The Bad “Bet”

Speaker 1: I've got a story for you here outlined in a court indictment and civil complaint. I'm a lay it out for you.

Speaker 2: Hit

Speaker 1: me. Operation Absolute Resolve was the pre dawn special operations raid on January thirty this year that seized Venezuelan president Nicolas Maduro. They grabbed him and his wife at a resident in Caracas under heavy fire, extracted him to the USS Iwo Jima, like 150 aircraft, Delta Force operators, helicopters. It's a whole big thing. They're on the ground for roughly two hours. Seven service members are wounded. Maduro's on a heliport in Lower Manhattan two days later facing federal drug trafficking charges. This is not about those charges. Barely about that at all, actually. What this is really about is a trade. Between 12/27/2025 and 01/02/2026, which is to say like the 168 before the helicopters crossed into Venezuelan airspace, a user routed roughly $33,000 in a USD pegged stablecoin through a Polymarket account under the handle burdensome mix, and bought Yes shares across four, like, very long shot Venezuela related event contracts. The market priced the odds of Maduro being removed at about 7¢ on the dollar. We'll explain the mechanics of how all this works for anyone who is unfamiliar, but basically, right before Maduro gets got by all of these very fancy military operators, someone makes a really big, very specific bet that Maduro is about to get got by some very fancy military operators, like right away. And it happens. When that happens, that bet pays off huge. Dollars 409,000 in profit, the bulk of it on this Maduro out by January 31 contract, which resolved, yes, dollar a share at, like, 07:00 in the morning on January 3, a few hours after the president announced the operation on Truth Social. The trouble with all of this has to do with who made that bet and their day job. Allegedly, sort of. Sort of allegedly. Master Sergeant Gannon Ken Van Dyke, 38 years old of Fayetteville, North Carolina. The defendant on this indictment isn't a, like, political prediction market hobbyist person. He is a Green Beret. Van Dyke has been an active duty soldier since September 2008, a master sergeant in the US Army's Elite Special Forces since 2023. He's on the same kind of unit that runs the kind of mission that just unfolded in Caracas. Specifically, on December 8, the day prosecutors say he is in in the process of planning absolute resolve. The day that started, he signed a Western Hemisphere Operations Non Disclosure Agreement promising he would quote, never divulge, publish, or reveal by writing words, conduct, or otherwise, any classified or sensitive information. Nineteen days later, this indictment alleges he starts buying those shares. Dun, dun, dun. Van Dyke wasn't, allegedly just batting on the raid. He was, it seems, on the raid. At, about 05:00 in the morning January 3, ninety minutes after the assault element pulled Maduro out of his compound, a photograph gets taken of Van Dyke on what the indictment describes as the deck of a ship at sea at sunrise wearing US military fatigues, carrying, like, the rifle standing with the other guys, that ship was the USS Iwo Jima. He uploaded that photo to a Google account from sea, by which point the Maduro out position that he bet on had already been resolved. This one's a doozy, Scott.

Speaker 2: I remember watching this as it happened, both the raid and the poly market fallout and the arrest of master sergeant

Speaker 1: Van Dyke. It to me, this is the story where the rubber of our prediction market's insider trading hits the road of disclosing military secrets sure is illegal. Like, that's finally gonna get resolved here. So we have the cases, a five count federal indictment in the Southern District Of New York, a parallel civil suit going on. Van Dyke pleaded not guilty in an April 28 arraignment. He surrendered his, passport firearms. He's free on a 250 k bond. I wanna get into this story today because I think this is a a fascinating important story in the world of technology. His defendant, Mark Geragos, outside the courthouse said, quote, mister Van Dyke is an American hero, someone who is charged unfortunately with something that is not a crime. And therein lies the whole thing. A poly market bet by a man who just allegedly finished doing the thing he bet would happen. Let's start this chatty chat episode with the very strange case of Master Sergeant Ganon Ken Van Dyke, here on Hacked. The scatting got called out in the last episode, so we're gonna do it more. Did it?

Speaker 2: I mean, I didn't like the scatting? I don't know if they didn't

Speaker 1: like it. They commented on it, and I felt seen. Because You felt seen. I felt seen.

Speaker 2: We we vary genre. We vary rhythm. We very very rarely have melody, but but,

Speaker 1: the jazz beat. Next week Yeah. It'll be a acid jazz. After that, it'll be sort of a polka.

Speaker 2: Poke? Poke. It's a it's a polka.

Speaker 1: How you doing, Scott?

Speaker 2: We see you out there, polka fans. I'm doing good, Jordan. How are you?

Speaker 1: Doing good. Keeping busy. I got the screaming cat here temporarily not screaming. I've got some weird text stories

Speaker 3: in front

Speaker 1: of me. They are.

Speaker 2: The audience is used to your goblin. That's Jordan's cat's name, by the way. There's a little insider info.

Speaker 1: My cat's name is Goblin, and he earned it. It's an accurate name. We got some, we got some interesting stories for the folks.

Speaker 2: Yeah. It's been, it's been an interesting couple it's been it's been an interesting six months, honestly. It sure has. There's a million things we could talk about, but this is an interesting story to start with because it it really hits a cross section of what's going on in the world of, you know, prediction markets and the markets in general Mhmm. Politics

Speaker 1: Mhmm. Because

Speaker 2: you've now got political laws being drafted to prevent people from betting on these things. A bunch of stuff going on in this, so I think this will be an interesting one to chat about.

Speaker 1: It's an interesting technology story. It's, in a sense, a story of a person hacking something in the sense of using it as not intended. And in a much realer sense, it's someone using a technology as ex exactly as designed. Intended. So it it there's a lot of layers to this. And that whether you feel this was this technology being used as intended probably differs based on whether or not you work for Polymarket. They would maybe disagree or Kalshi. Well, Kalshi comes up in this story, and it's really interesting.

Speaker 2: Of course they do.

Speaker 1: They do. They're where this didn't happen. Did you know, Jordan,

Speaker 2: that there are now hundreds of new prediction markets Oh, I love that. Coming online. Yeah. That's really, really cool. Pretty much every online gambling and casino is opening up a prediction market as prediction markets are not seen as gambling. Sure. So they can go into all the states that still outlaw gambling.

Speaker 1: It's interesting that it's the gambling sites that are getting into prediction markets and not the market sites getting into prediction markets, though I'm sure they are too. And it gets to so interesting.

Speaker 2: That even, like, media companies, like, Sure. Are now launching their own prediction markets because they're way less regulated and way easier to open than, let's say, an actual online gambling site. Sure. So if you were, say, like, the score Mhmm. And, you know, you had a allegedly had a large audience of sports fans that followed it, you could just whip up a prediction market to allow people to put skin in the game to interact with the outcome of sporting events, which is not gambling on them?

Speaker 1: And there's such an interesting question, and we're gonna dig into prediction markets. If you are part of this audience that doesn't really know what prediction markets are and you're sitting there thinking, please explain that at any point. Don't worry. We will. But there is there are these sort of, like, dual questions at play here of, on one side, is it gambling? And as you swing away from yes on that, you get to the other side, which is, like, well, is it trading? Like, is it equities? Is it vulnerable? Is it, do things like insider trading laws apply to it? You know, you're not gonna have an insider trading law for a roulette table, but you sure might for a stock. Mhmm. And where exactly on that spectrum does this technology sit? Because if it's just sort of perfectly balanced in the middle and therefore ineligible for all legal protection, that's a really interesting place for us to be.

Speaker 2: Totally. Here. Here. I'm gonna I think I'm gonna I'm gonna jump in and take the start on this, if you don't mind. I'm gonna say I'm gonna try and make a pro case for prediction markets because I think that they do have a really interesting they have a really interesting place in the ecosystem. So here here here we go. Here's my best chance. Is if you believe in open markets, which I do, the the wisdom of the group always exceeds the wisdom of one. So if you go to something like the an old economics adage is like, if you go to a country fair and there's a cow there and you have to guess the weight, if one person guesses the weight, the standard deviation of the error is massive. But as you get more and more guesses, the median of the guesses gets closer and closer and the standard deviations tighten up more and more. So the wisdom of the group exceeds the wisdom of one, which is what prediction markets are supposed to be. Hey. There's this potential outcome. Let's all essentially vote on it. But the difference is is now the voting is done with money rather than just voting. But in reality, what it is is querying the group for knowledge on a potential outcome, which does have validity and importance.

Speaker 1: Yes. Wisdom of the crowd, interesting. The utility of these things as they are used to predict stuff is, like, debatable, but seems like there is some.

Speaker 2: Yes.

Speaker 1: The question is whether it is a kind of gambling that reveals useful information and would therefore still be subject to laws governing gambling, or is it a kind of commodities trading or trading at all that is therefore, like, subject to the laws governing that that also produces this useful information?

Speaker 2: I listened to an interview with, Calcio CEO once. Yeah. And they're from the finance world. Like, they came from big investment banking.

Speaker 1: Makes sense.

Speaker 2: Yeah. Like Jane Street, stuff like that, like hedge funds. And one of the things that they hated was that they couldn't hedge based on global events, election outcomes, you know, weather situations, any of those massive you can't buy derivatives in the market currently that let you hedge against these outcomes. And that's where they kind of got the inspiration to create Calshi, apparently. Was like, hey. Wouldn't it be great if on election night, you could diversify a portfolio by hedging against the election outcome? Which, like, as as somebody who's interested in finance, makes a ton of sense.

Speaker 1: Yeah. If you're trying to financialize literally everything

Speaker 2: Correct.

Speaker 1: A platform that lets you financialize literally everything would, of course, be compelling.

Speaker 2: Correct?

Speaker 1: Yeah. Wait. I I under I understand the argument. I'm more I'm actually gonna insist we explain what these are.

Speaker 2: Yes.

Speaker 1: So what is a prediction market? A prediction market is an online platform where you bet yes or no on real world outcomes. Elections, sporting events, weather, the Fed interest rate decision, a geopolitical flash point like a president getting taken in the night, that kind of thing. You buy yes or no shares. At resolution, when the thing does or doesn't happen, the winning side pays out a dollar, like, 1 US dollar per share. The losing side pays nothing. They had to pay to buy the share. Share prices float between zero and a dollar, which is sort of like the live probability that you were kind of alluding to. Right? Yeah. The $7.07 cent share means the market collectively thinks there's about a 7% chance of the thing happening.

Speaker 2: Yeah. The easiest way to think about it is if if, say, there's a thousand dollars being bet on an outcome, let's say that outcome is like, will Scott and Jordan record an episode today, and $930 is bet on yes, and $70 is bet on no, then there's a 93% chance of a yes outcome. It's kind of the way that the market looks at it and the way that they set their odd lines. It's all supply demand.

Speaker 1: There's two big players. It's Polymarket. They're the sort of more, I'm speaking generally here. Crypto based runs on the blockchain offshore, uses stable coin kind of route. Mhmm. Worth a $9,000,000,000, I think, as of last year, worth more now. Right. The other one is Kalshi, which is it's US licensed. It's regulated by the CFTC. It takes dollars. It requires full ID verification. I bring up this distinction because this distinction is very important.

Speaker 2: Very important to this story for sure.

Speaker 1: Yeah. Yeah. So PolyMarkets international platform is officially like, it's off limits to Americans under a 2022 settlement with regulators. Like, that that whole thing is supposed to be, like, blocked off by IP geolocation as far as I understand. I'm not in The States, but that's my understanding of what's going on with Polymarket there. If you have a VPN, you have a VPN. This is a big industry. This is you've almost certainly heard stories about it. Billions of dollars a week. Importantly, Kalshi is regulated by the CFTC, which is different from the SEC that governs things like insider trading. Fun little piece of trivia, though billions of dollars moving through these markets, the CFTC has roughly one eighth of the staff of the SEC, a not itself famously well funded or staffed organization. So that seems important with all of this. Should we begin

Speaker 2: Let's begin.

Speaker 1: With more lofty questions of gambling, or should we begin with begin with the defendant and loop back around to the lofty questions?

Speaker 2: I think we go story first. Story focus Let's do it. Will pull us in many directions and

Speaker 1: Four six. There you go. Okay. Let's talk about sergeant Gannon Ken Van Dyke. 38 years old, Fayetteville, North Carolina. It's like a town next to Fort Bragg. He's an active duty US Army Special Forces. He's Green Beret since 2008. He was, promoted to master sergeant in 2023. He's on the US Army Special Operations Command. He's a senior non commissioned officer. He's the kind of soldier that, like, other soldiers are taking their cues from. He'd signed a pile of nondisclosure agreements over the years, held a sensitive compartmented information clearance since 2018, It signed the standard SCI nondisclosure agreement promising to, quote, never divulge anything marked as, you know, special information.

Speaker 2: Top secret. Top secret. I have

Speaker 1: a list of, like, pieces of paper this guy has signed saying, like, top secret. Totally understand. In December 8, very, very relevantly here, he signed an NDA specific to Western Hemisphere operations, like, right before all this happened. I I talked about that a little bit in the intro. An interesting detail from the indictment because this is all PDFs. You can read through it. I've gone through a chunk of it. One month before the trades, Van Dyke uploaded a screenshot to his Google account of a Google AI search result confirming that special operations files are, quote, not available to the public and that, quote, specific sources, methods, and full operation timelines are consistently withheld. A sort of perfunctory Google search, it would seem as to what exactly did I sign a piece of paper saying I wouldn't disclose? I'm just

Speaker 2: doing a little background research into what I've what I've agreed to.

Speaker 1: And then uploading the screen. That part, I don't get. But, hey. How you use a computer is up to you. The mission itself. Operation Absolute Resolve, January 3. The largest US direct action rate in Latin America since Panama in 1989. Fun little trivia. A 150 air airplanes. 20 plus bases involved in the whole thing. They really pointed a lot of energy at this. I did. There's, like, a ground element of Delta forces going in, like, two, 04:00 in the morning kinda thing. Madero and his wife, Celia Flores, gets seized under heavy fire and extracted to this this ship, the USS Iwo Jima. And then Trump announces it at 04:00 in the morning on Truth Social. A very important moment in this very compressed timeline. Ninety minutes later, this photo gets uploaded. I talked about this in the intro. It's like a sunrise photo taken of Van Dyke on the deck of a ship at sea. He's he's kitted. He's got the fatigues and the rifle. There's the other dudes with him in the operator outfits. He upload The whole gang's there. The whole squads. Rolling deep. The whole squads there. He uploads it to his Google account. And then shortly thereafter Maduro lands in Downtown Manhattan at this, like, heliport to face his charges. So that all that all seemingly just happened. The issue is to do with what happened before that, which is this series of alleged trades. You got 13 separate transactions between December 27 and January 2. These were importantly on Polymarket. We'll talk about why they weren't on Kalshi in a minute. It basically was just a bunch of yes positions. We talked about the structure of these work, the yes no bet. There's these four Venezuela related contracts mostly centered around the idea of Maduro out by January thirty four first. Then there's sort of, like, subgenre bets of, like, US forces in Venezuela by January 31. Trump invokes war powers against Venezuela by January 31. Just a series of this is gonna happen related bets or contracts.

Speaker 2: If you knew, these would make great bets, great contracts.

Speaker 1: So this Polymarket handle burdensome mix. I've got the wallet right here. I've got the wallet number. You can track it. Lord knows some journalists did. The account was created on December 26 after he wired roughly 35,000 US dollars from a personal bank account into a crypto exchange. He uses a VPN whose exit node was sent to geolocated in a foreign country. We actually know a lot about his tech pipeline from this indictment. It's really, really interesting. Starts with a stake of 33,000 US dollars. The bolt goes into that Maduro out contract. The market price Maduro's removal is, like, a pretty big long shot. Most of the time he was buying, it was fluctuating, but it was under 13¢. So pretty big upside.

Speaker 2: Mhmm. I always feel like this is one of those situations where maybe you should have spread the money out a bit, made a few play bets on the side to bring a little bit less less heat and attention to the fact that you just showed up on the platform, put a bunch of money in, and then put it all on red.

Speaker 1: Yeah. Sure.

Speaker 2: And then red happens. Like, if if you if you'd maybe you put 20,000 on Maduro out and you put 5,000 on

Speaker 3: g

Speaker 1: two six comes out in 2026.

Speaker 2: Release date.

Speaker 1: Just some dumb shit. All hurt.

Speaker 2: Yeah. Just so you don't you don't pop the flags as much than somebody that just comes in and is like, I'm only betting on one situation, and I'm going all in on this outcome.

Speaker 1: Well, and seemingly, and we'll talk about this in a minute, that level of certainty is what flagged it off. It is not that he was the only person trading on this contract. He was actually a minuscule amount of the trading volume. It was, to your point, seemingly, the, like, this one account just sort of burst into existence to make up $35,000 bet on a really specific thing happening. What's going on there? We'll get to that. But, like, that is very specifically, it seems, why all of this popped off. Any technology company these days has some form of modeling on user behavior.

Speaker 2: Yes. And especially when it comes to a a technology company that's in predictions, you know, has financial incentivization. There's no way that they're not auditing and scanning for people doing this exact situation. You show up. You've never had an account. You create an account, and a week later, you put a $100,000 on the situation.

Speaker 1: So there's that blitz you're describing. Right? January 2, kinda starting at night, this, like, series of rapid fire trades. The share price is ticking up a little bit during all this, but it's staying pretty low. Then after that Truth Social post announcing all of this had happened at 04:21 in the morning, the price rips. It goes from, like, 37 it had already crept up to 37. It skyrockets to 95¢ in minutes. The certainty that this is gonna happen skyrockets to 95% according to the logic of these platforms. Contract resolves at a dollar at 07:00 in the morning and the final profit to these bets was $409,881. Roughly 404 of that was just on the Maduro out market alone. Something fascinating about this because Van Dyke's situation does feel, particularly egregious given his role and to go back to what we were saying. Wall Street Journal reported that about 56,000,000 in total trading volume across that Maduro con out contract happened in this window of time. Van Dyck's Hall was just under was under, like, 1% of

Speaker 2: that. Mhmm.

Speaker 1: So once this starts, the volume explodes. There was just this one user that got in weirdly early in specific that flagged the whole thing. That's all on Polymarket. I wanna talk about Kalshi for a second. Three days before opening the Polymarket account on December 24, Van Dyke allegedly applied to open an account on Calshi. Calshi is the one that runs it's called KYC know your customer ID verification. It is an American legal concept. You see it in other countries as well. Basically, for every new account, like, you gotta prove who you

Speaker 2: your driver's license. And

Speaker 1: You've done it before?

Speaker 2: I have. Not on Kalshi, but I have to

Speaker 1: No. Van Dyke obviously couldn't pass this given what he was seemingly attempting to do. He pings Kalshi customer support on December twenty sixth, twenty seventh, and twenty eighth trying to fix it, gets nowhere. PolyMarkets international site, which is which is, it's only by any kind of Yes. I can tell you how to use it, but you figure it out on

Speaker 2: your own. Quick Google search will get you there.

Speaker 1: Yeah. It asks for an email address. Oh, and a wallet to send the money to.

Speaker 2: Of course.

Speaker 1: An anonymized crypto wallet. Crypto's fine. Crypto will do just fine. That account was opened the same day he was rejected by Kalshi. Just a little quote I liked in all of this. Former SEC Gensler era policy lead Amanda Fisher said in to a journalist, it's curious that the CFTC and DOJ didn't charge Polymarket for not appropriately prohibiting US bettors from accessing the platform.

Speaker 2: Ta da.

Speaker 1: Anyhoo, the cover up. January 3, hours after this contract resolves, cashed out of the account, $437,859 in this USD USDC, it's a US dollar backed, like pegged stablecoin. Gets sent into a foreign cryptocurrency vault, just like yield bearing offshore story your crypto product. This is all publicly visible. And within hours, some journalism starts. NPR's Bobby Allen and political researcher Tyson Brody had identified, wow, this one account seems really, really weird. This trading behavior is very, very odd. They start posting about it, and the story goes viral. January 6, three days after this trade first surfaced in press reports, VanDyke asked Polymarket, hey. Can you go ahead and erase that whole account, please? Can you delete it? I lost track of my registration email. I would like you to vanish this account that is currently going viral, please. Immediately. He changes his crypto exchange, like, registration email to a brand new address that he created a couple weeks earlier. January 15, he pulls $444,000 in fiat dollars out of the vault, wired it to a personal bank account at a Texas headquartered US financial institution. And therein lies the critical error.

Speaker 2: Well, I'd I thought the error was gonna be way more cryptic than that. I thought the the photo posted from the deck of the ship was gonna be on the same VPN. I thought there was gonna be some breadcrumb that led them back, not just like, oh, I straight up wired it to my bank account.

Speaker 1: Yeah. He was anonymous on the Polymarket, but not on the chain. Every trade was permanently kind of publicly inscribed so that when he went to cash out through a US regulated like, that requires the ID verification, that wallet now ties back to his legal name. PolyMarkets says that it then flagged him internally and referred the case to the DOJ. So that you're starting to see them attempting to be like, we know we let your fancy man on the boat bet on our platform, but, like, we found him.

Speaker 2: We're gonna play ball. We wanna keep our business. We're sorry this happened. They have a disclaimer at the bottom of their web page that says you

Speaker 1: shouldn't Don't do crimes here. Yeah. Don't

Speaker 2: do crimes here. Please don't do crimes here. Yeah. They literally have that disclaimer.

Speaker 1: Just don't do crimes.

Speaker 2: Pretty much.

Speaker 1: That's gonna be their Super Bowl ad next year.

Speaker 2: Yeah. And if

Speaker 1: you would like to pay us to make it, we'll make it really, really good.

Speaker 2: Yeah. Yeah. I'd love to make that ad.

Speaker 1: Just please don't make don't do crimes

Speaker 2: on our policy. Do crimes on it.

Speaker 1: But you score it like a very earnest, like, financial like like, one of those feel good bank ads where it's just what are your dreams? What are you trying to create? With Polymarket, just don't do crimes.

Speaker 2: Not here. Just not here.

Speaker 1: But, like, do you want a boat? Don't hey. Don't do crimes. Anyway, let's talk about the charges. Five counts in the Southern District Of New York. So this indictment was unsealed April 23. That's why we're talking about it now. And we can dig into the legalese of what, you know, specifically what do these charges outline. It's basically like, hey, you can't do this. It's unlawful use of confidential government information that's worth ten years, theft of non public government information. He's charged with both wire fraud and commodities fraud, which are really, really interesting charges given what this is all about. The total maximum exposure is, like, sixty years. He has to forfeit the accounts. There's parallel civil action, quote, from the CFTC chairman, Michael Sellegg. The defendant, quote, took action that endangered US national security and put the lives of American service members in harm's way. He was arraigned on April 28 in the Manhattan Federal Court. He pleaded not guilty. He was released on a 250 k bond. His next hearing is June 8. We'll actually be in New York on June 8. I don't think I'll be in town on time to go to the court, but I briefly considered it. Kinda wrap up with the defense here and really to me what the big question here is. Like, so I I I give you that quote from his his lead attorney, Mark Geragos, which is mister Van Dyke is an American hero, someone who's in charge unfortunately with something that is not a crime. And that defense theory is basically like, hey. This is clearly super unflattering, but it isn't covered by the federal statutes prosecutors are charging it under. That seems to be his argument. It's like, I'm not denying he did the bad thing. I'm denying the bad thing is illegal. This is, from what I could find, like, the first criminal insider trading case ever brought against someone to do with prediction markets, which is really, really relevant. It's the first time the CFTC is invoking a rule that I'd heard of, but I didn't know it was called this, called the Eddie Murphy rule.

Speaker 2: Oh, nice.

Speaker 1: It's in reference to the film Trading Places in which two commodities traders manipulate the orange juice futures market using a stolen government crop report. So it's this idea of, like, you enriched yourself on a marketplace using this privileged government information. But that central legal question is, like, does federal insider trading law actually reach this conduct? Like, you've got a factual story that is seemingly in agree it's, like, 13 time stamp trades, a wallet address, a VPN, a botched cover up. It doesn't seem like they're fighting

Speaker 2: for bank account.

Speaker 1: A withdrawal. They're not fighting that. They're gonna fight whether all of that stuff that it seems like happened is a federal crime under any of the statutes that the prosecutors are applying to fit it.

Speaker 2: Well, the there's you'd you'd think that the master sergeant would actually be in more trouble than just insider trading. Yeah. Because, technically, by him putting the bet down, it's a disclosure of confidential information.

Speaker 1: 100%.

Speaker 2: So so he would then be up on charges for, you know, a number of other federal crimes related to, you know, whether you're doing right by the by your country or not, which would be much more severe than just, you know, white collar financial crime, which, you know, we see and read about every day by people at all levels of power.

Speaker 1: Yes. On that point you just brought up, like, there's a really weird quirk of these platforms, which is that you aren't Van Dyke promised to keep secrets for the US army. He didn't make any promise about to the people that he was betting against. And that is, like, a weirdly meaningful legal concept here. It's like, the law has never been tested on whether that counts. Like, he didn't the the US government didn't lose any money.

Speaker 2: Mhmm.

Speaker 1: He just screwed over the people he won against, which is sort of, like, the function of these market places. That's all separate from the question of, like, is a poly market bet a swap, which would make it eligible to insider trading. And then there's the wire fraud thing, which is like, was anyone actually robbed? Like, wire fraud, I think, typically requires a victim that lost money or property. And, like, the government who we signed the thing with didn't lose the dollar.

Speaker 2: People on the other side of that their money.

Speaker 1: But they they were betting. Well, they or were they betting? And I just made the face to say, are they betting? Or were they? But so

Speaker 2: that but that's exactly it. That's exactly

Speaker 1: it. It's all of these, like, well, technically, it's Well, the the the question is, can he sort of just, like, narrow path wriggle his way through those? I it seems

Speaker 2: If if if this one case manages to narrow path wiggle the way through it, I would call that the legal system closes that narrow path quickly. But the but the thing for me again, just to go back to the the bigger crime here. Like, say you are, you know, authoritarian dictator somewhere in the world. Would your due diligence of safety and protection not then just include constantly monitoring prediction markets? Like, if we know like, say you're say you're Vladimir Putin who has been hiding for two weeks because he thinks he's about to be assassinated, why does he think that? Maybe he saw a spike in prediction markets, which is indicative of insiders betting that they were going to kill him to make make back end money on it. So it it it is it is in fact a way to communicate motivation and planning behind a specific outcome to the market, which is a disclosure of private and confidential information, which therefore would be treason.

Speaker 1: Sure.

Speaker 2: So if you really wanted to to if you really wanted to get into it, this person's probably gonna be in a lot more trouble than just, you tried to make a quick buck.

Speaker 1: Yeah. If the government wins, like, this is a precedent, and therefore, the government has a really big incentive to win. Like, every prediction market insider trading prosecution after this, if they win, is gonna run through United States versus Van Dyke or whatever it's called.

Speaker 2: Totally. Yeah.

Speaker 1: And if they lose and the got congress, like, decides to write a new statute trying to, like, make something some part of this illegal, Van Dyke will still be remembered as, like, the case that exposed that huge gap. Either way, this is gonna have a big impact on that.

Speaker 2: Well, and you wanna talk about efficacy of the government to pass laws of this type. Nancy Pelosi, who is retired, there's entire tabled acts called the Pelosi Act and things to stop Congress and

Speaker 1: and Yes.

Speaker 2: Politicians from maybe not insider trading, but, you know, disclosure of confidential information to partners and husbands that insider trade. You know, there's a bunch of this is all alleged. But, you know, Nancy Pelosi's net worth went from hundreds of thousands of dollars to hundreds of millions of dollars during the the course of her tenure in politics. And they have they have failed to stop or persecute anybody in that regard.

Speaker 1: Yeah. There's I mean, Nancy Pelosi is a a great face for it. There is a a current sort of, like, golden era of insider trading and backhand dealing happening right now, throughout I I wouldn't even just say the US government, but certainly in the US government. Yes.

Speaker 2: There's a

Speaker 1: lot of people that have figured out that if you have privileged information about the shit that's gonna happen, you can make a buck.

Speaker 2: Totally.

Speaker 1: This is just the first guy that did it by uploading a photo of himself in fatigues mere moments after he launched an international event, the odds of which were so low. It drew attention to him, but, like, this is happening from the stock market through poly market. This is this is happening with people with privileged information.

Speaker 2: Well, just actually this year, Gildebrand and McCormick, two senators in The States, tabled an act called the Prediction Market Act, especially banning anybody from congress, president, executives, and branches, senators from from being able to utilize these services at all.

Speaker 1: Without knowing a ton about it, good idea. Like Exactly. Like, I am not it's not official take. I'm just learning about that specific thing. But I would say broadly speaking, the

Speaker 2: Not a bad idea.

Speaker 1: The information you have, the the less you should be allowed to act on it in a otherwise competitive market.

Speaker 2: Totally.

Speaker 1: It seems pretty fair to me. Your mileage may vary. Super interesting story. Wanted to

Speaker 2: kick off the episode with it. Should we add oasis?

Speaker 1: I think we should kick it over to the add oasis. And when we're back, let's let's talk about birds. Sounds

Speaker 2: let's talk about all kinds of birds.

Speaker 1: Let's talk about birds. Think about the last time you heard a Breach story on this show. It always starts the same way. Someone, somewhere, saw something too late, an alert buried, a signal missed, an SoC that just couldn't keep up. Arctic Wolf set out to solve that problem by rebuilding security operations from the ground up for a world where attackers are already using AI. They created the Aurora Superintelligence Platform, a fully agentic system powered by the swarm of experts. Instead of single purpose bots or lucky guest LLMs, the swarm is full of deterministic agents that handle whole entire workflows. Humans stay in the loop and on the loop to validate the critical decisions and keep everything trustworthy. And all of this is just off running on their secure operations graph, a constantly updating intelligence engine fueled by more than 9,000,000,000,000 telemetry events every week and over a decade of real world incident response. The system reasons on real signals and real context, not synthetic training data. And the result is the new Aurora Agent SOC. It's the first SOC that is agent led by design. You get agents that coordinate, agents that investigate, agents that respond at machine speed, and hundreds more that automate the repetitive work that normally buries human analysts. Arctic Wolf didn't try and bolt AI onto an an old model. They rebuilt the model entirely. What makes it even more effective is how it works with Arctic Wolf's concierge experience. The team brings customer specific context directly into the platform so every AI driven decision reflects your environment instead of generic assumptions. The automation frees your concierge security team to focus on higher value strategy and proactive risk reductions while the agents handle the grind. If you wanna see what trustworthy production ready AI and security operations actually looks like, go to arcticwolf.com/hacked. Starting something new isn't just hard. It can be downright terrifying. You put a lot of work into a thing. You're not entirely sure it's gonna work out. You're taking a huge leap of faith. I've started a few things. Now I know I was right for believing in, you know, the idea, the product, despite all of those fears and hesitations. But boy, does it sure help when you have a partner like Shopify on your side. Shopify is the commerce platform behind millions of businesses around the world and 10% of all e commerce in The US. From household names like, well, hacked podcasts merch to brands just getting started, you can get started with your own design studio with hundreds of ready to use templates. Shopify helps you build a beautiful online store that matches your brand style. Did I mention that that iconic purple shop pay button that's used by millions of businesses around the world? I don't know why I wouldn't. I should. It's why Shopify has the best converting checkout on the planet. It also helps boost conversions, meaning less carts, sort of getting abandoned in the parking lot, and more sales for you. It's time to turn those what ifs into sign up for your $1 per month trial at shopify.com/hacked. Go to shopify.com/hacked. One more time, that's shopify.com/hacked.

Speaker 3: No one goes to Hank's for his spreadsheets. They go for a darn good pizza. Lately though, the shop's been quiet, so Hank decides to bring back the $1 slice. He asks Copilot in Microsoft Excel to look at his sales and costs and help him see if he can afford it. Copilot shows Hank where the money's going and which little extras make the dollar slice work. Now Hanks has a line out the door. Hank makes the pizza. CoPilot handles the spreadsheets. Learn more at m365copilot.com/work.

Speaker 2: Let's talk about birds. Do we wanna talk about, like, AI birds? Do we wanna talk

Speaker 1: about No. I just wanna talk about, like, old school birds. This is a palate cleanser. We just talked about a big techy crime story. I think either last episode or maybe the episode before, we talked very briefly about the technology underpinning crosswalks.

Speaker 2: We did.

Speaker 1: And people really seem to like that. People seem to really enjoy the weird tangent on, not relevant, but interesting tech stuff.

Speaker 2: The history of the crosswalk noises.

Speaker 1: And I went down a really interesting side road. This isn't going anywhere. Just so you know. They had to do with birds. There's, like, birds flying around inside my window, and I was noticing there's a thing that birds do called a murmuration.

Speaker 2: Mhmm. You

Speaker 1: know this term? Nope. Yeah. It's like

Speaker 2: Tell me.

Speaker 1: You're like, no. It's whenever you see a flock of birds and they seem almost like a single mass, and it's kind of like moving through the air. If you Google a bird murmuration, it's like a big flock of birds flying in sort of density. And there was this question for a long time of, like, man, how do those birds not just be smashing into each other all the time? Why aren't those birds constantly smashing into each other? That's such a tight tolerance for it to remain coherent. It's just an interesting question. The thing I wanna talk about here is an artificial life program from 1986 developed by a guy named Craig Reynolds, used to simulate the flocking behavior of birds. He called it Boyd and Boyd's algorithm in reference to a shortened term for this idea he came up with of a bird oid object.

Speaker 2: K.

Speaker 1: So, like, a bird like object trying to predict the behavior of that birdoid got condensed down to Boid, which also just sounds like the way the word bird would be said by a New Yorker. It's a Boid. Boid. Literally. This concept, this algorithm has been used in, like, film, video games, simulations, science for years since. And it figured out that this, like, the way they do that, this emergent behavior of birds is rooted in, like, a set of three rules. Basically, if every single bird observes these three rules, you get these big kind of murmurations of birds and birds that never crash. Can they separate, steer to avoid, like, smashing into each other? Do they align towards the average heading of where the whole group is going? And are they coherent, always moving towards the center mass of the whole thing? If you just have the first two, they'll, not smash into each other and go in the same direction, but they'll eventually break apart. But if you add the third one in of cohesion, you get this, like, emergent behavior where birds can fly in these beautiful, like, single almost objects. This was reproduced by this guy Craig Reynolds, and he called it Boyd's algorithm. And we've now just sort of known how birds work ever since. And I thought

Speaker 2: that was cool and interesting

Speaker 1: and good. That's what I tell you about that, Scott.

Speaker 2: No. It's it's for a digression, it is an interesting one. I learned something. That that is that is cool. I've never really thought about it. Maybe that's a failing on my behalf. You know, they're really Growing up in the in the rurals and watching flocks of birds take off all the time, I never ever sat back and said, wow. Why aren't they smashing into each other? But now next time I see one of these, I will be enthralled by it. Also, what an interesting field of study. Imagine your life's work. Imagine you were the boy Right.

Speaker 1: Like, you had created awesome. Yeah. Kind of awesome. Like, you cracked how birds worked for the first time. It was like he did other stuff, and then his algorithms were, like, used in films and stuff, and he worked on those. But, like, yeah, just, like, off the side of his desk, cracked out birds.

Speaker 2: I'm a bird simulation expert. Pretty cool. Pretty cool.

Speaker 1: Pretty interesting.

Speaker 2: Pretty A

Speaker 1: real dead end narratively. Yeah. Hey. Hey, birds.

Speaker 2: Let me transition on that one. I We really talked about all birds AI. So Oh, yeah. We do. Us. Yeah. Yeah. There would have been a good chance there.

Speaker 1: Sure.

Speaker 2: I wonder how they're doing in their their new AI service provider thing Life. I wonder what happened to all

Speaker 1: the people that liked their shoes. For anyone who's unfamiliar, Allbirds, the shoe company, decided to do the strangest pivot I've ever seen and become a AI infrastructure company

Speaker 2: As you do.

Speaker 1: Really proving as as you do. If you simply couldn't have given less of a shit about your shoe business.

Speaker 2: Well, the shoe business had failed.

Speaker 1: So, like, they needed it. They sold it. So it was worth

Speaker 2: some Well, it it had failed in the sense that it was essentially dead. So they needed to re come back to life as something else. So why not come back to life as an AI service company with, tons of funding, raise a bunch more money?

Speaker 1: You wanna build some server farms? Rock on, guys.

Speaker 2: Yeah. You you're just gonna be on the customer list for AMD and NVIDIA waiting for chips like everybody else is. I don't know if you've been following the looks like we talk economics, finance coin

Speaker 1: for a second. Finance corner.

Speaker 2: Man Sound

Speaker 1: effect I haven't made. This just hit me.

Speaker 2: The So you're keeping up Yeah. Literally. I'm not sure if you've been keeping up Intel insane. Like, for a company that had was completely market uncompetitive, like, two years ago, had lost most of its or was losing in the progress of losing most of its server server and personal computer chip market. K. Share had hit an all time low. You know, I think even as early as last summer, we could have bought it for, like, $19 a share. And I don't know where it's at today, but it's probably around 140.

Speaker 1: I feel like the story about Intel has been just that they're bleeding their biggest customers. The famous one is Apple made the switch to silicon four or five years ago. I think there was a rumor they were going back to them for something. What do you attribute to, the '19 to one forty switcheroo? It is a,

Speaker 2: so it's a $127 as of recording. 483% increase in the, past year. Five x. Pretty good. Pretty good.

Speaker 1: Did did Van Dyke make a bet on it? Like, what what happened here?

Speaker 2: Well, pretty much. It's very similar in the sense that, The United States realized that microchips were the future. When COVID happened and the chip pipelines dried and all of a sudden Ford was not rolling trucks off the, production lines, you know, all of a sudden you realize that microchips that we buy from third party countries, notably China, Taiwan.

Speaker 1: This is written in the American investment.

Speaker 2: Yeah. Yeah. Totally, are completely required for every single piece of modern consumer product and, industrial product, commercial product, government product. The government policy shifted to bringing fabrication of chips back to to America, and Intel is the American chip company. So the government jumped in, and they changed CEOs, and they've been killing it ever since. So

Speaker 1: Wait. When you say killing it, in what way? Like, killing it in the sense that there's money flooding into the stock or killing it in the sense that the company is performing better in a material way?

Speaker 2: I think both. They're they're producing new product that people actually wanna use for stuff. They're expanding their manufacturing capacity. The share price is way up. You know, there's a bunch of things going on in that company, investments and joint partnerships with other manufacturers. So I think it's Right. All in all, I think it's doing they've been doing very well in the in the market and in the in the industrial side of things. You know? I think it with the government shifting policy, identifying it as a major risk and and pushing forward, not just monetarily, but also policy side's been a big win for them.

Speaker 1: Outside of the question of, you know, the American government investing in an American chip company, When you refer to them making products that people are excited like, what is your sense of what Intel is up to on either the consumer or even the b two b side? Because I have accumulated all of the plaque of the story that they're just sort of like, we ran out of ideas. Intel is no longer inside of anything, and we don't know what to do. And that's just sort of where the story is left for me. I'm an Apple user, so I'm just not exposed to it. Where do you see them? Like, what kind of things are they doing that people are like, oh, Intel? Sick shit.

Speaker 2: They they I think they've been putting a lot of drive behind their GPU side developing. They're not nearly as supported, of course.

Speaker 1: Smart. Yeah. Good fair play.

Speaker 2: The, and and and by that mean, like, they're no longer in the sense winning the market. They don't have a big chunk of the market share, but they're at least structuring and positioning themselves to try and become a competitive player in a market that the supply is nowhere near the demand levels. Like, I don't know if you've tried to buy a consumer GPU recently, but, like, a premium NVIDIA GPU is like, if you go out and try and buy a fifty ninety, you're paying, like, $5,000 for it, which is you know, would have been the cost of the entire gaming PC Yeah. Three years ago. And now that's just for one part of it.

Speaker 1: Yeah. That's driving the the cost of pretty much every piece of consumer electronics up sort of down the supply chain. Like, not obviously everything has an NVIDIA, graphics card in it, but somehow a Nintendo Switch two costs $50 more and no one can get Steam boxes or machines or whatever. Like, it's having all these weird knock on effects throughout the rest of the industry.

Speaker 2: Yeah. The, some of the other big things like their new Xeon chips, like their server chips have really focused on performance per watt. So bringing down the power consumption, bringing up the perform like, stuff that AMD and NVIDIA and Apple, specifically, have done very well. So they're just kind of I would say they're retrofitting, which is, I think, a good a good good way for them to go.

Speaker 1: Yeah. Catching up.

Speaker 2: Catching up.

Speaker 1: Like, retrofitting. I I say that not even smartly. I'm like, yeah. You you kinda needed to catch up, and maybe you were undervalued. Yeah. And can you? Because then if the answer is yes, then I I kinda get it. That's really,

Speaker 2: really fast. They've always made, I'd say, performative chips. Like, their chipsets have always been pretty good. Yeah. Yeah. Except for, like, they were just bottlenecked by their fabrication cap capacities and, like, how many nanometers they could get their chips down to. So even as early as, like, a few years ago, you know, they were still 12 nanometer chips when they're competing with AMD at, like, a Yeah. Nanometer, new meter, nanometer, I think, nanometer.

Speaker 1: Nanometer. But I think we're even down to, like, four now.

Speaker 2: Yeah. We're down to almost two, I think. Yeah. So so there's been a big pushes in in just productivity and gains, and that's the big thing. Like, as you see the data center world kind of blowing up, you know, power, heat, massive massive parts of Of course. How do we get the most out of these things without it costing and environmentally taxing the most?

Speaker 1: Yeah. I think that I'd be really curious. I feel like I haven't heard this as much, this argument, but I'm I'm waiting for someone to start really making the longevity argument. Like, there's a lot of interesting stuff about the scale of the cost of the, like, data center build out that we're living through right now. Like, just unfathomable amounts of money going into data center production. And you hold that against the cost of other infrastructure projects, Highways, bridges, really physical waterways, pipes, like the physical stuff. And that's all well and good, if you believe in where the technology is going. But what's not great is that those things typically last twenty five to thirty to forty years and a server farm is like, oh, it's a lot less. So I'm really fascinated to see which companies start coming up being like, let's just talk about these will last a decade. Like, that is being the primary sales pitch for these things. But you should use ours because it's more like a road. It's gonna be here in fifteen years or something. I think that that's a really interesting case that won't start feeling urgent until the wildly expensive server firms we're building now start aging out and the cost comes back, and we go, oh my god. This is a subscription service. We have to keep building these things out.

Speaker 2: I would I would counter that by saying that I if you believe that anything in the infrastructure world is not a subscription service, then you might have some rose colored glasses on. Like, roads have massive amounts of annual budgets to maintain them, improve them.

Speaker 1: Right. But not on the order of a of rebuilding this the road from scratch every three d.

Speaker 2: Depends on what the climate's like. The,

Speaker 1: But in the vast no. Those are different. Like, those are really I I hear what you're saying, but they're pretty

Speaker 2: different. Yes. Yes. But but but but here here's what I'd say is that the data center itself like, the data center refers to typically a facility. The facility will not depreciate in seven years. Some of the hardware inside of it but here's the reality is that in the IT infrastructure sense, you know, servers generally have not had a longevity of that long anyway. So every single system that you use, be it cloud or in a corporation, chances are they're constantly upgrading, changing, and evolving their infrastructure stack rapidly, maybe every three years. So so Mhmm. I think that, like, Michael Burry, the big short guy, the doctor guy who Oh, yeah. Yeah. He he came out and was all critical about the depreciation schedule for GPUs.

Speaker 1: I didn't know that.

Speaker 2: Yeah. And he said that that was one of the biggest flaws in a lot of these companies is that people were, depreciating them too slow, that they needed to be on rapid depreciation schedules. Interesting. And, it got countered pretty substantially by the by the market because the intention is is, yes, there will constantly be innovation and growth in it, but old computing capacity still has usefulness. It still has utility. So, essentially, like, you're even seeing that now. So Elon built Colossus one for XAI and Tesla, built what his first big data center. They're already built Data Center 2, Colossus 2. And they had a bunch of excess capacity on Data Center 1 or Colossus 1, and he just last week signed a a lease agreement with, Anthropic. So Anthropic's gonna utilize all that computing capacity. Even though they've moved their business forward onto newer stacks, all of this excess computing capacity was just sitting idle. So Anthropic was like, well, we actually need it, so we'll pay you for it. And yeah. So so I think the I think like any industry, like, the the massive AI data center industry is interesting and, you know, it's growing rapidly, but it'll also given the amount of money moving in it, it's gonna innovate rapidly. Like, the data center that was built three years ago is gonna look a lot different than the data center that gets built five years from now.

Speaker 1: And Exactly.

Speaker 2: Yeah. But but but but but but it wouldn't improve without the level of investment and without the the market initiative. So you're already seeing that with cooling systems, with energy systems. You're seeing you're seeing rapid improvements in all of the the industries around the data center as they're all getting so much capital that they're pushing r and d forward to kind of progress it. So going away from diesel generators to, you know, modular nuclear.

Speaker 1: Solar or whatever. Yeah. I'm fascinated to see that feels the, like, rapid growth and improvement of them over the next coming years, I can't see how that doesn't have some impact on the depreciation of the ones that came before it. And while there's always been that depreciation in server farms, there's an unprecedented explosion in the manufacturing of these server farms. It's like that's just a that's a weird economic situation to be in that we're all gonna have to kinda just sorta watch how it gets managed because some firms will manage it better. Some firms will be on the upgrade cycle in tighter little loops. Some will go too tight with it. Some will go too slack with the iteration. It's like, it's just gonna be fascinating to watch how people manage these assets knowing that they're tech, and tech depreciates in a different way. Do roads depreciate? Yes. But differently than a GPU.

Speaker 2: Let's let's let's let's not use roads as the analogy. Let's use the electrical grid.

Speaker 1: Sure.

Speaker 2: So the electrical grid was put in, you know, in various stages over the last hundred years. Grossly inefficient, loses a boatload of power to heat energy, you know, loss. You know? But here's the thing is that it's it's essentially largely a government piece of infrastructure paid for by the government. There hasn't been enough capital and market forces to push r and d forward on it. Like, anytime that we transmit and move massive pieces of power across long distances, like, you can lose 10%, which is a massive like, if you were if that was an economic and private well, if that was a private entity, they would start optimizing to reduce that. And whether that's relocation of generation facilities, better forms of generation, it's not it's the same incentives structure that we look at with things like alternatives. Like, yes, we know that solar is not the best. But you know what? The only way that it gets better and it has gotten so much better in the last twenty years is by incentivizing the development of the industry. The same thing is gonna happen in in data centers. But to go back to the power grid that I was trying to talk about, you know, the like, most of The USA's power grid is seventy, eighty years old. It's critical, critical infrastructure that has had very little investment. You know, it is the maintenance plan. It is you know, imagine trying to operate a data center from seventy years ago.

Speaker 1: Agreed.

Speaker 2: But that's my thing is is I'm not mad at it. I like to see the market activity because all it's gonna do is push whatever the windows and problems and, externalities caused in the industry are gonna get cleaned up because the momentum's there, the capital's there, and the pursuit of optimization will will make it so.

Speaker 1: That's fair. Pretty optimistic. Yeah.

Speaker 2: I'm you know me. I'm the optimist on the show.

Speaker 1: So I know you are. You're a market optimist. I I totally I have maybe a I harbor some skepticism when it comes to the like, and the market will simply make it more efficient so they can be more profitable. I'm like, totally. Canadian Internet's great. Like, I can think of all these private market things rooted in physical infrastructure. They're like, why would we spend the money making that better? We're printing we've we've captured it. We make more money than God.

Speaker 2: No. No. But but here's the here here here's the flaw in your argument is that, Canada has essentially a noncompete oligopoly when it comes to telecommunication.

Speaker 1: That would ever emerge when it comes to AI. I simply cannot imagine something like that happening right now.

Speaker 2: In in all honesty, I can't. Given the given the quality of open weight models and the open source models, given the optimizations that are occurring in the in the public space, in the open source software, given the mess ups by companies like Anthropic just fully disclosing harness code and information sets, the I think that there will always be competition. Like, I can go out today and buy a computer, like an Apple Mac Studio, and essentially run my own anthropic super facility in my house on Mac hardware, which uses no energy, ultra fast memory bandwidths, all the rest of it. You don't need, like, the the as the model optimization so the same thing is happening in the models themselves where, you know, the first one that we made, we made this monster model. It's like, hey. We got this thing called GBT, and it it's we trained it on everything, and it knows everything, and it's kinda, like, bad at everything. And then people have been working on ways to optimally structure them. Then we got mixture of experts models. Then we've got, you know, that that research field is evolving so quickly. And now it's being facilitated by the fact that the AI can help, can help Your

Speaker 1: argument is the competition in those spaces is in some way different.

Speaker 2: And we see that where it's like, yeah, the oligopoly of AI. Sure. Last week, it was open AI. To this week, it's anthropic. Next week, it'll be Gemini.

Speaker 1: Right. But but market leader and oligopoly are compatible concepts. Like, you can have 10 companies that

Speaker 2: just, like, capture

Speaker 1: the whole thing. But I take your point. I take your point.

Speaker 2: But then you've got but then you've got moonshot releases an open version of Kimmy k two six, which is in competition with, like, Chachi b t 5.4. You've got, you know, Alibaba releasing Kwen models. You've got Meta releasing Lamma models. You've got Gemini releasing Gemma models or Google. Like, there's so many open weight models and so many people doing so many things that within the last couple of years, I've talked about how, Apple and perplexity there was discussion in the market about whether Apple was gonna buy perplexity. And I originally didn't love it as a great idea, but now I've come full circle where I actually think it's a great idea because perplexity has really shown that they know how to build the harness, the thing that runs the model, the thing that communicates with the technicality of the model and gets the most out of it. Perplexities, that's pretty much been their business model since day one. They don't build their own models. And I think that that's kind of where the market's going. The models will change based on the situation, you know, whether it's running on your phone, your watch, your laptop, your organizational AI server, off-site cloud data center stuff. Plus, it gives the ability for the organizations, like somebody like Apple who has all of the surface with computers, phones, Siri, for God's sake, do something about Siri. The, it gives them all this surface that they can then tune their connections. So the way Perplexity changes the harness to get the most out of the models in the back end, they can tune the interface to get the most out of the harness. So they can link the harness in the interface better because the harness is linked to the model. And I think that that's where we're going. I I don't know I don't know like, the more I look at the AI investment, I see the market value return on artificial intelligence. I see market penetration right now in the sense of who's using what solution. But I think as we go forward long term, most of those solutions won't be worth as much as people currently think they are. I

Speaker 1: think so. To me, it reinforces the idea, though, that the availability of open source models as a competitive balancing force is less important in the future than it is currently just by way of the fact that, like, if you're saying that the model is the interchangeable part and that we're relying on the existence of open source models as a market balancing force, I'm like, well, those two things seem at odds with one another. It seems like right now that's an insurance policy that is gonna become increasingly less valuable. Mhmm. And I think that you're right that those models are gonna be, like, the hot swappable things. Like, you just sort of pick yours. It's like when I sign in to a new iPhone or a new phone, I just, like, plug my email into it. I'm not worried about who my email provider is. It's kind of just like a come it's a utility ish. It's, like, It just gets funneled over to this thing over here.

Speaker 2: It show all shows up in the same inbox.

Speaker 1: Whichever client I use, it all shows up in the same inbox. And I to to shift a little bit, I think that you are right that, like, these things are gonna become hotwired in commodities. And I think that has a really interesting effect, especially for OpenAI who's getting into hardware. Like Apple Apple Siri. We've talked about that a ton on this show. We won't get into the consumer tech Apple side of things too much, but it is worth talking about that they just agreed to pay a $250,000,000 settlement to a class action lawsuit over how they marketed Apple intelligence before they they didn't admit wrongdoing. This is just an interesting story from the last couple weeks. Basically, the plaintiffs alleged that Apple had overhyped a, like, version of Siri that was super context aware. The thing that you saw in the commercials starring, I think, Bella Ramsey was this idea that because your calendar is on your iPhone, the iPhone Siri would be able to check your calendar looking into the past, figure out who was someone you'd met with at a certain event, and conjure that answer in real time. They postponed those personalized series features, citing engineering challenges. And as a result, this lawsuit happened saying, hey. A lot of people bought iPhones because you were running ads saying that they'd be able to do that. And now Apple has basically agreed to this $250,000,000 settlement up to I think it was up to $95 per per device. And that is literally from an era where they thought they were gonna be developing probably their own models to your point, deploying them on the device. And now we're looking at, like, you can just plug any one of these models into your device for any individual task. You can have five of them wired in. So, like, so much has changed over the last two years of where we think the value in this market is, and it's all kinda encapsulated there. It's interesting.

Speaker 2: And that that's just it. Like, I for me, like, it is a true a lot of my belief is grounded in the sense that there still are gonna be open way models accessible and that people will still provide them. If that goes away at some point, I think you start to see not for profits spinning up training their own models from releasing them. Like, I I think that there will always be competition in that space because the value is too high. I still don't understand how Apple hasn't done anything about Siri. Even with their minuscule Apple intelligence models running on our phones, they still could have made Siri

Speaker 1: not so terrible. Any day now.

Speaker 2: I don't know why. The the the fact that they're taking so long to do anything worthwhile tells well, no. It shouldn't tell me. I'm hoping is an indication that they're actually gonna do it right. And and they're not just gonna rush stuff out like they did with that commercial that got them sued. And their settlement is gonna be pennies on the dollar compared to what the enterprise value change was for their share price. So I don't think they really

Speaker 1: That's an interesting question of did they make more money on the on the stock pop after running that ad than they paid on

Speaker 2: I guarantee they did. Yeah. Guaranteed. The but yeah. So I think, you know, the more and more and more that I play in this space and get to know it and tune it up and really dig into it, I think we're going to a world of specialization just as we did with laborers. You know, we had generalists, then we got into to fields of specialization. You could become a generalist in a field, or maybe you were a hyper specialist working in an esoteric place inside of a field. And I think we're gonna start seeing that with models. Like, if you are a law firm, you will have a model that has been hyper specialized in case law, precedence, you know, etcetera etcetera. And there will be a custom harness built around that model that takes the most out of it as possible. And I think the company that's showing me that the the best at doing that right now is perplexity.

Speaker 1: You really like the heart you really like the front end basically for all this shit that they're making.

Speaker 2: Let's do the front end is different. The mid layer the mid layer is what I'd say the harness is. Like, you're you got the model at the base, the the harness in the middle, and then you've got the UX. Perplexity's UX leaves some things to be desired. But I think Apple's an amazing UX company. And if you gave them an amazing mid layer company like Perplexity to go through every functional component and interaction in an operating system, be it a phone, a watch, an iPad, a a laptop, a server, and you allowed Perplexity to wire in, you know, functional AI at those moments, I think that Apple would leapfrog.

Speaker 1: It's interesting to imagine with them knowing that this is kind of maybe their new route. It's this idea of, like, you want Apple notes to rewrite your note. You tell us what you want to do that. It's like, oh, okay. I see where you're going with this. It's gonna be interesting to know what the, like, five years after that's gonna be. Is it that they buy one of these companies and start really promoting it, weaving it in, and sort of promoting that internal option? Do they Sherlock the entire AI industry at some point and just go like, well, now that we are the surface for all of this, when everyone is just using it through their iPhone, boop, and switch something over and go and just sort of, like, decimate all these things. It's like it's a it's a really interesting deal to make because obviously you want your your model in front of all of the iPhone users. That's that's the Of course.

Speaker 2: Huge surface area. Area. Massive.

Speaker 1: So he's definitely giving a lot of control to one company.

Speaker 2: In other Apple news, just while we're rambling about it, Tim Cook obviously stepped down. Retired, took his billion dollars and exited stage left. Good for him. He he added, I think somebody I heard a joke that he'd added an entire zero to the back end of the enterprise value of Apple since he took over. So I think he did a a great job as a managerial person. I don't think as somebody that fell in love with the company Apple based on rapid innovation, definitely didn't see that under the Tim Cook era. So I was happy with their appointment to their new CEO, John Ternus. He's a he's a product product person. Which

Speaker 1: makes sense with what we're

Speaker 2: talking about.

Speaker 1: If Apple's saying, like, we're just gonna go back to being the hardware front end company. You put your fuel in our engine. That's fine.

Speaker 2: Totally. We'll build the UX. You take care of

Speaker 1: the rest. AI plays to own the hardware. Like, honestly, super smart. Be like, we're just gonna own the hardware. Yeah. To speak nothing of the Mac mini of it all, we're just gonna own the surface that you engage with these things on. It's, like, honestly pretty smart. Stay out of the suit.

Speaker 2: Well I can get it. OpenAI spent billions of dollars acquiring John Ives for this time.

Speaker 1: About that. Apparently, it's a phone. Everyone is saying now it's the rumor mill is that it's it's a phone.

Speaker 2: Oh, Interesting.

Speaker 1: Best of luck.

Speaker 2: Best of luck. The thing for me is that a phone is now no longer a phone. We use the word phone colloquially to discuss the mobile computer that we carry. The amount of people that actually push the phone button on the compute on the on their mobile computer is is infrequent these days. I don't get as many phone calls as I used to. But the extensibility of having a mobile computer that comes around with you everywhere that has fully AI power. I'd be interested to see what they do.

Speaker 1: Very curious to see what they do. I bet it's Johnny Ives, so the hardware will be nice. I'm curious. It's like I'm not a hardware guy, and I'm not I'm sure I'm not a mid layer guy, so to borrow your sort of framing. But, like, I think about design and front end and the kind of experience of using a designed object pretty regularly, and I'm really curious how much they commit to the chat layer. Like, I think you could make a version of a phone that is, like, pretty unpleasant to use if it over relied on the text and natural language interface, like, full full stop. I think it's like you could re you could really tune this wrong and be like, yeah. Just ask the phone to book that for you. Be like, that is 27 syllables when I could previously do it in four taps. You haven't made it.

Speaker 2: I'm curious. That's so one of my pet peeves with chat AI right now is I ask you a simple thing, and I get back a

Speaker 1: Flip a novel. Flip a novel. I'm like, I don't want that.

Speaker 2: And I'm just like I'm like, give me give me three bullet points. Like, give me give me your recommendation pros and cons. That's it. Like, I don't want you to discuss the world with me, And it just these are synced for the love of God.

Speaker 1: I heard someone liken it to, like, the brittleness. It was like we escaped I can't remember who said this, but it was like we escaped the command line in terms of how we use computers because it was like it was just very brittle. You you had to

Speaker 2: type it in you you get No. These exact syntax.

Speaker 1: I'm borrowing that frame Semantics

Speaker 2: were everything.

Speaker 1: Brittleness. And then we got we moved to the mouse keyboard and eventually multitouch, but this idea of just touch it. Touch the thing that you want it to happen and it will. That removed the brittleness. Large language models don't have the original brittleness of the command line, but they introduce a new set of brittleness. Like, it will respond, but it might just make shit up that isn't relevant to what you're trying to do, and it might write you a novel when you need two words. So it's like you

Speaker 2: have Mhmm.

Speaker 1: The the future seems like a really thoughtful blend of these two. And if you're the chatbot company, I'm curious where you fall on that.

Speaker 2: Well, that's the that's the mid layer. That's the harness. We we know the we know that the model and it's also the model tuning, obviously. Like, they've spent a lot of time tuning the model to be very descriptive in their responses to make sure that they discuss every case that they made an assumption on. Just just also for liability's sake where you're just like, you asked me this, and, you know, it's impacted by these 75 things, so let me go through all of them in great detail. And you're like, okay. Yeah. Great. Just tell me where to go eat brunch. Exactly. Like

Speaker 1: yeah. Yeah. I'm really if it turns out to be a phone, I'm really interested to see where that goes. Like, how how good a camera does OpenAI make? Like, just all these weird questions about, like, phone engineering and, like, the post processing pipeline of images and and, like, all these weird little things that have just nothing to do with their core business. So it's like, do they just buy nothing? Like, do they just buy a mid sized Android phone maker and, like, repurpose it? Be like, you work for Jonathan I.

Speaker 2: They don't even need to. The the reality is, like, you can go on Alibaba and buy bulk Android, Snapdragon Trunks. And have them branded. Yeah. Exactly. It's not like, you don't need the hardware engineers anymore. They're yeah. There's problems been solved, so they don't need to focus on that. The the thing for me is is is Apple's being successful because of and in part by the ecosystem. You know? I have an Apple computer. I have multiple Apple computers, so I bought an Apple phone. And because I have an Apple phone, I bought AirPods. You know? They might not be perfect, but, damn, are they easy

Speaker 1: to use. Competition.

Speaker 2: Yeah. Better than the competition. If I wanna really listen to music, I'll go sit in, like, my listening room or I'll I'll use a set of high end headphones. But, like, for daily use and phone calls and walking around, I'll listen to a podcast while I get groceries. It's they're amazing. So the ecosystem becomes a thing. So to just show up with the Trump phone, the OpenAI version of the Trump phone and here's the other thing is given the fact that code is now a commodity, the building of code, Everything comes down to the product ID and product design because the AIs are are rapidly prototyping things at speeds unseen by companies in in the past. So, you know, even Apple released a a service update to a piece of their software this week, and they left their claud instructions file in it accidentally. So, like, Apple's using claud code internally. Yeah. And and nobody's surprised by it because It's barely

Speaker 1: a gaffe at inputting to see. Yeah. Like, of course.

Speaker 2: Yeah. The Jensen Huang quote of, like, if I hire a half $1,000,000 engineer, I want them to spend a quarter million dollar in AI tokens is coming true. Like, the more productive my human capital becomes, the better the better investment in the person. So so the yeah. To just build a phone and crank it out even if they come up with the world's greatest way to interface with the AIs, Google would probably be able to replicate it inside of twenty eight days. So it's like, what kind of market moat are you gonna have to keep your business sustainable?

Speaker 1: I would bet their argument is gonna be like, the vision of all these things is just like, well, if we have unlimited personal context about you because you input everything into something and you receive all your messages through something, and maybe it's just sort of, like, got a camera on it and you're every time you take a photo, like, the more context these things have, I think the argument goes Mhmm. The more sort of powerful and oh my gosh, they become. And so if you don't own that physical ID layer, if you don't own that object, and that object's manufacturer could put any kind of a privacy wall between you and that information, you can't get that thing, that precious tranche of context thing, that pile of context about the individual user.

Speaker 2: So who has all of our context, though?

Speaker 1: Well, right now, Apple. But Google to an extent. Yeah. Apple and Google too.

Speaker 2: Enterprise increasingly

Speaker 1: less, but for enterprise work a thousand percent they do. Like, that's what they own. Sachin Adele is a smart person. And it's like, okay, correct. I lost the microphone, like the Windows phone race. So I've lost the personal context, but I can get the business context. And so I think the question is, like, is ChatGPT sticky enough to get people to wanna feed their context into it? And face you just made same face I'd make too, not compared to like, no. Not on its own. Unless Johnny App comes out with some hardware that's just shit hot, and everyone's gotta have it. I'm not sure that, like but ChatGPT knows all my stuff. I'm like, I'm not sure that's a value add, friend.

Speaker 2: Yes. I don't know. That that that that to me is that like, to loop back to the earlier conversation about model portability is that to me is the the the the fault in all this. Like, actually, after one of the last episodes where I asked, I was like, oh, man. I wish I could invest in Databricks. Somebody Somebody messaged and was like, oh, you can actually buy these venture funds. But they're they're trading at, like, 18 times value of the, like, VC value. So, like, if they if they bought a a $100,000,000,000 of equity at a at a in a trillion dollar raise for OpenAI. They want $1,800,000,000,000 from the market to buy that same equity, and I was like, there's no chance. Like, the there's people buying the OpenAI like it's gonna be the next coming, And I just can't see it. Like, they just don't have a moat. The moat is that they make good models. But guess what? If you go look at the model arena billboards

Speaker 1: and stuff,

Speaker 2: lots of people can make a good foundational model. It's coming down to who like, even the competitive differentiation now you're seeing is, like, Claude Co work, Claude Code, Codex. That's all harness. That's all mid layer. There is some model tuning going on for sure, but perplexity's mid layer, where perplexity is sitting and and building and growing and developing skill sets is now what the frontier model providers, the foundational model providers are now competing in. It's like, hey. Look how good our tool is that uses our model.

Speaker 1: Sure.

Speaker 2: So the models have become less and less important. You know, we're we're almost sealing out on the models, but getting really good at building the midlayer that communicates with them.

Speaker 1: I'm I'm I'm interested in

Speaker 2: this

Speaker 1: because I think this is gonna be where we see the fork of, like, what is the application of this technology for people versus software developers. Like, that Totally. That gulf of, like, it's so hyper useful for this group of people. Yeah. That are making the tools for the other people, but it is untested how useful it is for these people. And there's all these cool theories and stuff that you'll be able to do this. You'll be able to do this. Like, totally not happening today. So how do we get to those tools that make that midlayer really powerful for the average person is like whoever answers that question is like, oh, you win. Like, you made that midlayer valuable to people, and now you've turned everything else into just like a waterline or a commodity for your layer that provides value to the actual end user and not just software developers. I think that's an important distinction.

Speaker 2: Totally. But I will say that the focus on software development has facilitated the speed at which the entire transition is happening.

Speaker 1: Of course. You start with what it's useful at.

Speaker 2: Totally. Rational thinking. Like law, wild, what it's gonna do to the it can read legal precedents and and build a build a case. So, anyway, I I still wanna focus on I was gonna make a point there. I don't wanna digress too much. But the the thing that the biggest shock to me like, when we talk about the AI bubble, I think there is a bubble in the anthropic world. I think that there is a bubble in the open AI value. I don't think that AI as a societal change, you know, disruptor is a bubble. I think there will be massive changes from it. The the big thing that has confused me Mhmm. Is Apple Siri is a case study in the failings of a massive company that has an unlimited amount of money, could have built the world's greatest personal assistant utility, could have been on the forefront of this. And we're still seeing this. Apple like, the people that have the surfaces to make the disruption, Microsoft, Apple, aren't doing the disruption, Microsoft, Apple, aren't doing it. Even Google Gemini, the way that they've integrated Gemini into the into the office suite, Google suite, is really bad. It's like the the the like, if you have an unlimited amount of ungodly resources and power and money and you have the software developers that are now enabled by AI agentic engineering, they're you're getting 10 x the output out of every single one of your software engineers. How have you not built better products to utilize your surfaces to make this transition? That's the thing that really blows me away is is the companies that could win it all are losing in my eyes. Like, they're they're behind. Like, why is a little tiny company like Anthropic pushing out co work and OpenAI pushing out codex, which is their coding tool that they're now rebranding as, like, it can also help you do regular stuff. Same thing Cowork is. It's just the OpenAI harness for cloud code, but repurposed to, like, business things, operational efficiency stuff. So why is Microsoft solution Copilot chat? Like, like, you guys have trillions of dollars.

Speaker 1: You had all the opportunity to be able to help us.

Speaker 2: Some of yeah. Some of the best software engineering minds in the market, and, like, Copilot chat is your solution.

Speaker 1: But then so too should we all be using Windows phones. And it's that great thing of, like, you can have all the money in the world, but if you don't have the the product or the idea, it doesn't matter. A buddy of mine is a, like, a he is a developer, but he he works in product now at a tech company.

Speaker 2: Mhmm.

Speaker 1: And he was outlining how the relationship had always been, on the product side. Comes from an engineering background, but he works on product now. And they had a series of different engineers, like, say, three or four below them. And it was the idea that being, like, engineering takes so much longer that we would come up with concept like, product concept working with marketing and sales and design, and then we would allocate it to the engineers, and they would have to take time to do it. That's why we had multiple of them. It took time for them to execute and to make these features that the product wants. And then in the last two years, that relationship has completely flipped where they're executing on the ideas faster than the product pipeline can come up with them. And I'm imagining that relationship multiplied over the scale of a company like Microsoft or Apple or any of these things, where it's like you suddenly don't have nearly enough resources allocated to the what, and you're way over invested in the execution and the how. Like, one of those people can now do what the other three were doing, and you have this asynchronousness that has emerged. And the design problems that would lead you to not releasing Copilot in the shape that it is currently in aren't being tackled because you've misallocated all of your resources. And I think that that's a really interesting thing for all these companies to have to figure out is, like, what is our relationship between engineering and design

Speaker 2: In in world where

Speaker 1: engineering costs what it costs now.

Speaker 2: Say you gave me a job tomorrow, VP of AI integration at Apple. First thing I would do is make a bunch of tiny teams, designer led, product manager led. Like, you like, UX first and then a couple of engineers, and I would send 50 teams away to compete and be like, bring me bring me back. Like, here's one small task. Everybody bring me back on yes. Skunk Works. Bring me back an independent solution to each of these.

Speaker 1: Skunk Works.

Speaker 2: Which one did we like? We're gonna case them to everybody. Everybody's gonna get to vote, trial them, pick the one that works. Maybe you get a hybridization then. Like, we really like this from there, and we like that from there. Great. Let's put that together and see if it works. And do that over and over and over until you figure out how to integrate it. Because the reality is is, like, a a tiny little team of of highly competent engineers matched with a a competent project manager, design focused UX person could bang out a product in like, I can bang out a product in a month as a person. Imagine what you could do if I was being paid to do that, not just doing it while I watch tennis tournaments.

Speaker 1: Yeah. I I I think that that bigger investment in the design side of things. It's like you you were talking about the design process. It's like ideation prototyping and testing. Like, that little tick, tick, tick. It's like reorient around that because it feels like you're a little bit letting the, like you're letting something else lead the process from the reality. Doesn't seem to be working. Is is Like so maybe go back to that fundamental

Speaker 2: The harness is the thing. Like, you don't need to have a chat interface. The harness can have the chat for you. You just need to give it a simple instruction. And if you've got all the surface area and UX surface area that's provided by the operating systems, you can integrate tiny little instructions that go into a background harness that pull context from the apps that it has access to, your calendar, your messaging, your emails. It would be simple. It wouldn't be simple, but it wouldn't it's not challenging. It's not like we need to, like, solve a new problem. And it did I don't know. It just it shocks me every day that these massive companies that are so well funded and so well capitalized are yeah. And they're not progressing. They're not rapidly moving. Like, the thing that's giving Anthropic and Claude and OpenAI and Codex momentum in the market and valuations in this Goldilocks scenario is the fact that they're agile. They're moving quickly. They're trying things out, and they're they're showing successes rapidly where a lot of the bigger companies aren't. Like, when was Google's last model? Like, I know they released, like, 3.1 or something, but they really haven't changed any of the interfacing. There's there's nothing really that's changed about how you interact with AI. They just have a new model that's a bit smarter, and it's like, that's nothing anymore. Like, I would actually prefer an older model that's a bit dumber with a really good harness than the best model with, like, just a chat interface.

Speaker 1: Yeah. I wonder if Google at this point has started going like, we never really owned enterprise of a lot of this stuff. We owned a consumer chunk of the market. It's always done really well for us. It's very compatible. Like, low cost, high volume is great if you have an ad business bolted onto the side of it because I'm like, I actually don't care about your bill being that big. I care about your usage being high because there's a trillion of you. Like, that worked really, really well for them. And maybe they're like, you can go develop software wherever you want. We're gonna control the chat interface on the iPhone and the email and all of the Internet. You know what I mean? Like, they're gonna start segmenting based on what's useful, and eventually someone's gonna really own software development. Someone's really gonna own the chat interface on a phone. Someone's gonna really own each of the major market segments, which are gonna become calcified and clear over time.

Speaker 2: Mhmm.

Speaker 1: And we'll kind of, like, just sort of end up not quite back where we started. There might be a new entrant or two

Speaker 2: kind of.

Speaker 1: And an old entrant that's gone. But, like, it happened it's happened every time since.

Speaker 2: Yeah.

Speaker 1: Probably gonna happen again. I would I would make a bet on Polymarket. And then do it. Yeah. And I apparently could. Me and sergeant Van Dyke. Is there me and sergeant Van Dyke, just to bring a full circle.

Speaker 2: Just to bring a full circle. Anything else I wanna close on? No. I think that was a

Speaker 1: big enough

Speaker 2: rant. I think we solved it. I think

Speaker 1: it was a good one. I think some people are here for the rants. Sergio Van Dyke.

Speaker 2: Talked about, but we didn't. Oi? Not a big deal.

Speaker 1: Wanna talk about birds?

Speaker 2: Did you wanna talk about birds?

Speaker 1: Well, I already talked about birds. What did you wanna talk about?

Speaker 2: Just if it flies and flies. Thought I already mentioned that before. Famously. Famously missed that. No. There's nothing else that I really need to chat about. This this just it's wild wild times out there.

Speaker 1: It's a very interesting time

Speaker 2: right now. There's gonna be maybe we should do some talk some cybercrimes about AI, not just about AI because there's some pretty interesting stuff going on. Yeah. But maybe we'll set

Speaker 1: up a future up. I think for a future up, it's gonna be a a busy summer, so we might be coming at you with a hotline hack or two while while Scott and I are gallivanting around, to various places. But, save that for the next one.

Speaker 2: You make it sound so nice. Like, we're gonna be gallivanting and not just sitting in meetings.

Speaker 1: A meeting is a gallivant for the mind.

Speaker 2: My oh my.

Speaker 1: My oh my. K. Alright. Thanks for listening, everybody. As always, appreciate you tuning in, and we'll catch you in the next one. Take

Speaker 2: care.

Speaker 4: Where's your playlist taking you? Down the highway, to the mountains, or just into daydream mode while you're stuck in traffic? With over 4,000 hotels worldwide, Best Western is there to help you make the most of your getaway, wherever that is. Because the only thing better than a great playlist is a great trip. Life's the trip. Make the most of it at Best Western. Book direct and save at bestwestern.com.

Speaker 5: The right window treatments change everything. Your sleep, your privacy, the way every room looks and feels. At blinds.com, we've spent thirty years making it surprisingly simple to get exactly what your home needs. We've covered over 25,000,000 windows and have 50,005 star reviews to prove we deliver. Whether you DIY it or want a pro to handle everything from measure to install, we have you covered. Real design professionals, free samples, zero pressure. Right now, get up to 45% off-site wide, plus get a free professional measure at blinds.com. Rules and restrictions apply.

Speaker 6: Athletic Brewing Company crafts award winning non alcoholic beers for those who wanna be part of every round. With over 185 flavor awards, they're exceptional NA beers that fit your lifestyle and any social occasion. Summer's full of good times and athletic fits right in. Go to athleticbrewing.com to have brews delivered to your door or find them at a bar, restaurant, or store near you. Near beer, athletic brewing company fit for all times.