Jobs Boom, Astra Reactions, Cybercab Roll Out, The Dyson Debate | Hunter Somerville, Bar Winkler, Bridgit Mendler, Carina Hong & Ken Ono

27:44Once you break the seal of like, okay, we're doing it. He did it. Would it actually be successful? Because Replica has seemed to get to scale there's been other products that have played in this world and and seemingly a reached adoption and scale but uh it's very i i this was this is the same thing as the sora discourse where everyone was caught up in sora is is either going to be the most powerful thing ever and we're not gonna be able to stop watching it or it's gonna be good and so fun and and it's gonna be amazing and dominant but no one was counting just like oh it might just go away in six months and it's the same thing here i don't know i internet i think i was saying it was gonna go away just because i thought it was gonna be a tool yeah and i think i think we benchmarked the market for this like if you if you look at other romantic stuff yeah so so when it's just not a trillion dollars first said okay i'm going all in on on adult entertainment i did think it was a potential path for for grok to get into the single-digit billions.

28:50I probably overestimated the market there. But it felt like one of the plays that he had to get back in the game at the time. But again, this was last year. And back then, if you could get into the single-digit billions, you were doing pretty well. And then the game obviously really shifted to enterprise. Yeah, it makes sense to wind it down, focus on enterprise software. That was what was in the SpaceX S1 was the, what was it,$13 trillion market he was going after, something like that. It was in the, it was a shocking, shocking number, maybe$20 trillion or something. Absolutely huge, huge numbers, and it makes sense.

29:35There's a lot of value in the enterprise, much less in this controversial topic. Well, phish.audio ran a billboard campaign. We love Out of Home. This one sort of confused people. Heshy Brody says,$100 for anyone that can explain what this company does without looking it up. This is on the New York City subway today. And we'll read it to you, and you can take a guess. Fish.audio says, we put voice AI on a silent sign. You see the problem. Is this one of those jokes, though? I think it's a joke. I think this is an 11 Labs competitor. We even know, but is this a real ad from a real company or is this a prankster making fun of tech ads?

30:23Because there was that prankster who put up a bunch of billboards, like fake billboards. Remember? I think it just makes you think. It really makes you think. It made me go to the website. Okay. They make text-to-speech, speech-to-text, audio separation, voice changers, translation. and they partner with global innovators, John. They're working with HeyGen, Retail, a bunch of games companies, it looks like. Clout Kitchen. You ever heard of Clout Kitchen, John? No. You ever been in the kitchen cooking clout? Okay, so isn't it like they put voice AI on a silent sign. You can't, like, if you have a billboard, you can't listen to it, but their product is audio.

31:06So you can't listen to the billboard. That's the problem. Yeah. Right? I guess I would expect the application. Your explanation is a problem. I would expect the application to. More importantly, we have our first guest. Well, you just take a picture and it reads it to you. That's what I would expect. Anyway, we do have our next guest in the waiting room. Let's bring in Pablo Torre. And Pablo Torre finds out. He's a host, investigative journalist. What's going on? And he's on an absolute tear. What are you doing? Pablo, it's an honor to have you. I was telling John before the show started, we podcast for a living.

31:36I'm not a big, I don't follow very many sports very much. but every time there's a sports story, I go find your content. And when I watch your content, you make me feel like an amateur because you're just so good at what you do. So good at yapping, but then you're also an elite investigative journalist. And we wanted to take a victory lap with you. My show is designed, thank you, A. B, my show is designed for people who don't care about sports at all to find it even mildly entertaining and interesting. and this is a story that has immersed me in the world of securities law and the funneling of money and billionaires and especially one particular billionaire who used to run a certain company called Microsoft.

32:20And so all of this, I think, is actually in your guys' wheelhouse. So happy to be on with you. Yeah, and I remember I watched some of your content around a year ago when you were originally breaking this story. And I'm surprised that the story at least went away out of the public eye for some time. I'm sure you were still following it. But take us maybe from back a little bit to first kind of uncovering this and then we'll get all the way to the present. Yeah, so this was an investigation that started with a tip. And the tip was there's a weird company out in LA called Aspiration. It was a tree planting startup, AKA a carbon credits company.

33:00The ESG thing, as you guys may recall during the pandemic, was a real thing. We're going to be good guys, right? Everyone's going to be a good guy now. So cynical. Insane cynical. Hey, hey, hey. I love trees. I love planting trees, too. I love what they do to carbon and oxygen, reportedly. So Aspiration has all these endorsers that are public. There's Robert Downey Jr. There's Leonardo DiCaprio. There's Frank. There's Cindy Crawford, people who grew up in the 90s. That's a good deal. Toronto figures into the story in lots of ways. as it turns out. But the point is that there are all these A-list stars, Orlando Bloom, I didn't even mention, all these A-list stars that this good guy company is paying to tell everybody about what they are.

33:48And what I get a tip on is, hey, you should look into this company. It's kind of weird. They just signed a deal,$300 million to be the jersey patch sponsor of Los Angeles Clippers. And they have another endorser that you'd be interested in. And when I look into this, it's not immediately obvious what they're talking about. But when this company goes bankrupt because, and this is going to be in your wheelhouse again, they were going to go public via SPAC. What a time, right? What a time. SPACs, ESG, we're all going to get rich being good guys. And no one really needs to ask many questions. Just trust us.

34:23It's going to be fine. And what turns out is this company is co-founded by two people, two big damn donors, classic good guys. went to Harvard. I mean, I resemble the remark. I want to say that this has been also awkward for me. Steve Ballmer, Harvard, all of these guys, all of this, right? Pedigree, all of it. The thing that's interesting is that when you dig in to how this company fell apart and they go into bankruptcy, you of course get to examine some public filings. And one of their big creditors was a company called KL2 Aspire LLC. And if you're a basketball fan who is aware of the Clippers, you may realize that KL sounds like Kawhi Leonard 2, sounds like his jersey number.

35:07KL to aspire sounds like a vehicle you've invented to accept money from Aspiration. And he was owed$7 million outstanding. And the weird part was that this dude had no public record of being associated with Aspiration personally at all. And so when you dig in and you begin to ask questions to people who used to work at a company that has now gone into bankruptcy, in which the co-founder, Joe Sandberg, is now, by the way, serving 14 years in federal prison for fraud, you get people who are interested in explaining how crazy their life has been. And what they say and what they provide in the tonnage of all the reporting I did for months, seven months before we came out with part one of the series one year ago today, was documentation that attested to the fact that Kawhi Leonard was paid, according to this agreement, a total of $48 million, 20 in stock, 28 in cash, to do nothing for a deal that never got announced.

36:02And the question was, why? And so you follow the threads and you get to, oh, wait, there's a massive salary caps or convention scheme in which the richest owner in American sports, Steve Ballmer, is trying to use all of his wealth in ways he's not allowed to to get money to a guy that he needed to take away from the Lakers and the Toronto Raptors in order to make his dream of owning a professional basketball team exactly the dream that he imagined. So how strict are these rules? because I can imagine... That's a funny... Yeah, so we covered the whole, like, the AI talent wars last summer every single day.

36:40It was crazy. And we kept coming back to this idea. Part of why the talent wars worked in many ways is there's no salary cap, right? So Zaka could just spend exactly as much money as the players or the talent would accept. But in this case, rules are... There's actual laws. Yeah, I guess I just mean, like, If I'm a player and I know that the owner runs a hedge fund and I see the benefit of putting some of the money that I earn directly with their hedge fund, it gets me access. Or, oh, I know that the owner of the team is friends with the CEO of Nike and I might be able to get a shoe deal. There's some level of just doing business above board that's probably acceptable.

37:18But is this a blurry line? How defined is this? How clear is it to you? So two things to know. One is that this is a cardinal rule of sports in which you raise a very astute point. If you are LeBron James, it's kind of insane. No disrespect intended to the latest person who got bidded up between, you know, meta and open AI and Anthropic or whatever. No disrespect. LeBron James is probably thinking to himself, why can't I make$100 million a year? Yeah. This salary is capped. And if you have problems with that, I get it. Sports is a fun mix of socialism and capitalism that is convenient, typically, for the owners of these teams who are wealthier every time you check the news.

38:00So point A, well taken. Point B, though, is that it's a cardinal rule of sports, meaning that sports is one of the few places where your spending power is not automatically supposed to let you just buy whatever you want. This is how big markets and small markets ostensibly get to some level of parity. this is how and this is debatable of course we're getting into more philosophy than i expected but it's a fair point it gets into the question of like what's actually moral and not what steve ballmer did given that blurriness around the ethics of it was violate and really um i would say blow past any semblance of plausible deniability that hold on i thought this was something that we could do here and i say that because according to the nba's investigation and my own this was not merely a scheme that he ran to funnel money with one company aspiration he did it with four he did it with the scoreboard manufacturer multi-million dollar deal for kawaii lennard to do nothing he did it with the insurance company locked in insurance which was the insurance company on the build out of the intuit dome he apparently did nothing for that and he did it with and this is a fun one boingo wireless oh yeah which you may know as the wireless provider of Los Angeles Clippers.

39:20And the thing you say to yourself, do I really need to pay for Boyd N 'Longers? Yeah, I'm like, oh, they don't have Starlink. Which is my personal review of the product. So when your original story broke, you got a bunch of pushback, even from a bunch of people that are pretty tapped in and knowledgeable. And some of that pushback was just that there's no way that Balmer would be this dumb, right? So this story couldn't possibly be true, because who would ever risk it all in this way? Is that somewhat accurate? I think that's even the most generous defense. I think there are a lot of people who are just being told by the Clippers and Balmers, Crisis PR handlers, this weird podcaster is clout chasing.

40:05None of this makes sense. Steve would never do this. He's Steve Balm. The less, I think, surprising version, though, which you just articulated, is a common one, which is he can't be this though. And I dare say that one of the things you learn when you investigate financial impropriety in our great country is that that is something that you should never assume. There are many phenomenally successful people who because they are desperate to get the thing they can't just buy do things that they think will never get found out. And the problem in this case across these four companies and across these employees and across my reporting is that he trusted people that he should not have trusted.

40:53And also he maybe shouldn't have tried to do it in the first place. Isn't there one weird trick that would have made this all work, which is just Balmer goes to Boingo Wireless and says, yeah, we got this deal. It's expensive, but you will get some Instagram posts. and then Leonard actually follows through on some of the promotions and it's fine? Yeah, would that have been enough if he was actually— Even if he was paying top of market for CPM, it could work. Yeah, if he had actually carried out the endorsements, would that have been enough? Yeah. Or is that still crossing the line? So I've debated on my show, literally Mark Cuban, about this whole story before it became obvious what this was.

41:33And I appreciate the apology he gave me on Twitter yesterday, genuinely. Cool. But there's a Shark Tank episode we could do, just like pitching ideas for how to circumvent the salary cap that would have worked. and I think one of them, by the way, just to play that game briefly, it's like telling Kawhi Leonard about crypto. There are untraceable flows of money that I am told are reliable at this point in the calendar that you can use. That's just one example. But what they did was actually almost too clever by half. What they really did was they created fake jobs for Kawhi Leonard and fake consulting agreements, consulting fees for the companies.

42:10So they were trying to create separation a familiar term in the investigation of financial propriety but they're trying to separate where the money was going from a to b to c the problem was that everybody in the course of doing it people they trusted left a trail of paper as well as testimony as well as a lack of rational explanation as to why this existed if you never were to announce the deals and kawaii and this is the great comedy that is sports in which salaries are capped but egos are not kawaii leonard kawaii Hunter said to everybody, I'm not doing a single thing for these off the books payments.

42:45I am not doing work for them, but I want them. And Steve Ballmer said, got you. We'll make that work. And because these deals could not be explained as endorsements because he literally never endorsed them, it became this comedy of errors. That's very, very odd. Let's get to the punishment. What's been your reaction to Kawhi got a$700 ,000 fine, doesn't feel very significant, at least compared to the actual payments and what was received. And then you have a one-year ban for Balmer. But what was your reaction to the verdict from the NBA? Yeah, this was the biggest punishment for an owner in the history of, I think, American professional sports.

43:37and the NBA took five first round picks, which is the most you could imagine. They took$30 million, which is a rounding error, of course, for Ballmer. They made him pay the$50 million legal fee to walk to Lipton, the NBA's outside counsel, which is also a rounding error, but still pretty annoying, I would imagine. But the real thing that I thought was meaningful was that they banned Steve Ballmer from his own building for a year. He loves basketball. He sits courtside. He measured literally the toilets at the Intuit Dome when he was designing the whole building. He was a micromanager who knew everything about every piece of the building.

44:16And they banned him from being inside his own building, which he funded for$2 billion privately to his credit. And they also banned his president of business for a year. And they banned his GM, his president of basketball, for six months. And so Kawhi got effectively a slap on the wrist. And that is wild on the merits. The reason they did it briefly is because when Balmer now is rattling his saber, because he is the former CEO of Microsoft, who when presented with antitrust findings by the literal federal government, also fought, right? This is unsurprising if you know the trajectory of his life.

44:54What he has threatened is litigation. And what he has not been able to pursue is arbitration, which is interesting. The arbitration, briefly, in the world of sports court, which is another TV show we should pilot together. In sports court, you have an arbitrator, a system arbitrator, but that is an arrangement between the player, Kawhi Leonard, and his union, as well as the league. And when Kawhi Leonard got a slap on the wrist, only$700 ,000, no suspension, no voiding of the contract, no nothing, he agreed to a settlement that was quite favorable. And the question was, why? Well, Kawhi Leonard's settlement meant that the arbitration option was legally removed.

45:37So now they boxed in Ballmer, which is, again, no small thing. My reaction was it's no small thing to be at war with a guy with$145 billion, depending on Microsoft stock, and to say you got one move and it's to enter yet more discovery. Yeah, he doesn't want to be discovered. Yeah, it sounds like a nightmare situation for Balmer at this point to get more of the details out. There's more. There's more. So your read on it is he just has to basically accept the consequences and get to watch as a fan for the next year. But how much does this set back the Clippers? uh like how impactful you know in many ways like he tried to cheat his way you know a couple steps forward but in the process of that set the team back like basically took the team out of probably contention for i want to say a decade like what what what player would want to go to this organization now knowing that they're not going to get any first round picks for the next five years like it just feels like a really tough situation the next clippers first rounder that they will be able to select hasn't even sniffed puberty yet like we're just in a timeline that is a nuclear winter kind of feeling if you're a clipper fan but i want to say that at a certain point perhaps things get so bad that sort of things almost need to reset and so actually the thing i'm wondering aloud with you guys is as we contemplate what is Balmer going to do next.

47:22He has now threatened personally with litigation, Adam Silver by name in a letter through his lawyers. He is signaling it is wartime. And we just gave you some of the stakes around what that would entail practically. But historically, if you're going to go to war with your sport and with the commissioner and with other owners, by the way, that's the sort of backstage politics of this. Adam doesn't do this as a crusade. He does this because he's read the room of other billionaires who own these 29 other teams if you're going to go to war with the other 29 ownership groups and the commissioner and the league and journalism and everything typically it stops being as fun for you yeah typically yeah and so does steve balmer even want to consider perhaps selling and taking a punishment that is a humiliation on one level, but also you know what the Lakers just went for.

48:16$12.5 billion. What could you make on the back end if money was a thing you cared about? That's another calculation. What does this do to the value? There's no way you could value the Clippers at least within 10 % of the Lakers, right? No. Doing back of the envelope math, They're not getting double digit. They're not getting eight figures. Sorry, excuse me. They're not getting 10 figures. What I think is interesting, though, is they're going to make more than people, I think, are prepared to intuit based on the fact that, intuit is a pun not even intended, based on how horrific this franchise has been.

49:05We're just at a place in sports where the scarcity is so clear that these are detached valuations from revenue. You know, again, there are a couple places in this world where that is true. You guys cover a lot of them. Sports, though, is on its own crazy ride that is getting divorced from the reality of things. I don't know. I think sports and the private markets are pretty naked at this point. but but uh i take your point no and by and by the way that's the story of the lakers and mark walter which we were also investigating my point being that they're not going to get 12 and a half they're not going to get 10 but for balmer it's a trade-off between what do you really want you have all of the money what do you want do you want to fight do you want to surrender do you want to walk away with something like your you know ego or dignity whatever i don't want to be too over the top here But like he has a calculation that is not a normal calculation to make is right now it's signaling that he's going to fight.

50:06Yeah. Yeah. Fighting. Fighting seems like a rough going to war with the with with you seems seems pretty rough. What do you feel like do you feel like this has probably been happening? Do you think it's possible that that Balmer like felt confident in doing something like this because it was happening at a larger scale? And if you actually look at a bunch of other teams, it's really much more widespread. And if you start looking at a bunch of these endorsement deals, there's definitely a better way to go about. You said you could have a whole show about getting around the salary cap. And I just have to imagine there's so much money involved.

50:49There's so much ego. If you own a team, you want to compete. You want to win. And I would guess that there's a bunch of other owners and GMs and things like that that are kind of a little bit nervous now because they may have done something similar or even at a smaller scale. I think two things are true. One is, by degree, lots of other examples of salary cap circumvention funneling money to players have happened, will happen, are happening. but the other thing that's true is that in terms of the scale and ambition and the paper trail and the sort of almost just like subplots nothing is quite like a story in which a guy who doesn't want to do anything who has zero discernible endorsement value even when he does something has leverage over the richest owner in sports who is willing to spare no expense almost literally to funnel money through four different companies one of whom by the way is a public company Daktronics that has now acknowledged in yesterday's earnings call that their CFO, according to him, is now dealing with an SEC investigation.

51:55So there's also a civil suit happening in LA court against Steve Ballmer personally by 11 aspiration investors about fraud. My point is there are lots of other examples about how to circumvent the cap that are, I'm sure, getting no attention and maybe we'll get to some of them. But in terms of what this one is, the reason it's the biggest punishment is because they found stuff that is singular in terms of all of the webs that it entails. And that is why it's still ongoing. But now the person that is most incentivized to uncover all these other salary caps or convention, you know, potential deals that have been happening is actually Steve Ballmer.

52:39Because you imagine in his war, the only thing that he's got his back against the wall he's sitting there thinking the only thing that i could possibly do to kind of clear my reputation is make it come out that you think he's gonna start feeding pablo tips yeah i i i would gladly welcome back checkable information from any source i also welcome the idea that maybe the biggest consequence of my reporting is that steve balmer becomes himself a podcaster and that would be something that i welcome as well that'd be fantastic final job once you have everything it's only you and the mic I will say based on what I've learned from your show that trajectory is also an increasingly common thing for a billionaire to do so perhaps we're not so different well thank you so much for coming on the show this was fantastic honor to have you congratulations

53:36it's a strange thing to say congratulations for a story that is ultimately quite sad and unfortunate it but um yeah credit but the craft journalist is on display here yeah it looks as always um comedy is when bad things happen to other people um so there are laker fans who think this is the funniest story in the world i do shed a tear for the clippers fans who are like yeah really uh again again this again another owner another owner that we might not anyway yeah uh last question is is it possible that he sells the Clippers and overpays for another team just to get right back in the game? Look, what he wanted from the beginning, what he was interested in, of course, because of Microsoft and geography, was a Seattle team back again.

54:26Now, I will advise this just as a podcaster to a potential future podcaster. I am told that one way to be approved to buy a new team is to not go to war with the 29 other ownership groups that will need to approve that. so just the consideration as he continues to examine contingencies that makes sense well thank you so much for coming on the show yeah thank you so much this was uh anytime guys we really appreciate it congratulations on on your overall overall run everything we'll talk to you soon anytime thank you goodbye let me tell you about the new york stock exchange want to change the world raise capital at the new york stock exchange up next we have mohit aran from syfin coming out of stealth live.

55:09Finally. How are you? Welcome to the show. Hey, thank you for having me here. Thanks so much for hopping on. I would love to start with a little bit of your background. This is your latest company, but not your first. Can you give us the career highlights thus far? Yeah, absolutely. You know, my last company was called Cohesity. And the one before that was called Nutanix. So I'm the founder of two previous companies. Both of them, fortunately, are doing north of a billion dollars in ARR. The first company is already public. And this one is Cohesity is yet to go public. So you had a tough time raising for a new company, I'm assuming.

55:58Sure, it was a quick round. You really had to do all the laps up and down Sand Hill, scrape together pennies to get this done, I'm sure. No, the round came together, I'm sure, pretty smoothly. But what were you laying out? I imagine it was like I've gotten to a billion of ARR twice. Here's the plan to get to a billion of ARR really, really quickly. What is the plan? What was the pitch? Yeah, the pitch was that, look, in my first company, I brought together or converged infrastructure. Yeah. In the second company, I converged data. I'm here to converge context for go-to-market team. Okay. Somebody had to do it.

56:40Somebody had to do it. I imagine with the connections that you've built through your previous companies, you can start up market with your go-to-market. Is that the plan? Are you thinking work with bigger companies, bigger deals? Or do you still want to scratch the bottoms-up itch, the smaller, more agile, early adopter crowd? What's the go-to-market here? You know, I'm very passionate about serving customers. I think the problem is all over the stack, both small companies and big ones. My sweet point is obviously going to be the big enterprise, but I don't want to leave the smaller companies behind.

57:25So it's going to be all of them. How do you think about the actual value that the product will bring to these teams? because there was a little mini boom cycle for like AI SDRs, which feels adjacent. And a lot of people were saying, hey, it's way too early to let any AI, even if you're wrapping a frontier model, I don't want it emailing my customers who I might have been golfing with this weekend, and you don't have that context. And so I don't want you embarrassing me. But it feels like that's where we're going. How do you see the process developing over time? Yeah, I focus on the problem. And the problem is something that we describe as the context gap.

58:11And I've seen this problem running my previous two companies, even pre-AI. We execute our go-to-market operations without enough context. Sure. The context is all over the place. It's sitting in multiple tools, people's heads, and it's not even accurate. It doesn't reflect reality. And we are trying to make decisions without it, right? And the way we try to do stuff is we maybe do a lot of meetings. 80 % of the time spent in meetings is to gather the context, not change the news, right? Gather the news, not change the news. And so this is a unique opportunity, especially with AI, to actually solve that problem.

58:50So how much, yeah, because I feel like if you were able to create an eighth day in the week and sit down the whole team and say, everyone dump everything into some voice notes and some shared text files, the frontier models can summarize and put all of that together. But it's really a data acquisition problem. And so how much of this is about enabling teams to do change management, the way things work, versus autonomously going and gathering data both? What's the actual solution? Yeah, the actual solution is all of that. So automatically gathering the data, making sure that humans are in the loop so that AI is not just hallucinating and putting garbage.

59:37It is also in helping people in real time, real time coaching and stuff where they can ask any question or know anything they want from the context. So the solution includes all of that. Well, it's a key lesson from the first company that you brought to the second company and then key lesson from the second company that you're bringing to this company. Key lesson from the actually both my companies, I would say, is it's all about the people. It's all about the people inside the company. It's all about the people outside the company, which is our customers. And so you focus on that, and the right things will happen.

1:00:13Bearish on AI. It's your third company, but it's your first gong hit here on TVPN. How much did you raise for this? I don't think it will be the last. How much did you raise? How much did I raise? $44 million.

1:00:32Well, thank you so much for coming on the show and breaking it down for us. Let's do it again soon. Great to meet you. I'm sure there'll be many milestones. We'll talk to you soon. Thank you. Have a good rest of your day. Let me tell everyone about Figma. Agents meet the canvas. Your AI agents can now create and modify your Figma files with design system context. You don't get a lot of CEOs, a lot of successful founders that say, you know what? It's really, it's not about the people at all. It's actually just the code. It's just the AI. It's just the AI agents. That's all that matters. No. It, of course, is the people.

1:01:02And we have a great person next. Often the best advice is the most simple. Lindy. Yeah, it's true. Well, we have Akshay from Pocket. He has sold over 200 ,000 of these devices. What's going on? We're going to show you what they look like on the screen. Welcome to the show, Akshay. How are you doing? Hey, John. Hey, Jordy. How are you guys doing? It's great to be in TBPN. I'm glad to have you here. We started hearing and learning about your company probably a year ago at this point. We're like, what's this company that's just selling a lot of hardware? Somewhat under the radar. I'm sure it doesn't feel like that to you, but you guys haven't really chased the spotlight as much as other companies that sell hardware that haven't sold any hardware.

1:01:47Yeah, I mean, the phrase in Silicon Valley, hardware is hard, don't go after it. It feels like AI has unlocked new opportunities, both in there's demand for new devices, and then there's also AI that you can ask to help you procure things and help you design things. But what has the road to actually building the first device, then scaling to 200 ,000 devices, been like for you? Yes, interestingly, we actually built an app before we actually built the hardware. And the simple thing was that, hey, it's the most obvious thing to do. It's the most easiest thing to scale, so let's just go build an app.

1:02:23And we built a Meeting Note Taker app, and we released it to a bunch of people, and there was not a lot of response. And being surprised, we thought to ourselves, hey, what about that device that we were all thinking about that we should go do that will be like a necklace? and that's kind of what we did with open source work at OMI. We went and did a bunch of Kickstarters and we printed a bunch of these devices and gave it to people. And we actually saw that people were using the device 10 times more than the app. There were a couple of other challenges regarding being always on and being available.

1:03:09So when I started Pocket, my first immediate thought was this should not be always on. People are still not comfortable. There's still dialogue that needs to happen before always on wearable becomes a thing. And we said, let's go build something that's a wearable for a phone. So the people on Wall Street are happy to use it. And it doesn't augment their style of their suits and coats that they wear. And that's kind of where Pocket came around. That's very cool. So, yeah, walk me through the current product, specs, price point, what the favorite features are, sort of like how you think about where you are now and then where you want to go.

1:03:50So currently, this is Pocket, and this retails for$129. The hardware comes with a freemium subscription, so you kind of get to do unlimited summaries, unlimited transcripts. You get three messages you can ask about your conversations per day. If you would want more, like speaker tagging, advanced speaker recognition, all these kinds of things, and advanced AI models for reasoning and summary agents that can make better details out of your summaries and have access to 300-plus professionally sourced templates like soap notes for doctors, case notes for lawyers, and CRM entries for salespeople. you can get on our pro plan for$20 a month or$200 per year.

1:04:38And that's kind of the whole product, basically. So the thing that stands out to me is you launch the initial app. You're not seeing the kind of growth that you wanted to see. And so then you're thinking, okay, the solution is to launch a hardware device. Let's turn up the difficulty level to 11. Normally you'd think, okay, the product's not working. add a hardware thing that functionally does a lot of the same stuff, it's probably not necessarily going to, I don't know, my intuition would be that it wouldn't solve the problem. But I keep coming, like, what is why? Why does it make sense for this to be a separate device from the phone?

1:05:17Because I'm sure, you know, if you met with investors, a lot of investors would be like, well, I have a device that's a hardware device. It has battery, it has a microphone, it has a screen has all these things so why are your 200 000 plus customers saying like no i want this i want this separate device because like clearly the customers are right yeah absolutely uh it's 300 000 now and uh right uh so when we actually went and asked these people like hey why are you using this 10 times more than the app that we had. We actually had one of the user who was actually using a different phone he just bought for recording conversations.

1:06:02And he also had a battery attached to the phone on top. So that's kind of what Pocket ended up being a product by just watching how people use these recording apps on the phone. There are a lot of limiting factors for recording on the phone. A, you cannot record your own Zoom meetings and Google Meet If you're already on the phone, you cannot start another recording. So there are a lot of people who have issues with that. And there are people who get incoming phone calls all the time. So if you're recording something and you get an incoming phone call, it interrupts the recording. And if you take the phone, your recording is stopping, essentially.

1:06:40Apart from all of these technical reasons, the real reason is actually that the people who take 10, 15 meetings a day, these doctors, consultants who are like, you know, patient goes out and their patient comes in, the client goes out and the client comes in and there's 10 to 15 back to back meetings. They feel awkward in the first eight seconds to take their phone and start a recording by unlocking their iPhone and setting up the recording and hoping so that the operating system doesn't kill background running apps for a long time. So people just felt that, this is a much more reliable thing, a quick access thing that can immediately start recording and I don't need to feel awkward on placing it on a desk.

1:07:23So people don't take their attention. Why is this guy looking at his phone? We just met. That's kind of what we came around that convenience beats intentions. So if your users have intention to record and you don't make it convenient enough, they will not record. But if you actually make it convenient enough to record and they want to record even a little bit they'll 100 record interesting should more people be taking notes with and recording their conversations oh yeah i haven't recorded a conversation in years yeah um but what am i what am i missing yeah absolutely i think like there are a lot of record recorded hundreds of hours of conversations through the show.

1:08:08We have people recording tens of conversations almost daily. Most of these people are actually field workers. Consultants, salespeople, real estate agents who are showing people homes that are noting down requirements. Places where note-taking is actually useful. For example, DoorDash is one of our customers. They use Pocket to go to restaurants for the salespeople to record their pitches and then come back to their HQ and sync with everybody else in a knowledge base of, hey, how did my pitch go with this vendor, with that restaurant owner? So I think there's definitely a use case for field note-taking, and that's kind of where Pocket comes and sits in.

1:08:56but yeah, I think in a broader sense your AI needs a lot of context about you to help you and every single time you essentially use Pocket, you can connect your Cloud, MCP or OpenAI's API and your ChatGPT already knows about all your conversations and you can pretty much manipulate all your transcripts and understand how people are talking to you and all these cues. For example, if you go to a VC meeting, the VC says a hundred other things. Like, it actually sounds so entrusted. Like, I felt they almost invested in the startup, but they never said the word invest. So the founders were going back thinking, oh, I have a term sheet or something.

1:09:43But the truth was, it was just a high. Yeah. No, no. I've seen that play out where someone comes away and they say, oh, yeah, this VC said they're going to invest. They tell it to another VC. They call each other. I didn't say that. And it becomes a who said it. Are you broadly bullish on new AI hardware? Because I think one of the reasons that people have been generally bearish is you've had the rabbit. You've had a friend. You've had a bunch of these shots and attempts. Humane. Humane. So there's been a handful that haven't got the level of traction that you have had. But given your experience so far, do you think there's a lot more devices to build that are AI native in the real world?

1:10:26I think so. And I think like, you know, Rabbit and Humane died so, you know, Pocket could live. And we learned a lot from all these other devices that essentially died. And they primarily died because they were trying to replace the whole smartphone game. Doing too much, for sure. Too much stuff. Yeah, exactly. And they were actually just going against going towards real world works. You know, the way that the workflows work for real people, you know, they don't want all the other things like ordering, you know, overeats from AI. All they want is like that AI to fit in their existing workflows.

1:11:05And what we did was like we looked at a lot of people, had a lot of meetings. And we didn't go into things like personal note taking, for example. all these others are like you know dead basically whoever went and did anything other than note taking and note taking was essentially a product market fit it was almost like fitness for for apple watch kind of product market fit and everything else was basically like people didn't want them yeah yeah i when i saw rabbit r1 i never got a chance to actually use it but i was thinking like it's so it's such a beautiful design i thought it would be perfect for kids where if they're just going around taking some photos and learning a little bit about the world.

1:11:46And I actually wound up buying a different product that's a circular device with a screen and a camera on it, and it has little games where the kid can go and it'll say, like, find something flat, find something round, and they'll go and find it. And then that other company, Stickerbox, that we've had on the show is doing really well in what I would call AI hardware. But you push the button, you say a prompt, and then it prints a cartoon for the kid, and it makes a little sticker. And it's these like very focused things that have, it's just, do you want this at this price? It'll do this for you.

1:12:17It makes a lot of sense. What are you doing or what do you need to do on the regulatory side? Because I imagine if it has a radio in it, it needs FCC approval. But you mentioned the medical discipline and HIPAA. Is that relevant to you? How have you solved that problem? Yeah, so we're HIPAA compliant and we essentially have HIPAA compliant servers that we run HIPAA workloads on specifically for medical use cases. And yeah, like from day one, we thought about being HIPAA compliant and SOC to compliant for enterprise as well. So FCC is definitely like if you're making a device with Bluetooth, radio, you pretty much need FCC.

1:12:59So from day one, you would need that as well. So, yeah, in terms of like, you know, consent is what comes up, you know, most of the time for these kind of recording, you know, devices. And what we did with Pocket was we said we would like to bring the risk level down to almost a user action. So everything happens with a user action. So you're supposed to like tap a button to start and stop recording. although it might be a friction step to this but we would love for the user action to be the risk level where we are for Pocket so everything starts with the consent of the user at least it starts with one party, one state consent and then it's on the user to basically ask for other people's consent and surprisingly not that people actually are very open when you actually ask them to record Sure.

1:13:58And and they're actually happy that you would share the transcript and the meeting notes of recording. Sure. Sure. Do you think you'll ever launch something like a coworker agent or assistant functionality? Is that because because I imagine if you can give your device a bunch of context, hey, I want to do this thing. Eventually, it could get to the point where you can send off tasks in the background that the user can check on maybe on their mobile device. Yeah, so that's actually our roadmap in the next three months that we would actually like to build agents that would actually take context directly from your conversations and actually act on those.

1:14:37Make reports, make docs, PPTs, presentations, slides, all kinds of things from your meetings. So this is increasingly becoming the regular workflow from all kinds of consultants, sales pitches that people take the conversation and make slides out of them and come back for the next meeting. So we would love to make an interface for that in the next few months. How do you think about picking different AI models for various pieces of the workflow? Because I can imagine that you're selling something pretty valuable. So cost might not be the most important thing. At the same time, you can just wait and things get cheaper often.

1:15:20Switching from one model to another might inject like a different flavor or vibe sometimes. So how have you thought about this? Are you fine-tuning your own models using open source, bouncing back and forth between whatever frontier models are available? What's your decision criteria right now? So surprisingly, we have the highest margins in the industry for AI. I can imagine. Probably 75 % margin in topical terms, essentially.

1:15:52We do this with different kinds of routing. Oh, okay. Yeah, so we have our own version of Open Router where we essentially route to different kinds of providers and models. Okay. We use a section of open source for transcription because people love to choose what model they would like to use for summarization. Oh, they do? Okay. Yeah. So transcription is pretty much left to us. So we do it on ourselves. So that's kind of why our margins are super high because we get to use whatever we like. And we use our own models that are fine-tuned on top of OpenAI's Whisper. because a lot of these online models were trained or YouTube datasets like WogCeleb, which are extremely clean datasets and work really well for Zoom meetings and meetings of online note takers.

1:16:49But when you come for offline, there's like a train going next to you. There's a bunch of things happening. So they actually go crazy when there's like an offline recording. So we need to fine tune for them to work for offline reporting, essentially. That makes a lot of sense. Thank you so much for coming on the show. I forgot that I am a featured customer on the Zapier blog from 2015 because I developed a workflow that would record all of our conference calls, send them to a human transcription service, and then upload the transcription into Google Drive. And then you could search by keyword just using Google Drive search.

1:17:36Nowhere near the power level now. Interestingly, Y Combinator actually currently uses Pocket to record all their interviews and send them to their online systems through our APIs. There you go. Very cool. Well, congratulations on the progress. Thank you so much for coming on and breaking it down. Love the approach. Have a great rest of your day. We'll talk to you soon. Let me tell everyone about Railway. Railway is the all-in-one intelligent cloud provider. Use your favorite agent to deploy web app servers, databases, and more, while Railway automatically takes care of scaling, monitoring, and security.

1:18:10Who we got next? Our next guest is Hari from Aura. He's the founder and CEO with a great update for us. How are you doing? Welcome to the show. Hey, guys. Good to see you. Since it's your first time on the show, would love an overview of the company and yourself, and then we can go into the actual news. Sure. The company Aura were in the consumer security, consumer safety space. So basically we thought about all the various different ways that a family could get impacted by using services online, scam, spam, transaction fraud. All the way from that, all the way to making sure that if you have teenage kids, for example, if they're using devices too much, We have the ability to kind of figure out how best to sort of guide and navigate them around digital detox, et cetera.

1:19:01So, yeah, that's the core of the product. And I've been an entrepreneur my whole life. This is my third company now. Awesome. How big is the problem? Because now that I'm thinking about it, I mean, we were just at CrowdStrikes Falcon on Tuesday. And we heard that phishing open rates, phishing email open rates have jumped from 12 % to something like 60 % in the AI era. And when I actually go back to the number of cybersecurity scams, I have just as many examples of friends who thought that their grandmother was asking for gift cards as I do in a corporate setting. And so how prevalent is this? What's the data that you monitor to understand the scope of the problem?

1:19:44Look, I think that over the years, both the breadth of the problem and sort of the number of people it impacts has gotten astronomically bigger, basically, where certain scams used to be, I don't know, a few thousand dollars worth of scams. Now we see that's gone up to like$25 ,000 per scam on average. the incidence rate is quite high because now that there are a lot more AI based tools the bad actors also use the same tools to do deep fakes, to do ID theft with a lot more data out on the dark web that ends up becoming a precursor to basically being able to use that to do nefarious things to families and I think the other big thing is if you thought about kids where when I was growing up we weren't native to phones and native to online services.

1:20:32My kids, I mean, they are digital natives, so they basically are on their devices all day long, which means the incidence of them putting information out there is just much higher. And so as a result, there's just more and more and more of this happening, which is pretty scary. Talk about the recent hack leak. There was some ID verification service that had a breach, and I think from what I could see, it seemed like half the people in the U.S. were impacted, something like that with their now image of their ID out on the web. But break down the breach and then what people should do. Yeah, look, I think starting with even a couple years ago, there's the NPD breach, the national level sort of social security number, etc.

1:21:17Now there's a lot more ID, digital image theft, etc. I think the key thing I would say is the incidence of these is so high now that when people hear about it, you just start kind of immunized. You're like, okay, well, whatever. I'm sure my data's already out there. It's what's going through people's minds. The trouble with it is this is just an early tell for the next set of things that are going to start happening. So, for example, at Aura, we have a fully trained foundation model that is looking at sequences of stuff. Hey, what's the first thing that happens? And what's the second thing that happens?

1:21:47What's the third thing that happens? And how can you analyze risk with systems? and we see that with data breaches and information getting out on the dark web is a pretty early and good tell. If it's happened multiple times, you see that the incidence of actual identity theft is bad at the back end. So the very tangible things I'd say, monitor your credit, make sure that you're looking at your credit card numbers and statements, don't wait for the whole statement to show up. If you start seeing odd things on physical mail, keep an eye out for that as well. We've had even weird situations where people have stolen information and it gets sold to folks for physical crimes as well.

1:22:27So we see a lot more intersection of physical and digital happening a lot more these days as well. Interesting. What does the industry side of the business look like? I imagine that as you're protecting homes, schools, individuals, identity theft, there's the flip side, which is if I'm a business, I don't want someone purchasing with a stolen identity and having a clear communication line between those two parties probably makes sense. But what does that actually look like in practice? I think that's a great question, right? Because if you thought about your own life or me, the surfaces I spend time on are my home, my workplace, and a parent as a parent at my kid's school.

1:23:12So there's a lot of data that kind of goes across that stack. And even more than just, are you using a nefarious card for purchasing something from me? Even more basic than that is a lot of the enterprise scams, like the ones you were talking about, even with Falcon, for example, many of those originate on the consumer side. And many of the breaches that happen on the enterprise side is social engineering attacks anymore. So it's basically going through people who are employees and then kind of using that to get into the enterprise. So on both those pieces, I think getting the consumer to be more aware of these issues ends up becoming pretty critical.

1:23:49We see a lot more overlap now where we do sell our product through large enterprises as well. And so we talked to a lot of sisters of big companies. And the feedback we get is, look, the lines are very blurred between what's at home, what's at work. and so even besides sort of the loss prevention piece of it, which is, hey, you use a fake credit card to buy a product, it's even more imminent that they want to make sure their enterprise is kept safe and sometimes keeping the employee safe is the best way to do that. Yeah, yeah. How much time do you spend working on streamlining onboarding? When I think about these security products, we've talked to the CEO of 1Password, a fantastic product, but onboarding can be like a stumbling block for people that want to secure their life, secure their identity, but the actual integration of getting deep into all the accounts, collecting everything, making sure that everything's set up properly, that can be a hurdle.

1:24:48I imagine that you have low churn, but the conversion to, I heard about this, to actually I'm using it properly, has got to be a hurdle. How much are you focused on that? We spend a lot of time on that. Time to value is a huge metric for us, which is how quickly can you get the customer to something of value, basically. But I'll say two things. One is, the way that the industry works today, if you thought about a product you bought for either of you guys, it's going to look the same. Like you buy something to keep your identity safe, or you buy something to keep your passwords locked up, or even something for kids, for example.

1:25:25that the solution doesn't really understand or know you. It knows the problem, right? And so one of the things we have done, which is very different, is we're probably the only product that puts the actual family at the center. So there's actually a large sort of family graph that maps out all of the relationships for people. Who are you? Who are the people that you sort of connect with? And then all of the reasoning and the inference systems that we run on top of that have good ability to have a view of you end-to-end, which means that when you go into onboarding, we can do a better job first getting you on board and then as we're watching and observing we want to make sure that uh that um you know you it's very personalized for you and your digital footprint we have a massive gong here any any recent revenue milestones or growth growth milestones you could share that we could uh use to hit this gong for you oh yeah sure we uh we hit we're about 340 some odd million of uh error so

1:26:26Thank you. Thank you. Not too shabby. And thank you so much for coming on the show. Yeah, great to see you on the show. Have a great rest of your day. We'll talk to you soon. Take care, guys. Let me tell you about public.com. Investing for those who take it seriously. We've got stocks, options, bonds, crypto, treasuries, and more with great customer service. GPT-6 Astra has landed. The blog post is up. You can go check it out on openai.com. To the stars. To the stars. And the headline, I believe, good performance on a bunch of things. But the RKGI 3 number is crazy. The score is 99.9%. So it feels like they just beat that.

1:27:08They just beat RKGI V3. So that's the video games, the ones that Tyler was briefly. Globally ranked. Globally ranked. You're out of a job, Tyler. Say goodbye. Hang up your RKGI V3 hat. Don't worry. The team over at ArcGi is working on V4. We're going to move the goalposts soon. We're going to move the goalposts soon. But this is very impressive if you've played around with ArcGi V3. It requires some real creative thinking to actually learn how the games work, how to be efficient. What else is sticking out? Has anyone been able to monitor the timeline at all? Very chaotic launch, so I think it's hard to get a real reaction yet.

1:27:53Tyler, what are you seeing? Yeah, I mean, there's still no actual post on OpenAI's X account. It's just a blog post that's now live. But, I mean, there's a bunch of benchmarks in there that are... Yeah. Terminal Bench Science, we're going over into the world of science. GPT-6 Astra scored 64.6 % on reasoning effort max, cost$26. 26 bucks uh i'm sure there will be a lot more also the uh exploit exploit gym honeypot lower is the better gpt6 astra zero percent so good performance there uh the world's best computer use model i'm putting that to the test asap let's see if it can 1v1 me on rust because if it's good at using the computer it should be able to no scope right that's the bar that's where my goal posts are.

1:28:41Agent's Last Exam, good performance. So you can go check it all out. Sam is going to be on Bloomberg in just a few minutes over with our buddy Ed Ludlow. So that will be fun. So we'll be digging into this and we have some special guests lined up to talk more once we've been able to digest, take it for a spin and have a lot of fun with it. We have our next guest joining in just a second. But first, let me tell you about Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds, online, in-store, on mobile, on social, on marketplaces, and now with AI agents.

1:29:17Very exciting. We have two guests joining at the same time, Matt Caldwell and Jordi Leiser from the Minnesota Timberwolves and Lynx and Jump. They're both CEOs, and we're going to have them both on at the same time. Uh, let's, we need to check in on, uh, Ed Zitron, see what his reaction to Astra is. Is it any better or is it just more of the same junk? Because he has, he has, uh, he has been a bear for a long time. Uh, he's coming up on, coming up on the three year anniversary of the bear posting. Uh, Dan Liu has collected all of Ed Zitron's position. You think he has sort of a gambler's mindset, like 80 % of gamblers quit right before they're about to hit it big?

1:30:02Yeah. I think it's just an entertaining shtick. It gets views. Kevin Roos, formerly of the New York Times, now independent, hard fork co-host, who's writing the AGI Chronicles on sale October 10th. he says anyone who has interviewed Ed Zitron or had him on their show in the name of AI skepticism has made their audience dumber and less prepared for what is actually coming wow that's a crazy thing Eric Newcomer chimes in and says it's his audience they follow him around which is interesting because I believe Eric's best episode of all time was with Ed Zitron and he was like the Ed Zitron fan base like stuck around for a couple more episodes and was like i don't like this guy i don't like this at all i don't i don't want reason wait reasonable takes and eric of course is i don't want to see both sides eric's skeptical sometimes he's optimistic but he uses these and he doesn't he doesn't believe that it's like a rs rsc says when you ask ed zitrum why he keeps writing all his predictions are when all his predictions are wrong and there's a quote from dion waiters i'd rather go zero for 30 than zero for nine because you go zero for nine that means you stop shooting that means you've lost confidence that's pretty good i like that well speaking of basketball we have the ceo of the minnesota timberwolves matt caldwell here with us and jordy leiser joining as well welcome to the show what's going on how are you doing great hey guys see you great to have you uh thanks so much for hopping on um i would love to start with the news can you both uh introduce uh how this all came together and the various roles that, how you guys see yourselves working together.

1:31:49Yeah, Jordy, you can kick it off. Yeah, well, great to meet you. Thanks for having us on, big fan. What you guys have been doing here. Basically, I started this company, Jump, with Mark Laurie and Alex Rodriguez. I think you had Mark on, actually. Yeah, we did. You also had Alex Mohanian, one of our boys with Jump, too. Yeah, nice. I love him. Yeah, so the whole theory was that Mark and Alex are going to buy a team. And if they were going to buy a team, these guys are not sort of in the business of doing things the old way. And so buying the team, actually, I just saw the Shopify plug. We're trying to do for sports teams what Shopify does for merchants, which is basically totally unlock the direct to consumer proposition for a sports team.

1:32:32And so Matt was hired, you know, right when Mark and Alex took over the club. And so we got to know each other and then we were able to launch our platform in the NBA with the Timberwolves, with Matt, who's an unbelievable leader in sports executive under the ownership of Mark announced when they finally took control of the club. Yeah, when you think back to sports ticketing generally, just the different eras of technology, the risks, what they unlocked, what do you draw on as things that organizations got right? Any organization that jumped on waves early and saw success? What are you pattern matching against when you think about where you want the team and the organization to go from here?

1:33:16Yeah, sure. Thanks again for having me on. But, you know, listen, traditionally teams outsourced ticketing, right? If you look at it from a team perspective, like there's a lot of work to be done. You try to win games, you're signing players, you're marketing the brand. And, you know, to create your own ticketing system that's, you know, transacting and selling season tickets and single game tickets, you know, it's a lot of work. You know, Ticketmaster has built a great business on this with both concerts and sporting events. And, you know, I think in the last 10 years or so, teams are saying, OK, we have a lot of season ticket holders, but we don't really have data on people that just come to like one game or, you know, pick up a couple of games during the year.

1:34:04And, you know, when all that data is outsourced to another provider, you know, it's hard to figure out the behaviors of that fan and how do you market to them? How do you make them a season ticket holder? You know, essentially just grow with that fan. So, you know, what Jordy has done with, you know, Mark and Alex, you know, built a ticketing system that's in-house, you know, that, you know, when someone goes on our app now and, you know, traditionally we've had like our schedule and some content and highlights on the app. but now you can just scroll and buy tickets on the app. You don't even know that you're on Jump's platform.

1:34:38It looks like the Teams app. So it's a way to have the data on your side of the table, on your app, and you're working with a great partner with Jordi and Jump. So how do you think about actually scaling the marketing now that you have more data, more of a direct relationship? I've thought about times when I've gotten invited to a sporting event and my friend might have bought all the tickets, occasionally they'll say, oh, to get in, you actually have to download an app and claim the ticket and then you'll have it on your phone. And then I should be getting retargeted to return the favor. Maybe I should buy them a round of tickets next time.

1:35:20And I have probably been served a few, I don't know, in one ear or out the other with this stuff. How do you think about building your marketing organization internally? Shopify has some buttons where once you're set up, you can just say, hey, I run some Facebook ads. You're at a much larger scale. How do you think about the rest of the organization internally executing this strategy? It's a great example. And traditionally, the experience you talked about, your friend transfers you a ticket, you download Ticketmaster or StubHub, SeatGeek, all that data, that person's information, cell phone, email, all stayed with the third party.

1:36:00Now we're getting access to it. So we can have our sales staff call them. We can have automated emails going to them. We can go visit them in their seat. You know, we know someone came in, we know their name. But, you know, something that's really helped for us, you know, going to the next level is, you know, we've gotten to the point with Jump where, you know, even if someone puts like a ticket in the shopping cart, you know, but doesn't close it out, or even just browses over a game, you know, we get that information, we get an automated email to that person, hey, these two tickets are still available.

1:36:31Or even better, hey, those two tickets were just sold, but there's two other ones that are similar. So you just have just more engagement, especially with, you know, whatever I call the casual fan, single game buyer. Like our season ticket holders, we know them really well. They sit courtside, they're in suites, you can visit them at the games. Every season ticket holder has their own individual concierge, sales rep. But it's the people that, like yourself, got transferred a ticket, come to a game. We want to make them long time fans and now we just have so many ways to reach out to them now i went last last time i went to uh i went to an nfl game and i swear i had to download three apps to get the actual ticket and i'm like i hope i got all the apps i need to get it to use my ticket the parking hot dog app and it was a free ticket too i was like it shouldn't be this hard um uh how are you It's a lot of work.

1:37:24Yeah, a lot of work. A lot of work. Time is money. I was committed, though. Jordy, how are you thinking about, like, using this to deepen the, like, fan engagement, knowing Alexis, like, he's, you know, obsessed with collectibles. I imagine by having that direct relationship, you can unlock, you know, different products and things like that for fans based on their actual engagement with the team so that, you know, fans have to actually, like, earn certain things. But where what does that look like? Yeah, I nailed it. And actually, this hits the problem of, you know, the three apps and the new login and the Lakers do some deal with some startup.

1:38:00And then you got to create a login for that thing to like it's just the whole thing is just one Frankenstein tech stack, you know, mess. And so, again, Shopify is the best comp. Like it sort of consolidates that into one seamless experience. Then everything else plugs into you. so in that same thing collectibles merch concessions add-ons parking you should have you know the timberwolves login the timberwolves account add to cart cool jersey add to cart cool collectible oh hey i know that you you are a season ticket member and you came to you know kg's coming back for the wolves this year it's a big part of the story so they should know that these people who were there during the kg era you know it's not just that they know the crm like we know bob smith and we know where he lives and we know it's like did bob go to those games was bob you know kind of there during the era and then you can nudge and you can you can sell and you can upsell and you can engage and so it's content yeah it's merch it's media it's everything sort of in one system are you thinking about cross-selling across different sports when i think about the shopify example uh they've launched the shop app you know you oh you bought this pair of boots.

1:39:10Maybe you want this pair of pants. Is there a world where you bought this ticket to a basketball game? Here's, you know, it's the off season. Here's a football game or a baseball game. Is that something that's a little bit more, that's a little more of the market. That's kind of the marketplace model that, you know, that's the, there's a bunch of ticketing marketplaces. Sure. There's YC versions of that and there's stuff up. And I think that that's the thing that, you know, Jordan, you were saying, it's just kind of the beginning of the mess of this whole thing where if I want to buy, you know, Delta Airlines, like if I'm going to fly on Delta, I get the Delta app, you know, everything about me.

1:39:44They went direct to consumer 20 years ago. And like, that's, that's it. And so I think that's the missing piece in tier one sports at least, but it's really like, if you're, if you're in Minnesota, you've been to a Wolves game, Hey, let's kind of like get to know you as a Wolves fan, just like you were, you know, a customer of any other brand. Yeah. How sharp are the elbows of the, of the other players in ticketing? I mean, I can't imagine they're thrilled that a, a platform that's allowing people to go DTC popped up with a bunch of backing. What do you think? That's the question. Well, knives right here.

1:40:17That's the question. But yeah, it feels like something that's so aligned to the team, so aligned to the fan, it's just misaligned with the legacy players that no one actually, I think, likes. Yeah. Well, that's a great question. If you're investing in startups, Do you want to invest in a platform that is beloved by its customers and beloved by its customers' customers, but not beloved by the 50-year-old incumbent? I kind of like being on that side of history, and I feel like we're in a good spot. But at the end of the day, I mean, I'm in Los Angeles. Thank you guys for here. This is a town that just – and you're in this space, sports, entertainment.

1:40:58I would say also in the team owner space. The headlines are pretty wild recently. Yeah. it's just a lot there's a lot of going yeah i was gonna say i don't i don't you know we're not super tapped into to the industry but i was gonna say if you do any endorsement deals with athletes make sure they actually endorse the company uh just that's what i've learned we had pablo on the show earlier uh and i that was one takeaway you know make sure they actually talk about jump and and what yeah well no that's that's matt's that's matt's point yeah no comment What else is happening in the world of technology and sports that you're tracking?

1:41:37I mean, AI is getting slapped on everything. And I love this story because it's just a very clear software enablement, like the actual relationship. It gets to the core of a business problem that you're trying to solve. And then there's technology that is really powerful, but it's maybe a little bit further out. But what else are you harnessing at the Timberwolves that you think is interesting or you're starting to explore us? Talk to us about technology's role over the next year or decade. Yeah, Matt, go ahead. Yeah, I mean, the first thing that pops to mind for me is the pricing of our tickets.

1:42:19If you think about, let's call it 20 ,000 seats in an arena, maybe half of them are season ticket holders, right? So you have 10 ,000 seats that you're selling at least 41 nights a year. And if you have a manual process where you have different price codes and there's supply and demand in every couple of hours or every day or so, you're updating prices and there's transactions happening, you're missing out on margin. Or you're missing out on lowering pricing for a certain game and getting more people in the building. So, I mean, AI is going to explode sports, just like it's doing for every other industry.

1:42:58And, you know, to be with someone like Jordy that's, you know, very AI forward, you know, our pricing has gotten so much more better automated, you know, pushing revenue. And then we talk a lot about open distribution, you know, with all these different ticketing systems. You can imagine, you know, there's some tickets that are on Ticketmaster, SeatGeek, StubHub. They're all kind of spread out. You're not getting the full marketplace looking at your tickets all at once. So what we've done with Jump is, you know, any ticket we put on the Jump platform, let's say a single game ticket in the upper level, that same ticket is now being put on Ticket Masters, TM Plus, secondary market, Steve Geek, all the secondary markets so that you're getting all that demand, all those eyeballs looking at the ticket.

1:43:50and hopefully driving up pricing if the demand's there. And that's not possible in the old way because obviously Ticketmaster wants them on Ticketmaster and SeatGeek wants them on SeatGeek. And so our model is like, if you've got AirPods, they control the distribution. Apple says, I want some in Best Buy. I want some at Target. I want some Amazon. We give the teams the total control to distribute and that's a totally different model. Our head producer, Ben, from Minnesota, he just texted us and said, I actually bought wolves tickets last night using jump. It was great. All right. Two thumbs up.

1:44:24That was my plant. That was my plant. Yeah. I texted Ben. I saw on your feed there was some drop about a little bit of a little bit of a negative vibe about maybe the wolves won't get all the way to the other side. I saw that recently. I didn't want to call it out. But since you mentioned it, like, what's going on with that? No, Ben's a fan. Ben looks confused. He's a true fan. True fan. Thank you so much. Yeah, great to meet you guys. I love a business that just makes so much sense. You guys were probably feeling out this idea. It's like, is there a reason this thing doesn't already exist? Seems really obvious.

1:45:03Seems really aligned to everyone involved. So very, very cool. Great to meet you. Thanks, guys. Thanks so much. Appreciate it. We'll talk to you soon. Let me tell you all about Cisco. Critical infrastructure for the AI era. unlock seamless real-time experiences and new value with Cisco. To death match. Up next, we're heading to the portal. We've got to get to the bottom of this. Ben, actually, this is true, Ben, you bought Wolves tickets last night using Jump? Yeah, yeah. Okay. Yeah, I did. It was great. Wait, are you a Wolves fan? Yeah. Okay. Why the hesitation? Not huge. Not huge? It's a surprise for someone.

1:45:41Oh, okay. Oh, sorry. Why are you watching? Okay, edit that out. It's not like it's a live stream or anything. Anyway, I believe we have our next guest already here, so let's bring in Jeff Thornburg from Portal Space System. It's portal time. How are you doing? Fantastic. Great to have you. Thank you so much. Let's start with the decision to start this company. I mean, you have experience from SpaceX. What was the original thesis? What was the first prototype pitch deck? How did you even begin this journey? So many things, but I think the simple answer is after over 30 years in the space business, I had a lot of colleagues in the defense side that was really struggling with how do they combat adversarial advancement on orbit.

1:46:38And we're running our spacecraft like hot air balloons, and they're running theirs like fighter jets. And so we really set out to build the fighter jets for orbit here at Portal while also allowing more space exploration for NASA and the civil space community. What is the benefit of being able to maneuver in space generally? I mean, we've seen the trajectory of traditional rockets, ballistic missiles. Seems like a lot of stuff can happen in space, whether it's the Starlink constellation or the International Space Station. None of that required too much maneuverability. Why maneuverability? Why now?

1:47:15Well, you've all seen the movies, right, where the the adversarial country runs out in the field and covers their stuff with tarps because they know the satellites coming overhead to take pictures. And and so most things on orbit are very predictable. And, you know, to mix it up, we used to not have any real competition on orbit. And now guess what? China and Russia are challenging us on the defense side. And, you know, we don't want people throwing tarps over stuff. We want to show up and do the things we need to do when we want to do them and not be constrained by the lack of fuel in the gas tank on orbit.

1:47:49And a lot of the ways this has been looked at in the past is it's like you went to buy a new car and you throw that new car away as soon as you use the first tank of gas. And, you know, we really set out to build platforms where gas is not in the equation anymore. Use it, move it quickly. you know there's some generals out there that have this phrase i really love where you know we drive our spacecraft like we're going to church and our adversaries drive them like they stole them and and and we really want our customers to drive them like they stole them and that's really what built the foundation of the business five years ago i love that so well yeah what has progress been like over the last five years uh is this are you at manufacturing stage is this prototype level.

1:48:32I imagine that you got to actually send stuff up to at least low Earth orbit to really test the capabilities. But what's the progression been like? Yeah, I first have to really give a shout out to my team because none of what we've done would be possible without them. And we're about 60 people now here north of Seattle. And the progress has been amazing. I've got to work with some amazing people over the years. The biggest compliment they've given to me is wanting to come back and work with me again. And we were able to launch our first mission to orbit in March and successfully test a lot of our electronics hardware for the brains of our systems.

1:49:09And then we just finished our first small Starburst spacecraft. It's about 600 pounds that's going to go up and really demonstrate our ability to do some of the things we just talked about. And that's going to launch October 19th. So the team has been grinding for the last several weeks to get ready to ship to the Cape. And we're going to do that in the next few days. And they couldn't be more excited or more fatigued all at the same time, but they're doing a fantastic job getting us ready. Very cool. Space, you know, conflict in space is something that you kind of, we hear about from entrepreneurs and various people that are in defense tech, but it's not something that you necessarily read about in the newspaper.

1:49:52It's happening way up above us. And it's not something, you know, it involves private companies and governments, but no one is really incentivized to come out and say like, hey, we had this issue. It seems like it just kind of gets talked about behind closed doors. Do you think this is something that over time private companies will be like, end up disclosing? Like when do you think there's more of like a conversation around this or is it something that just kind of stays talked about behind closed doors? I think there's changes happening right now in the conversation, but it's tough, right? Because when national security is impacted, you don't necessarily want to be telegraphing all of the things that are going on.

1:50:38So I think there'll be some element of protecting that information. But I think there's going to be more companies like Portal and you're seeing them now that are going to have a significant part of their business be defense-related. And the Department of War and the Department of Defense in general are really trying to bust up the legacy compartmentalization of information so that we can support the Defense Department and the agencies in ways that, frankly, they have to have. And I think what's happened with a lot of the acquisition reform over the last few years is trying to get capability in the hands of the warfighter as quickly as possible.

1:51:18So there's a much more willingness to partner with industry. A lot of the decision makers are saying, hey, bring it all. We want it all. We want to maintain our number one position in the world and the Western world with our allies in controlling the space domain. So you're seeing a thaw in that. But I think there'll always be elements of national security where you will know there are things happening, but you won't necessarily know all the details just so the public can understand why it's important. But what I would point people to is just take a look at that 60 Minutes report from a couple of years ago where they were with the Philippine Navy in the South China Sea, and they were actually filming how China was engaging the Philippine Navy.

1:51:57It's all public domain. It all gives you a great idea of what's actually happening in other parts of the world with adversarial aggression and tactics. And I think it's a great example that, you know, people could then kind of take forward and why is this important? It's important because we protect our interests in land, air, and sea, and now space, and space has to become a domain that we defend for future commercial and commerce activity. What's the biggest lesson that you're taking from SpaceX to Portal?

1:52:33Tenacity. Not taking no for an answer. Every problem has a solution, and with the right team, you can get there. And I think those are the biggest lessons I took away. Do you have to show that to the 50 employees that you have on your team? Do you, is it enough to say it? How do you actually display it if you're a CEO? Because tenacity can look different in this particular seat. Yeah, I think it's tenacity coupled with, you know, maintaining a cool head, working the problems as they come. I joke with my group, you know, how many times do you see me running around with my hair on fire? You know, that's not the right approach to inspire confidence in your team.

1:53:13So I think the bottom line is you've got to project a calm but aggressive attitude to work through these issues. And I think just having experience and doing that in the past, which certainly all of us that came out of the SpaceX environment have an incredible amount of experience in solving impossible problems and moving forward with a great team. Well, Jeff, congrats on the progress. Very, very cool. Thank you for everything you're doing, and thank you for coming on the show. I'm glad we'll all be driving it like we stole it. I was about to say the same thing. That's what I want to hear. I want to hear about people in space.

1:53:47We must drive it like we stole it. In AI, they say you don't need to drive a Ferrari to get groceries, but I hope we're going to be driving Ferraris like we stole them in space to do simple things like getting space groceries. Absolutely. Kind of lost the plug. Anyway, thank you so much. Great to meet you, Jeff. Thank you. Have a great rest of your day. We'll talk to you soon. Next, we got Face 10. People are not talking about Face groceries enough. Really mixing metaphors there, I think. Face 10. We got Charles from Face 10. Charles, the head of AI model training. How are you doing, Charles? Welcome to the show.

1:54:26How are you, Lloyd? What's going on? What's the best model you ever trained? Best model I ever trained? I can't talk about it. Name every model. The traditional answer. I didn't realize this. Name every parameter. I think Tuggy Face has 5 million models trained. Is that enough? Do we need more? Well, yeah. I guess our bet is that we're going to end up in a world with some great models from the Frontier Close Source Labs. Sure. But we're going to end up with not 5 million, but probably hundreds of millions of models. Possibly even one model for each person. Possibly tens of models for each person.

1:55:00And I guess that's the future that Base 10 is betting on. Yeah. So what is the framework or what is the next model, the thesis behind model development that you want to execute on in this role? Yeah. So I think, like, to be honest, and the closed lives will tell you differently, but everyone is scaling the same recipe right now. Like, there is no difference between OpenAI's RL stack and, you know, the Chinese open source RL stack and the American open source RL stack. We've got the same recipe. People believe it scales. we first scaled pre-training and model size we're now scaling RL and you know people are going to keep doing that till the cows come home and the bet is that you know you hit higher and higher levels of intelligence and you'll be able to do more and more economically useful things.

1:55:45I think to us like we care a lot for instance about continual learning so we announced BaseLabs today which is going to be doing like less myopic longer term research around what models can actually do and continual learning looks very different for us as it does to the big labs. Like the big labs already in this kind of continual learning loop of you know They train a model, GPTN or Clawden, and they release into the world. They collect feedback on what it can do, what it can't do. Then they build a fuck ton of RL environments to patch the holes in it. And they go back. And from a high level view, bird's eye point of view, that is continual learning.

1:56:18The continual learning that you or I might imagine is very different. It's where you have an open source model that you specifically are using either as a firm or a team within a firm or even an individual. And that model is organically adapting to the information that it's learning. It doesn't have to write everything down in memory, mark down files because it learns about your business and so on. And then we think there's major paradigms to be unlocked within that regime. And it's not necessarily going to get the focus from the big labs because that doesn't necessarily benefit them. They want to serve one big model at scale.

1:56:48And the pitch they've sold to their investors is that you do that at a large enough scale and you don't need this kind of continual learning. Yeah. How do you process their claim? Because a lot of the big labs, there's this dance between, oh, well, there's a fine-tuned model. It was really good at this one benchmark. Then the next version of the big model that does everything is better than the fine-tuned. And it feels like this horse race where I can totally see the cost argument. And I can see even like the, yeah, for three months, this fine-tuned model was better. But if we're talking just like raw capability, how do you interrogate that claim that the big God model will always be better as long as you give it time?

1:57:32Yeah. This is where I think people are thinking about intelligence capabilities in the wrong way. People think about intelligence relativistically. They say, okay, the open source gap is like six months behind closed source and GLM 5.3 is at the point that Opus 4.8 was, whatever. I think the best way to think about what models can do for you and for the world is absolutely. So for any given task that you want to do with an LLM, there is some intelligence threshold that below that you can't do the task. And above that, you have very diminishing marginal returns to more intelligence on the task.

1:58:04And so when you think about it that way, the game of LLMs over the last five years has been, okay, we have these things we want to do with them. Closed source hits it first, which to be honest, we think is a good thing for many reasons, which we can get into. But open source eventually, like six months later or nine months later or whatever it is, can then do that task. And then for many reasons, like whether it's to control your own intelligence, whether it's to improve at that task specifically, once you have the base level of intelligence required to do it, you probably do want to swap to open source.

1:58:33And so it's not really about, you know, the God model being better. Like if I'm filing a tax return, there is just a limit to like how much intelligence I need to do that particular thing. And so I think the world is going to look like, you know, the frontier close source labs are going to continue to push the frontier. Like we you do want to use the most intelligent model. You have very like inelastic demand for intelligence when you're doing like, you know, frontier science or frontier maths. but for a lot of the economically valuable things it looks a lot like okay you know i'm a cursor or i'm one of these big companies who are now realizing like i can't just be a rapper anymore i've been through the life cycle of building a great product that people love and they tell me what they love and hate about it and i should be using that information to you know make my model better at the things that i care about and not at anything else and so that that pattern was executed fairly well with composer um it's obviously early days and the ecosystem isn't mature enough for anyone apart from, you know, the curses of the world and a few other big companies to go about training.

1:59:28But, you know, I think eventually we'll get there where it's much more organic. Can you talk about the goals of this project? I mean, I understand the research direction, continual learning, but is the goal more to advance the research or produce a continual learning model product that is then sold? How are you balancing the discussion that needs to happen within the ecosystem versus productizing something that could be a really meaningful breakthrough? Yeah, it's a good question. I think the founding mandate of BaseLabs is do whatever we can to make open source models and probably bleeding into closed source models eventually as useful as possible and so it's very difficult to specify a priori what that looks like like one obvious place to bet is yes this continual learning paradigm and doing research around that and like thinking about that in a different way to how you know the big labs think about continual learning on like you know millions of people at once yeah but like we're not hubristic enough to say that like that is the only way in which we're going to make models more useful so for instance another thing we're thinking a lot about at the moment is everyone talks about aggregating compute for open source to keep up like you need a certain number of chips to be able to train these things but not as many people are talking about aggregating data.

2:00:43Like the closed source labs are spending billions a year on our environments. And again, like RL is the next paradigm that everyone's scaling. You know, distillation and like, you know, cheap data and centralized data. There's a lot of discussions around these things about how the open source labs are currently keeping up. But, you know, what keeps me up at night is I wonder if there's a point where it bifurcates and you can't like get all the way there from, you know, distillation and whatever data you have access to. Like someone needs, without a commercial incentive, needs to be making these incredibly complex RL environments that normally cost billions of dollars in the aggregate and open sourcing them to the world.

2:01:17So a key part of, I guess, base labs is can we make those environments? And we've been doing this for the last few years. We're making them for individual people. Why don't we just make them for everyone and release them? So any open source or closed source provider can train on them and you kind of cut the gap that way. So aggregating data is another big bet that we want to make. And there's a few other things. One thing that we're starting to notice a lot is like as the capabilities have risen and even the open source models have kind of subsumed all the economically valuable tasks that most people are going after.

2:01:48And it's very difficult to tell the difference between an open source and a closed source model. Then you start to think about what the values of these models are. And you can't not have an opinion when you're training a model about what the values and ethics and morality of that model is. Like in your pre-training data and your mid-training data and your post-training and your classifiers and your safety stack you run on top of it, everyone has an implicit or explicit opinion about what the values are. It's a reason why so many American companies don't want to use Chinese open sources because we're not very clear what those values are.

2:02:13So how do you organically shape those values to what you want them to be, both as a country, as a firm, as an individual? Can we do post-post training to elicit the right values and models? Trust in benchmarks feels like it's at an all-time low and maybe is headed lower. What other – do you have any other ideas of how to communicate the sort of – maybe it's still that they work well enough, but any other ideas around how to communicate the value of certain new models? Bench maxing, bench hacking, and then also just like inundation with so many that a lot of consumers and enterprise buyers, they sort of just roll their eyes when they see a new one because they're like, I've seen a hundred of these.

2:02:57I know that you can probably do well on one. But yeah, I'd love to hear this. Yeah, I think that let's think about like who makes benchmarks, right? Like it's typically a bunch of like, you know, research fellows from Stanford or what have you who pulled together and they're very smart people. and they're like, okay, this is what, you know, this is this weird way in which we're going to trip this model up. Like I think RKGI is like a very good example of this like weird pocket where the models like traditionally don't do well and they've obviously updated the benchmark more and more as the labs have kind of caught up.

2:03:27The common saying is like, you know, once you've benchmarked it, you can RL on it. So, you know, releasing these makes the models better. I think the best way to do this is aggregate the economy. And this is where we actually see us having a really big advantage compared to particularly the close source labs. Like I do believe Anthropic and OpenAI are generally good. and like, you know, they don't look at user data if they say they don't. And like, they have this very like bird's eye view of like, what the models are good at and what they're bad at. It's why they go on Twitter and ask for feedback.

2:03:52We have a real advantage in the sense that we have like, you know, thousands of people using them for different things. And each of those individual companies has tried in some way to build their own evals and benchmarks to test how good a particular model is at the task that they care about. And so rather than, you know, like there's no like silver bullet here. Like there is no set of 10 benchmarks that is going to tell you, exactly the core and the jagged frontier of whatever model it is you're testing. The best way to do this is to look at how everyone is using them in the economy for real things that people are paying for, not weird niche things like ArcGGI and aggregating those benchmarks.

2:04:27And I guess that's part of what we're trying to do with the RL environments and pumping them out at scale. But yeah, we get a lot of really good signal from our customers. For the record, here at a TBPN, we had Tyler do ArcGGI v3 tasks manually. as a human he technically got paid for it so you know what did you score time i he was he was he was globally ranked globally for like a week we were very early i think day of launch he was like number seven uh charlie what does it mean to feel the whole elephant oh yeah um i've gotten a lot of flack for this um and people have interpreted it in quite inappropriate ways including my CEO actually yeah um but there's this old analogy of like you know blind men touching an elephant and like they don't really know what it is they're looking at and one's feeling the trunk one's feeling the leg one's feeling the tail i think it is a little bit like that with things like lms and particularly like continual learning you know some people say that continual learning is just like having a god model with you know a million tokens of context and it can search whatever it needs to and organize the information that way other people really believe that no every single token it should be updating you know it's information um we know that that fries the model in different ways I think Thomas Kuhn wrote a lot about the structure of scientific revolutions.

2:05:40And I think we are pre-paradigm when it comes to things like continual learning. No one can agree on what the definitions of these things are. No one can agree on, apart from the core recipe to produce the base LLM in the first place, what the right ways to be scaling this is, the ecosystem around it. Compaction is a great example of this. OpenA and Anthropic have gotten really good at compaction in Claude Code and Codex. At the moment, that's just summarizing models. like there's probably like really really cool things that you can do if you train like you know neural compactors if you have models themselves doing compaction in kv case space so i think this is a lot of work to like make this a science because so much of it is inside the closed source labs and i guess that's the the mission of base labs is like how can we bring as much of this into the open as possible without a commercial agenda like even the open source labs have a commercial agenda they need to produce the best model this quarter and we don't have that pressure.

2:06:31And so I guess we can pick the most interesting scientific problems and work on them for as long as we need to before we feel like we've made traction. What is your P brute force? The probability that the answer to continual learning is just brute force. When I think about what OpenAnthoropics do for updating a model, you mapped it out. It's a couple months of data collection, building RL environments, retraining the model. That takes GPU hours. But if you get a 10x speed up in the amount of time it takes to train the actual model versus you can build the RL environments 10 times faster. You can generate the data 10 times faster.

2:07:08And you start working at this over maybe it's a decade. Is there a world where you could just do exactly what we're doing now, but every second, and it feels continual because when I talk to anyone, they're continually learning, but they take a second. They say, oh, yeah, OK, I'm updated. I now know that fact. Yeah, I think there's a few ways to break this down. From the perspective of RSI, like recursive self-improvement, I actually think that continual learning is either unnecessary or it is brute forceful. We're going to asymptote towards models that have access to the whole OpenAR Anthropic training stack.

2:07:45They're going to make slight architectural improvements. They're going to drop pre-training loss. They're going to be able to pump out RL environments and scale by themselves. And then that process will speed up and speed up and speed up as we get more and more compute. But for the everyday person and the everyday, like, you know, AI native startup or enterprise or whatever, continual learning doesn't look like that. Like at the scale that they're operating at, you can't afford to like open AI and Anthropic. They wash out all the noise and the gradients. They take all the useful stuff and these big pre-trained runs makes it work.

2:08:11But when you just focus on like, you know, I have an agent, which is a legal associate. And I'm trying to fine tune it on all these like complex relationships and all the things that the firm does and this implicit behavior that we want it to have. Continual learning breaks down. We don't have an answer to it. We can't SFT, it degrades the model. We can't RL because it doesn't give knowledge acquisition in the right way. You know, there's a lot of work to be done there. So I guess it depends on, again, which part of the elephant you're touching, like what definition of discipline you care about.

2:08:35We got to get an elephant in the studio. We got a dog, we got a horse. Part of the elephant you're touching. Thank you so much for coming on. This was a fascinating discussion. Congratulations on the process. Yeah, great to meet you, Charlie. Very cool. Very excited for you to solve this. Come back soon. This was fun. We'll talk to you soon. Have a great day. Goodbye. Team, we need an elephant. Snowflake. Bye tomorrow. We got the CEO with us here live on TBPN. Shrihar Ramaswamy, welcome back to TBPN. How are you doing? Thank you so much for joining us. And congratulations on the fantastic success.

2:09:07Break it down for us. What's working? Is there anything that's not working? It seems like everything's going really well. How are you doing? Hi, am I live? Yes, you're live. We're live. Welcome to TBPN. Thank you so much for hopping on. Oh, thank you. we had a pretty amazing quarter 1.49 billion dollars 37 % year on year our AI products Coco and Cowork getting really broad adoption we feel very good overall but this is also a time of intense competition there's the hyperscalers but also the foundation labs so we think there's lots of business to be had but a ton of change to keep up with both for our product teams and for our go-to-market teams.

2:09:53So yeah, it's a day after earnings are done and it's back to work, pedal to the metal. How much time are you spending trying to identify, like a venture capitalist, the next company that's going to be a major Snowflake customer? Because I feel like the big labs, you identified them, they're obviously huge consumers of data, Huge businesses there. But it feels like every time we talk to somebody on the show, there's a new business that's getting venture funding. They're getting users. They're getting revenue. And I can tell that they're just generating a ton of data. Yeah, they're ramping revenue way faster than any company.

2:10:36And they're probably ramping data two orders of magnitude faster than they're ramping revenue even. So what does that look like for you and for Snowflake? Yeah, we spend a lot of time both with our own innovation, what are great new ideas to be had at this moment because so much is possible. AI is industrializing software. It's much easier to create it than it was before. So I spend a lot of time with the product and engineering teams back to basics innovation. We also meet a lot of startups and companies, both established ones, talking to them about the opportunity that is possible with AI, talking to them about what we have done with our own sales teams, but also brand new startup.

2:11:16I met a startup, I think it was the day before yesterday, barely three months out, but they have dozens of customers all doing reinforcement learning on their platform. We were talking about how we could better partner together. So a good amount of time spent on both sides of the cycle. But what I think is unique and cool is how quickly ideas go from, It's just an idea to prototype, too. It's a product feature, too, getting adoption with a lot of customers. Yeah. With all of the growth, I imagine that there's new challenges. Where are you going to be focused on un-bottlenecking the organization?

2:11:55Are you going to be hiring, putting more AI, as you mentioned, in the hands of an even broader swath of the organization, even though I imagine everyone has access to some level of token budget? But what does the growth side of the business, what are you trying to unlock in the next quarter or the next year? For the majority of the company, the biggest mindset shift that they need to go through is scale is not just about people any longer. What AI makes possible is stuff that needed individuals, people to go and do can largely be automated. It's much more about the judgment. What's the work that you're trying to get done?

2:12:41How do you want that done? And then setting up a framework by which things can get stamped out. But that's a pretty tough change for an org or a set of people, even you and me, that have traditionally looked at organization size as an important barometer of growth. And that's something that we are stressing with the entirety of the Snowflake team. I expect some functions to grow, but these are typically the ones that do things like interact with the external world. So account executives, I can see that growing for customers that are spending. But for a lot of other functions, including in engineering, there is so much leverage that you can get by being at the forefront of what is possible with agentic AI.

2:13:25We continue to hire folks, especially young folks who know of no other world because they bring a perspective that is fresh and they know how to go from zero to 100 straight off the bat. But a lot more focus is on how do we become effective as a company. And a lot of it is also about how do we set up new efforts and give them space to experiment so that they can find that magic in a bottle. AI is not going to help us create great new products just like that. There's an amount of experimentation to figure it. And giving space to small teams to execute is among the biggest challenges that we need to make sure that we solve.

2:14:07Coco, for example, it's a breakout success. But for much of its existence, it never had more than five people. And even now, the team that works on Coco is tiny. But that's the kind of impact that is possible today. Are internal meetings underrated? Would you expect that in a world where AI can do more of the work but lacks some of the context and taste and decision making and deciding what to do, if you woke up and you said, wow, as a company, Snowflake is having 10%, 20 % more internal meetings between various members of the organization, would that sit well with you? Because there's been a long history of, oh, internal meetings are such a waste of time.

2:14:52It can be very cumbersome if everyone's calendar is just full. That's just layers and layers of management. But is there some world where that's actually the correct way to be running a business of this scale in this era? I think bringing people along is an important function of every company. I wish I could tell you that we've solved this information exchange problem perfectly. There are a number of things that we are working on. We have an internal enterprise brain project like many other companies do in order to capture all of the relevant knowledge about the different things that are happening within the company so that the right piece of information gets to the right person.

2:15:37so I do think of projects like that as greatly enhancing internal communication. Remember, in a regular company, people go to meetings so that they don't feel left out, which is something that I really discourage people from doing. My attitude is like, if I have nothing to contribute to a meeting, I should read the notes. I really should not have to go to that meeting, but I would say it's a work in progress to make sure that we do a good job of transmitting internal information. It also has more profound implications. I think things like how many reports a manager should have needs to be dramatically different in the age of AI.

2:16:17Of course, making sure that people feel happy and motivated about their work, that's always going to be the role of a good manager. But, you know, information about what exactly did you get done last week, that's the kind of stuff that AI can facilitate a lot. It's a work in progress. I truly hope. You know, I've not measured it recently. You bring up a good point. We should go look at it. I hope we are not spending more time with internal meetings, but we should also not pretend that communication is a solved problem, even in the world of AI. How are you thinking about your own internal AI spend and budgeting heading into next year?

2:16:55I think a lot of companies spent a bunch of time planning next year, and then there was a capability jump, and they blew through their budgets more quickly. I think as a leader, you have to assume there's going to be capabilities jumps, which may mean that you spent more. But at the same time, there's a lot of drive for efficiency, cheaper models, open source, et cetera. But how are you planning around token spend looking forward? My take overall is that the money that we are spending on AI tokens is well worth the cost. We continuously optimize. Absolutely. We don't tell people to token max or do dumb things like that.

2:17:39It is about driving real results, impact, as it were. And when our cost does go up, we have a good team that focuses on optimization, everything from what's the default model to can you create task graphs where the simpler aspects of solving a problem are handled by models that are not quite as expensive. And my take is that we gain a lot by having people embrace the technology and feel like it can make a real difference to their job. I feel pretty good about optimizing. We also practice what we preach, where we have things like the AI gateway that's meant to make model access more efficient. We are absolutely experimenting with open-weight models because they can be a good vector for lowering costs.

2:18:29Because we also control the harness, which is Coco, a lot of our internal teams use. There's a lot of instrumentation that we have for what exactly are people doing? How can we come up with better ways for doing the same thing? Our support and our SRE teams, the folks that keep Snowflake up, they spend a lot of money on tokens. But on the other hand, if they are running through tens of thousands of alerts that are coming in every day, it makes sense to go there and optimize because that's very leveraged work that can benefit everybody. So, you know, yes, we are planning for it, but AI token cost is not the top thing on my mind.

2:19:09Creating great products, getting our customers to adopt them, having the framework by which these things become more self-correcting, that's kind of how I think about it. Based on all your experience in the enterprise, how do you think the model routing landscape will evolve? This seems like something that a lot of big companies are excited about, you know, getting a slice of that market. You saw Stripe's deal with Open Router focusing more on developers. Ramp, our partner, has a product. Everybody wants to be in the token flow, but how do you think that it'll evolve? That's not the highest value creation point for Snowflake as a company.

2:19:50We have products like Cowork that can literally get deployed to every employee in a company. So we spend a lot of time thinking about what does it mean for an enterprise sales team to be AI-filled, to be operating at the edge of what is possible with AI. And we are seeing deployments of Cowork go to thousands of users within companies. it's operating at a much higher level than simply model routing. I think it's a good infrastructure capability, but I focus a lot more on things like how do we get every data engineer within a company to be using Cocoa or Builder product, or how do we get large fractions of employees within companies to be using Cowork?

2:20:36What are high leverage, high value projects that we could be doing for customers? Because our customers have always trusted Snowflake with all of their most important data and focusing on how we can drive real business outcomes is where a lot of our energy is. Absolutely, the Gateway is a good product, and it's not just model routing. We are also offering things like access to tools, MCP tools, as it were, that provide governed access to lots of different applications within an enterprise. We are also actively experimenting with is there a security solution around agent trajectories to make sure that people are not misusing models.

2:21:14So there's a slew of these things that are there at the infrastructure layer, but I think our bigger prize is in delivering value for our customers. Last question. There's a lot of M &A news, obviously. It's a very exciting time. You spent 15 years at Google, very acquisitive company. How do you think about M &A, what makes for a successful acquisition? How is it unique at Snowflake when you consider it when you don't? So our strength is as a data platform. People trust us with their most important data. People trust us with helping them get insights and drive actions from their most important data.

2:21:56My primary lens is, will a company being part of Snowflake accelerate that mission? We are thrilled that we bought Natoma because MCP is increasingly really, really important for Snowflake and all of our customers because it provides the real-time context of everything that's happening in your and my life, whether it's Slack or email, right in the harness. And that was a great acquisition to make. That's the kind of lens that we bring, which is how does something being part of Snowflake accelerate both the company that we buy but also the larger mission of Snowflake as the AI and data platform for every enterprise that there is.

2:22:39Thank you so much for coming on the show. Great update. Great quarter. Congratulations on the quarter. Yeah. Congrats to the team. Thank you so much. Can't wait to talk to you again soon. Thanks for having me. Have a great day. Cheers. Goodbye. Take it. Didn't get a chance to hit the gong, but a very gong-worthy quarter. Huge update in artificial intelligence world. Someone has created a product that speeds up Lex Friedman when he asks questions on his podcast. You saw this? No way. LexSpeedman.com. Mario Dion says, I wanted to watch the Lex Friedman episode with DHH, but Lex talks way too slow for me.

2:23:13So I built Lex Speedman. It speeds up Lex to 2x speed and keeps the guest at 1x, cutting up to 20 % of the episode. Wait, so Lex will talk for 40 % of his episodes? That's not possible. I feel like Lex is like, he asks one question, he really lets the person talk. That's kind of a benefit of the point. He does. He talks for a while? Kind of drift off. I wonder, we should pull some stats on like, on like who talks more? Because sometimes we have good back and forth, but we're all talking with the guest. Sometimes it's just us short question. They go on a rant for a couple minutes. Yeah, sometimes we'll get some very angry comments around.

2:23:54About what? Cutting each other off? Would you please let the guest talk? Oh, they say that. Interesting. I remember early on they were saying, you guys got to stop cutting each other off. And was I cutting you off? Or were you cutting me off? I feel like this is just the way we talk. And, like, it never— Our real fans went to the rescue. Yeah, we never really got to the bottom of it. I think it was me cutting you off sometimes, but especially with the ads. I love cutting you off with an ad. That's the best. That's the best. But also, no dead air, you know? I love cutting you off with a flashbang.

2:24:25No, don't do it. Don't do it. Flashbang. We're going to the Stars Astra. GPT6 is out. Go check it out. There's a crazy video by Matt Schumer. he one-shotted a game in Unreal Engine now. Unreal Engine has MCP so you can actually build the game of your dreams basically just by chatting with the model. Mike over at ARK is moving the goalposts. Thank you. Let's do it. Thank you for not waiting to move the goalposts either. He said Astra is the new state-of-the-art on ARK AGI 3. It's a qualitatively large leap towards AGI and the pace of progress is frankly surprising. That said, we lack evidence to call this AGI yet.

2:25:15While we are still studying the human capability gaps, we believe open-ended invention is unsolved and this will form the new basis for ARC AGI-4. So now it's like, you got to invent new physics, new science. You got to go to that. You actually, Astra has to actually go to the stars. Yeah. He really said, what have you done for me lately i love it i love it it's it's agi when mike says it's agi uh it's a good time uh anyway very interesting you can dig into his post he gives a lot more context there about uh arc agi v3 benchmarks astra you can go check it all out and of course yeah we'll do it tomorrow we have a bunch of special guests so have a great day we'll see you tomorrow leave us five stars on apple podcast and spotify sign for a newsletter at tbpn.com and we will see you tomorrow

2:26:04Please read the video and listen有沒有 humor at this section.