finalists. You know, he's like dunks in the whole thing and then, and then we end up winning that hackathon. And like, well, maybe we're onto something which got us into Y C. And then we're like, well, we have to give Y C a shot, like, you know. And at the time it was like, you know, wow, like never expected to be getting into Y C. And then like this is the, the first year was crazy because you know how there's this thing about Y C? Like they're the cool companies are building products and getting all these investors excited. Like we were the total opposite of that.

• 7:34Speaker 00

  We had no product, no customers. Week to week, we go to office hours and everyone's like, here are my KPIs and here's attraction. And we were like.

• 7:40Speaker 01

  We got nothing.

• 7:41Speaker 00

  Nothing. Like we were just like, well, we, we talked to this lawyer who said no, and then the next week.

• 7:45Speaker 01

  It's tough because you know, I did Y C and that was one of the, one of the most notable parts of the experience, which I think is a very positive part is every week you come back with your group and everybody else has grown seven percent week over week. And how much have you grown? And you're just like, none, doesn't build it.

• 8:00Speaker 00

  I don't even know what the product is. But we knew the, the vision was always clear, but for us, the key question is like, how do we get it regulated? We were very, from the beginning, we made a decision, we're not gonna launch a product outside of the realm of the law or regulation. We wanted to figure out how to get this regulated in the US onshore, no matter how long it took, no matter what. And, and the early days were really tough because we had no progress on, in, in, in, in regulation is not linear. It's not like you get sort of encouraging status updates from regulators.

• 8:29Speaker 01

  It's like there's big bang moments almost.

• 8:31Speaker 00

  Exactly. It's like zero all the way up until like approval.

• 8:34Speaker 01

  Yes.

• 8:35Speaker 00

  And nothing in between.

• 8:36Speaker 01

  Can you talk about what those were for you?

• 8:38Speaker 00

  So that was twenty eighteen.

• 8:39Speaker 01

  Yeah.

• 8:40Speaker 00

  Then we spent the first two years. Essentially, think of it as like, we were figuring out like, which lawyer would take this on? And it was this one, think of it as like this thing where like, basically, I became essentially somewhat of an expert in the law. Like, in the law around commodities, which is where I thought this would get regulated. Essentially, there was no proof in the law of why this shouldn't exist, but there were a lot of like, sort of like, things to figure out.

• 9:03Speaker 01

  What was the law at the time? Like, what was not allowed at the time?

• 9:06Speaker 00

  Well, it says that a commodity could be an occurrence or a contingency.

• 9:09Speaker 01

  And so was the issue the definition of the commodity?

• 9:12Speaker 00

  It was, yeah, the issue of like, well, but we're used to futures, like grain, and like, things are tangible.

• 9:18Speaker 01

  Right. An election outcome is hard to sort of put a thing around.

• 9:21Speaker 00

  Imagine like walking into regulator, you're like two, you know, twenty-one-year-old, twenty-two-year-old MIT kids, just like, walks into, like, you know, walking into the... I mean, we got this lawyer, Jeff, who was ex-CFDC, the regulator, is a CFDC, and he just like, got us the first meeting with the regulators, and like, you know, two kids are like, here's our like forty kind of page deck plan of how we could regulate this thing. And they're looking at us like,

• 9:42Speaker 01

  What are you talking about?

• 9:43Speaker 00

  And here are all the issues. How are you gonna like, police for manipulation? How are you gonna list this sheer number of markets? Because, you know, usually in our markets, like, you know, like, the CME or New York Stock, like, those exchanges, they list one or two new things like a year or every few years. Like, you're talking about like, listing hundreds and, I'm talking about tens of markets, sounds like crazy. So, it was a lot of these kind of like, like hurdles, none of which felt impossible, but if you add them all up, it started to look like Mount Everest.

• 10:12Speaker 01

  Yeah.

• 10:12Speaker 00

  And the problem is that you start climbing the Mount Everest, and then it, somehow, they're like...

• 10:16Speaker 01

  You see a higher peak kind of thing?

• 10:18Speaker 00

  Yeah, it starts sort of like, you know, it keeps going, and we had no, no certainty it was gonna end. That was the toughest part. It wasn't actually the work. I mean, the work was regulatory all day.

• 10:26Speaker 01

  Usually, we could fix this thing, and it might be like, we haven't made it done.

• 10:29Speaker 00

  It's like a desert, you don't know if it ends. And so psychologically, it's very taxing. Because you're walking in that desert, and you have no idea if this thing is ever going to end. You may actually just die.

• 10:38Speaker 01

  Yeah.

• 10:39Speaker 00

  And then you just walked for like, years in this desert, and...

• 10:41Speaker 01

  So what happened?

• 10:43Speaker 00

  We were just so stubborn, because like, we're like, look, and in those situations, you have to just like, you gotta stop thinking, you have to have no kind of like, introspection.

• 10:50Speaker 01

  No, Mark Andreessen.

• 10:52Speaker 00

  Yeah, I mean, you know, he got like, he got a little flame for that one. But no, I mean, more like, you have to have a bit of tunnel vision, or like, look... We're gonna keep going until we're proven wrong, like I, I, we die. Yeah. Or we find the other side. So can you talk about finding the other side? Towards the end of 2020, we started seeing like, think of like, okay, they would send an issue to us and then one after the other and after the other, after the other. And then it started fizzling out, like the issues started, like these guys started being like, wait, maybe these people are actually serious, like they're, you know, and like at some point, you kind of run out of issues to find. We, you know, we, we walked through all of them and worked through all of them. And you're, and think of like thousands and thousands of legal documents and pages, et cetera. And then we, we started kind of aiming towards an approval and we got approved in, in November 2020

• 11:38Speaker 00

  to get the first sort of regulated exchange for prediction markets. Then the new administration, on the same day of our approval, the election happened. So the new administration came around and our approval was bipartisan. It was like them and Republican, but like, but then the new administration was like, wait, wait, pause, pause. We're gonna have to think through this. In some ways, we're like, oh, we're finally through the desert. But all of a sudden, actually, oh shit, we got dropped back into the middle of the desert. And it was like, we're gonna have to see if we can let you do all these things. Maybe we'll let you do like a four economic markets, but not this sort of broader vision. That was disheartening. It was really hard because like we'd spent two years, we're finally there, we're gonna launch. Yeah, of course. And so this is not like, we started the first battle to launch the exchange. And we're like, fine, you know what? Like we'll launch with the four economic markets.

• 12:19Speaker 00

  We never thought that would get a product market fit, which it didn't. But we're like, we gotta get off, off the door now and launch and see what, what happens. So then by the end of 21, we kind of launched with, I think, a few economic markets, no traction whatsoever, et cetera. And at the end of 21 is when we're like, okay, we have to open up the space to get all the markets we want. And this one, we started to talk about the election market. And for prediction markets, I think like, and we can talk about the dynamics, but we always thought that you need the diversity of markets. But you also need a catalyst. You need enough, like something that is enough of a driving force to get people noticing. So that you can like kind of break through the supply and demand. You need something strong enough to get the chemical reaction going. Cause you know, you have the supply, the supply and demand problem, the chicken and the egg, and the chicken would come, there's no egg and vice versa.

• 13:03Speaker 00

  Need something strong enough to get everyone at the same time to start trading. And then after that, the thing can get going. But also I think it was one of the best ways to explain to people why prediction markets are powerful. It's like you need a event that everyone cares about and where we can provide a better product, like give a better forecast. And End of twenty one, we start talking to CFTC and they say, well, maybe, et cetera. Maybe we'll do it by end of twenty two for the midterms. A whole year of that, just regulation again. So now you're talking about three years and three to four years and just doing regulation. End of twenty two, the regulator sort of kind of like nudges the approval post the deadline, which essentially it just didn't make a decision. And that was a very hard time with the company because we thought the approval was gonna come. We'd done all the work possible, very kind of tunnel vision again.

• 13:48Speaker 00

  We didn't get it. And so in those circumstances, what happens is like, people kind of, they blame the execution of the strategy. It's never kind of like, you know, things are outside of your control. It's like, we made the wrong decisions and it was bad and, you know. And we lost a bunch of the team at the time and, you know, we had to do some layoffs. It was really hard time, like that was really, really like hard time. I think back at that time, it's like, I think it was one of the most painful times like I've ever sort of experienced in my life. And by the way, like I went through war in Lebanon. Like I've had kind of like missiles drop next to my house, like, you know, things like that. Like, it doesn't compare. Like, I think there's some form of, because it's, you feel shame as an entrepreneur. Totally. Right? You get it, right? Like, you know that feeling of like- Yeah, I've had to do a laugh, it's awful. And, and it's like you have responsibility and people are like trusting you with all this.

• 14:29Speaker 00

  And, and then we come out of this in January, February, we're kind of sort of reconvening, what do we do as a company, et cetera. And I remember Luana has like this sort of dogmatic belief in this, in this vision. Should we pivot? Like, clearly the government, you know, we're not gonna be able to do this. And then it was like, we're gonna try again. So that's the strategy for twenty three is we're gonna do the exact same thing as what we did in twenty two. And we're gonna try again. It was pretty, I mean, it was unpopular, but like, we did it. A whole other year of the same thing, talking to policymakers, regulators, same regulator, et cetera. Then they ban it, like, they block it at the end, they block the election market at the end of, of twenty three. And same thing happens again. And this was the point where I think this was, I would say, the most sort of like, you know, Sequoia likes to call these like crucible moments.

• 15:12Speaker 00

  But, but I think like, the kind of key decision that I think got the company to where it was today, which is like, we sat down and we're like, what do we do from here? And again, Luana was kind of driving a lot of this, but it was like, look, we, we strongly believe we're right on the law. We do. We also strongly believe this thing should exist. Like, we have come so far, you know, we're like, you're talking now we're five years in, we just got to sue the government. And we got to sue our own regulator. You know, we, we talked to Subor, talked to Outfit, and- You know, the interesting thing that came out of that conversation is that like, it's definitely an anti-pattern for a company to sue its own regulator or the government in general. It's even more so for a company of like twenty people that has no real product, no real like, we're kind of like a nobody company.

• 15:56Speaker 01

  Is it an anti-pattern? I think a lot of great consumer companies have got into, I don't know if it's a full dispute of their own regulator or full lawsuit, but at least some legal battles.

• 16:07Speaker 00

  It's maybe the sequencing.

• 16:08Speaker 01

  Yeah, maybe they got big.

• 16:09Speaker 00

  Like Airbnb and Uber were really big.

• 16:11Speaker 01

  Yeah.

• 16:11Speaker 00

  We're talking about a platform that has.

• 16:12Speaker 01

  Coinbase, maybe.

• 16:13Speaker 00

  Coinbase got really big, right? We're talking about a platform that like.

• 16:16Speaker 01

  Yeah, it was tiny.

• 16:17Speaker 00

  Tiny, like, you know, we had like, like hundreds and thousands, like maybe thousands of users a week. Like, it was, it was, you know, the evangelists, the really early adopters. In terms of sort of this is the unlock that will get us going.

• 16:27Speaker 01

  Yeah.

• 16:28Speaker 00

  And like, you remember Alfred was saying like, even if we win, even in the offshoot, kind of the crazy shot that we win, we may still lose because the regulator could kill you in the meantime.

• 16:36Speaker 01

  Right.

• 16:37Speaker 00

  And, and, and it's like the death by a thousand paper cuts type sort of. And, and it was real, right? This kind of notion of like lawfare or people just like coming after you for all these unrelated things. But you kind of know that it's because you sued, you sued your own government.

• 16:49Speaker 01

  Yeah.

• 16:50Speaker 00

  Lawsuit is usually pretty, it's a big battle, it's a big deal. But then, I remember like Alfred like kind of saying this is like, but sometimes sort of, some of the best companies I've, I've ever seen it kind of start with an anti-pattern. Like, there's something weird that happens in that company that is unusual, and maybe this is yours. As we decide to sue, all the kind of bad things that were predicted happen, all of them. Like, like, all the little things, like, oh, we're not gonna let you do this, we're gonna delay this, we're gonna kill you on this, we're gonna, the audit that was supposed to be two weeks now is like eighteen months.

• 17:17Speaker 01

  Oh, my God.

• 17:18Speaker 00

  And, and it's like a non-stop, just like knife after knife. But the most important thing is we won. Like October, like October twenty twenty four.

• 17:26Speaker 01

  So how long did that suit take?

• 17:27Speaker 00

  A year.

• 17:28Speaker 01

  A year. And during that year, you're just stressed out of your mind.

• 17:31Speaker 00

  Yes, but not more than the other ones because it, think of at that point.

• 17:34Speaker 01

  Yeah, I've got, it's my last shot, what else am I gonna do?

• 17:37Speaker 00

  It's like walking the desert has become, had become our life. And it was like our last shot, it was a bit of a desperation, like, it was like, you know, your back is against the wall.

• 17:43Speaker 01

  Like, if I don't do this, I'm not gonna make it anyway, so who cares?

• 17:45Speaker 00

  Basically, like, I, I think we didn't think there was like any shot at making, like, we had to get the election market. At that point, it was more, it was more than just business, it was, it was like a mission thing. Like, we wanted to deliver this to the world. We were so dogmatic about, we want the world to see this market in action and see how powerful this thing can be.

• 18:02Speaker 01

  Okay, so you win the lawsuit, now we're.

• 18:05Speaker 00

  Now, it's interesting because we won the lawsuit and like, it's like this feeling so, okay, we won the lawsuit.

• 18:10Speaker 01

  And specifically what the lawsuit enabled us what?

• 18:12Speaker 00

  So the lawsuit is basically saying, it was in some ways redefining what constitutes like gaming or gambling versus a financial market. And it's interesting because there was a lawsuit prior to that.

• 18:24Speaker 01

  So basically, it's now saying things like betting on the president or the outcome of a sports game.

• 18:30Speaker 00

  Can be a financial market.

• 18:31Speaker 01

  Is now a financial market.

• 18:32Speaker 00

  And it's, and there was kind of two, two kind of elements to that. And, and very simply put is basically, one is what is the structure? Are you in open and free market, market where people are just trading against each other? Versus like a, a house where you're accepting bets from someone. And again, your business model is like gambling, is like your revenue is equal to customer losses.

• 18:50Speaker 01

  I see.

• 18:51Speaker 00

  And then the second thing is like, is this a real thing that's happening in, in, in the world? Where like, some people may benefit from hedging or some people may benefit from?

• 18:58Speaker 01

  Basically by being the marketplace where other people are betting against each other. That's critical and not being gambling.

• 19:04Speaker 00

  That's a, that's a very critical thing, societally, but also legally, a bunch of kind of, you know. But also just like, very simply like, you know, there's still also a difference between like, you know, like, two people kind of transacting on like, hey, what is this dice going to land on? Because it's an artificial risk that you're creating just for the purpose of

• 19:21Speaker 01

  Right.

• 19:22Speaker 00

  trading or betting on it.

• 19:22Speaker 01

  Yeah.

• 19:23Speaker 00

  Versus if you're trading on a stock, which exists, a company exists, or, or oil, or an election.

• 19:29Speaker 01

  Got it. So it's also the, the event existing, whether or not

• 19:32Speaker 00

  It's a natural risk. It's a natural thing. It's a natural event, not an artificial event.

• 19:35Speaker 01

  Yep.

• 19:35Speaker 00

  And that's important. That's very important.

• 19:37Speaker 01

  Yeah.

• 19:37Speaker 00

  And it's interesting because the, the decision that came out of that lawsuit is very similar to one that came out close to one hundred and twenty years earlier in nineteen oh five in the Supreme Court, which is the one that legalized grain futures, the most boring financial market, the, the OG hedging market. Because at the time, there was a state versus federal like, kind of fight, where the states were claiming, well, this gambling because some people are speculating.

• 19:59Speaker 01

  Right.

• 19:59Speaker 00

  Like farmers were going and kind of betting on the price of grain. So that's gambling. It must be, it must be gambling. And the Supreme Court said like, look, a lot of people will speculate.

• 20:08Speaker 00

  But there is some people that are like using it for hedging or getting smarter about the price of grain over time. So there is, that's why it's a financial market. And actually, in many ways, speculation is necessary for that market to exist. Like if you want a market, if you want the stock market to exist, if you want commodity markets to exist, if you want prediction markets to exist, you need speculation. You cannot just have people that are insuring themselves against stuff because the person on the other side needs to be a speculator. In some ways, it's kind of history repeating itself, but it can redefine the aperture of what's allowed.

• 20:37Speaker 01

  It would be legal for somebody to speculate on like whether or not we were going to say a certain word in this podcast. Would that fit the definition if people wanted to trade on that?

• 20:45Speaker 00

  Yeah, because it's happening.

• 20:46Speaker 01

  It's happening anyway.

• 20:47Speaker 00

  It's happening anyway.

• 20:47Speaker 01

  They can bet with each other.

• 20:48Speaker 00

  And they're trading against each other, right? And like, it would not be legal for us to, and we can talk about that.

• 20:52Speaker 01

  Yeah.

• 20:53Speaker 00

  If we had a position. So like, if we cannot go and trade on that and then you just go say something, because that would be market manipulation.

• 20:58Speaker 01

  Is it illegal to bet on something where you see, you know, a bet playing out in the world, but you know the answer for sure?

• 21:05Speaker 00

  So it depends. And that's the whole kind of conversation we've been having around insider trading. And there's a whole long history here. But the line that, you know, so we're regulated financial market, we're regulated exchange and clearinghouse. And a lot of the rules we have are mimicked after the rules of the stock market. In the stock market, the line is drawn, it's like you cannot trade on where it's material, non-public information. And the way that that's defined is like, you have a piece of information that you acquired under certain rules, right? And one of those rules is that you cannot disclose it. So material, non-public information is information you're not allowed to disclose. That like, if you own as an executive of Tesla and you went and said it to the press, you would get in trouble. That's, you're not allowed to do it. And trading is a form

• 21:47Speaker 00

  of disclosure. That's a whole bunch of prediction markets, right? Like, prediction markets are a way to disclose information. Like, when you trade, maybe you're not saying it on Twitter, but you're actually trading that information and you're moving the price in a way that discloses the information.

• 21:58Speaker 01

  But like, let's say, let's say this morning I saw, you know, a trade that was, well, Jack and Tarek see each other today. And I'm like, I know the answer to that. So I'm going to make a big bet.

• 22:08Speaker 00

  Are you Jack or are you someone else?

• 22:09Speaker 01

  I'm me.

• 22:09Speaker 00

  Well, you have influence on that. You have direct control over that.

• 22:12Speaker 01

  Got it.

• 22:12Speaker 00

  So that would be market, that wouldn't be insider trading, that would be manipulation.

• 22:15Speaker 01

  Yeah.

• 22:16Speaker 00

  So the majority of participants in grain futures are grain farmers? Right, like they and the way that the price of grain futures is done, this is gonna be a little surprising.

• 22:25Speaker 01

  Yeah.

• 22:25Speaker 00

  Can you guess, like, how do you determine the price of grain? How do you think we determine it?

• 22:28Speaker 01

  I don't know. How?

• 22:29Speaker 00

  You literally survey a bunch of the farmers are trading in the market.

• 22:32Speaker 01

  Wow.

• 22:32Speaker 00

  It's a little weird, right? Like, it's like you, they definitely have inside information then, like, right? Because they're the guys, I mean, they know what the price is. And it's interesting because the line there has been like, okay, insider trading is very hard to define grain futures. But what we're gonna draw the line is, is you cannot put a position and artificially manipulate the underlying price. You cannot move the prices of the, like, you cannot move the event or the underlying in a way that will kind of help you profit. And so it's the same thing here. It's like, if you have direct control over an event, if you're a politician that was looking to pass a bill, you take a position, then you tank the bill, or you try to pass it even harder, that's illegal.

• 23:09Speaker 01

  Yeah.

• 23:10Speaker 00

  And that's banned on Calci.

• 23:10Speaker 01

  I could see that could get a little gray, though. Like, let's say you were, let's say back to the, you know, us talking on the podcast today. Let's say you're a friend of mine, and you knew that we were, you knew it was happening. You don't really have control over it, but you could be like, you know.

• 23:24Speaker 00

  It's the same as the stock market, is the cousin, like, is the cousin sort of responsible? And if, like, if someone on the street heard an executive talk about, like, some MNPI, are they allowed to trade it or not? And like, and these lines have always been.

• 23:35Speaker 01

  So does this stuff come up a lot, or is it not?

• 23:36Speaker 00

  Yeah, definitely, because it's interesting. And like, look, this is a conversation that Calci alone will not have all the responses to. And it's a conversation where, like, having regulators and overtime policymakers, but like, you know, my principles are kind of generally simple when it comes to this. It's like, I always go back to, why is insider trading banned in the stock market? Now, there are some people that argue, well, maybe we should let insider trading happen in the stock market, because it will make the prices more, more accurate.

• 24:00Speaker 01

  Right.

• 24:00Speaker 00

  If you let it happen.

• 24:01Speaker 01

  Yeah, it feels like, I mean, my reaction to it is, it feels unfair.

• 24:04Speaker 00

  Exactly.

• 24:05Speaker 01

  People got money for no reason other than they were told something, and that shouldn't be a source of people generating wealth.

• 24:11Speaker 00

  It's, it's exactly, like, it's all about unfairness.

• 24:13Speaker 01

  It feels like there was no skill and no effort that went into it.

• 24:15Speaker 00

  Yes. And, and it's actually even worse than that. There's a very practical implication, not just sort of a moral implication to this. The practical implication is that, well, if people believe the stock market is rigged. They stop trading.

• 24:26Speaker 01

  Yeah.

• 24:27Speaker 00

  Like you, you, the liquidity dries up.

• 24:29Speaker 01

  Right.

• 24:29Speaker 00

  There's kind of this nice property of market. It was like markets that have a lot of insider trading in some ways are not going to exist.

• 24:34Speaker 01

  At some point, like at the limit, you'd be like, if I don't have insider information on a stock, why am I trading? Like, I'm definitely the sucker.

• 24:39Speaker 00

  It's, it's, there's a mix, right? And, and so I, I think, no, you have to have information on, on something.

• 24:44Speaker 01

  Yeah.

• 24:44Speaker 00

  And seeking information is very good. Doing research, like when, like, for example, you know, some of the, I don't know if you ever heard that, like, at the time, apparently two sigma used to like, I don't know if it's two sigma specifically, but like, he used to like use satellite images of like the parking lot at Walmart.

• 24:57Speaker 01

  Yeah.

• 24:58Speaker 00

  To figure out how many cars were coming in.

• 25:00Speaker 01

  Yeah, probably even before that, people would just, you know, hire somebody to sit outside of Walmart.

• 25:02Speaker 00

  Yeah, that's not insider information.

• 25:04Speaker 01

  What's the foot traffic?

• 25:05Speaker 00

  Exactly. That's information.

• 25:06Speaker 01

  That's just work.

• 25:06Speaker 00

  That's work. Yeah, that's work. Exactly. But I think there's a balance. But I think to me insider information is, the way to define it is information that you could not get access to would work.

• 25:15Speaker 01

  Yes.

• 25:16Speaker 00

  If you're not an insider.

• 25:16Speaker 01

  That's right. Yeah.

• 25:17Speaker 00

  Like, and that's the, and, and I think the reason you should ban it and the rules that you have to build in the marketplace is like, how do we keep it fair?

• 25:23Speaker 01

  Yes.

• 25:23Speaker 00

  And it's very practical. If, if it's not fair, then people will stop participating.

• 25:26Speaker 01

  Yes.

• 25:27Speaker 00

  And this was a message I always say is like, there's something nice about insider trading, which is like, if the marketplace is really not fair, you could trust that people will just like stop doing it. They won't, they won't want to do it. And that's why we take this very seriously.

• 25:37Speaker 01

  Yeah. I have a topic I want to get your take on because I can tell that you're extremely thoughtful about fairness, the way it should work, what's the better future. I think one of the discomforts people have with like prediction markets.

• 25:50Speaker 00

  Yeah.

• 25:51Speaker 01

  Is that they, they look like gambling and some people who are not comfortable with them, it's like this new idea. And it looks like people just pulling their phone out and they're starting to do gambling.

• 26:01Speaker 00

  Yeah.

• 26:01Speaker 01

  And obviously that is not at all what your sort of conception of it is. There's all sorts of function outside of it. But I'd be curious actually to start to hear sort of your steel man version of like, what's the way this goes wrong? Like, what's the version of it that is like?

• 26:16Speaker 00

  The bad version.

• 26:17Speaker 01

  Yeah. What's the bad version of gambling that you were not comfortable with? That you think crosses some line that you don't think is good. And you know, this is obviously, I think probably you and I share like a baseline value of libertarian and adults should be able to do what, what they want to do. Obviously with some balance of like, we shouldn't. You know, expose people to things that are, you know, short term addicting that are long term bad for them. You know, there's some balance here.

• 26:42Speaker 00

  Yeah.

• 26:42Speaker 01

  Where are you not happy?

• 26:43Speaker 00

  Look, I'll tell you, like, I I'm a risk taker, I'm a trader, like, I I and I've never, I don't consider myself having really gambled ever, like, when I trade. And that that's, you know, I speculate, there's like a lot of similarities of between this and. And there's a lot of arguments, I mean, the argument I hear most about is like, people like talk about ducks a lot, like the the it quacks like a duck and like, you know, that's usually the argument of like. Well, it looks like gambling, so maybe it is gambling. And it's interesting because the the thing I always like say is like. That argument has been made about every single new type of financial market that has ever come. To the US or really anywhere, right? Like, the argument has been made about grain futures, like we just discussed, it's.

• 27:24Speaker 00

  In some ways, you know, when when we started with life insurance back in the back in the day, you know, the the headlines at the time were like. Oh, this is like morally horrible, like you you're gambling on people's lives, this is terrible. We should not have this at all. I mean, you know, now I think a lot of us would agree, we should have grain futures, we should have. We should have the stock market, which is, you know, has been, we should have life insurance, we should have all these different things. But I think there is a basic, like, yes, speculation has a flavor of. It looks sometimes like gambling, but it doesn't make it as such. And so I like this kind of frame of like, let's actually like play this out. And how does it go wrong? In my opinion, the things that end up contributing to this bad perception in gambling is the incentive structure in the system. It's how is the system built?

• 28:09Speaker 00

  And what are the incentives that are, you know, built in this into the system? And and when you think about a gambling business model. It's a business model who's like where the primary KPI, right, the thing that will. Not just predict your net income, will be pretty much equal to your net income, is your customers' losses. If that's your business model, and that's what your incentive is, what are you gonna do? You're gonna promote.

• 28:30Speaker 01

  Losses.

• 28:31Speaker 00

  Losses, like that, what else are you going to do, right? If you if you do a great job at stopping losses, you're gonna lose money.

• 28:36Speaker 01

  Be a more throughput, bigger rig.

• 28:38Speaker 00

  Yes, it's just the the inevitable. And so. What a lot of these businesses do is, you know, if you're sitting in a casino and you're making money, what do they do? Like, the bodyguard comes and takes you aside and says, stop. If you're doing something informed, if you're doing something smart. If you're seeking information, the very point of financial markets, like. You get blocked, you get banned, or at least limited.

• 28:58Speaker 01

  Well, part of that happens because they're trading against you. So in a casino.

• 29:01Speaker 00

  That's the business model.

• 29:02Speaker 01

  Blackjack, it's against the house.

• 29:03Speaker 00

  Yes.

• 29:03Speaker 01

  And so you winning is exactly me losing.

• 29:05Speaker 00

  Exactly. Online, all these models are like, the counterparty is the house.

• 29:11Speaker 01

  Whereas for you in a marketplace, you don't care who wins.

• 29:12Speaker 00

  I don't care.

• 29:13Speaker 01

  Yeah.

• 29:14Speaker 00

  And that's fundamentally different. So the way that it goes bad is like when the house is trading against its own customers, you are inevitably the algorithms.

• 29:21Speaker 01

  One thing that does persist, though, is theoretically, you don't care if on net the two of them leave the day with more or less money between the two of them. Like, you don't care that two people betting against each other.

• 29:33Speaker 00

  I'm neutral.

• 29:34Speaker 01

  You don't care. Yeah, exactly. If they both start with a hundred dollars, you're okay if at the end of the day, one has a hundred and ten and one has eighty. That's still okay.

• 29:41Speaker 00

  I actually, in some ways, prefer if they're both at a hundred.

• 29:44Speaker 01

  Yeah.

• 29:44Speaker 00

  In some ways. I mean, because, but think of it as like, but to me, it's the incentive in the system. Because, okay, and going back to kind of how it goes bad, if you're the house, what are you gonna do? You're gonna figure out, you're gonna build algorithms and you're gonna, you know, whether it's physical algorithm, the casino. Like casino has all these smart ways of figuring out who are the big losers in the room. And then you're gonna figure out how to get them hooked, get them to come back, get them to come back, even if they're losing. Even if they know that they're losing. You give them a suite, you give them all these different things, right?

• 30:10Speaker 01

  Make the lights more flashy.

• 30:11Speaker 00

  All of that. Like, you know, the waitress comes in with cocktail, right? Like, all, and so that is where the unhealthy behaviors emerge. Because you have an algorithm, it's just promoting unhealthy behaviors, right? And, and we've seen it in a bunch of other, kind of like, even in the context of tech platforms, et cetera. What I like about it in free and open marketplace, and that applies to the stock market, it applies to crypto, it applies to options, there isn't that dynamic. That dynamic doesn't exist. What is my incentive as a company? As my company, my company, I take a small fee, a transaction fee, right? So what I want is volume. I want people to just trade more, right? And I'm actually incentivized, if I want people to trade more, is the things that I want the platform to be fair.

• 30:50Speaker 01

  Yeah.

• 30:50Speaker 00

  And perceived to be fair. I want the platform to be neutral, as neutral as possible.

• 30:54Speaker 01

  Yeah.

• 30:55Speaker 00

  And I want it to be transparent, which is another key thing. All the trades are public, everyone can see what they do. And I like this model significantly more because now. And we think about going back and was our responsibility as a platform. I have a much better shot like structurally at creating healthy feedback loops into the product. Like if I, and we do this a lot, we have limits on like how much people do and how much they trade, et cetera. But it's not just something that we just say, like our business model is tied to it. If someone is doing too much excessive behavior and losing too fast, we as a business will not be hurt as much as the other types of business models. If we tell this person, hey, maybe you should pause. Now, I don't know if it's our job to block this person. That's a different story, like that's, but we have all the incentives to say like, hey, maybe you should stop. Maybe you should like self exclude, maybe you should like put limits on you.

• 31:39Speaker 00

  Because again, they're not losing it to us.

• 31:41Speaker 01

  Right.

• 31:41Speaker 00

  They're losing it to someone else.

• 31:42Speaker 01

  Yeah.

• 31:43Speaker 00

  And I, that's not a positive thing for me if that's happening. And so that's what's exciting me and, you know, and I hope over time, not just that Kalshi, Kalshi spends a lot of time like thinking about customer protection in the context of like, how do we limit unhealthy behaviors or excessive behaviors? And I hope that this gets applied to also all the other financial markets where like people, retail participation is going higher. Like whereas crypto options, all these different things.

• 32:04Speaker 01

  Let's say that what you were, that what people were trading was like, just like stocks instead of, you know, the outcome of, you know, an election or something like that. In that world, even with a fee, you know, over 10 years of trading, like the stock tends to go up. Versus with, you know, an election, it's just to trade back and forth with a little fee. And so the outcome that you're producing is not incrementally more net worth over time. The outcome you're producing is better information and people being able to express their views.

• 32:31Speaker 00

  Yes.

• 32:31Speaker 01

  It does seem to me like it would be cool if you also had the other type of product where you were helping people.

• 32:38Speaker 00

  Like the investment type product.

• 32:39Speaker 01

  Yeah.

• 32:39Speaker 00

  Yeah, there's a difference in investing and trading.

• 32:41Speaker 01

  That's right.

• 32:41Speaker 00

  That has always been existent, right? Like, yes, the stock market is, look, I think holding a stock for five years, that's investing.

• 32:47Speaker 01

  Yeah.

• 32:48Speaker 00

  Now, if you trade a stock in and out over the next few days.

• 32:50Speaker 01

  You're gonna get crushed by all the fees.

• 32:51Speaker 00

  That's trading. Yeah, and not just fees also, it's like your directional view.

• 32:54Speaker 01

  It's not enough time.

• 32:55Speaker 00

  Yeah. Yeah, it's like you're trading, you're, you're, and that's a zero sum game. And options are a zero sum game. All crypto, in my opinion, we'll see over time, but like most of crypto trading, not like, not if you, if you hold Bitcoin for five years, that's investing, but if you're trading Bitcoin and out, you're zero sum. And so my, my mental model for this is like, yes, that's true. But it's interesting because we ask our customers, a lot of them, hey, like, do you trade, not invest, they're different. Do you trade, for example, S and P or do you trade traditional like options? And consistently, like nine out of 10 of our customers, their response is no. And the reason is I don't gamble. And like, wait, but you know, in people's mind, but like elections, trading or betting,

• 33:39Speaker 00

  that sounds more like gambling than trading in options.

• 33:41Speaker 01

  Yeah.

• 33:42Speaker 00

  Because that sounds financial, you know? But actually, like, if you ask people, it's like, well, I don't have a way to win.

• 33:48Speaker 01

  Right.

• 33:48Speaker 00

  You know, I don't have an edge.

• 33:49Speaker 01

  Yes.

• 33:50Speaker 00

  There is no way for me to do it.

• 33:51Speaker 01

  Those markets are so efficient.

• 33:52Speaker 00

  They're efficient, the hedge funds have way more information than I do. There isn't a way for me to be truly informed. And if I put a lot more research, so the whole point is, but if you put a lot of research, can you get better and can you win? And the reality is, in a lot of traditional markets, the answer is no. Wall Street will always be mainstream. Wall Street will always be the average person. The beauty of what we're building, it's just not the case. The average person is winning more than Wall Street. Like, our best inflation forecaster is not a Wall Street person.

• 34:19Speaker 01

  Well, I guess by definition, the average person is neutral with you because there's a, there's a buyer and a seller.

• 34:26Speaker 00

  But, but it's more about a point of like, there, there isn't that structural advantage that like Wall Street has in our markets.

• 34:31Speaker 01

  Yeah, I mean, what I would argue is they might be neutral with you and they're definitely going to be negative if they're going to try to trade against the dollar.

• 34:37Speaker 00

  Generally, yes.

• 34:38Speaker 01

  Yeah.

• 34:38Speaker 00

  And, and yes, our average user is neutral, but I'm, I'm talking more about like.

• 34:42Speaker 01

  The people who want to put in real work.

• 34:43Speaker 00

  Yes. People, if you put in real work and figure out how, how do people vote on bills or why? It's like, you know, the, the, back in the 2024 election, you know, the, the guy who put like a lot of money on Trump because he did the neighbor poll.

• 34:56Speaker 01

  Totally.

• 34:56Speaker 00

  It's genius, amazing. That's the markets working exactly how they should, which is like, they're rewarding someone going out there, doing the research and doing the truth seeking on behalf of society.

• 35:06Speaker 01

  Yeah.

• 35:07Speaker 00

  And then you get, and get rewarded for it. Like, you're, you're doing a reward mechanism for someone to do research, which does not exist in a lot of the traditional markets.

• 35:14Speaker 01

  Yes.

• 35:14Speaker 00

  And that's why, like, when you talk to these people that are on Cal Sheet, the prediction market, you know, I don't know if you saw the New York Times article about the rise of the prediction market trader.

• 35:21Speaker 01

  Yeah.

• 35:22Speaker 00

  That class of people that are doing this as a full-time job.

• 35:24Speaker 01

  Yes.

• 35:25Speaker 00

  You know, they're excited about this because it's a way to, for them to get rewarded for all the things they are learning about the world.

• 35:31Speaker 01

  By the way, one of the things that I think is very interesting is whenever there's like a new financial product, there's all these emergent behaviors and properties. And like, an example with yours is like, like insurance and hedging and things like that. Can you talk about like? Like when I first learned about that, I was like, oh, that's surprising, but it makes sense with like a hurricane or something like that. Isn't it? It's getting used for those types of things too, right?

• 35:49Speaker 00

  Yes. And that's, I would say like the trajectory over time is like that is becoming increasingly bigger part of the platform. Uh, obviously we started with retail, like people, individuals, but now as we're getting into the institutional, that's becoming a bigger and bigger.

• 36:01Speaker 01

  Right.

• 36:01Speaker 00

  Piece. But let me talk about retail and then let's talk about institution. So, so yeah, there's the two functions of the market. One is what we call like price discovery, which is predicting all these events, right? And that's one of the benefits of prediction, right? Just you're giving people an incentive to do the price discovery, which is predict all these events. And that's working, right? I think a lot of people now at least understand increasingly more. I don't know if you saw the Fed paper that came out. You saw that?

• 36:21Speaker 01

  Yeah, it's cool though.

• 36:22Speaker 00

  Can you see the rise of micro markets, right? Like, and it was like the Fed itself is saying this is the best gauge we have on the economy.

• 36:28Speaker 01

  It's crazy.

• 36:28Speaker 00

  It's like amazing. And, and by the way, the people is not Wall Street again, it's Main Street. We, we've figured out how to build this community of people that are dispersed across America that like are making us smarter about the economy.

• 36:37Speaker 01

  It turns out that like, if you ask like a big enough crowd of people, like how much does a cow, like a particular cow weigh? They get like really close.

• 36:44Speaker 00

  That's the OG, uh, original prediction market.

• 36:46Speaker 01

  Yeah, it's pretty cool.

• 36:47Speaker 00

  That's how it started. It's like literally bringing wisdom of the like crowd wisdom.

• 36:49Speaker 01

  And it's happened with the elections too, with like Trump and stuff like that. Where like everybody's like, no, Trump won't possibly win. And it's like, well, maybe.

• 36:54Speaker 00

  If you have an incentive to actually do the research, I think you may actually, you know, but, but so that's that. And you, and, and the second prong is hedging. And hedging is a little different from insurance. So insurance is usually regulated at the state level because it's also there's a house.

• 37:09Speaker 01

  Right.

• 37:10Speaker 00

  So you go to an insurance company and they give you a price. Hedging is on the open market.

• 37:13Speaker 01

  So hedging is just like, I'm on a coast and I'm just gonna bet that a hurricane is gonna come knock my house over.

• 37:17Speaker 00

  But the key thing is it's an open and competitive market. You say, I wanna buy X amount of something that protects me and then people can like fill you at whatever price and they compete for that price. And we see this a lot, for example, in Florida, in the Keys, you know, insurance companies have pulled out because they don't know how to price hurricane risk anymore. It's like really expensive. And so we get like calls.

• 37:38Speaker 01

  As of when?

• 37:39Speaker 00

  It's been like two years, three years, like where we get a lot of calls around hurricane season where people are like, hey, I wanna buy X amount of hurricane hitting this town.

• 37:47Speaker 01

  Yeah.

• 37:48Speaker 00

  I don't want to deal with the insurance process. Oftentimes, they don't pay me back. There's deductibles, there's all this. I don't, I just want, if the hurricane hits the town, I get paid.

• 37:55Speaker 01

  Yes.

• 37:56Speaker 00

  And that's a hedge.

• 37:57Speaker 01

  Yes.

• 37:57Speaker 00

  And that's one, like, you know, Chris, like, really clear sort of um use case that we've seen. The other one is like, at the time with Biden and the forgiveness market, a lot of like students were hedging, like smoothing out their student loans. They were super worried about having to pay back. But the interesting thing about the vision long term is like, as we're sort of, I mean, now we're seeing, you know, really, like, we're seeing a massive acceleration in institutional adoption of prediction markets and Kalshi. Is think about it this way, like, you own S and P as an institution, but you're really worried about an upcoming election. You're really worried about the midterms, one way or the other. If the Republicans win or Democrats win, you think it's going to impact your portfolio in a certain way. Today, you don't have any options. You may just have to sell your position before the event happened, if you want to protect yourself.

• 38:41Speaker 00

  With prediction markets, you can actually put the hedge. So if you're worried about, for example, Republicans winning or Democrats winning, you can buy Republicans or Democrats. If you think that's going to impact your portfolio, your hedge is going to basically complement for that. So you don't have to sell your position anymore. You can put on the hedge. And that's, I think, where the next generation is, like, AI, COVID, elections, bills passing, regulatory, like regulatory changes, all these different things can become just insurable risks. And what Kalshi has provided for that is like the layer one of being able to, you know, kind of think about those risks, which is pricing them. Like, any of these risks now, we can put on the platform, we have this platform, we have this, we basically have all the top super forecasters on the planet that will give you the price.

• 39:21Speaker 01

  Yeah.

• 39:22Speaker 00

  Like, you send this thing to the system and it'll come back and spit out, hey, well, Citrini scenario happens. I don't know if you read that. So have you seen the research report from Citrini?

• 39:29Speaker 01

  Oh, Citrini, yes.

• 39:30Speaker 00

  Yeah, yeah. We put it on Kalshi and like, you know, it started at 11%, now it's at 33%. This thing has gone up.

• 39:36Speaker 01

  Yeah.

• 39:36Speaker 00

  But it's amazing because you have a market that you can probe now. Instead of like listening to different pundits and Twitter and people are battling on Twitter.

• 39:42Speaker 01

  And then based on that, if you believe that, then you can go do other trades against that.

• 39:46Speaker 00

  You can, you can either use that to hedge, if you're worried about that impacting your portfolio, or the interesting thing is like, pricing this thing. Can enable us as a society to make the prices of all of our traditional assets better. Now, there is this theory about infinite markets. Have you ever heard about that?

• 40:01Speaker 01

  No.

• 40:02Speaker 00

  So this idea that like, you know, as society gets increasingly more complex, the vector, like the number of dimensions that matter for asset prices increases. Right? Like a hundred years ago, you maybe needed to understand supply and demand in industrial, like in labor and, you know, maybe the agricultural economy in the US. Now you have to understand those things. We also have to understand what's happening in Iran and what's happening in COVID. AI and what's it's gonna do? How technology is rapidly progressing, cyber, all these different, like society is just getting increasingly more complicated and more interconnected. So everything impacts everything. The interesting thing is like, as this vector, as a number of dimensions increases, our pricing of traditional assets, like the market, like the S and P or home price, et cetera.

• 40:45Speaker 00

  The entropy there goes up, like we have less and less information, like we have less and less of the relevant information. So you have to actually over time price all these different dimensions so that you can then price the S and P more accurately. And like one of those dimensions, for example, is this training report, like what will happen with AI, what will happen with COVID? And that that idea of infinite markets is very tied to prediction markets because prediction markets fill that gap. Prediction markets can actually price all these different things that if you get smarter about all the subcomponents, then you can be smart about the actual component.

• 41:13Speaker 01

  Right.

• 41:14Speaker 00

  Right? Like if you wanna price a Tesla stock, you have to price whether Elon is gonna leave, whether they're gonna over or under deliver on deliveries, whether, you know, how fast autonomous vehicles are gonna come around, all these different questions. And prediction markets can price all these different factors that then feed into the stock price.

• 41:30Speaker 01

  Yeah.

• 41:31Speaker 00

  This is very important for us to keep being smart about resource allocation over time. Otherwise, our model of the world is gonna just like get worse.

• 41:36Speaker 01

  Yes.

• 41:37Speaker 00

  Gonna get less smart.

• 41:38Speaker 01

  Maybe as a last topic, I'm sort of interested in, I didn't realize until chatting with you that your your company is small relative to sort of the scale you're at. So you're not much over a hundred people.

• 41:48Speaker 00

  Yeah, we're a hundred and twenty, I was just asking, a hundred and twenty seven now.

• 41:51Speaker 01

  So how does that work? I mean, like that is very small relative to what you've accomplished.

• 41:55Speaker 00

  So what's interesting about it is that we didn't sit down proactively and like we didn't ride a dog of like how are we gonna build a small company that's lean? It just sort of happened.

• 42:06Speaker 01

  Did you do any particular other things that this was a byproduct of?

• 42:10Speaker 00

  Yeah, so I I think a few things like, and I'm not a hundred percent sure. So I'm still kind of figuring out like, why are all these other companies so much bigger? I'm still like trying to figure out, am I missing something? Or one is Luana and I work very, very hard, very, very hard. Like, and tilted it like we really have a chip on our shoulder. Like, we'd like to think we're the underdogs. What I learned over time is like, so, so if you look at kind of, we're generally like first to office, last to office, uh, last from office, work on weekends. And I think that just generally the output per person in the company just is heightened because, you know, generally the leader is really in the front line doing a lot. Number two is, um, we have a lot of direct reports.

• 42:47Speaker 01

  Like how many?

• 42:48Speaker 00

  There's not really a managerial layer in the company yet.

• 42:51Speaker 01

  It's like a hundred?

• 42:52Speaker 00

  Like, if you ask the one, uh, what maybe like eighty, eighty-five of the people at the company today are doing, she knows.

• 43:00Speaker 01

  Wow.

• 43:00Speaker 00

  Because she probably checked with them on Slack in the last twenty, forty-eight hours.

• 43:03Speaker 01

  Wow.

• 43:04Speaker 00

  And the rest is maybe me. Well, I mean, there's a chunk of people that just don't need, like, you don't need to know what they're doing. You know that they're just doing like, you, you got, you gotta let them cook, like, you know? So that's something number two. And then I think number three is, um, we don't think about org charts much. And I don't know how that will scale. We're still thinking about that, but like, we think about like, here are the sort of, like, we keep sort of dynamically listing here the top, like, X problems of the company today. And how, who do we have on those problems?

• 43:29Speaker 01

  And people move between problems.

• 43:31Speaker 00

  Yeah, sort of like, yeah, it's like, uh.

• 43:33Speaker 01

  Do people self-organize to the problems?

• 43:34Speaker 00

  Yeah, yeah, it's, it's like, uh, you know, like cells in an organism, like, you know how like,

• 43:37Speaker 01

  Yeah.

• 43:37Speaker 00

  if you have like, uh, if you, if you, if you get cut.

• 43:40Speaker 01

  Yeah.

• 43:41Speaker 00

  Your cells will just kind of come around the cut and like do their thing.

• 43:43Speaker 01

  Yeah.

• 43:43Speaker 00

  It'll be like a bit like that.

• 43:45Speaker 01

  I mentioned to you, I really want you to read the Valve Employee Handbook, I think.

• 43:47Speaker 00

  Yeah, I'm excited about reading it.

• 43:49Speaker 01

  It's very good.

• 43:49Speaker 00

  But it, it just sort of happens and it's kind of like, make sure there's like, like, as little kind of constraints or bottlenecks of that sort of self-organization to happen as possible.

• 44:02Speaker 01

  Is this what people expected when you hired them? Is it the type, did you hire types of people that you thought could only function in a place like this? Like, how did you, how did you end up with that culture when it's what I would describe as extremely uncommon?

• 44:16Speaker 00

  You know, we, we don't have all the answers, obviously, but like the, um. One is we do bias on slope versus intercept because people have intercept, I think generally can land this culture and be like, what on earth is going on? Like, this is crazy. And that's just happened. We've had this happen.

• 44:32Speaker 01

  Someone who's used to like a big, more structured organization comes in.

• 44:36Speaker 00

  Or just, yeah, even not even big, like an organization is just structured in a different way and they show up, they're like, this is like crazy, like, you know, this is like complete chaos, right? And, because, yeah, it looks like an organism where like these organisms are moving around. And, and so, so slope, because slope is, they don't know, they're, you know, they're super smart, very high, and they're like, oh, like, they don't even think about what's happening. They just think it's normal. So, so that's one. Number two is like, I always say, I mean, Brian Chesky put better, I didn't, I verbalized it when he put it into towards, but like, I don't manage people who manage work. So people that are just like have, just generally high agency, we never have to check on whether they're doing something. Sometimes we have to reorient a bit. Hey, like, actually, this is not actually that useful, like, we should like do something else, or, you know, or like be in very much in the details.

• 45:20Speaker 01

  But it's about the work, not the people.

• 45:21Speaker 00

  But just they're, they're doing stuff. They have this sort of high agency, I want to always be doing something. And I, I kind of bias honestly towards like execution over strategy.

• 45:29Speaker 01

  Me too.

• 45:30Speaker 00

  I really do, like, because, look, I think strategy is hard, but like, you know, what I've found over time is like, the natural next step for a company is generally kind of natural. Like, you know what I mean? It's like, it's not like, if you probe, like, for a public company, for example, and the CEO lays out a strategy.

• 45:45Speaker 01

  It's not like, what should we do? It's like, can we do it?

• 45:47Speaker 00

  Most of the time.

• 45:48Speaker 01

  How quick can we move and all of that?

• 45:49Speaker 00

  Most of the time.

• 45:50Speaker 01

  Periodically, there's probably like a non-obvious strategic decision that like the founder needs to make, but that's probably a couple of times a year kind of thing.

• 45:56Speaker 00

  Yes, max, max, I think. And it's usually a little bit longer horizon than a year.

• 46:00Speaker 01

  Yeah.

• 46:01Speaker 00

  So I, I think of our role, Luhan and I, is like, I try to, very, very high level, like, are we, are we just like directionally, generally in the right direction? And what are the big risks in the next three to four years? And like, make sure that we, like, are thinking about those and are executing against those. And I really, I really mean in three to four years. I'm, I'm pretty paranoid. Again, from my time in Lebanon, I always think like, what is the thing that's gonna go wrong in three, four years? And like, let me work through that. And then very much in the details. So like, I, I literally, I'm often like in specific copy in the product, like a lot of Luhan and I wrote, still to today, or like even ads, like, we get into the copy, like, is this good? It's very, very, very specific things. And everything in between, we try to like, not spend any time on. And that pushes other people to not spend any time on.

• 46:44Speaker 01

  Yeah.

• 46:44Speaker 00

  And sometimes there's subset of people that that doesn't work well for.

• 46:47Speaker 01

  And then people can just opt out.

• 46:48Speaker 00

  Basically.

• 46:49Speaker 01

  Yeah.

• 46:50Speaker 00

  I mean, there's not a clean solution, you know, like.

• 46:52Speaker 01

  Yeah, of course.

• 46:53Speaker 00

  Just hard, right, barely accompany it, but but a lot of people kind of like it, like they they they just don't want, they don't want to be managed.

• 46:59Speaker 01

  Are you going to be able to keep the company small?

• 47:01Speaker 00

  I really hope so. I mean.

• 47:02Speaker 01

  Even there, scaling fast.

• 47:03Speaker 00

  That's one of the worries I have.

• 47:04Speaker 01

  Small as possible, at least.

• 47:05Speaker 00

  I think about this a lot. That's one of the worries we have. Um, I would say maybe the trade off, which is, you know, people sometimes walk away like, oh, this perfectly run company. And the answer is like, no, like, not at all. The the the trade off is usually, I think we take on more organizational chaos. Does that make sense? Like, and to me, I think there's a bit of a decision you make as a company, like, either you're more chaotic or you you have you have more process, which means bureaucracy and and some degree of slowness.

• 47:29Speaker 01

  Yeah.

• 47:30Speaker 00

  And so Calogie is very comfortable with putting something out there and getting bashed for it, but like, that, you know, three, four weeks later, it gets much better. And now you're much better than you've than if you had waited the two months. We're very comfortable with that.

• 47:41Speaker 01

  It's great. Tarek, this is super fun. Thanks for making time to do it.

• 47:43Speaker 00

  Thanks for having me. This is awesome.