Cheeky Pint - Creating prediction markets (and suing the CFTC) with Tarek Mansour and Luana Lopes Lara

Episode Date: March 17, 2026

Tarek Mansour and Luana Lopes Lara are the co-founders of Kalshi, the first federally regulated prediction market in the US. They sit down with John and Matt Huang to discuss growing their revenue 11x in six months, why they sued their own regulator to list election markets, and how they are building the "New York Stock Exchange of events." They cover why prediction markets are an antidote to social media polarization, the mechanics of market making for culture, and their vision for trading everything from GPU shipments to the Oscars and the weather.Timestamps(00:01:39) Suing the government(00:14:42) Why now?(00:17:12) Kalshi by numbers(00:20:58) Solving market making(00:31:33) Agentic trading(00:33:43) Sharps(00:38:45) Stripe Connect(00:39:33) Evolving Kalshi(00:44:50) Who loses from Kalshi?(00:47:35) Insider trading(00:53:28) The ethics of sports contracts(00:58:08) New derivatives(01:04:27) PoliticsArticle(s):On the Observational Implications of Knightian Uncertainty – Kevin Hassett & Weifeng Zhong (AEI)The 2028 Global Intelligence Crisis – Citrini Research

Tarek Mansour and Luana Lara are co-founder of Kalshi, one of the new prediction market firms that rose to prominence in the November 24 elections. They spent four years pre-launch fighting for regulatory approval to build the first onshore prediction market in the U.S. And now trade more than $10 billion each month in prediction contracts. Cheers. Cheers to give us to you guys. What is this that we're drinking, Luana? Some Brazilian beer. Okay.

It's our most famous Brazilian beer, I'll take. Very light. I don't know if you like it. I like it. I like it. So what is the split between you guys? Maybe in terms of responsibilities, but more interestingly, in terms of outlook. Well, we actually come from the exact same background.

We studied math and CS at MIT, same internships, everything. But I'm a very, very optimistic person. Love taking risk. I think everything's going to work out. He is very paranoid, more on the negative side. So it's always like a very good, I think, balance. And I think that real is outside of what we do day-to-day, that's really the difference between us that works out.

I mean, there's a limit of background. So I was going to be a traitor. that was really what I was going to do. And, you know, when you're a trader, and you probably, I don't know if you've ever met, sort of, or spent enough time with the persona, but it's like a very expected- John is a secret trader.

At heart, yeah. But if you're a trader, you're like an expected value calculator. Like, I think about these sort of tail, really bad outcomes all the time. And Luana oftentimes doesn't. And I think this is the thing that actually leads to great outcomes.

Okay, so I want to ask about that starting out. Because this is really interesting. You guys, started Calci and for several years we're not able to operate until you got CFTC approval. And that's interesting where most companies don't start out that way. And secondly, I feel like the Silicon Valley standard that people sometimes trot out as a criticism is sort of the PayPal, Uber, early days model where you start doing the thing and maybe retroactively a structure is put on top of it, but you do a bit of ask forgiveness rather than permission in the very

early days. And so can you just tell a little bit the story of how you started and that approval process? And then I want to get into whether that generalizes to other companies. Yeah. I think that the approach we took from the start was that financial services or healthcare, I think you can't ask for forgiveness. I think there's a big difference between losing people's money and see what goes wrong with like an FTX example that can go very wrong. With healthcare, there's a lot of other massive examples of it going wrong. And we wanted to do things the right way. Because also when we look at the market, we thought the biggest question to be answered was not,

is this going to grow? It was, can we do this legally in the U.S.? And we're like, let's just actually address the biggest problem first and go from there. And I think the strategy for a long time, people looked at it as the wrong strategy. I think up until we won the election lawsuit, everyone was saying the folks that went offshore,

they're doing a lot better, they're growing a lot more. But I think once we won the election lawsuit and proved that the legal interpretation we had was right and we could do the company as we won in the US, I think it just really, really took off. What were the timelines here? So when did you start and when did you win the election lawsuit? Right. So we started the company in 2019. We started NYC in 2019 and then it took us three years to be able to get regulated and launch. I think it was up 20, 22 at that point. And then we won the election lawsuit and that end of 2024. And that's when we really started ramping up.

There were a lot of like Elon. I mean, there's some overlap to the timelines. But maybe going back to the question, and maybe we can talk a little bit more about the sort of history afterwards. But I think it was like a two-fold sort of, or two-step process. Like, one, it was a pragmatic thing, which is we felt like to get proper mainstream adoption

and institutional adoption, the elephant in the room was like, could we do it in a regulated, credible, and safe way? Because it's a complex marketplace. You're moving people's money. And we have to solve that problem first. That is the hard problem to solve.

And, you know, that will be the road to success. The second thing was a bit more principled. We were, what excited us, like when we, you know, we created this stock, one page on Google Docs, and we wrote a set of things like, why should we do this company and why are we so excited about this? We wanted to build the next generation New York Stock Exchange. We wanted to build a financial market that is in the U.S. that is credible, this regulated. We were not very excited about this idea of building something offshore.

No. And so that was really important because it's like, what kind of company do you want to build and why are you doing this in the first place? There's many paths to success. We just weren't very excited about the other idea. We wanted it to be here. You're the first CFTC approved prediction markets at any scale.

Yes, yes. And still to this day, all the contracts are individually approved. And so... Yep. Yeah, every single contract we file of the CFTC and they have 24 hours to stop it. Yeah, yeah. Okay, so they get kind of a real-time feed of the contract. Exactly, exactly.

Yeah, and it was a very long journey to get to where we are in terms of the contract process and how it works. Because you got to imagine the first time we walked into the building, actually the picture is right here. This is the first time we ever walked into CFTC. You know, you walk in and you're talking about this idea and it's, you got to imagine. the regulators head starts spinning. It's like, you know, you're talking about things that don't have a financial underlying, and then there's this idea of, like, potentially hundreds of, tens of contracts, hundreds of contracts a week.

I mean, now we're like, you know, but there's all these things where the model wasn't really set up for this. So a lot of the process was actually like this iterative process. We're trying to figure out how to actually regulate this as you get feedback from the regulators and what can we do to satisfy the concerns. So it was a bit like building a product, but you're not building it for a customer. You're actually, you know. A regulatory market fit in a way.

And so now you've gotten uncomfortable with you shipping them unless they know. Yes. Have they said no to anything recently? Not well, the biggest they said no to was the elections. That's why we had to end up suing them. They said no for two years. But at this point, I think we've worked with them for so long that we know exactly kind of like they trust us as well. as a self-regulated entity to know kind of what we can do and cannot do,

so we don't do anything around war, assassination, those things that we don't do. So within the parameters that we've worked with them, it's a lot faster. So sorry, the election lawsuit was they were willing to approve contracts generally. They were not willing to approve contracts around who would win the election, which is a pretty popular contract at the U.S. presidential election. And so you sued the CFTC? Yeah. Our own regulator.

I mean, and. Which is generally not considered a best practice. It was, I mean, okay, so. So we started talking about the election market at the end of 21. And we started talking to, you start engaging with policymakers, like talking with Congress, a bunch, and the regulator. And like, yeah, I think it's a good idea. It's a good idea.

But then they weren't moving. We started noticing like, okay, something is off. By the end of 22, they sort of like delayed the approval until after the election, what we call a pocket veto. That was brutal. So that was one of the hardest times in the company where we had to lay off a bunch of people. But the harder part of this is that your team and some of your investors or majority of investors kind of stop.

Believing the idea. Yeah. But believing in the strategy, the idea. And it's a bit like this is getting a little bit unhealthy. You know, you guys should do something else. Like, you know, clearly this is not going to work out. But we could not. we couldn't get ourselves to do something else.

We just couldn't. I mean, and so we're like, okay, we're going to try again. And end of 22, so imagine the team is an all-time low in morale. They're waiting for a new strategy. A bunch of people left, a bunch of people, you know, got laid off because we had to downsize. And, you know, our message in that next stand-up was actually, guys, here's the 23 strategy is we're going to try again.

We're going to do the same thing. Same thing. But this time it'll work. Exactly. But this time it's going to work. even though every inch of evidence was pointed in the other direction. And I will say, a lot of this is her.

Like, you know, I wanted this to happen so bad, but I'm like, my rational brain was like, better listen to these people. And Luana is much more dogmatic. So we try again. End of 23, they block it again. And I was really at the point where I'm like, okay, these prediction marketing

is just not going to work. It's just, and then, and then Luana was like, well, the only thing we can do right now, out of the entire range of possibilities we've got to sue the government. And I mean, yeah, at the beginning it was like, this is crazy.

And we took it to the board and we had Alfred and Michael at the time and they're all like, well... Alfred Lynn and Michael... Seibel from YC. And I remember that board meeting, it took a few board meetings, but it took a few times.

At the beginning it was like, well, we have to tell you guys it's a bad idea. Like, you know, these are all the ways that it's a bad idea. Because your regulator, you're like now a 25 people company like they the government can do anything like they can shut you down take out the license i mean it is it true so so rare you work and even if you win you will probably lose

like you will end up getting killed in the process um and it took a few times and remember very really there was a meeting we had internally before talking to the board and this was the night before We had line up the lawyers and everything and I got like cold feet. I was like let's just focus on getting like a clearinghouse where you could focus on financial products we can focus on all these other things

we don't need to sort of tank it all on this and you know really bet the farm on this and I remember no one in that call I forgot the exact word but it was something along the lines of like are you fucking kidding that sounds like me

and I realize like all right I'm not going to win this fight and but then I But the other part of me is like, we got to do this. Like I knew it, you know, and so we went on the board, and the response was basically, it's an anti-pattern, it's a bad idea, but a lot of great companies are built by an anti-pattern. There's something off that is weird that happens, and maybe this is yours.

Yeah, it's a good way of putting it, that every company is different in some new way, and so, yeah, this could be yours. What was the basis for the decision where you won the election last year? Like, was there any interesting policy angle? Right. So the whole point is that the government cannot stop any type of contract unless it makes a finding that's against public interest. And it has to fall within certain categories of war, terrorism, assassination.

And the CFTC was taking the stance that they were trying to fit elections into any of these things. They're like, oh, elections might be illegal on the state law. And, you know, because betting on elections, there's this one state that in bucket shop law, they try to find something to stop it. We knew we were very, very clear on the law, like elections have economic impact. If the elections have economic impact, they need to be allowed to trade on a futures exchange or derivatives exchange. And it was basically what the lawsuit did is it told the CFTC that they couldn't just do

whatever they wanted. And that kind of like... The categories of prohibitors, it needs to actually fall under one of the prohibited categories, which elections did not. Right, exactly. And I think that's important because the law, you know, the thing that we all say like the law applies to companies, but it also applies to the government. Right.

But you should make your point about maybe suing the government's under Reno. Well, I think certainly in crypto and prediction markets is sort of this unique thing of suing the government. But I was sort of surprised to realize that Coinbase has sued their primary regulator in GovTech, SpaceX, Anderil, Palantir all had to sue for various reasons. So it seems like it's actually more common than Silicon Valley conventional wisdom. So like what, I guess, advice would you have having dealt with that guy? To people out there trying to build businesses, like, what sort of situation would be, you think, right, to actually make that kind of job? I think it's a sort of no other option situation, right? So it's still painful.

But did you actually have no other option? Because couldn't Calci have done fine without elections? I mean, elections are obviously very helpful because they're such like a big shiny thing. But I presume elections are not a majority or contracts today. I think it was just too important. And maybe that's the dogmatic or whatever. But it's like it is the holy grave of market. It is like that's the one that you can see the use case of the data the best.

And you can see the use of the, and you can see the 2024 election, right? Like the polls were completely wrong. And the markets were so much better in bringing that sort of information. And I think that it's the shining example of why these markets are forced for good and we need to have them in the U.S. and regulated, which other markets so we just won't have. So the John's point on PayPal and Uber

and asking for forgiveness, there were other prediction markets operating and showing real usage offshore. And so I'm wondering how much did that help demonstrate that election markets weren't against the public interest? Like did that factor it all into the court case? Like the fact that people were already doing it?

I don't know. But I mean, specifically on the court, it was much more great. grounded in sort of like... In the law. Yeah, the law. Like reading our law is the Commodities Exchange Act. So that's one of the financial statutes.

The other one is the Securities Exchange Act. Instead of reading it and really interpreting it and is the regulator overstepping. Now, I think for us it was like a good way to learn, right? Because we could not learn about our product because we took this sort of regulatory first approach, like where we will ask for permission first before doing something.

And so in some ways it was helpful that you could have some data, some evidence that could guide our decisions over time. And I think it also helped educate some people about the existence of prediction markets and they are here, here's how you can use them, et cetera. But I don't think on regular offshore players really help from a policy perspective.

Could Kaukesi has been started 10 or 15 years? prior or was there some moments of openness in the CFTC? Was there some tech enablement that was required, where stable coins required, just. I do think that there's a part of it that crypto at the time was auger and there was like some very early prediction markets. I think that that, the existence of that made the CFTC also be like, we need a legal regulated alternative to this.

Because before you could just say no to things. I do think that that played a role, but maybe like 5%, 5%, maybe 10%, I don't think it's more than that. The broader thing is like, I think, you know, there's always intellectual interest in prediction market, and I think that starts in the 50s. It is a better source of signal than most other mechanisms of getting signal, right? But there wasn't a real pain, I think, 10, 15 years ago and the way there is a, there is pain in the last few years.

And that pain, I think is a sort of, I think the country is more polarized. I would say the world is more polarized. Social media has really bifurcated social feeds. you know, clickbait is rampant. Like the incentive structure for most things that we read these days is clickbait, whether it's a lot of traditional news or social media or other. So there was more of a pressing problem, I think, that, you know, helped create the wave

and this sort of adoption that you're seeing in prediction markets. That I don't think happen or would have happened 15 years ago because the problem wasn't that. Yeah, and that's because, like, most of our users, like 80% of our users are actually just looking like consuming information. They're just coming in and seeing who's going to win the Texas primary yesterday

and seeing like, okay, the polls are saying they're tied, they're not tied and all those things. And those, that consumption of information is way more important and relevant now. Okay, so you were saying like algorithmic feeds in Kalshi markets do very well on algorithmic feeds

and just maybe people wouldn't have been as interested 10 or 15 years ago. Yeah, I think I just think that sort of there's a meaningful and accelerating. of distrust in traditional sources of information. And so you need a new one. And this does work, right?

Like the incentive structure for prediction market is truth, right? It is more volume. It is more liquidity, which translates to better and more accurate forecasts. And it took a few iterations for people to start trusting it. But like, you know, as you start building a track record, people start trusting it and they're never going to use a better product. Well, to the point of substantive volume, can you guys give us the outline of, it seems like it's grown very quickly. So volume in February was 10.4 billion.

Dollars of contracts traded. And that's up 11x over six months, I think. Wow. I mean, since August. It's going so quickly, you don't even bother to go back a year because that's just ancient history. I mean, you know. I mean, a year ago, it really is. It's like we just had, for example, one sports.

We only had the Super Bowl. In February, yeah, I mean, it's growing very fast. Fastest growing company outside of it. Yes, I think so. And we compete with some, I think, even some of the top AI companies. I don't know what Cursors and Anthropics' last, latest numbers are. But I think 11X is very quick, even in AI. It's quick.

And I think because it's a, so we are a marketplace. It's a true marketplace that has all the attributes of, you know, has network effects. So what happens in those situations is that users retain better because there's more diversity and more liquidity. Their participation and volume grows over time, which obviously grows their usage, but it also grows other people's usage

because there's more liquidity in the system, and then they share it more with other people because the product is getting better. And so the sort of trifecta of factors is leading to this sort of growth. When some of your early growth depended mostly on other brokers, and I think you've evolved that mix today, like, what's the broker mix and how do you think about that? Fair, what the broker in this context? Like, Robin Hood.

Okay, like, it's just true. Well, to explain what that is, which is interesting. I mean, the truth. I can explain the broker part, but I don't know what we want to show on the numbers part, but basically. That was the tough one. That's why we look at each other. I was like, all right. So because we're in exchange in clearinghouse, we basically,

function like the New York Stock Exchange. You'd never be here for her. Yeah, exactly. The Chicago Mercantile Exchange. So brokers can connect to us, right? So you can go to Robin Hood to trade stocks. You can go to Robin Hood to trade on cows. You're same with Coinbase or whatever.

And it's always been part of how we think about we always wanted to be in an exchange in the clearinghouse first and actually a connection to a Goldman Sachs or a Robin Hood is very important for how we thought about like this ecosystem as a whole. In the beginning of last year, we launched the first broker partner that we had. had was actually Robin Hood and the Weeball. And at the start, actually, when we were starting to ramp up, the brokers were a very, very big part of how we started growing, which was actually very great because the brokers bring so much

demand, then we get all the market makers to come in because they want to treat against retail flow. And then we could kind of like buy ourselves time to ramp up the direct product a lot to where it is now. But basically how you think about it is, well, we really are at the cores in an exchange at a clearinghouse. And then you can access us for our app website API, but also any broker.

We're investing more into institutional now, international brokers, so you can be in Brazil and you can trade on Kaoshi, all those things. They're coming soon. But on the numbers, you can take it. I mean, maybe we won't share numbers,

but the direct, what we call direct, Kashi direct, which is our Kashi.com, Calshi app, the consumer business, that has grown, you know, that has sort of dramatically outpaced the rest,

our other, the sort of intermediated or broker business. And I think it's just that the brand has gone mainstream. I think people, when they think about, have a difference of opinion on something, it's sort of becoming synonymous. So like, oh, let me pull up Cali and see the odds or let me sort of place a position on Cali.

And there's just a lot of organic growth now. And I think that's going to continue over the next few months. You're describing how you grow the individual retail kind of side of the market, whether people are coming through brokers like a Robin Hood are people coming directly to the Calci website. There is also, when you're in exchange like this, you have to spin up market making. And, you know, in the end, like, you know,

the New York Stock Exchange doesn't have to think too much about market making because just the economic incentive is there. And so when something is at large scale, that's not as big of an issue. But I'm curious what that was like in the beginning. Like, were you guys doing the market making? Did you work with market making partners? Now, how do you incentivize market makers

to participate. I'm just curious what the market-making scale-up has looked like. So there's actually two groups of contracts on markets on Kaushin. They behave very differently, and the market-making incentives are actually pretty different. So you have the long tail of markets, right? Like the ones like, well, one direction have a reunion or, you know, all those things. And they are actually very hard to price. And because there's not necessarily a lot of demand, we actually have to incentivize market makers to come in. And there's like liquidity incentives, all those things for them to come in. And I think it's actually how we think about

how to build our remote long term. It's actually how do we get very, no, sustainable, solid liquidity in this long tail of markets. So we can get like, we have like, I think 10,000, how do we get to 50, 100,000 markets with still. But on the other side, you have the more classic like crypto sports,

all of those guys. And on that side, it's actually a lot easier to market make because you have very clear, proven demand, there's a lot easier to price. So the market making incentives on this side is actually we don't pay them for it. we just rebate fees, but they have very, very hard conditions to meet. They need to have uptime of certain amounts, spreads, and top of box size and all those things,

because we see it more as like incentivizing stability of the book than it is incentivizing them being there. So what does incentivizing stability of the book mean? For example, if you think of a live game or like if you're trading like an hourly crypto. You actually don't want the price flying around a whole bunch if there's no new information? Right, exactly. Or even if there is, right? If someone is about store a touchdown, you don't want the book to just have no liquidity whatsoever. You want it maybe to go a little bit wider, but you want people to be able to trade.

And actually, when we go into the intermediated model, the brokers come with expectations that they have from traditional markets, right? So they're expecting we want this spread and this size at any point in time. It doesn't matter. So we need to go to the market makers. I'm like, how do we incentivize this? Even though if you think about, you should just let the markets do whatever they want to do and if they're going to go way wider because they need to do it is.

but we have to kind of play with incentives in a way for all of our users, including the brokers. But during those moments when the spreads would normally blow out wide, are market makers losing money then and they're cross-subsidizing to the other parts where it's more stable?

Well, now there's so much demand that I don't think they're, like, you can make money on spread even if the spread is like a little lower. But that's the point of the program, right? It's like you have to think about all the benefits you get in this program and then even if you're

losing a little bit in this time, having the benefits is worth it. So you want tight spreads all the time for the major markets. That's what markets have been. And that actually takes work to engineer. It's hard to get there. But there's more to it, which is, so I think the magic and the uniqueness of, I would say, or the special thing about prediction markets is that a lot of the liquidity is not what you consider a market maker.

Right, right. It's people. And so this goes back to the whole point. So let's just go back to from first principles, right? Like, you know, there was, okay, the regulatory thing that we figured out, but then there's a liquidity problem, which is historically, it's like, a bit like we said, the New York Stock Exchange or the CME, okay, they're like, we're going to create a grain future.

We're going to take two years to figure out what it looks like, and we're going to call all of our buddies. Like, you know, the 50 market makers and that we all know, we all, you know, hang out Christmas parties together, et cetera. We're going to get them ready and they're going to start helping us get this product launched. And then we're going to market it for next three years and then it's just the same thing. The liquidity is there. But prediction markets is really different because now you have to create liquidity in these products on like a weekly, daily, maybe even hourly basis.

Like how do you do that? It's much more dynamic. There's new things all the time. I think it's counterintuitive to people that you have to incentivize market makers to create liquidity. Because like in the stock exchange, you don't have to incentivize high frequency trade. firms to create sub-second liquidity. They are very excited to take on that project themselves and build the high-speed interconnect between New York

and Chicago to accomplish and everything like that. And so is this just the stage that prediction markets are at? Or is there's something fundamentally different? I think this is where I was talking about, which is this idea that you need, so maybe finishing that sort of line of thought, and then I'll get to the answer there. you now have a model where you need liquidity to be built on the fly, much faster, much more dynamically, right?

And the market makers, the traditional Washington market makers, are not geared up for that. It's not like they can spin up a new desk to price like politics or price culture in an hour, right? And so, but this is the part that gets really interesting, which is like, and this goes back to the foundational principles around prediction markets, is like a lot of these markets, the people that will price them the best may not actually be the experts

or the authority figures that you usually would think about, it's actually random people, like, you know, that live... Right, internet anons. Yeah. Exactly. The super forecasters. Those are, it's like extremely dispersed. You cannot find, like, clearly define the demographic or who they are.

And I think that the thing where we got to now, and that took a very long time when you had to incentivize, is we have the community, a strong community of super forecasters that are on Calshu. They can help price these things. extremely effectively and fast, where you know, you don't have, but it took a while to kind of get them incentivize

and come in and spend the time and resources to take it from a hobby, which was a hobby for a part-time job. Now it's a full-time job because the pie is so big. And a metric that we can share is actually the, when you think about traditional market makers, the biggest percentage on a platform of a traditional market maker is less than 5%

of the maker orders in that market that have matched. Of the liquidity. Of the liquidity. Sure, see that's 10 again? Yeah. So less than a lot of, 5% of the order, so people come and make orders, less than 5% of the ones that match, actually come from the big institutional market makers you'd think about.

I see. Over 95 are just like... Peer to peer to peer, like, or funds that have like two people that just got stuck... Which is unusual for it. How many of those small, full-time little shops are there? There's over 2,000 people that market making... People slash small shops, yeah. Yeah, on like...

Yeah, I think what Matt's getting asked is like, who is a market maker on Calci? Like, you know, there's all these Jane Street conspiracy theory means. Is it like Jane Street? Or is it like some guy in his garage, you know, drinking Red Bull at 3 a.m. market-making The guys in the garage are the most crucial. And you're saying those are 95% of the flow. They're like extremely crucial to the ecosystem because they price fast. They're monitoring the situation.

All the time, right? They're the original situation monitors. Yeah, yeah, I see. Calchry is built on people who are monitoring the situation. So, so in those guys, so one example I'll give. So the, and I've given this in the past, the, the, the, the best inflation forecaster on cash for the last few years is not, none of the institutions or the, you know, the big name hedge funds. It's this guy who lives in Kansas, never traded financial markets before, just likes to read the news and just knows that I predict inflation. He can feel it.

Like, you know, and you have so many of these people, like, now you have like, I mean, I would say like a few thousands that are formally kind of like committed, but like there's tens of thousands of like these people that know a bunch of like, but a bunch of different topics. And they're sort of actively pricing these things and they do it for as a full-time job and they get rewarded for that. You need to talk about my favorite user. Oh, yeah. Well, I have a new favorite user, by the way. Okay, each of us, each of you can tell us your favorite user. I was thinking about this morning. Your favorite user?

The Washington Journal article about the tax guy. Oh, yeah, that's true. He's a good candidate. But no, my favorite user is this Ariana Grande super fan. And he found cows during the election season. He's like, I don't like the elections. Like, whatever. Then he found our billboard ranking markets of, like, charts.

He's going to work on important markets. Important market. To me, very important. And he's made over $150,000. He's getting every single thing. He paid back student loans. He put himself for a master's degree, we bought a car, and all those things.

He just loves these markets. And he's never really traded, never done anything like that before. But it's the first time that he actually has a way to monetize this very compulsive hobby that he had on music charts. And he's able to do it. And he's also very, very nice to us on Twitter. So I like it. So I had many over the years, but maybe I shift a lot. He's not loyal.

See, I'm loyal to my guy. Well, I love all of our users. But there was an article last week. in the Washington in the Washington about a tax accountant who was very active on Kalshi, Alan. And he, you know,

when Doge came around and like there were a lot of sort of talk about how much they could cut, he actually read a bunch of tax codes and a bunch of statutes, just like dug extremely deep and then realized

there is no way they could hit the target. like and even if like he really kind of deterministically realized and then he basically talked to his wife and he's like I have extremely high conviction in this trade I know I you know it's a bit like Michael Berry at the big short so this guy put a big short but on Doge this time right and and it was big like he really kind of went all in and you know he won and it's just like one of those like amazing sort of showcases of what this can do like now you have a market that like if you have that sort of knowledge which maybe oftentimes is esoteric like i'm assuming none of us have read all these tax codes you can actually go out in the

world do research get smarter about the world and then you know get rewarded for that and and that's awesome right you know an early field of AI was poker bots are you seeing any good AI market makers when you say no one's read all these tax codes i mean no one except Claude that's where that's where we should We are seeing more, like, increasingly more people using agents to trade. So that's definitely, I mean... On the API side. On the API side, it's very big. And, you know, like...

But like, do you have users who are successfully running market-making businesses that are mostly agentic? Users don't exactly tell us their strategies. But, like, you've talked to them, you know. Yeah. Generally, yes, yes, yes. But, you know, the, I mean, it is... The way I think about it is, like, you know, do we think RENTEC back in the days was using agentic models?

I'm talking about Renaissance. to trade, like, yeah, the early versions of them, right? And so I think they're just evolving and they're getting better. And like, most of our traders in their stack have some sort of like summary and synthesis module that's

AI-driven. Yeah, I guess what I'm curious about is fully autonomous, no human in the loop, consuming information and providing a market based on that. Like, that feels like it's coming quite soon if it's not, like your cloth making a market. Yeah, I don't know if there's a full

I know that for example there's a lot for international elections just on like for example translating all documents, polls and be able to kind of do all of that. But I don't know if it's all. We're doing, so we don't know if the models are there yet, right? And I was, so, you know, we launched calcium research recently, which in one of the threads that we want to work on is we're talking to some of the research labs

to create a new benchmark around which models actually predict the future better. Which could be a unique benchmark. mark around, like, are these models developing some understanding of the world that goes beyond memorizing, you know, old patterns? And I'm honestly excited to see how it goes. And what's the eval for that? We don't know yet. But I think you can roughly kind of let the models run for, you know, make predictions on the same set of markets for like a month or two and see which ones perform, like, you know, percentage of predictions that were correct, P&L over time, etc. Right. Yes, yeah. Okay, another market making, um,

Question. So sports bookies have this need to crack down on what in their industry is called sharps, you know, people who are too good, where, like, I think people don't think so much about this dynamic. But for a sports bookie, the best possible punter is someone who is kind of unsophisticated, bets on like their home soccer team's game. Inrespective of the odd. Exactly. And just wants the home team to win or whatever. And the worst kind is someone who's like super sophisticated, finding the narrow markets. Because for a bookie, you know, maybe they're making odds on 10,000 different markets.

Like they only need to be wrong once or twice for, you know, people get to choose which they pay on. And so they presumably can't be right on all the odds that they're offering. And these sophisticated people go find those. And so what happens is they basically use behavioral signals to identify if you are just, up and you're betting on your home sports team's game, that's good. And if you appear to be really sophisticated with all the signals that they would use that, exactly, they shut them down. But it's interesting, right?

You think, like, I'm just booking on the bets that, you know, on the odds that you're offering. But, like, if you're too good, they'll shut you down. It's maybe, like, Carg County in Vegas. Do you have this dynamic with sharps? Like, I would have thought, no, that you just are fine with it. But, like, do the market makers worry about two sophisticated counterparties on the other side?

The sharps are the market. To be clear, we don't limit any winners. We don't have any of the, like we, we want all the winners. Please come, sharps. Well, we need the sharps because how do you get market accuracy without the sharps? Right. This is the difference of like the... Well, yes and no, right?

Because what you want is different because the sharps can snipe. They can just turn up once when the odds are wrong, grab a big win and then disappear. Whereas what you're describing is you want during the game, or during the election, you want narrow spreads all the time. And so I feel like providing good market making is different than being right. A lot of the sharps can actually do better if they provide market making and, you know, like become part of the liquidity.

So this is the being difference, which is very important. Like that the, the, the, maybe the skimmer. Like, I don't gamble. I trade, which I've always found a difference. And I think gambling is this idea where the business model is you're the house and your revenue is your customer's losses. So a lot of the dynamic that you describe has to be true because your incentive is like,

well, if somebody's making money, I got to stop them because they're making me lose. That's just going straight from my bottom line. And the opposite is true. If somebody's losing money, I've got to figure out how to bring them back. That's a very different model from like traditional financial markets where like the structure is you have to incentivize

fairness and transparency. That's the structure. Like you want to create fair rules of the game for people to participate. Maybe Matt is better than Luana. Maybe it won is better than Matt, and like, they can battle it out. They can figure it out. You think the incentive system is very different where you do not, like a casino or something,

you do not monetize on some zero-sum other person losing. You monetize just on transaction fees. Yeah, the best outcome for us that people are like, this is fair. They have good prices. They have stable liquidity. I'm going to go there. But of course, for us to get there, we also need to incentivize different players differently. So that's why, for example, a lot of the liquidity programs coming to effect.

They're like, okay, if we're providing liquidity, you're taking a lot more risks because you're putting yourself out to be sniped. then we're going to lower your fees. But if you're taking and you're going to snipe, you're going to have higher fees so you can pay for that activity. So in a lot of ways... You'll use fees to incentivize pro-social behavior?

Exactly. And I think that that's actually how we see a lot of how financial markets actually do the same thing. The same thing. But it's more balancing out the marketplace so that people are providing value to the marketplace have some, you know, a little bit more tilt. And then people that are like taking away value,

have a little bit less. What behavior is pro-social and what behavior is antisocial? Well, insider trading is antisocial. Right. That's a big one. Yeah, yeah. And illegal. Yeah.

But, you know, but it's, and look, sniping is part of it, right? You need people that, like, all of a sudden have gained some information edge and they, and they do it in traditional financial markets all the time, right? Like that, but to have liquidity and make sure that people are there and they're investing the resources, they have to get, you know, as you said, some incentives. But the interesting point, I think, and I think this is part of why prediction markets are being adopted so so so so much is people like this idea that if like your edge is proportional to your research how informed you are how much time and energy you put into this um and and i think that only

existence prediction markets or traditional financial markets except that for a lot of people traditional financial markets they're just less interesting right like in here you're researching about doge and what's going to happen or what the election and how people think about elections and how they vote that at least to me feels a little bit more interesting than, like, anything about IBM's quarterly earnings every quarter. Calci has built a new kind of marketplace where real-world outcomes are traded, like whether the US will confirm whether aliens exist before 2027.

You have thousands of participants opening, transferring, settling their positions, all in real time. And underneath it, as you can imagine, there's a complex multi-party flow of funds. That choreography on Calci is powered by Stripe Connect, onboarding participants, processing payments, routing funds, managing payouts. When money movement becomes programmable, new products or even new market structures become possible.

So if you're building something new with complex money flows, Stripe Connect was built for you. Let's talk like different market verticals. And I think today everyone gets elections, they get sports, they get economic indicators. But I think you can look at prediction markets as this kind of search function across the set of interesting markets, humanity wants to trade. And it's kind of a weird artifact that the CME used to green light, like wheat and oil and corn. But now you get to green light a thousand markets a day. So what do you think we're going to find as we do that?

One thing that we're very excited for, we're actually starting to go in the direction of, for example, things like watches and bags and all of those things that are like more going to the collectible side. they were actually able to do derivatives on those things. One thing that you should talk about is the, you know, GPU, compute is a very, and I think the compute, what we're thinking a lot about is that there's a lot of these types of things that they function better as a more traditional future. So things that, like, don't have, like, a binary, will it be at this price? Yes, no, but it's more like an actual future.

You can have margin. You can have more, like, institutional grade liquidity and all of that. And I think that that's a great example of, like, when we start going more and outside. of binary markets and more into the traditional ones, then what we're doing is expending kind of that from grain to compute from green. So it strikes me that obviously the futures markets that have worked best are these large commodity categories.

We're sort of in an era where humanity is spending more money than it's ever spent before on a new commodity category. Right. So and the other traditional markets don't seem to be attacking compute. So the way that we think about we want to be the biggest derivatives exchange in the world, right? And for that, when we think about product roadmap, there's four things that matter. The first one is breadth of topics of markets, right?

So we think about compute. We think about sports, think about elections. We think about securities. We think about all of that. The second bucket is really market structure. So right now we only have the binary as no. We want to have things like futures, like swaps, options, all of that. The third one is really margining systems.

Right now is very bad. You have to put all the money up front. You have to tie up all the capital in the national. a lot of, for example, will a hurricane happen this year? Very, very bad for you to be actually like market making and selling those contracts. It doesn't make almost any sense, like capitalized. And then the last one is liquidity.

And when we think about it, is like, if we win these, we have the broadest set of markets, we have the broadest set of market structures. We have great and, you know, very, I don't want to say cheap margin, but in a way around that. And then good liquidity, we're going to win on everything that we do. So everything that we do in the company is like, it needs to be in one of these four buckets.

And I think a lot of the topic side is like how do we actually match the right topic with the right market structure of the right margining and how do we make sure that it's all coming together. But you're completely right. I think that being able to build all the margining systems, all those things from scratch, we're going to be able to do margin models a lot faster and list a lot of these kind of new markets a lot faster. Because of your direct mobile app interface and the fact that you target a lot of retail, do you, do you, worry that sort of the markets you're going to gravitate towards are the ones that are most interesting to just retail? And how much do you think about... As opposed to like the pro markets? Yes, the kind of institutional markets. I think of compute as much more of an institution to institution market. So yeah, how do you think about building liquidity and interest

upmarket? Yeah. We almost like divide the company again in the ways. Like we divide the markets and like sports, crypto and everything else. But in how do we make what we have great, but very new things because I think what got Kaoshi here was not the regulatory side was not it was really that we're just really pushing what is the next thing it was elections and then after election in sports and for us it's like we need to be pushing what the next thing is and doing that very well and I think that if we don't if we stop doing that we're not we're not going to win the company's kind of structured that we have the the market operations we have the engineering side all of that that's set up for maintenance and improvement of what we have

and then the new teams like institutional the margin team international that are kind of pushing forward and we just try to kind of find a balance on like those teams and then a platform layer that is like the core exchange and compliance and all of that. But it is tricky because we're still like 120 people to do it. Are you seeing pull already on the institutional side in certain topics? Yeah, no, for sure.

And I think that we are, we actually just launched a week ago this thing called block trades. I don't know if you know a block trade. It's a very institutional way to do it that I can call you and negotiate a trade and then we go and put it in the exchange versus trying to do everything that way. So we're trying to build a lot of features

to start getting more in the institutional side. Are they trading the same things that are on the CalShe retail or are you offering new types of products for them? Yes and no. So whenever they're interested in something like the, there was a lot of interest on the tariff situation. Is there going to be a tariff or not?

A lot now with the petroleum, like the reserve and count of how that's going to go. So whenever we hear, we want to trade this market, we just listed directly and then it's accessible to everyone. But I do think there's going to be a very big gap on what the institutions are going to end up trading versus not. But we just listed to everyone. It's very cheap for us at this point to least in the market.

In the early days of Uber, it wasn't bad for the taxi business because it was just excess capacity and, you know, serving on net need. But then after a pilot was bad for the taxi business. Are there existing businesses that will feel the effects of Cal She and other prediction markets because it's a bigger market, there's more liquidity. Like, I can think about there's just existing futures exchanges, like maybe Calci is a better place to hedge your soybean prices or what have you. There's sports bookies, obviously. There's political polling firms where maybe you can get kind of the same information way cheaper.

So who do you think will start feeling the effect of prediction markets because they have been in some way superseded? Yeah, there's that funny meme of like the guy knocking on the door and it's like, Who is the next one? The grimbrisca meme. Yeah, yeah. So you don't want to do that. But I think that a lot of what you mentioned, right?

I think that just traditional betting that we talked about, all the issues that that industry has that we're very different from, there's a traditional future. Now we're going way more into their space. So I think there's going to be difference there. There is the political polling that I think since the last election, there's just a lot of campaigns using our data and all that. There's parametric insurance. Once we have margin, we can start going to more hurricane, natural disaster,

all of that side. Is there a tragedy of the commons with the polling? Part of the reason the prediction markets are accurate is because they interpret the polls. Right. So like if people stop using polls, like in some sense, poles are the sensor that you get

of what people's opinions are. And then the prediction markets are like the mathematical interpretation of the polls. Yeah, my take is that polls are just going to get a lot better because what people are going to be is like, okay, I can make money if my polls are right. So I'm just going to commission this poll.

And I'm going to do this. And now you can actually, like, compete a lot of polling models into one market. It's like 538 did kind of the meta-pole interpretation. Exactly. And you can kind of have one number that's kind of aggregating all of that. And even in the last election, there was someone that actually did this. They commissioned a specific poll to do like nearest neighbors type of thing. It was like, I don't know how it was, but a different type of poll.

And then they were able to make a lot more money in the markets. And that's the whole point of, like, having money and skin in the game. aligns the incentives with truth, and then the polls are not just paid for like, tell me what I want to hear, but what the real number. So I think it's complimentary. Same with the news. A lot of people are like prediction markets

will destroy the news. I think it's way more complementary. Like when you're talking about an election, you're going to give your opinion. The market's not going to give you an opinion. You still need the commentators, but they're going to be able to show a number and be like, this is what the forecast is,

and this is my opinion on it. I don't think the opinions are going to disappear. You guys referenced insider trading earlier and there's just the policy question as to what the right policy should be around insider trading when it comes to prediction

markets. I think it's pretty nuanced. Like it's nuanced from the stocks case, right? Where famously there's lots of you know you see SEC enforcement actions all the time against things that aren't allowed but there are cases like a hedge fund can have proprietary satellite data

of the Walmart parking lot and use that to trade earnings And that is information that only that hedge fund has, but, you know, that is permissible. Right. And so similarly, I think there's just like a complex set of line drawing exercises here where presumably we don't think government officials should be trading in advance of military actions. Right. What about leading up to the Super Bowl, you know, predicting the bad bunny halftime show length?

I mean, you know, people have that information. And so where do you think the lines should get drawn on insider trading? Yeah. And it's just, you said it perfectly. It's a very complicated question, and it's a complicated question for stocks way more into a bigger scale than it is of prediction markets. The line that we take now is that we follow what the federal law is. So it's basically if you have... These are, sorry, CFTC rules?

Well, CFT and SEC. They both have it. So basically, if you have signed an agreement that says you cannot share some part of data. So if I work at the Bureau of Labor Statistics and I have in my confidentiality, then I'm not able to say what the inflation numbers before, then it is you have like, You cannot be sharing that data. But if you know, if you know that they're going to be rehearsing the Thursday before the Super Bowl and you're outside and you're like, I hear Lady Gaga's singing, that's fine. And that's the same thing that, you know, a lot of hedge funds do with like Starbucks and people know, okay, there's more people, if you're people in the store. And that's the point.

Like, markets are very good at incentivizing information. We want information to come to the markets, but we don't want it to be unfair. And if you have access to it in an unfair way, you should not be trading on. Okay. So you cannot trade on information where you have some. duty to hold that information confidential. We actually take it even a step further. For example, if you are a government official, you cannot, like if you're in Congress,

you cannot trade on bills passing, even though I don't know if they have an agreement. Famously, Congress people can trade on stock. Right, right, right. So it's like we're actually like taking a step further there. And we're working a lot of the regulars because obviously it's a very new problem for them and for us, but we have an entire part of being regulated, we have an entire surveillance division that is looking at every single flag. They pretty much don't sleep.

And they just try to figure out everything. And we put out two cases of two weeks ago of two insiders that, because we also regulated, we're able to charge them a lot of fines. We charge them over five times what they made and all those things. They banned and all that. What's very interesting to me about these stories is that you guys were doing that, where with the public equities markets, the SEC is extremely enthusiastic about information.

enforcing their insider trading doctrine. Just what has the CFTC been like on this topic? It's a great question. So obviously the CFTC, you can think about it at three steps, right? The first step is our own surveillance and enforcement. Then the next step is it goes to the CFTC and their own surveillance and enforcement. The last step, if you go to the Department of Justice, you can. And I think the biggest difference is when people look at the SEC cases, most of the time, they take a long time.

because the exchanges that their research and their investigation, and they put some plan, they blocked them on, and it kind of goes through the process. So it's still like that. Like every single trade on Kouchy goes to the CFTC, they have every single thing, every single case goes to the CFTC for them to review. So they might take action. We don't know, but now the ball of the quality of the law.

Okay, so you refer cases to the CFTC. We refer cases to them. But we kind of do our first step of our first level of protection there. I'm curious. There are clearly markets where nobody knows the answer. yet of some event in the future. So like it's sort of impossible to insider trade. And then there are markets where a single person can change the outcome.

Like the mentioned markets in a speech or maybe a sports player doing a specific number of shots. So like how do you think about kind of that spectrum? Like are mentioned markets a bad idea because they're just so inherently game. Yeah. Or are they like limited in scale fundamentally because... Mention markets like the Brian Armstrong Coinbase earnings thing and stuff. That's the worst example. But yes, I think that, well, inherently, I think major markets are actually great.

If you think about the Fed, right, like the amount of hedge funds that are just sitting down being like, is he going to tilt his head this way or this way? And if he does that, it means he's not very sure. Fed meeting minutes are the original mentioned markets? Exactly. That's actually pretty much the, and it was because we just know that specific words being used mean very specific things and he can move the market so much. The same thing with Trump, right?

If Trump says, we're going to war, that's going to move the markets a lot, right? Or if he says a lot of things, like tariff, everyone knows moves the market a lot. Even in, yeah, just a lot of everywhere, things that people say move markets and move a lot of different things. So I think the major market is very important. Obviously, the person that is working on the speech or that is saying the speech cannot trade. And that's kind of how we enforce it. So like if you are Gavin Newsom and you're, there's a market on where you're going to say, you cannot trade it. and your staff cannot trade it.

That's part of the political kind of cuts that we do there that they cannot trade. But I think that's the point, is like, if there is a way to restrict some players in the market so that the market's fair, and the market's positive, and there's an economic utility for it, the market should exist.

We shouldn't say like, okay, there are five people that could manipulate the market and the market shouldn't exist, then you said stock market shouldn't exist, right? So I think it's more about how do we view the system that is strong and resilient enough and with the right prohibitions that you could. of the market. The other big debate you guys are in the middle of is just that about sports contracts generally. And, you know, I was trying to reason about my own thoughts here on this

debate where on the one hand, you know, the criticism is that with more sports gambling comes proven bad effects. You know, you can measure some of the bad effects that it has on on people. And, you know, we have this, especially in the US, where there was a lot of legalization of sports betting over the past 10 years and there's some data on that. On the other hand, you know, I have no real issue with alcohol, despite the fact that it has kind of a similar distribution where many people enjoy it and then there's a very bad set of outcomes for a small fraction of the population. And so I feel like the societal discussion of, you know, the morals of alcohol and the morals of betting are different despite the fact that, again, it's similar

shaped to the distribution. And, you know, also just thinking from my experience, online sports betting has been legal in, well, legal's a complex term, has been available in Europe. Right. For a very long time. Basically, since, you know, the start of the internet, I hear there there was all these, like, cross-border hacks and Malta, and now it's like a bit more regularized, but it's been available to people who want it for a long time. And life goes on, you know what's and it hasn't led to any kind of major societal collapse over there. But clearly, like, this is one of the big debates that raged around Calci. And so I'm curious how you guys think about increasing access to sports contracts and the effects there.

Well, there's a lot of parts to everything. I think that the way that we think about sports, how do we decide it to first list sports is obviously something that a lot of people are interested in. That's unquestionable. But also there's something that a lot of people do a lot of research. and know a lot about, and there aren't traditional ways for you to make money on that, that are actually good when we talk about the winners, they get cut and all those things, and it doesn't really work. And regardless of whether people like that some people bet or dislike that some people bet,

people bet, and it's just about what is the best way for them to have access to something that they can get exposure to sports. And I think that the whole point of markets versus a bookie is that markets are just objectively better, right? I think that it's almost, I've never heard someone make a question. case that a state-by-state regulated casino is actually a good thing. I'm actually hearing nowadays that a lot of like the paid propaganda by the gambling guys trying to say that. But if you push them, two questions. And just to put numbers on that. The order of magnitude rake for sports betting companies

is around 10% and the order of magnitude for prediction markets is, you know, one percent or a few points. Right. But the predatory part doesn't even come from that. Like for sports betting, if you start losing, because they want the losers, they don't want the winners. If you start losing, the first thing that they're going to do is give you a bonus. They're going to give you $1,000 for you to come back or like a deposit boost and all those things so that they can hook you to keep you coming back because they want to incentivize the losers. We don't do anything. The people losing the most money are the most profitable for sports bookies.

Yeah. Which creates a bad incentive. Yeah. And we don't have that at all. And I think that the whole point is like there's a moral question. Like some people are going to go into Robin Hood or Coinbase or whatever and speculate. on stocks and speculate in crypto and whatever they want to do. And some people want to speculate on sports and they should have the best,

the access to the best possible thing for that. And right now it's just, the sports books are just not it. And we really firmly believe that what we do in our markets are significantly safer for all of that. And if you just take a stance of prohibiting, it's like, same way, you said alcohol, right? It didn't change. People just went to like a speakeasy and drink.

And people are just going to go offshore when there's way less protections. There's no, none of the self-exclusion. and the positive limits, all those things that we do, don't have any information about them, and it's actually very bad for them. So I think it's just this prohibition concept just never really works. It's also, the whole policy discussion around this stuff

is also very interesting when it kind of reminds me of in Canada. All the liquor stores are run by the government, or at least in British Columbia. And, you know, you have the government saying this must be very carefully controlled, but also we will sell it to you and have the revenue source. And obviously, that's much more a factor in lotteries and things like that.

It's all about money at the end of the day. The states won their money, the casinos won their money. It is what it is. Speaking of sports, one thing we were talking about was just what interesting new verticals are there going to be. And so I'm just curious, like, which ones are you most excited about? Well, I think that anything around dissecting, like, a stock into its sort of like... KPI's.

More atomic components. So this would be like betting. directly on Nvidia GPU shipments versus like Tesla deliveries or whatever like their earnings

the you know but because like the and then like you can expand that to things like okay dissecting sort of the macro economy

and like what are the main sort of like factors are influencing the economy broadly like AI and like

have a series of questions to price what's going on at AI things like you know health scares

like COVID and so on but the sort of we're thinking things get really interesting is this idea where, so there was a paper written by Kevin Hassett around this idea that like as society gets increasingly more complex, our asset prices, our understanding of asset prices will naturally decay. Like entropy will go up because the things that influence or the sort of vector that, you know, the number of factors...

Much higher dimensional vector for any given amount. Right. And if those dimensions, you don't have a good understanding of X1 to XN, you cannot get a good estimate of Y. Right. And so the paper basically says that you need infinite markets. In prediction markets are a disnotion of infinite markets, which is like you have to have a market for each one of these X's so that you can then take that back into pricing traditional asset, getting good traditional asset prices. And an example of that this last week, so you know that there was the. the Citrini put out a research report, right? And it got a surprising amount of... People got obsessed with that. Yeah, I would say it got a surprising amount of love and interest.

This is the AI 2028's world. Yeah, like 38% unemployment. And I think, look, I think there's a little bit of like a society wants to believe that AI is going to end us all. I think right now there's a bit of that. But this is where the, you know, and that impacted markets, right? Like the stocks got, you know, there was a sell-off. And so we launched a prediction market on that. Well, before that Citadel came out with a rebuttal and we launched a prediction market on that.

And, you know, the odds are at 10%, right? So of the economic scenario that they predicted being true as in 2020. It's three out of five things. So they have like five conditions. If three hit, yeah. If three out of these five condition hit, you could reasonably say that, okay, this outcome has somewhat materialized. And it's just 10%. Five out of five is much lower, right?

So that is important. If you can put that back into pricing models, maybe the markets wouldn't have reacted that. Like maybe people wouldn't have sold up. of DoorDash, because at least I believe, but you don't have to trust me, maybe you should trust markets that this sort of analysis around DoorDash was actually quite poor. So one thing you're sort of envisioning is this world where everything has a price all the time. And I'm curious, like, is that a good world to live in? And I would note that Stripe, I think, benefits from being private and not having the real-time price and smoothness for employees

and comp and all that. Which is, by the way, the biggest... some noise in the sub-second pricing. Sentiment swings publicly. Like there's, on average, in the long run, it's a truth-telling machine, but in the short run can be a panic. So I'm just curious for you guys to think about, yeah, is that the world we want to live in?

I mean, we're obviously biased because we love markets. We think markets are good. So we're definitely biased here. But I think our view on this is that it's always better to have more data than less data. If you don't think the data is good, If you don't think like the sub, like whatever, the second by second stock price is good, you can just choose to ignore it. It might, the world might not just ignore it. I think CEOs of public companies would say it is not all of us possible to choose to ignore it.

I guess that's fair, that's fair. But in a way it's like it's better to have the data and then use it as an input to something than not. But when we say like, you know, we want to have prices on a lot of things, it doesn't mean everything. There are a lot of things that we wouldn't do like wildfires. We don't do war, terrorism, assassination. Those things are bad and like there's a moral side of these markets and we're not going to ever go there. But in general, it's in a world of social media is like, you don't know what's true anymore. My feed is like, is it real?

Is it not real that this happened? It's just better to have a source, an unbiased source of information that you can kind of use it for other things. And I think that that value is is there. But I don't know. Well, I mean, I think that like maybe the simple frame for this is like you are, increasing market efficiency for all these questions, right? Like, that's what's happening, right?

It's including potentially some events or things that relate to maybe private companies. And I was just thinking about the question. It's an interesting question, like, why do companies go public, right? And why is it important to get like a, you know, real-time market price? Because there are downsides.

Sometimes markets are erratic, Sometimes they overshoot in either directions. But the market, on the long enough time horizon, is a good sort of allocator. It's a good weighing mechanism. It's a good allocator of capital. And I don't really see that, like, I just think that like pricing a lot of these questions will just increase efficiency, make our function, our allocating function better over time. And there will be some net losers, right?

Like some people that maybe capital shouldn't be allocated to, right? It's also a good feedback loop, right? Like if you're a CEO of a public company and you announce something and it just keeps going down, you're like, okay, maybe I'm wrong. And I think the same thing is the politicians where you can see in the live debate. If they say some answers and they see their prices going lower, they're like, well, maybe the answers aren't great. And I think a lot of these things, when we see even the, for example, they use case of prediction markets in government, a lot of it is conditional markets, right?

They can say, if we pass this bill, we'll unemployment go up or down. And you can price these things for better decision making and just, like a tired of feedback loop, um, kind of like good inside this, but... Do you guys feel like we have started to see... Like, clearly we have seen

the effects of social media on politics, where politics is a different game now and different politicians are popular and the political discourse is changed by the existence of, I mean, first Twitter and now to some extent, short form, uh, video.

Do you guys feel like we have seen the effects on politics of prediction markets yet? Definitely. I mean, the... What are they? Well, the candidates are using the prediction market prices to inform. Sure, but that could just be like a handy thing.

Whereas again, I think with social media, like the candidates are different. The debates are different. Reflexive. Yeah, yeah. I do think that what the markets are good at is that they are more unbiased by party dynamics. So if there is a underdog that the public really likes, there's a lot of like... Maybe there's like a party that's like, we don't like this guy. We like this guy from the establishment.

markets are very good at actually showing the real odds for that person. So you think the party machines have lost a little bit of power? I think you can shine more light into what people really want, which might not be necessarily what the parties want to put forward. I don't think we've seen that necessarily yet, but I feel like if I were to say, there was a, for example, the Texas primary and I think that the polls were saying one person was really going to win, another person that was way higher on prediction markets won. Right.

And I think a lot of it was more of like, they give them more. a fair view of the state of the race than a lot of the party. I think we do see this a lot with also, well, there's a set of the piece where people use it and that's sort of reacting real time to certain things, but I think there's some degree of depolarization. And that's what Luana's alluding to. Right.

And in some ways, an antidote to social media, like social media has really polarized. Like when you have two candidates running for a Senate race, we're sort of set, right? Like your feet is set. Like either your feed is saying the Republican candidate is awesome or the feet is saying the Democrat candidate is awesome. Prediction markets don't really have that.

Because the people that are engaging in this are not in the sort of like who's great and who's, you know. I think what you're saying is social media feeds ultimately try to resolve up front. They're like, I need to figure you out. Are you a Democrat or you're a Republican? Like what post should I show to you? And pretty quickly, I mean, you know, people have complained

about this phenomenon where you end up down a, you know, particular rabbit hole because they have pigeonholed you as kind of this type. And you're saying just prediction markets do not have that phenomenon. There's a reverse phenomenon. Are we feeling too certain about this person? And I think that deep polarizes things because the dimension is not, we're not one dimensional anymore, which is like Republican Democrat. And that's where you're seeing and what you're hearing about.

Now it's like, well, this guy is kind of cool. Right. And that's Colorado Rico. And maybe he might do good in Texas even though he's a Democrat. And, you know. And the same thing happened with the New York mayor. situation, right? Like, everyone's like Cuomo is going to win 100%, 100% Cuomo's going to win. There's not even a chance. And we were just seeing Mondani's odds going up. And I think it's

just the progressive message was really working with New Yorkers and the markets. We're really seeing that that uptick and that decrease in polarization really comes from people taking a step back and being like, what do I actually think is going to happen? I'm incentivized the right way. There's a bit of like an Iowa, New Hampshire effect here for, you know, in presidential elections in the U.S., there's like some big name leading into the election. You know, maybe it was Hillary Clinton in 2008. And then Iowa and New Hampshire are measurements of the sentiment of those two states, but they also create narrative.

Right. And I think what you guys are saying is prediction markets create this Iowa, New Hampshire, where they can create narrative in a way that changes the ultimate outcome. I don't know if it changes, though. I wouldn't say it changes the ultimate outcome. I think it sheds light into what the ultimate outcome is going to be. And potentially changes it. Well, I think...

There clearly is something like... There's always, but it's like with the poles too, right? Like the, yes, I mean, there's poles. Aren't you guys hiding your lamp under a bushel here? You're like, well, we're not changing anything here. You're just like... I just think that the one thing I would say, the reason where we're like... Like prediction markets are a big deal.

It's okay to say they'll change things a little bit. High odds don't always correlate to like a good outcome. So you saw Mamdani when his odds were 94% on Kalshi. The thing that he was messaging pretty consistently, and I think there was a little bit of worry there, it's like, you got to show up. Right? Like, because if you're very high odds, that could also lead people to be like, okay, this isn't the... So it's not as clear. Yes. And I don't think this changes things more than polls changes. Does that make sense? So the response is more like in a vacuum, yes. If you had nothing else, if you didn't have social media, if you didn't have news, if we didn't have any of that, yes. But because we have all these other things and you add prediction market to it, like impact modern, but I want to make one point that I think is actually very interesting. And we're seeing this off...

We'll be the judge that. Okay, you can judge that. Let me know if it's interesting. But a lot of... But a lot of... of times when you see people start participating in prediction markets, they get more engaged in the underlying. They legitimately just get more informed. It pulls people in. It pulls people in, but to do research. Now you have, because you have some skin in the game or you're about to put some skin in the game, you read, everything changes. You're not just like saying something crazy on Twitter anymore. You're putting money. And now it's like, let me read. Let me actually figure out, oh, who's this person? What's happening? It's like, are they pro this? Are they against this? What's their view and everything? And you go, because, you know, it's like amazing because this happened a bit in

in the New York race, right? Like, or it happened a bit with Brexit. People voted for Brexit because, oh, no. We want to break. And after they voted for it, they're like, oh, God, wait, I don't think we, we wanted this. Wait, wait, we didn't even understand what we were voting for, right? Like, and I think this heightened engagement is very good.

Like, you know, like, it engages people further to like learn and understand. You know, in sports, basically, if you ask sort of like a lot of the leagues, they would tell you the same thing, where people got more engaged with a statistic. Which player is good? What's happening? And I think that will happen is already happening in politics, which is a good. politics, which is a good thing. I think that the...

I'm going to say something and then I'm going to call it to say. I think that politics are going to get better because you're going to have a way faster feedback loop on the messaging and the policies. Right now when a candidate says 10 things and they win or they lose, you're trying to make one assessment of like so many things

that the candidate did and did that go well or not in which point was it? And even if you do a pause, like always delay it as a very specific example. But now you can have really... time of like they said this, what was the response? And you can get that and kind of like that faster feedback loop, which I think makes startups great, right?

You're able to iterate very fast. And I think if candidates are able, everyone wants to win at the end of the day, and if they're able to optimize their message to what really people want and what policies people want, I think they're going to end up being better, because they're just going to know what people want better. It's like a, you get a score on all of the different things you've done, not one score that encompasses the good end of that.

When you ship on your future, you're able to have like 10 metrics and you're like, okay, this went up, but this went down, and you're able to, markets can kind of contribute to that, but also, like, I think to a lot of other things as well. Music with, like, charts, when someone listens to the song and they're like, definitely not going to hit number one. You're like, okay, that was that song, so we should do something else.

Do you guys try to use prediction markets in any way internally to make decisions? Every single decision we make is always probability. Even the election lawsuit, right? When we're doing it, it's like... But that's you guys evaluating the probability. Yeah. But do you ever think?

about creating markets for your employees to participate. So we have one knit, which is as a regular exchange, we can't trade. But we do it like internal... There's like a separation of church and state thing there. Exactly, exactly. And so we've been asking that we've been working on regularists, could we do something small? Like could we do small dollars where... So that, you know, because obviously that's one that we really want to...

And you can't even dog food the product, I guess. And then dog fooding the product, right. Which has been hard. It's hard. You know, that... Everyone's on the demo. And it's sorry, employees cannot trade in their personal capacity? They can't.

Yeah, not at all. Wow, interesting. Yeah. But yeah, that makes it very hard when you, as you say, you just can't dog food your... They can't try the product. People that Facebook use Facebook and that's how you make the product good. Right, right. So that's why it's so important for us to just be, like, asking the users all the time.

Yeah, yeah. Oh, that's so interesting. Yeah. It sucks. But the power users, the super forecasters are a lot of what influences or where it goes because they're very engaged. You guys. You guys presumably spend a lot of time with those power user super forecaster type. and seven months be down.

They're day one. So you want to make sure they're happy. Last question. Where do you guys want to see prediction markets policy go? Like when you're talking to someone in government or if you had a magic wand, what are you arguing for? So our stance as a company and I think this may differ a little bit from like, I would say like your average tech company or big tech company.

So we are pro-innovation. Innovation needs to happen in America. You know, we have to lead and we have to do it right. And we have to win. Like we have to be, you know, all the things that Americans want to do or we need to win as a country we should have here. But we're also pro-regulation. And so at a high-level principle, like,

there's usually this tension that, you know, generally it's like, you know, it's like the policymakers, like want to regulate. I think you're maybe more like a traditional financial firm in that way, right? where maybe Silicon Valley, you know, a lot of firms grew up in unregulated way, but financial firms have always had a regulator and that's just a fact of life. Yes. It's just a constraint for you to work. So it's part of the culture.

And again, we spent four years getting regulated a front. So it's part of, but we believe in regulation. Like I think it's important because, you know, regulation is a bit like insurance. It's like it's protecting you from things going wrong at bad times. And so when I think about like, okay, where does this land? I think anything that is oriented around preserving. needs in America and making sure we win, but then elevating the fairness and transparency of the markets. Right? Any of the internet like, how do we make it more fair? Banned insider trading. Add more

restrictions on, for example, like, you know, government officials, members of Congress trading on like, you know, information they shouldn't trade. I'm obviously big fan of like banning insider trading for members of Congress. We talked about it. Yeah, yeah. But, um, presumably you mean just banning trading, period for a member of Congress. I think it's not a bad idea. Like, you know. Yeah, that's how we kind But I think, and then things around like, you know, loving, like creating also social fairness and transparency. Because of all the questions that we asked, like if people are basically training on politics, let's have all the trade data be as public as possible. So anyone can audit it, anyone can see it, which is a good thing, right? Now you don't know, like imagine a poll where you can check every single person that basically got.

And the general public can check who was polled and what the sample was like. And then anything around customer protection. And because that is important long term in the sense that like when you build a consumer product and it goes mainstream, there is like a massive sort of like burden on the on the companies to educate. And you've seen it like, you know, over and over. And in our case, you know, you want to make sure that people like know what they're getting into. They're not like overextending themselves in terms of like how much they're sort of trading. They're not like getting into an area of discomfort. And how do you kind of like, you know, we can do as much as we can do on the marketing and on the product side, but like we need policymakers and regulators help to basically make it an industry standard but also help us elevate ours.

By the way, we're pro that I think that like even the classic retail brokerages should also be adopting a lot of these customer protections that we're talking about that they don't. I think that every retail trading platform should be taking a lot of these steps. Yeah, I mean, that's sort of our general view. And we hope that this is sort of the direction that things take. because you know there's kind of you can have a variety of views right and some people believe that like hey like you know any type of speculation should be banned whether it's in the stock market or crypto or prediction market we don't believe that like you know we think that would be a bad outcome for all the reason because there's a lot of upside to having liquid markets and a variety of different things

but also because if you ban it you're actually heightening the risks that you're trying to prevent because now that activity is going offshore right like and where you cannot monitor it or police it or do to protect it. Awesome. Well, I'm tired, Lana. Thank you guys. Thank you.