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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're welcome to TBPN.
Speaker 2:Today is Tuesday, 04/07/2026. We are live from the TBPN LPN. The temple of technology.
Speaker 1:The fortress of finance, the capital of capital.
Speaker 2:Let's pull up the lineup because we have a great show for you today, folks. We have Riley Walls, the jester of Silicon Valley. You had a different name for him when he came on. There was something else.
Speaker 3:Internet Rascal.
Speaker 2:Internet Rascal. Was it.
Speaker 1:Is a rascal.
Speaker 2:He's he's coming on to talk about the auction to name a street in San Francisco. We have a whole bunch of funding news. Aditya Bandi from noon. Zach Shore from Hermes is coming on. Wangwei Liu from Mappadin is coming on.
Speaker 2:And then Zach Kukoff and Thomas Laffont are joining us live in person in the TBPN UltraDome. Well, there is a whole bunch of news to run through. The first story is that Meta employees are apparently token maxing and competing on an internal leaderboard called Clawdonomics for status as a token legend. This is from the information. Over a recent thirty day period, total usage on the dashboard topped 60,000,000,000,000 tokens, and this sparked a huge debate over how much is Meta actually spending with Anthropic.
Speaker 2:Of course, the other big news is that Anthropic just passed 30,000,000,000 in run rate revenue with one of the probably the steepest revenue growth chart in human history. Absolutely legendary.
Speaker 1:Yeah. This this chasing status
Speaker 4:as
Speaker 1:a token legend reminds me of kind of maybe it was a year ago at this point you were saying like, will tokens ever become like eyeballs the way eyeballs were during the Yeah. During the era. Yeah. Right? Just optimize for eyeballs.
Speaker 1:Obviously, not every eyeball visit to a website is created equally. Yep. But people were optimizing for eyeballs. And now, you know, I don't the reaction to this I think has been generally, at least online, like been, I guess, reassuring. A lot of people are saying Gary Bason says, you, why?
Speaker 1:Marty says, Goodhart's Law. When a measure becomes a target, it ceases to be a good measure. And so who knows what's actually going on internally? But we do know Zuck is pushing the entire to be as AI native as possible. And this guy loves spending money too.
Speaker 1:Right?
Speaker 2:I have a crazy bull case here that I will run through. Let's get through some of the story. First, we got to pull up this comic from xkcd in the comments here. When a metric becomes a target, it ceases to be a good metric. It's right under the leading post.
Speaker 2:There we go. And says and the other counterparty says, sounds bad. Let's offer a bonus to anyone who identifies a metric that has become a target. It is good. Don't Max, think that's what's going on
Speaker 1:lighter was texting a friend at Meta and sent the post we just discussed on Tokenmaxxing Yes.
Speaker 5:And said, true? And the person said, yes.
Speaker 1:It's pretty sad. But I mean, imagine. So so Meta has been there's been rumors Yeah. Of Meta layoffs for a while now. Sure.
Speaker 1:Unclear how many, if any, if any have happened. But if you're sitting there, the company Zach is saying like, we need to get AI native. Is saying, we need to get AI native. And then suddenly there's a token leaderboard. Yeah.
Speaker 1:You do not want to be at the bottom of the list. Yeah. I will say that. Right? Yeah.
Speaker 1:You know, you don't want to be the don't want to be the guy who's having to explain like, no, well, I'm actually getting the most out of each incremental token and the other guys just like set up a set up an agent that just counts one one to a million single line and over and over.
Speaker 2:Or something. Yeah. Yeah. I mean, you have to measure the actual output, the impact on the business. I mean, fortunately, Meta has been a huge beneficiary and a huge winner of AI.
Speaker 2:The ads are getting better targeting. They're seeing they're delivering more ads and the quarterly earnings have been strong. The headline number here that sort of took everyone by surprise is that Meta's staff used this is from the information Meta's the story claims that Meta's staff used 60,200,000,000,000.0 tokens over thirty days, which would pencil out to about onethree of Anthropix's ARR was the number that was thrown out. But both of these claims are pretty questionable. And so Tyler did some back of the envelope math to show that the one third revenue estimate is way, way too high.
Speaker 2:And I don't know. Do you wanna take us through some of the reasoning there? And then we can talk about the knock on effects of
Speaker 1:all this.
Speaker 3:Yeah. Okay. So 60,200,000,000,000.0 tokens is the number. Like, we can just assume that's true.
Speaker 6:Mhmm.
Speaker 3:So basically, I I'm gonna assume that the all the employees are basically just using Opus four six.
Speaker 2:Yeah.
Speaker 3:So then there's basically three numbers you need to look for
Speaker 2:Yep.
Speaker 3:In like the API cost. So there's like input Yep. There's a cashed input, and then there's output.
Speaker 5:Sure.
Speaker 3:So for OPUS four six, it's $5 per million tokens on input. Yep. It's 50¢ per million tokens on Cached. Input cashed, and then it's $25 on output.
Speaker 2:Yeah. So if you multiply that 60,200,000,000,000.0 tokens at the highest possible rate, $25 per million tokens, then you do get like a billion dollars in
Speaker 7:them.
Speaker 2:Yes. Which is crazy. Not what's happened.
Speaker 3:The crazy number.
Speaker 6:But like
Speaker 3:you have to think about it like, you know, if you're using like Cloud Code or Yep.
Speaker 6:Or any
Speaker 3:of these coding agents, you know, the vast vast majority of the of of the tokens used is input. Yeah. Because like so imagine you're working on some, you know, coding file. Right? Yeah.
Speaker 3:There's like thousand lines of of code in the file. Maybe the the model's only changing like like 10 at most. Right? Yeah. So that's a very small percentage.
Speaker 3:So the output tokens are gonna be, you know, a very small percentage of the total tokens going in. Right? Yeah. So Open Open Router publishes like a lot of this data so you can kind of use those ratios to figure out what is actually like what are the actual numbers of of the, you know, input versus cash versus output.
Speaker 2:Yep. This is get Just sort of like market standard averages baseline benchmark.
Speaker 1:Yeah.
Speaker 2:Now Meta could be using these tools differently but if we are to assume that they're the the shape of their agent decoding efforts are similar to the average, this is what the numbers
Speaker 3:Yeah. Look like. So so maybe that there is like some, you know, bad incentive where people are just saying to the model like count up to a billion and then do it again. Yeah. So then it's like totally skewed.
Speaker 3:But if if they're doing it relatively normally
Speaker 7:Yeah.
Speaker 3:So on OpenRider, it's about 98.9% of all tokens are input.
Speaker 2:Input.
Speaker 3:And that's including cached ones.
Speaker 2:Because you're stuffing the context window with all your code base or Correct. Huge amount of context.
Speaker 5:Yeah. It's going around finding
Speaker 3:That's not changing every time so you can cache it. Yep. Yep. Yep. So then that's like 1.1% is is output.
Speaker 3:Yep. So basically, if you basically get all the numbers, that means like the kind of mean token Mhmm. The mean million tokens is gonna be $2 and like around 26¢. Yeah. So that'll get you to something like a $136,000,000 a month Mhmm.
Speaker 3:For the 60,000,000,000,000 tokens. Yep. Right? So that's like way less than the 900.
Speaker 2:Yep.
Speaker 3:So that that would be 1,600,000,000 a year like run
Speaker 2:rate. Still huge.
Speaker 3:That's a lot. But but that is still in the max. Yeah. That that's like
Speaker 5:I'll tell
Speaker 2:you Assuming they're in the top. Yeah. Yeah.
Speaker 3:That's assuming that OpenRouter, the the the the kind of breakdown of how they're using the tokens is the same as OpenRouter Mhmm. Which I think it's not. But if we assume that, that's like $4,500 per engineer if there are, I think, 30,000 engineers at Meta Yeah. Every month. $4,500 on tokens.
Speaker 2:$4,500. That's actually in line with what I've heard a lot of other people spending in terms of their token budgets Yeah. 5,000
Speaker 3:not bucks like absurd. Absurd. If you're trying to incentivize people to use them.
Speaker 2:Yeah. Yeah. No. Not
Speaker 8:at all.
Speaker 3:But so so you can actually see the breakdown on OpenRider of how people are using tokens. So 17, the biggest plurality is Open Claw, is 17.6%. Yeah. And then Cloud Code is is 16.8.
Speaker 5:Sure.
Speaker 3:So I think if you think about Cloud Code, you would imagine that like in Cloud Code, there's the the kind of percentage of cache tokens is gonna be higher than in in Open Claw. Yeah. So I think Meta's usage is actually gonna be more heavily based on the the cache tokens. Sure. So if you do it just based off like Cloud Code usage, you'd actually see a higher percentage of of the input tokens be of the total tokens.
Speaker 3:So it's only like point 8% is the output. Yeah. So then if you get all those numbers through again, it's only like 55,000,000 Yeah. A month which would be 669,000,000 a year. Yeah.
Speaker 3:And each engineer would be like $1,800.
Speaker 2:Yeah. That yeah. That's actually pretty low.
Speaker 3:Which is like I think very reasonable.
Speaker 1:Yeah. John Chu over at Cosa says, Plenty of my Meta friends told me folks have been building bots that just run-in a loop burning tokens as fast as they can It due to this is an app it's an absolutely stupid policy and it's similar to how Meta uses lines of code to measure engineering output. Managers are supposed to use it as a proxy and dig in to understand work complexity, but plenty of managers are lazy and just don't. That was in response to Christina over at Linear saying, ranking engineers by token spend is like me ranking my marketing team by who's spent the most money. Yeah.
Speaker 1:We may not have hit our KPIs, but Joe spent 200,000 on a branded blimp that only flies over his own house. So he's getting promoted to VP.
Speaker 2:I'm I'm pro branded blimps though. I like that idea. The so so so my take on this was that, yeah, it it it sort of ties to what Jensen Huang was talking about at GTC. He was saying that an engineer that's making $500,000 might soon command something on the order of $250,000 a year in token budget. Andra Karpathy had a similar line.
Speaker 2:He said, It's all about tokens. He said on a podcast last month, What is your token throughput and what token throughput do you command? And so Meta actually has two different harnesses internally. They have a version of Open Claw called My Claw and then they also of course acquired Manus. But it appears that they're running Claude, maybe Opus under the hood to actually generate the tokens that come through those harnesses.
Speaker 2:The interesting thing is that at $2.50 ks AI budget per engineer, you're at like 20,000 a month. And so based on Tyler's math, feels like, okay, there's going to be another maybe 4x to get to Jensen's prediction. The baseline that was going viral around, oh, Meta spent like maybe $1,000,000,000 last month with Anthropic. That would work out to like $83,000 a month, which is absolutely insane and I don't think anyone's really thinking that that's what's going on here. But this felt a lot of people were saying like this is, you know, there's lot of
Speaker 1:negative things other thing is about like the ARR Yeah. Is is the annualized run rate
Speaker 2:Yeah.
Speaker 1:Version, right? Yeah. Which which does come down. We don't know how they calculate it.
Speaker 6:Sure. Sure. Yeah.
Speaker 1:I'm assuming they're not choosing like a Saturday
Speaker 2:Yeah.
Speaker 1:Like multiplying that. Right? Sure.
Speaker 4:Sure.
Speaker 2:Sure. The bigger question is like a lot of people, you know, John Chu there is is saying that, you know, oh, this is like a bad metric and maybe it is. But I think it makes clearer the strategy with Meta Super Intelligence Lab. Because if you're looking at, you know, it's clear that they're spending hundreds of millions of dollars on this just for internal code gen tooling, like running their business. They are going to spend an inordinate amount of money on frontier inference.
Speaker 2:And so training a model there, they will be able to amortize the training cost of the next model that they build, not just over can they get a product out that goes viral and becomes its own standalone chat app that people pay for or maybe it's ad supported. Like just on the internal usage, they could be running a multibillion dollar token bill that they would have to pay another lab. And so if they develop that internally, it's pure vertical integration. And then you also have everything that's happening on the actual ad targeting and content delivery side. And when you add up all of those, all of a sudden the big question has been like, does Meta is Meta going to be able to launch an entirely new AI product like Vibes or something like that?
Speaker 2:And this is a data point that to me says they don't need to because just from a pure vertical vertical integration story, the investment in MSL can pencil out. What? Wait. Are you laughing?
Speaker 1:I just want you to get to your schizo theory.
Speaker 2:What's the schizo theory?
Speaker 1:That you that that this this this whole like Tokenmaxxing thing is like a is like a barrage while they distill the model.
Speaker 2:Oh. Oh, yeah. Yeah. I mean, there is a there is a world where if you're running if you're if you're generating trillions and trillions
Speaker 1:of tokens
Speaker 2:of a frontier model
Speaker 1:They're like, meta is really, like, burning through a lot of tokens. And you have generate everything. It's like, oh, we're just Tokenmaxxing.
Speaker 2:Yeah. I mean, there's another story about distilling we'll get to later in the show. But there there is a question about if I if I have a if I write an essay and then I have a model rewrite it, those tokens, they are from that model provider. They, I buy them. They become mine.
Speaker 2:Can I train on them? That's probably out of terms of service. So you would think no. But you sort of wind up in this ship of Theseus world where if Meta pays Anthropic $100,000,000 or $1,000,000,000 to go rewrite every line of code, every email, every Slack chat, every internal message, like basically map the entire organization, rebuild it. They wind up with an incredible training corpus that they can use for their next model.
Speaker 2:But I would imagine that they can't and I imagine that the enterprise contracts go both ways. They can't the lab can't train on the corporate information. That's standard in all of the enterprise contracts. And I would imagine that the opposite is true as well. Although it is this fuzzy ship of Theseus world where if you're using coding agents to upgrade your infrastructure and then you want to run and train some model on your infrastructure, do you have to pull out the tokens that were revised by the AI lab that you don't have the right to train on?
Speaker 2:It's all very interesting. Apparently, startups that have gone out of business are able to sell their corporate histories for something like $1,000,000 to data brokerage firms and AI labs now. Have you heard about this?
Speaker 1:Yeah. Heard about it. Yeah. Skeptical? I'm I'm skeptical.
Speaker 1:I mean I mean, certainly, there there is a market for it. Basically, all the code needs more database.
Speaker 2:That a company built over a few years. Maybe they
Speaker 1:Code, but also usage within different enterprise.
Speaker 2:Yes. All sorts of different stuff. Basically, like an RL environment or something that can help whatever business process they were doing. So if you're And you could imagine a data broker buying the data set from a start up that has their go to market motion that can be RL'd on and then also their code base that can be folded into training on how to write better code and all of their marketing messages. And basically everything that they did on internal external columns, everything is tracked.
Speaker 2:Maybe they've been using granola or something. They have like very detailed notes of everything and how they built the business. Even though it wasn't successful, there's going to be a lot of lessons there that can be folded into the next training
Speaker 1:Yeah.
Speaker 2:Of the next thing.
Speaker 1:Anyway In other news Yes. Intel is joining TeraFab.
Speaker 2:Yes. Let's read
Speaker 1:Intel through is proud to join the TeraFab project with SpaceX, XAI, and Tesla to help refactor silicon fab technology. Intel says our ability to design, fabricate, and package ultra high performance chips at scale will help accelerate TeraFab's aim to produce one terawatt a year of compute to power future advances in AI and robotics. And throwing up a post of hanging with mister Musk himself. What Intel up up on the day, up almost 3% unsurprisingly, and just continues continues to be on a tear, up almost 15% in the past month and a 167% over that last year. So
Speaker 2:Let's go through the Wall Street Journal's coverage of this. Elon Musk is partnering with Intel on his ambitious TeraFab project, which aims to build specifically designed chips for SpaceX and xAI as well as for Tesla. In an announcement Tuesday, Intel said it would work with the companies to design, fabricate and package ultra high performance computing chips at scale. The company shared a photo of chief executive Lip Bu Tan shaking hands with Musk, CEO of SpaceX and Tesla. The partnership is a win for Tesla, which has struggled in recent year Intel.
Speaker 2:Which has struggled in recent years, leading the company to cut production capacity when demand was surging for data center chips and when competitors like NVIDIA and AMD have thrived. That was always a just such a tough pill to swallow when you would talk to the ASIC companies like Cerebras, and you'd say, hey, like you're doing something new. You're not you're not doing NVIDIA chips. Is there any way you could get off of TSMC? And they're like, no.
Speaker 2:Like we still need to be in Taiwan. Obviously, there's a huge geopolitical component here. We can get into all that. But last year, the Trump administration reached a deal to acquire an equity stake in Intel for around $9,000,000,000 to help secure the American chipmaker's business. The US government held 8.4% of Intel's shares outstanding in as of March 20 according to securities filings.
Speaker 2:The figure doesn't include warrants that could increase the government's equity stake in Intel. So as you mentioned, Intel shares gained 3% in Tuesday trading. TerraFab represents a step change in how silicon logic, memory and packaging will get built in the future, Lip Buuton said on X. Tesla and SpaceX confirmed the partnership in post on X. In March, Musk unveiled the plans for a single facility in Austin, Texas, to make chips to be used by SpaceX and XAI, which merged in February as well as by the publicly traded Tesla.
Speaker 2:He pitched the project as an opportunity to quickly experiment on chip design by designing and manufacturing the chips in one facility. The fab will make chips for use in Tesla's robotaxis, which they're already fabbing, I believe, at Samsung, although they do have NVIDIA Dojo chips, I think, that are TSMC. So they've been doing using both of those fabs, but Optimus will also need chips, they are planning to use Intel for that as well. So these are two areas of priority for the electrical vehicle maker as it shifts its focus to artificial intelligence enabled products. It will also make chips optimized for use in space where SpaceX is planning to deploy huge numbers of satellites capable of handling AI computing task.
Speaker 9:You know what?
Speaker 1:Yeah. So Yeah. Who who else do you think they need to get involved here? Because just the two of these the two of these got, you know, Intel Yeah. And Tesla Yeah.
Speaker 1:Coming together. It's it's it's good to have more involvement, but still I think the entire project
Speaker 2:No. We've seen we've seen a few of those, like, AI leader gatherings in DC where you see Tim Cook and and Sundar and Sam Altman and Dario and all the the whole all the leaders are together. And I was always hoping that at one of those dinners, they would say, okay. Everyone's gonna try and say the biggest number, but this time it's gonna be how much you're committing to Intel and how much you'll buy from them if they come online with a competitive product. Because the demand side has always been a big problem for Intel that they have the capability, they have plans to build the two nanometer, three nanometer plant like a frontier plant, leading edge fab.
Speaker 2:But every other company has been so tied to TSMC. But we I think everyone now acknowledges that TSMC is not investing super heavily in CapEx. They're not going they're not scaling up as much as the industry would like them to. And so lots of folks have sort of signaled towards a chip bottleneck coming in the next few years, and Intel has the opportunity to communicate that. This seems like the first step in that chain.
Speaker 2:So companies, including Tesla, often design their own semiconductors but need a supplier to actually make the so called make them in a so called chip fab. Musk's companies have sourced chips from a wide range of suppliers including Nvidia, Samsung, Taiwan Semiconductor. Oh, I got it. Musk said that TeraFab is needed because his company's demand for chips is is slated to far outstrip the supply it gets from partners. I was listening to Chuck Robbins from Cisco talk about data centers in space and the heating issue came up and and he was like, yeah, I don't I don't I I don't really have like a a solid answer for that yet.
Speaker 2:But I do think that if you are bullish on data centers in space, you have to start with the fact that Starlink works in space currently because it is doing compute. It's
Speaker 1:You not couldn't doing possibly put let's We be honest, couldn't possibly put a computer up there.
Speaker 2:Yeah. Like, there there are computers with they don't they they can't inference frontier models. They can't you know, it's not gigawatts in space yet. But there are, I believe, the entire Starlink cluster, megawatts of compute in space with solar panels. And they do heat up because you are running a chip that routes packets across the Internet from one satellite to the next to get you your Internet via Starlink.
Speaker 2:And so it's not that it's a solved problem. It's that we are actually we are on a path to, you know, deploy some level of compute in space. Tyler?
Speaker 3:Yeah. I mean, we we've seen like Philip Johnson, like, there are chips in space right now. Like, their GPUs, I think, Arthur, he said there were like five or six h one hundreds. Right? Yeah.
Speaker 3:Yeah. So so like they do work. It's like the Yeah. I think most people's problem with space data centers is that it's like economically it doesn't make any sense.
Speaker 2:Well, so yes, that is the correct angle but a lot of people are getting Not that it's like $100. No. No. There is a whole conversation about like like it is impossible. And you need to like move past that into the economic equation which then gets you into timelines and actually thinking about what needs to happen to dissipate that heat.
Speaker 2:But clearly, yes, you can. I mean, you can put humans in space on the IFS and cool that. They're like, have created ways to move heat around in space for decades. It's obviously a new challenge. But I think starting with the baseline of like, it's there is compute happening in space right now.
Speaker 2:We're going to try and I mean Elon wants to like 1,000 exit, 100,000 exit, million exit. I don't even know how what the scale is, but orders of magnitude. And so there's new engineering challenges. But at the very least, it's it's worth it's worth acknowledging that there is computation happening in space at scale with the Starlink cluster. Anyway.
Speaker 1:Speaking of space, looks like Elon is going to use SPCX as ticker for the SpaceX IPO which he had to acquire from Matt Tuttle, hence the ETF's ticker change shown below. Eric from Bloomberg says, we predicted this could happen in a December note. Nice catch by Will who famously gave the Meta ticker to Zuck. I did not know that Will Hershey had the meta ticker previously. So know we know somebody that spots on
Speaker 2:Who who had the meta ticker?
Speaker 1:A guy named Will Hershey.
Speaker 2:Oh, interesting.
Speaker 1:There's a company called Round Hill. But we know somebody who's
Speaker 8:I think
Speaker 2:it was Matt Ball.
Speaker 1:We had somebody here Yes. Come in outside of show hours and say that they were squatting on a bunch of tickers and the and the idea I seems so I I think I think what what what might be the reality is that you actually that it needs to be it needs to be further along than just reserved. I don't know
Speaker 2:I think so.
Speaker 1:Having it. You can go. If you're a startup today, you can go reserve your ticker today. You can. But I'm not sure that that actually gives you enough leverage to when when Elon comes knocking ready for an IPO, you actually have priority over.
Speaker 2:I think you have to actually be doing something with it. So if I have it correct, I'm looking it up to make sure that I have the facts straight. But the Matthew Ball started an ETF based on the metaverse, which was he wrote a whole book about the metaverse and had a series of blog posts outlining the broad trend and the various companies that would benefit from that. And so The chat Ticker squatting.
Speaker 1:Ticker squatting.
Speaker 2:The team does not like, okay. Roundhill squats on lots of tickers. That's interesting. I don't know. Apparently, Meta Materials was in that ticker for a little bit.
Speaker 2:There's been a few others. I think Roundhill creates ETFs. ETFs. I think if you have an active ETF, that's a lot different than just having a reservation. Although, I don't know.
Speaker 2:Maybe you do get paid off. What?
Speaker 3:So this fund, it was only like $10,000,000. So it's very small. So you actually could like Yeah. Yeah. Mean, $10,000,000 is still like
Speaker 2:It's a lot of
Speaker 3:money, know, but it's still a fair amount
Speaker 2:of money. But you could potentially launch an ETF with 10,000,000 of
Speaker 6:Yeah.
Speaker 3:Like if you have a really good ticker.
Speaker 4:Yeah. You know
Speaker 2:Good ticker.
Speaker 3:You could you could definitely make an argument that like, yeah, it's worth over $10,000,000 and you can somehow marshal enough capital to
Speaker 2:to Yeah.
Speaker 3:You know, do something with it.
Speaker 2:There was a there was a YouTube influencer who launched an ETF and it it sounded so good on paper because it was like, wow. Like his audience came together and put like $10,000,000 into this ETF. But it was like generating something like three basis points of fees or something. So regardless of how it was like regardless of what the fund did, like, actual flow would be, like, less than what he was earning in YouTube ad revenue. Like, a few thousand dollars a month would be, the net gain from the from the ETF effort, and I think it was something that got wound down pretty quickly.
Speaker 2:Anyway, I broader had take on Elon and Intel. So back in 2022, I was trying to imagine this divergent path, road not traveled of Elon buying Intel because Intel
Speaker 1:Yeah. We talked about this before. There was a moment where people were tracking like Intel's Yeah. Corporate jets Yeah. Elon's.
Speaker 2:And GlobalFoundries too. But yeah.
Speaker 1:Yeah. And it seemed but I think it ultimately ended up just being election related.
Speaker 2:Yeah. Yeah. I think so. Yeah. They happened to be at Mar A Lago maybe at the same time.
Speaker 2:But it it was it was such a cool idea because Elon had you know, mean, he'd run PayPal and stuff. He he had some experience in, like, software, but he hadn't run a social network. So there was a lot of there was a lot of questions about, like, what would happen to Twitter? Would he be able would he need to change the business model? He wound up doing subscriptions.
Speaker 2:He wound up being a good exit because he rolled it into XAI, which rolled into SpaceX, so everyone did fine. But there was a lot of like, okay, dollars 44,000,000,000 for Twitter, which after the ZERP era ended, all of those companies traded down 60% or something. So there was a lot of chatter around is this a good deal? Is this a good use of his time? He's known for running incredibly intense engineering operations, making self driving electric cars rockets that land themselves.
Speaker 2:Semiconductor fab feels more like that than social network feels like rocket factory, right? It is a factory at the end of the day. And so I was trying to work backwards from like, could that actually have happened? I don't know. The numbers I had were so at the 2022, Intel was a $110,000,000,000 market cap company.
Speaker 2:Like, that's a huge company still even though it had been beaten up in the public markets. But Elon had just put together $44,000,000,000 to buy Twitter, and the CHIPS Act had put, in 2022, had just put together $280,000,000,000, including 53,000,000,000 specifically for US semiconductor manufacturing.
Speaker 1:Also, just think about where Intel would trade if Elon
Speaker 2:Had been able to own it or I roll it mean, it would be it would be like just putting together the 44,000,000,000 was a herculean effort and there was a ton of debt and there were all these different parties Yeah.
Speaker 1:Just a much, much different business.
Speaker 2:110. And and it's not like you can just go buy the company at its lowest possible value. You have to make an offer that all the shareholders will approve of and potentially be higher than the than than what the market cap is because if you're if you're an Intel shareholder and you're looking at a $110,000,000,000 market cap, you would imagine that it could go up and it did. It's now over, what, 200,000,000,000 Intel market cap? What what what are they at right now?
Speaker 2:260. So, like, if you if you if you were a shareholder in 2022 and you were at one ten, you probably, you know, are happy that you didn't get bought out at that time. But it was possible. It wasn't that much of a stretch to imagine something happening there four years ago. We didn't wind up on that path.
Speaker 2:But, you know, my hope is that this is the first step on the long road to generate enough demand for domestic chip manufacturing to really move the needle Because I'm rooting for Intel and I'm rooting for American semiconductor supply chain. Tyler went over to the TSMC plant in air in Arizona. It seems like it's going well.
Speaker 3:Yeah. It's huge. It's huge. They didn't let me in.
Speaker 2:They didn't let you in. But we need more, very clearly. And Intel is working on that, fortunately.
Speaker 1:Alright. We got to talk about a corporate retreat that went badly wrong.
Speaker 2:Okay.
Speaker 1:Technology company Plexx took its 120 employees to Honduras for a week long bonding experience. It was a disaster from the moment they arrived. Senior executives at the tech company Plex were eager to treat their 120 fully remote staffers to a week long corporate getaway in a tropical paradise. Pop quiz. Tyler, do you know what Plex is?
Speaker 2:I don't know about Plex. No. Have we seen
Speaker 1:Plex before? I don't know either. So we all failed, but now it's your job to figure it out. I will continue. The plan for the Honduras trip was simple.
Speaker 1:Company meetings and team Streaming building company? By powdery soft beaches during the day and island fun at night at a cost of roughly half 1,000,000 to the company. They'd build the trip around a survivor theme with teams and challenges, but it'd be fun, not too physically grueling. The CEO of Plex, a free streaming platform, would play a role similar to that of survivor host Jeff. Perhaps the executive should have taken it as a sign that just as the first bus of staffers pulled up to the resort, the chief executive was already in his hotel bathroom experiencing the initial waves of violent stomach infection.
Speaker 1:What followed was a comedy of errors including military drills that outpaced anything this group of office workers had in mind, a rogue porcupine stranded airplanes and one syringe to the butt of an employee. Corporate retreats are generally assumed to be torture or at least a semi stressful chore, what with their forced fun activities and hybrid work play environments that leave workers confused about boundaries. Is that is that like the industry standard? That seems wild. I don't know.
Speaker 1:I don't
Speaker 2:think I've ever been on a corporate retreat. I've been on some like Founders Fund events, those aren't really retreats. Those are more just like conferences. But I don't know. Corporate retreat seems I don't know.
Speaker 2:Never unexplored territory for me.
Speaker 1:It's no wonder the new season of Jury Duty, a comedy series that tricks an unsuspecting non actor into believing his off the wall fictional circumstances are actually happening is set at a corporate off-site. But in real life, Plexcon twenty seventeen beats anything on TV. Here's the story of an all staff company getaway told by six people who were there, a trip where most everything that could go wrong did go wrong. Nearly a decade later, they're still working together and still talking
Speaker 2:about it. It was bonding experience.
Speaker 1:Yeah. We all worked together. Well, yeah. It's crazy that this
Speaker 7:is
Speaker 1:now now coming out. So Sean forty two, founder of Monoker Partners, an independent corporate retreat agency that planned the trip. About three weeks before we arrived in Honduras, we got an email from the hotel's general manager that said, I will be departing. I wish you the best with your retreat. I knew something was off.
Speaker 1:Three days later, another email. The head chef was no longer gonna be at the hotel. Scott fifty two, chief product officer and Plex co founder. We get there. We've got to take the bus from the airport.
Speaker 1:Dirt roads, you start getting closer and there are guard towers around the property. People with machine guns and stuff. A lot of people were like, where are we going? Keith, the CEO of Plex, fifty four. We usually go a day early and we set up.
Speaker 1:If there's any little thing, we have to get it right just so the employees have the best experience possible. Keith woke up the day that people were coming in Sunday morning and he is sick as a dog. Everyone there is fried. Basically, people are telling me don't eat the vegetables, don't eat the vegetables.
Speaker 2:Eat the vegetables. That's like the
Speaker 1:No. No. No. Because they they clean it, they wash it in water. It's usually not filtered water.
Speaker 1:Right? Because it would just be kinda crazy to
Speaker 2:Yeah. Yeah. Here it is.
Speaker 1:I I So I've gotta have a salad, just one salad. So I got e coli, which maybe the worst thing you could get possibly ever. Just as people were arriving on the buses, I was like, I had lost eight or 10 pounds. They had a doctor come to me, which apparently is pretty standard. They nailed an IV bag to the bedpost.
Speaker 1:Just nailed it. People are arriving for a party that night. The next day is Survivor theme kickoff. There's not one person on the planet more excited about Survivor than Keith and his wife. They have watched every single episode.
Speaker 1:My wife and I met Jeff, the host of Survivor. What what I wanted is when everybody shows up, I do a Jeff. Welcome to the island. Here's the theme for the week. But Scott got to do it.
Speaker 1:The opening Survivor thing was a contest where people on their different teams open up a platter. You have to eat what's on the platter. Sean. Sean, who's the Plex head of business development. Who are gonna call?
Speaker 1:Yeah. Somebody is somebody is cold texting me Oh, yeah. Pitching me their their startup and they've called me a bunch of times today.
Speaker 2:Wait. Is it actually them or is it their AI agent?
Speaker 1:I I wish I could pick up. It's just like a little bit Yeah. Little It's too bit much too to
Speaker 2:picks up
Speaker 1:But yeah, texting somebody like getting their number, I I don't think that's the new meta. No. It's it's it's bold.
Speaker 2:We we heard from an executive in in tech that they are getting dozens of emails every single day trying to recruit them. And every email comes from a new Gmail account that's un that's, like, unregistered, brand new. But it's all, like, you know, LLM written, very different, like, doesn't really do all the research but has a few keywords in there. And it's clear that someone is is building sort of, like, a next gen recruiting agency that's basically just a lot of spam. Feels like the the the end result will be like a return to relationship building and not like broad top of
Speaker 1:I should read the cold the cold text from this morning.
Speaker 2:Can you And
Speaker 1:I have nothing again nothing against cold, cold email and just, you know, being being bold, but I did read this out loud to you, John, so I'll read
Speaker 7:it to everyone.
Speaker 1:Mhmm. So I got a text from an unknown number today at 7AM. Alright, Jordy. Good news or bad news first? This is blank.
Speaker 1:And I'll leave the name out. And then I just get a PDF of a deck and then a text. Alright, Jordy. The bad news is this was an unplanned introduction and on the surface, probably lukewarm outreach. The good news is that there's zero doubt you're now in touch with the founder with the most grit of anyone you've interacted with the past twelve months and likely anyone you'll interact with over the next twelve months.
Speaker 1:50,000 seed round passes over the past ten months here to make 50,001. So so, you know, you should be coming in being like, I've been passed on 50,000 times.
Speaker 2:Yeah. I'm hoping is that the gets through.
Speaker 1:That gets through.
Speaker 2:That seems like a rough estimate though.
Speaker 1:Every months of feedback and iterations have made us better, so you're seeing more quality more quality presentation than rejection 10,000. Looking forward to your message.
Speaker 2:The chat wants the builder to pitch. They want you to hear this out. Everyone's in favor of this.
Speaker 1:Wait. Wait. Pitch who?
Speaker 2:You they they the wants you to get on the phone with them. Do it live. I mean, they wanted to do live. I don't know if you should do live, but you should take the call and and get to the bottom of it.
Speaker 1:I will take the call. I will take the call. But
Speaker 2:Let's go back to the Corporate Retreat.
Speaker 1:So they hire they hire a former Navy SEAL
Speaker 2:Okay.
Speaker 1:To basically haze the team on the beach. Mhmm. And you can pull up a picture, an image here.
Speaker 2:The quote is this is not a super fit group in general. One of our biggest mistakes was hiring a former Navy SEAL to pump the team up. As I'm in my room dying, I could hear them out there doing all the drills and yelling. And so I'm in here thinking, this is terrible. It sounds terrible out there too.
Speaker 2:We're doing army crawling on the beach. It was a 100 degrees. I bailed out partway through. I went into the ocean just to cool off. I went in probably on all fours because I was tired.
Speaker 2:It's not a fit group, not a super fit group in general, the ex Navy SEAL is like, we can tone it down. No problem. We get up there and it's hot and humid and people are passing out. I don't think he'd ever seen quite such an unfit group. We ended on, I guess, what's probably a golf course.
Speaker 2:On command, everyone had to hit the grass. Everyone's silent. We're pretending we're Navy SEALs, but I happened to land in the wrong spot. I'm just like, oh, God. What is happening?
Speaker 2:I was sitting on a fire ant hill. I was wearing shorts. I jumped and had my I had hives and bumps from the bites. This is ridiculous. Someone saw an alligator on the golf course.
Speaker 2:Sounds like a ridiculous There
Speaker 1:was a porcupine that fell through one of the ceilings.
Speaker 2:This is like a fire festival for
Speaker 1:corporate The fire festival of corporate retreats.
Speaker 2:I it's it's fun that this this porcupine is horrifying. Wow. Look at this guy. Rick Phillips discovered this in his room shower. The hotel got pretty much just got the porcupine and left.
Speaker 2:I guess it for me, was a good thing because being a non talkative software engineer, I got some notoriety. It's a beautiful resort there, sand fleas. They had to fumigate every day. What a weird quote. We did a nice dinner down the beach and everyone got bit by the sand fleas that weren't supposed to be there.
Speaker 2:We all got matching tank tops.
Speaker 1:Real life real life episode of The Office. Anyway. You can imagine Michael Scott.
Speaker 2:There is some breaking news. Anthropic is set to preview powerful mythos model to ward off cyber AI threats. The AI company is partnering with Amazon, Microsoft, and others to offer the new model to find and patch software bugs. This is from The Wall Street Journal. Anthropic is taking steps to arm some of the world's biggest technology companies with tools to find and patch bugs in their hardware and software.
Speaker 2:The company is making a preview of its new AI model called Mythos available to about 50 companies and organizations that maintain critical infrastructure, including Amazon, Microsoft, Apple, Alphabet owned Google, and the Linux Foundation. Cybersecurity researchers and software makers worry that artificial intelligence is becoming so good at exploiting vulnerabilities that it could cause widespread online disruption. Security experts have predicted that AI models will discover an avalanche of software bugs, and the effort is set to help companies stay one step ahead of cybercriminals and other threats. This feels like a very good rollout strategy generally, both because we've seen a huge amount of of cyber attacks and and hacks and accidental releases. Like, even if it's not, you know, there's been we had a member of the security team from CrowdStrike on the show last week talking about the the rise in cyber attacks broadly.
Speaker 2:And so getting the getting the the the the most frontier models in the hands of big companies early, Great from that perspective, and then also just great as a product demo, which will get the entire organization excited about deploying the technology broadly. So very good is like a as a b to b go to market motion. This makes a ton of sense. When measuring the dollar cost to find a bug, Mythos claims to be about 10 times as efficient as previous AI models. Details of Mythos' capabilities were previously reported by Fortune.
Speaker 2:While Anthropic has no immediate plans to release Mythos, other models will likely match its bug finding capabilities within the next few years. Graham said, we basically need to start right now preparing for a world where there is zero lag between discovery and exploitation. So very carefully rolling these out. The Cloud Opus 4.6 found more high severity bugs in Firefox in two weeks than the rest of the world typically reports in two months. And so good good news there for cyber security.
Speaker 2:There is some
Speaker 1:Some news yesterday in the New York Times, shots fired at Indianapolis councilman's home after a boat that was backing a data center. No one was injured, but councilman Ron Gibson called it deeply unsettling that's broke on X yesterday and Alex writes in the New York Times. Bullet hits bullets hit the home of an Indianapolis city councilman early Monday morning leaving shattered glass and holes through the front door and a handwritten note reading no data centers was left under the doormat. The councilman Ron Gibson was among the city's leaders who voted six two last week to approve a rezoning measure that would allow Metro Blocks, a Los Angeles company, to build a data center on the Northeast Side Of Indianapolis. Local residents had protested the proposed data center for months citing concerns about environmental impacts and changes to a historic neighborhood.
Speaker 1:Dozens of people filled the city council chambers city county council chambers last week before the vote holding signs and speaking in opposition to the data center, the station reported. Gunfire at his home crosses a line, mister Gibson wrote in an emailed statement. I understand that public service can bring strong opinions and disagreement, but violence is never the answer especially when it puts families at risk. So very, very dark, situation. Mister Gibson wrote that he and his eight year old son were awakened by the gunshots between 12:45 and 12:50AM Monday, and he rushed to reassure his son that he was safe.
Speaker 1:He said 13 rounds were fired at his home with bullets striking just steps from the dining room table where his son had played with Legos the day before. Incredibly incredibly dark. Rune says, just so everyone is clear, this is evil. You are justified in thinking it's morally bad. Tons of apologetics happening for bad people.
Speaker 1:If you think behavior like this is just desserts for the tech industry due to some hobby horse you have, you've gone insane. And, Noah Smith says, we may still be underrating how big of a political issue AI is going to be. Mhmm. And, there's a video here from CBS we can we can put the sound on.
Speaker 2:Oh, yeah.
Speaker 10:Just days after voting in favor of building a new data center in Indianapolis, local council member Ron Gibson says he woke up to the sound of gunfire overnight. Gibson said 13 rounds were fired at his home while he and his eight year old son were asleep. Some of those bullets landing just steps from their dining room table where his son was playing with Legos the day before. When he stepped outside, he says he found this handwritten note reading no data centers under the doormat.
Speaker 5:There are real benefits tied to this development. Construction is expected to support roughly 300 jobs over a three year period.
Speaker 10:While some counselors argued the data center will bring revenue and jobs, there was push from residents over environmental and quality of life concerns.
Speaker 4:Thank you very much.
Speaker 10:The vote to move forward passed six to two. Indianapolis police are calling this an isolated and targeted incident, and police have yet to identify a suspect. And one group that protested at data center last week released a statement today saying in part, violence has no place in our community or in our advocacy. The FBI now assisting in the investigation. Tony?
Speaker 5:Chanel, thank you
Speaker 2:for Yeah. Noah Herschel in the chat says people have gone insane. It is it is extremely disheartening to see. I mean, I I would hope that the, the case to be made for data centers is much more complex than 300 jobs over three years. Like the rate payer protection pledge, the environmental concerns, all of that needs to be addressed and communicated not because of this.
Speaker 2:This is, you know, horrible. But just in general from the from the public that has pushback and and reticence about the data center development.
Speaker 1:Yeah. Local tax revenues.
Speaker 2:Yeah. And and it should be it should be a boon to every community and the community should feel like the net benefit is truly positive. And I feel like people, many, many community members do not feel like it's in their favor. And so there's a lot to do on that front. In some other more positive news, OpenAI, Anthropic, Google are uniting to cop to combat model copying in China.
Speaker 2:This is a bigger discussion around AI safety. We've talked about this. Look at that. Some some Who knew? Faith in human Who knew that
Speaker 1:you could get along?
Speaker 2:Yes. I mean, I'm sure people in the chat have seen the New Yorker article where there's just tons and tons of quotes from various AI leaders all, you know, upset with Sam Altman. And the the the inter AI drama has been bubbling up since the dawn of OpenAI. Like, OpenAI was started as a reaction to Google, and then, you know, Anthropic leaves and teams up with Google. And then Elon doesn't like Anthropic.
Speaker 2:And then Ilya Sutskever and Mira leave, but they don't join Anthropic. And so there's been so many personalities and so many disputes. I feel like the the the takeaway is that this is all extremely high stakes. There's a technological, you know, transition happening, a huge amount of money on the table, a huge amount of influence on the table. And so everyone is sort of clamoring for their share, and it's creating a lot of a lot of friction.
Speaker 2:But my overall takeaway from the from the New York article was a lot of that had been already reported out. A lot of that was, you know, we sort of knew that there were rivalries and and and, you know, a lot of hurt feelings between different members of the AI community and nothing was particularly shocking to me. But if you have more comments, please leave them in the chat. Let's go through this. Pull it up.
Speaker 2:Thiscom what's actually going on with this this model copying in China question. So rivals OpenAI, Anthropic PBC and Alphabet Inc's Google have been gone have begun working together to try and clamp down on Chinese competitors, extracting results from cutting edge US artificial intelligence models to gain an edge in the global AI race. The firms are sharing information through the Frontier Model Forum, an industry nonprofit that three tech companies founded with Microsoft in 2023 to detect so called adversarial distillation attempts that violate their terms of service according to people familiar with the matter. The rare collaboration underscores the severity of a concern raised by US AI companies that some users, especially in China, are creating imitation versions of their products that could undercut them on price and siphon away customers while posing a national security risk. And so I was trying to square this question of distillation and model commoditization with the news that Anthropic has reached 30,000,000,000 in run rate and has agreement with Google and Broadcom for multiple gigawatts of TPU capacity.
Speaker 2:Like, clearly, is insatiable demand for frontier tokens, frontier models. They're incredibly expensive to train. We saw in the Wall Street Journal that that these
Speaker 1:Expected training costs from Yeah.
Speaker 2:It was training and and
Speaker 1:in France but it
Speaker 2:was hundreds of billions of dollars. And so the hope is that you is that you're able to amortize that over over at least a couple years, you know, a long time, ideally. The the the shelf life of a model after you train it is pretty limited if you're being commoditized and copied. If you're being distilled, it's even faster. At the same time, it's just staying on the frontier clearly leads to an incredible ramp in revenue.
Speaker 2:So is commoditization a real problem? It feels like it's almost just more of a problem from an AI safety perspective because you can't have the geopolitical conversation like what Bernie Sanders is proposing around different different labs working
Speaker 1:Pausing together element.
Speaker 2:Potentially pausing or slowing down or just just even adding more constraints and reviews before models get released. It's harder to do that if you have a different country that's racing ahead and moving much faster and trying to close that gap. Now, if the model is delayed in America and their whole strategy is to to distill the model, well, then they're still three months behind even if we take three months off in America. So maybe that's not an issue. But it it it was an interesting was an interesting development.
Speaker 2:So the I guess models get bigger and more powerful. Hopefully it becomes easier to track distillation efforts. Would imagine So what is the canonical example of the distillation question? Was that originally deep seek, Tyler?
Speaker 3:I mean, I I don't know if it's very hard to prove. Right? Sure. Because it's like, how do you you know, you don't if you just look at the weights, there's no way to really tell.
Speaker 11:It's just
Speaker 3:like you just ask the model, you know, who are you? And then it says, I'm Claude. Yeah. It's like, okay.
Speaker 2:Yeah. Yeah. That's the smoking gun. But that doesn't always happen because you can remove all references to Claude.
Speaker 3:Yeah. Like like people were saying when, you know, DeepGeek first like came on, everyone's like, oh, wow. This is so good. Yeah. People at OpenEye were saying like, okay, they've distilled on this.
Speaker 3:Yeah. But like was there any like proof? Not really. Maybe just like vibes if you talk models a lot, you see that kind of respond similarly
Speaker 1:Yeah.
Speaker 3:Compared to other models.
Speaker 2:And and I mean the smart strategy if you are a distiller lab would be to generate a bunch of tokens from Google, Anthropic, and OpenAI, mix them together so that maybe every once in a while it says it's Claude, but only one third of the time because you have a whole bunch of other tokens from other from other models and it all blends together. So that actually underscores the need for the Frontier Model Forum and the three companies working together.
Speaker 3:I do wonder how you, like, actually combat this. Yeah. Because it seems very hard unless you basically just say, the only people that commit the API are, like, trusted enterprises and you have to sign these big contracts before which I think is there's a good case for me for for for that being, like, the the way forward.
Speaker 2:I I mean, it doesn't seem that crazy to do, like, varying levels of KYC for varying levels of token spend or or enterprise contracts. So if you are if all of a sudden it's like you're doing meta level inference, well, let's make sure that it's meta that's actually the one on the other side of that contract and that they're not vending the Frontier tokens into another, like reselling them basically in some way. So you need a chain of know your customer. But in theory, you should be able to have a $200 pro plan that only that does not ever deliver the level of tokens to fully distill the model. And then as someone ramps up on the API and they're spending 5,000 a month, okay, you do a little bit more of a check.
Speaker 2:Then they're spending $100,000 then they're spending $10,000,000 And once they get up, like every lab must know, okay, to distill this you probably need to spend $100,000,000 $10,000,000 whatever the number is, set the KYC threshold there and but it's going to be cut in a third because it's going to happen across all of these labs. So whatever their whatever their threshold is for, okay, it's really time to go and and do the do the proper KYC, you sort of need to divide that by three because you have to assume that it's happening across all three. And then it's also probably happening across multiple smaller organizations that are, you know, essentially fronts and are harder to KYC. But I don't know.
Speaker 1:Let's do a lightning round of
Speaker 2:Timeline?
Speaker 1:Posts. Okay.
Speaker 2:What do got?
Speaker 1:Reid Wiseman. He's an astronaut. Yeah. He's on Artemis II. Yeah.
Speaker 1:12/07/2016. He posted at 08:47 a. M. Dreamt I was in lunar orbit last night. Been in that post vivid dream that wasn't real funk all morning.
Speaker 1:And yesterday, he made it real.
Speaker 2:Wow. I I I saw this post and I was like, oh, like that's just like some random poster like, okay, cool. Like, yeah, cool cool story. Like, yeah, anyone could have that dream. Didn't realize that it was actually the
Speaker 1:Almost 10 years old.
Speaker 2:Astronaut who is now on on around the moon and making his way back to to Earth. There was another cool video from the from the moon mission. Astronaut Victor Glover discussed what it means for him and the entire Artemis two crew to be observing Easter Sunday from space during their historic mission. We should pull this video up. It's on x.
Speaker 2:It's about a minute long. Let's see if we can play this.
Speaker 12:I think these observances are important. And as we are so far from earth and looking at, you know, the beauty of creation, I think the, for me, one of the really important personal perspectives that I have up here is I can really see Earth as one thing. And, you know, when I read the Bible and I look at all of the amazing things that were done for us who were created, it's you you have this amazing place, this spaceship. You guys are talking to us because we're in a spaceship really far from Earth, but you're on a spaceship called Earth that was created to give us a place to live in the universe and the cosmos. Maybe the distance we are from you makes you think what we're doing is special, but we're the same distance from you.
Speaker 12:And I'm trying to tell you, just trust me, you are special. In all of this emptiness, this is a whole bunch of nothing, this thing we call the universe. You have this oasis, this beautiful place that we get to exist together. I think as we go into Easter Sunday thinking about, you know, all the cultures all around the world, whether you celebrate it or not, whether you believe in God or not, this is an opportunity for us to remember where we are, who we are, and that we are the same thing and that we got to get through this together.
Speaker 2:I love it.
Speaker 1:Powerful stuff.
Speaker 2:Great mission.
Speaker 1:Great team cycle. Yeah. Having a g f is insane because it's literally unlimited chat with no tokens spent.
Speaker 2:There you go. What did sucks say? Is three weeks too young to give my baby a reticrutide? Not trying to raise a fat porky butterball. Yes.
Speaker 2:It's too young. Be careful out there. Have you seen this image of the Instagram growth growth guru? This goes viral constantly. And normally, it's reaction video, but someone took that this exact message and put it on accident.
Speaker 2:It went mega viral with a 130,000 likes. Instagram go growth gurus are so funny. He can't use his laptop because he's holding a drink. He can't drink because he has a cigar in his mouth. He can't smoke his cigar because both hands are occupied.
Speaker 2:I think I think this is surmountable, though. I think you can actually hold the cigar with the martini or something. But it is a true, like, peak performative growth guru. Very, very funny, but I'm sure I'm sure it had its intended purpose. Chase Passive Insuff says, that's my mentor you're talking about.
Speaker 2:He makes multiple 8 figures in passive income and only charges $25,000 for a full day full day boot camp mastermind to teach me his strategies. Delete this. What is
Speaker 1:High yield Harry dialing into our morning meeting. Morning stocks are down slightly after Trump announced a whole civilization will die tonight. Really dark over on
Speaker 2:It's gonna be crazy.
Speaker 1:Pretty social Crazy. Today and hoping
Speaker 2:Yeah. It's on the cover of the journal today. Trump Trump stirs fear in Iran over talk of attack. President says the US military could take out the entire country in one night. President Trump said Monday that the US military could take out the entirety of Iran in one night, and Iranian officials have told mediators now to trying to reach a last ditch ceasefire deal that they that they fear Trump will follow through on a massive attack Tuesday night.
Speaker 2:So we are we are continuing to hope hope for a resolution to the the geopolitical conflict. It's very, very frustrating. And, yeah, it would be so much better to refocus on problems at home and opportunities at home.
Speaker 1:Anyway Moving on. What is Piratewire saying about Sattrini, analyst number three? Ryan writes, our newspapers used to put reporters in active war zones. They've stopped, so new media is picking it up. Last week, research firm Sattrini put a man in the Strait Of Hormuz to figure out what is going on in the oil world.
Speaker 1:Sattrini's quadra quadrilingual employee referred to only as analyst three packed a bag with $15 in cash, some zins, and cigars before shooting over to Oman. After managing to finagle his way onto a speedboat, analyst three reported from the water just 18 miles away from the Iranian coast while smoking a Cuban. In a world, where the New York Times is calling, NATO the North American Treaty Organization, we've got live financial reporting from Iran. Yeah. This this was just absolutely an insane story.
Speaker 1:An insane story if you can just do things.
Speaker 2:Totally. Yeah. I'm talking to Sattrini about coming on the show later this week. Obviously, he's been working incredibly, incredibly hard with his team to report and publish this and and turn things into analysis. And there's a whole deep dive that you can read on Suttrini.
Speaker 2:And just what a fantastic piece of reporting. Truly unexpected. I didn't think anyone would do this. We were joking about it and they just went and did it.
Speaker 1:What's going on? We stopped doing ads but NASA NASA's doing ads torch.
Speaker 2:Okay. Let's see it.
Speaker 1:They have a
Speaker 2:Is that a A number. Spurge Daddy or something? Yes. Scrub Daddy. Yes.
Speaker 2:That's the viral, infomercial product. Right? Yes. And then a liquid death as well?
Speaker 1:Is there a liquid death?
Speaker 2:This is this has to be fake. Right? The Taco Bell thing. This is a joke? I can't tell.
Speaker 2:Is the Nutellas in here? These are all to be real Nutella. AI generator or something. Yeah. Grock wanted me to tell you it's real.
Speaker 2:I don't know. It does seem like people are are having fun with this. But, yeah. Very it's very funny.
Speaker 1:Alright. Andrew Huberman says ninety three years and two hundred and thirty day one days old in Isil Stin dead hangs for two minutes and fifty What? Two seconds to set new world record.
Speaker 2:We tried this this morning. Yeah.
Speaker 1:We did this this morning.
Speaker 2:Two minutes and fifty two seconds is truly an eternity. I don't know if that's in the cards for us. Maybe maybe we can get there. We what what is CARPA at? Five minutes something?
Speaker 1:Yeah. CARPA is at around five minutes.
Speaker 2:Absolutely insane.
Speaker 1:Yeah. These these numbers don't sound big, but you start hanging. Yeah. And it is absolutely brutal. So congratulations to to Anne.
Speaker 1:Yeah. What a feat.
Speaker 2:What a feat. Well, we have Riley Walls in the waiting room. Let's bring him in to the TBPN Ultra Realm. Riley, how are you guys doing?
Speaker 4:How are you guys? Are you We are good.
Speaker 2:Are you where I think you are? Introduce yourselves. Explain where you are.
Speaker 4:Are at the alley. We're live at the alley.
Speaker 2:Live at the alley.
Speaker 4:This is this is the street right here. Okay. Yeah. Life is good. This is my friend Patrick.
Speaker 4:We worked on the alley together. Yeah. This is a really fun project. Yeah. We yeah.
Speaker 4:It's it's been a blast.
Speaker 1:Give us the full history Yeah. Of of the alley, how you guys came to own it, and then we'll get into this project.
Speaker 4:Basically, we learned that this this alley was foreclosed on. It's kind of a long story where this this woman actually bought it thinking that she was buying this house right here. No. That is No. Is this one.
Speaker 4:Oh, is. Which which was which is worth like a million dollars She bid 25 k on it thinking that she was getting the steal of a lifetime. She won.
Speaker 1:Is this the kind of thing she didn't she didn't want to tell anyone like because she was like, okay, this is like probably thought it was too good to be true but then like Yeah. Maybe it was real so she didn't want to tell anyone if she she
Speaker 4:knocked on the doors because this is an apartment building and she knocked on the doors and told the tenant she was not raising the rent. So she was she so she really thought she owned this and then she realized she didn't and then there there was a whole news story about her mistake. And then we we eventually reached out to her and and negotiated for a little while, and we we bought it for a little more than she actually bought it for. So she got bailed out, and we we were able to do a nice thing and still do this crazy project.
Speaker 6:That's amazing.
Speaker 2:So did you find this alley from the news article? Is that how this all started?
Speaker 4:Yeah. We we had the the Patrick and our friend Theo and I, the three of us, we had been talking for, like, a a while before that about buying a different alley in San Francisco. Sure. But we we couldn't end up buying that one. But we we saw this news and were like, oh, this is perfect.
Speaker 11:Yeah. Yeah. And we we tried to we tried to email her to to, you know, get us get us the offer. But Riley had to send send a letter in in the mail.
Speaker 2:And she got the letter physically?
Speaker 4:Yeah. Physical sale mail
Speaker 2:works. Okay. So it transfers to you. You you own it. And then what what rights are you entitled to?
Speaker 2:Because clearly it's not the house next door, but you own something. Right. What exactly do you own?
Speaker 4:We we spent a a good amount of time with lawyers to figure out what actually is allowed. Yeah. There's actually a car. It's driving right at us right there. We have to move out of the way.
Speaker 2:If you need to move, you can show us wherever. Take us on tour. What neighborhood is this by the way?
Speaker 4:This is in the Sunset. Okay. Just like the 24th
Speaker 9:in 23rd. Yeah. 24th in Kirkland. Okay.
Speaker 11:It's sort of middle of Sunset. Sorry.
Speaker 4:It's live on air. There's a car coming.
Speaker 2:There's a car coming down the alley. Okay.
Speaker 6:So it's
Speaker 4:a This fun actually a great question because we we yeah. Live demo here.
Speaker 7:We we
Speaker 4:so we we legally can't block the alley, so we are obliged to move. That is actually in tandem with the the question you guys just asked. Yeah. We we can't block it. Cars have the right to drive down it because there's there's easements
Speaker 2:Okay.
Speaker 4:Here. But we do have the right to paint anything on the surface of the street.
Speaker 2:Okay.
Speaker 4:And we also can give the alley a name.
Speaker 2:Okay.
Speaker 4:So yeah, it's it's
Speaker 2:already assigned? Does the alley have a name? Has it historically had a name?
Speaker 4:No. So it it Google Maps calls it Dirt Alley. Dirt? We think that some editor randomly added that like a couple years ago but it's nowhere else.
Speaker 2:Okay.
Speaker 11:It says that name. No official name.
Speaker 2:And then and then is there any square footage that anyone could build on? Is it or is it just the actual road?
Speaker 4:It's it's just the road. It's it's it's literally like eight feet wide and Yeah. Nothing else. So So do you
Speaker 2:Well, and and the
Speaker 1:aura of, you know, if if you become the owner of this of having an alley named after you in the great city of San Francisco.
Speaker 2:Yeah. So, yeah, take us through the process to actually auction this, set up the website, draw demand. How did all this play out?
Speaker 11:Totally. Yeah. So when when when we when we first bought it, it was it was actually dirt alley. Right? Like, there was there was nothing on it.
Speaker 11:So so first, had to pave it. And so we we we found some pavers. You know, they paved it 80 feet of it or so. You know, built the website in in in a weekend, I think Yeah. With our our friend Theo, who's who's helping us with the project.
Speaker 11:And yeah. And then and then we we we thought about how to go live, and I don't know if wanna say more.
Speaker 4:Yeah. Yeah. I think this has been cool because, like, the the art side of it like, people can go to paintindustry.com. It actually just ended five minutes ago. But for, the the during the weekend, people could submit little, like, 48 by 48 pixel drawings and we have space to paint like 1,200 of them on the street.
Speaker 4:And that's like totally free. And then to to kind of cover the entire project and be a little more like capitalistic, we we auction off the naming rights. So that ends in like fifty five minutes or so. And yeah.
Speaker 2:So the full street is going to be painted with this this full alley? Like this whole mural of everyone that picked something?
Speaker 4:Yes. Yeah. Yeah.
Speaker 2:And this was free. Basically anyone that wanted to could go and was this inspired by Reddit the place, that idea?
Speaker 4:Yeah. That's been a huge inspiration. That's been really cool to see. So yeah, we're kind of reviving that and making it IRL and SF.
Speaker 1:Talk talk about the expectations because when when we first chatted about this, we were like, well, we'll we'll be we'll be we'll be the early bidder to to at least make sure you guys get your money out. And then by the time you actually sent us the the auction, it was already well well well above. So how's the response been?
Speaker 4:Yeah. It's been because we were we were kind of stressed because we're like putting a lot of money on the line and we're like, we we either this will either like flop and like or it'll actually do really well and it has done really well which is which is good. Right now the the highest bidder is is WordPress. Yeah. WordPress Way.
Speaker 4:Yeah. WordPress Way. 135 k which is which is insane. And how
Speaker 1:is the auction gonna work at the end? Is it gonna be like I forget the terminology of it, but if somebody places a new winning bid within the last, let's say minute, does it extend the auction? Are you expecting like, a are are people circling now? Where I feel I feel like I saw Josh Browder. Mhmm.
Speaker 1:I know that Josh is probably thinking, I'm gonna wait until the final minute and come in with the top offer. But how how what's the dynamic gonna work like?
Speaker 11:So in in the last five minutes, if somebody bids, then it gets extended by another five minutes
Speaker 6:Mhmm.
Speaker 11:Until until it ends. So so it'll be a
Speaker 8:while.
Speaker 2:And then once the auction closes, what's the process like to actually rename it? Have you have you traced through, like, what does it take to update Google Maps, Apple Maps, Waze, all the different mapping features? Do you think that would be pretty easy, or is it is it like is there like a self serve portal for like renaming streets? How do you prove this?
Speaker 4:There is this is a unique street because it's privately owned. Okay. And as the owners, we we kind of the source of truth for a name like this is the sign itself. So putting up a sign and then we can I I think Google Maps, like, you take a photo or something and you submit the edit and it should should appear soon? I actually when I was in high school, I I maybe I shouldn't share this on the Internet, but I I as like a senior prank, I installed a street sign like on an unnamed alley in my hometown named after my high school track coach.
Speaker 4:And it got renamed on Google Maps and it's been like five years this road has been
Speaker 8:on there.
Speaker 2:It's still on there.
Speaker 4:Yeah. Yeah. Five years later the yeah. Wow. Like people think it's real.
Speaker 4:It's really funny. Yeah. The mayor has mentioned it in a in a meeting before. Yeah.
Speaker 2:Did you did you have to do anything to sort of I mean, these projects, they always run the risk of like vandalization. Basically, I'm looking at someone clearly tried to paint wrong way on the street. Although, they couldn't quite get all the up votes to land the way they wanted, so it's a little bit out of order. But did you have a process for reviewing submissions or was this all community led? Like, how did you think about Yeah.
Speaker 2:The risk of someone putting up something that was, like, offensive?
Speaker 11:Yeah. We had we had some attempts at this, but but we we had some automated stuff remove it and then we were the, you know, the entire time it's been up since Thursday, we've been manually reviewing it. Yeah. You know, as a team, have a group chat and we're just, you know, reviewing it and and Yeah. Someone's taking the the turn and wake up in the morning and there's some stuff we remove it.
Speaker 11:But it's not it's not been so bad. It's been the Internet has been pretty friendly to us relative to how how bad it could be.
Speaker 2:It gets crazy. I remember didn't Justin Bieber put out a post? I'm like, I'll I'll go wherever the audience votes me for my next tour and they tried to send them to North Korea. It's a famous example of like the Internet going wild. At the same time, Bodhi McBoatface, successfully named Boat.
Speaker 2:You know, everyone enjoyed that one. Give us an update on some of other projects. How is the the Pokemon GO payphone project going these days?
Speaker 4:Yeah. That that ended a few weeks ago. Basically, I I had gotten a list of all the payphones in California. There's still like a few thousand that work. Yeah.
Speaker 4:And then made like a Pokemon Go type game where you have to go to different payphones and you can claim them by calling a number and yeah. Like, three or 400 pay phones were called from and it was really really cool to see people go out and and find them all.
Speaker 2:And there was a leaderboard but no specific prize?
Speaker 4:No no prize. Yeah. Just just the memories.
Speaker 2:What who who won? How many calls did they make? How much did they travel?
Speaker 4:This girl named Maggie won. She won by one point. Woah. And yeah. She she was she's driving all over the state.
Speaker 4:Seemed like there
Speaker 2:was there
Speaker 6:was a
Speaker 4:lot of lot of phones. I think I I nerd sniped quite a few people. That's cool to see.
Speaker 2:What what other projects are on your plate right now? Are you still working on the j suite or is that project sort of done at this point? I know that there's a whole documentary you can talk about, but what what else is in your world?
Speaker 4:Yeah. Jmail has been pretty crazy. There's, like, 15 or so people that are that have helped in some way for that project, and it's it's kind of died down now. Maybe there'll be some resurgence in the Epstein files. Maybe.
Speaker 4:We'll we'll see. But, yeah, that that's been really really crazy to see. Project that I'm I'm probably going to drop this weekend is we scraped a bunch of data about The US, like, much money the US government spends.
Speaker 5:Okay.
Speaker 4:And we'll hopefully make like a like a Spotify wrap style like, oh, here's here's how much you paid in taxes this year, like, oh, this much this many dollars went towards like defense or social security or things like that. Interesting. That'll that'll be cool to see.
Speaker 1:I'm sure Yeah. I'm sure that'll make a lot of people really happy.
Speaker 4:Yeah. Yeah. It's crazy to see like I'm like, oh, actually like I kinda, you know, seeing these actual numbers like where things actually get spent on like is is Yeah. Feel like it just makes you think a different way.
Speaker 2:Yeah. In general like with something like that, Spotify Wrap works so well because people screenshot it, they share it. How do you think about the user generated viral loop for these projects? Is that like a key piece of the the idea phase you you think about, okay, how can I actually create some sort of flywheel for generating attention? Or is this just like sometimes you get lucky and people share and and it's sort of an afterthought?
Speaker 4:I think it's fun thinking about like, I mean, like the Alley project, it's just like a fun idea. Like we were actually talking at like a party like a year ago.
Speaker 2:Yeah.
Speaker 8:And I
Speaker 4:was like, oh, wait, there's some some Alley's that get foreclosed on in SF like Wouldn't be a ball line. Yeah. And I said it as a joke, then Patrick and Theo were like, let's let's actually do it. And then there was a girl that was like in law school at the party. We were talking to her about like the legality of it and then it just it took a a while to actually make it happen, but like it's just kind of fun for us.
Speaker 4:And then thinking about how to actually make it go viral is also like a kind of a secondary thing, but it it is framing is so important for these sorts of things and like we also wanted something cool like this is kind of just like cool like thing to to to do for SF like Yeah. It's cool putting SF on the map and and doing things like this, especially when there's like yeah, think I think we're really really lucky that these sorts of things can get funded too. Yeah. I think SF is a very special place for that.
Speaker 1:What kind of inbound what kind of inbound pitches do you guys get at this point? Like, I'm sure people are DMing you like, hey, I found this weird kind of anomaly. I think I think I think you could turn, you know, something like an like an alley. Is there an inbound flywheel yet?
Speaker 4:There's sorts of weird things. I don't know. Like, someone's like, yeah, we have like a tank in SF, like, ideas for that. Like, there's like there's like a lot of weird things.
Speaker 1:I'm expecting you guys to to figure out some mechanism to, like, effectively take over a country at some point. Maybe that's the next step.
Speaker 2:I wouldn't put it past you. Well, congratulations. Where can people go to actually bid?
Speaker 1:Paintastreet.com/auction. Mhmm. Forty six minutes, twenty eight seconds left. We're gonna be keeping our eye on this. It's still at WordPress.
Speaker 1:As down. It
Speaker 5:I mean, you're
Speaker 8:pretty soon.
Speaker 1:Yeah. I'm very interested to see how people react when there's only when there's only a few minutes left.
Speaker 2:Yeah. This will be very fun. Well, thank you so much for taking the time to come give us the update and and chat with us. Congratulations on a huge success. I mean, I this is well well above.
Speaker 2:I mean, a $135,000, that seems well above what you paid and you should be able to recoup all the costs. Do you have a plan for what to do with the money?
Speaker 4:Yeah. Not going to use it for ourselves at all We're to be going to we'll it'll take some money to to paint the actual mural on the street, but there'll definitely be something left over. We'll just keep it for the next project of this sort in San Francisco. Some kind of IRL project here.
Speaker 2:That's amazing. Well, what a fun project. Thanks for coming on and sharing with us. Yeah.
Speaker 4:We'll talk to you guys as well. Yeah. It's crazy that we're yeah.
Speaker 2:We're complete. Yeah. We're gonna be having SF next Tuesday. Let's hang in person.
Speaker 1:We'll have to do a show from the alley at some point.
Speaker 2:That'd be amazing.
Speaker 11:Yes. Awesome.
Speaker 1:Guys. We'll talk to you soon. Congrats. Goodbye. Bye.
Speaker 1:Cheers.
Speaker 2:The Have you seen this map of the surface of Venus? Did you know that Venus has land surface?
Speaker 1:I did not.
Speaker 2:The land surface of Venus has some insane RPG world potential. Someone needs to vibe code a video game where you can go run around on this or or play some sort of four x game. Yeah. Someone says Hasbro is really messing up not releasing Risk Venus. There's another cool AI project that launched from Netflix.
Speaker 2:There's a video here showing their new project Void. The AI removes objects from videos, But it even corrects the physics after the objects or people are removed. And there's a demo in the comments here. So you can see that the bottom is the element that's being removed. And so if you have the kettlebell is deforming the pillow, once the AI removes that, which is often a very, very time intensive VFX task, the physics of how the scene would have played out if that character had not been in the scene are then recalculated.
Speaker 2:And so the duck, not only is the duck not being smashed, the duck just appears like normal. And this is just a project that will if you've ever done any of this type of work, it's incredibly cumbersome. And so I think this will be adopted very, very quickly. Nishan says he had a use case four years ago. A big Hollywood VFX company came to us, the company I was working with, and asked us to remove freckles and pimples from the face of actors and actresses four k movie footage.
Speaker 2:At the time, we really struggled and failed to do it. If it was now, we would have easily tackled the problem. And there are so many examples of this. The physics weight, the physics correction part, removing stuff from video isn't new, but making the background actually behave correctly is a completely different problem. And so this is a huge huge move for the VFX industry in Hollywood.
Speaker 1:Also, this has does Netflix have a history of contributing to Yeah. Source?
Speaker 2:I think so. They've done yeah. They've done I mean, they've done a lot of they they've done a lot of standard setting around cinema camera gear. They were a big proponent of the Blackmagic ecosystem, I believe. Great, like, price per value for shooting a film and delivering in four k, which is something that they sort of mandate across their entire ecosystem, but can be cumbersome for creators if they have to go shoot on a very expensive cinema camera.
Speaker 2:They've done a lot of stuff there. And then, of course, they acquired that AI company from Ben Affleck, I believe. Wasn't that the story?
Speaker 1:Oh, yeah.
Speaker 2:And I I don't know. It's possible that there were some researchers from that team that bled over onto this project, although this seems like it was in flight for longer than before. I agree. Corridor crew needs to do a video on that feature. That would be very cool to watch them road test it and see, you know, where the boundaries are because I'm sure it doesn't work in every possible scenario.
Speaker 2:The demo footage is always gonna be the best, but very, very cool. Anyway, without further ado, we have our next guest, Aditya Bandi, from noon in the waiting room. Let's bring Aditya in. How are
Speaker 7:you doing? Hey. Hey, John. Hey, Charlie. I'm doing good.
Speaker 7:How are you folks?
Speaker 1:We're doing great. Great. Welcome Great
Speaker 6:to you
Speaker 2:the show. Since it's the first time on the show, please introduce yourself and the company.
Speaker 7:Absolutely. Yeah. Thank you for having me. My name is Aditya Bandi. I am the cofounder of Noon.
Speaker 7:And, yeah, I'm, you know, originally, you know, from India. I moved here to the Bay Area in 2015 as part of my first startup getting acquired by Yahoo. Mhmm. I'm a product designer turned product manager and a second time founder. Yeah.
Speaker 7:You know, I have a cofounder. His his name is Kushagra. He's also a product designer turned second time founder. Yeah.
Speaker 2:What was the first company?
Speaker 7:So we were actually you know, back in 2013, there was this problem of, like, rendering PDFs and Word documents inside apps.
Speaker 2:Sure.
Speaker 7:And, basically, I was building this company called Bookpad out of Bangalore, and we we can render 13 plus formats in any app. So someone like Dropbox could integrate with us and
Speaker 6:Oh.
Speaker 7:Start rendering documents. So that's the company we built, and Yahoo bought it for Yahoo Mail Yeah. So we can part of the whole attachment attachment layer for Yahoo
Speaker 3:Mail.
Speaker 2:Yeah. So if you're in Yahoo Mail and you need to open a PDF, it just opens in the browser natively.
Speaker 7:Yeah. Word document.
Speaker 2:Is how how much of that is a technical challenge and then how much of that is just sort of dealing with like, you know, Adobe IP? Because I imagine that like Adobe has products and they maintain a standard, but you you can use some of it, but there's pieces that you can't. Like, what were the decision making criteria around building the product then?
Speaker 7:Yeah. It was very complex. Like, you know, if you basically, all of these formats were not made for for cloud or for browser. They they were built in nineteen eighties. Like, if you open up any PDF or a Word document, it's insane how complex they look inside.
Speaker 7:So we have to build a a rendering engine. We have to build a a conversion layer that understands these documents and and tries to recreate them for for the cloud. So or or so that's that's basically a very technical challenge for us to to do that. Yeah. And we just were very, you know, young and happy and guys called some something very, very complex and that just made us very happy.
Speaker 2:Yeah. So so walk me through the decision to start the next company. What was that like? What was the okay. This is time to run it back.
Speaker 7:Yeah. So, yeah, my cofounder and I, we've been product designers all our lives. We love building products. And then we've been, like, observing the AI space. We've been, like, using design tools for last twenty years of our lives.
Speaker 7:Right? Like Sure. From from grad school. And then for the most part of, like, you know, all the tools that exist in the market, like, they're all graphic design tools. Like, you can design the visuals of the product Mhmm.
Speaker 7:But not not the product directly. So so designer is limited to designing the visuals, and then they hand off the visuals to the engineer to build it. That's how it was always done. Yeah. And the moment the AI coding tools came into the market, everyone started realizing, oh, I can build.
Speaker 7:I can do the functional aspect of it as well. And then they started realizing how amazing it is to do both together. Mhmm. But all of that was happening in multiple tools. It's all broken.
Speaker 7:Yep. And that's that was the idea behind this. Like, hey. Why is it happening in multiple tools? Why can't it all happen in one tool where someone who wants to design and build products can just do it all in one tool?
Speaker 2:Yeah. So, I mean, when you when you hear about vibe coding projects, you you hear about, like, insane lines of code, so much so much functionality, like, instantiated just to, you know, a couple sentences dropped in a prompt. What changes about the product design workflow in a world where sort of the entire underlying structure of the product can change on a dime all of a sudden?
Speaker 7:So the the the tools that are very text based Mhmm. So the problem is, like, they're very limited in in how you can say something. Right?
Speaker 2:Sure.
Speaker 7:Now describe me a painting. Yeah. Let's say you start describing a painting, you can never fully describe the painting. Right? Yeah.
Speaker 7:That's the problem with text based editors or text based design tools.
Speaker 2:I mean, you hear
Speaker 8:a lot of people
Speaker 2:sharing that even just for, like, one off open claw tasks like texting an image or screenshot from their phone along with a prompt just to give a little bit more, hey, here's a screenshot of my calendar. I'm essentially exporting a bunch of information via PNG which is a richer format than people thought, I guess. And so how closely do you want to link the visual design elements, the interaction elements, the logic of how things fit together? Because, you know, like we've already sort of transitioned out of the, you know, visual designer in a pixel perfect like layered Photoshop file into something completely new and dynamic. But that that that barrier is bleeding and and or is is is becoming fuzzier, basically.
Speaker 7:I understand. And then then the way we look at it is if you if you're trying to understand, like, what what are we trying to do Mhmm. We are first of all, what we're saying is, we work on top of your product code. Mhmm. So, essentially, we we don't do any MCP.
Speaker 7:We don't need to do any sort of, like, any middle layer, like, plot or codecs. Like, we don't need any of that. We directly sit on top of your product Yeah. Code base. And then then what happens is, like, the the designers or anyone who's working on the product can see that that code visually rendered on the canvas.
Speaker 2:Sure.
Speaker 7:So now you can understand, okay. Okay. This is what my product looks like in different screens and different components. Yeah. And then from there, you have a lot of control to, you know, refine it, make it better, create new screens, create new features.
Speaker 7:Mhmm. So and then you don't need multiple tools.
Speaker 2:Yep.
Speaker 7:That's the second advantage. You're not switching between multiple tools. Things are not getting lost in translation. Yeah. You know, all the details are preserved.
Speaker 7:Yes. And the last thing is
Speaker 2:Oh, sorry. Yeah. Yeah. Yeah. Yeah.
Speaker 2:The last thing.
Speaker 7:Yeah. And the last thing is, like, you work on both the functional and visual layer. Sure.
Speaker 6:So you
Speaker 7:you it's up to you. You you you build you build the visual first and add functionality. Yeah. You could you can control both of them, you know, very, very you know, in a fine tuned manner.
Speaker 2:Yeah. So if you're thinking about just something as simple as, like, making a CTA bigger and you're dragging the size of a button, that can be quicker in a visual format than in a prompt where maybe you wind up describing the number of pixels that you want it to be or say a little bit bigger, okay, little bit smaller. It can be tricky. But what is the flow of actions that are happening behind the scenes once I actually resize a button, for example?
Speaker 7:Yeah. So let's take the button as an example. Right? So first of all, the button that you're seeing on the canvas Yeah. It's not a rectangular shape.
Speaker 7:It there's real button code behind, so that's why it's getting rendered
Speaker 2:on
Speaker 7:canvas for you.
Speaker 1:Sure.
Speaker 7:Then then when you're actually, know, trying to edit the button visually or maybe using some, you know, AI there or maybe directly you're doing it, the code is getting edited Mhmm. In real time. So, essentially, you can think of us as, like, a visual code editor. So you edit the code visually. So we're kind of building a code editor from scratch that can be edited visually.
Speaker 2:Yeah. How are you thinking about going after customers? Do you wanna be in the enterprise or more self serve? Like, where where where's the beachhead? Yeah.
Speaker 1:And how how much how much of this round was based on traction to date versus long term opportunity and and scale of the market?
Speaker 7:Yeah. No. I think for us, like, you know, we're a design tool design tools. People wanna try it first before, like, even thinking of, like, before thinking of paying it or getting, like, into a team. So we'll always gonna be a a a free tier free tier use it for free.
Speaker 7:If you if you like it, then pay for it.
Speaker 2:Mhmm.
Speaker 7:That's also model. So we're gonna we're gonna be we're gonna be bottoms up that way. But in terms of the traction, like, we are currently, like, you know, lot of some of the best known tech companies in the Bay Area, we have pilots with them and they're going live.
Speaker 2:Mhmm.
Speaker 7:So a lot of that has helped us, like, first build the product with their feedback and then and then do pilots with them to make sure, like, you know, it's working for for a team, for serious work.
Speaker 2:Yeah. Talk about some of the angel investors in the round. How much did you raise?
Speaker 7:So we raised 44,000,000 overall. And, yeah, I think it's it's insane. It's an amazing amazing journey for us. And and some of the some of the investors that we have is, like, First Round Capital, Chemistry, F4, Scribble, Elevation. These are the VCs.
Speaker 7:Mhmm. But the most exciting part for me and my cofounder is that we have some of the best design and product minds in the industry part of the fundraise. Right? So Leo, the second designer at Facebook, investor in Vanta, Perplexitya. Yeah.
Speaker 7:Versal. Then we have Katie Dill, head of design at Stripe.
Speaker 2:Yeah.
Speaker 7:Scott Belskya, founder of Behance. Then we have Mike Davison, head of mic design at Microsoft AI. Hendi Modiset, head of design at Publicitya Ian Silver, head of design at OpenAI. These are just some of the names. Like, we have Yeah.
Speaker 7:A lot. We we didn't share the full list actually for a fundraise. It's
Speaker 2:just Yeah.
Speaker 7:Some small yeah.
Speaker 2:Yeah. That makes sense.
Speaker 7:Just how
Speaker 2:are you how are you tracking the way design is changing in the era of vibe coding? It feels like more and more small businesses, more companies are building custom software. A lot of it is sort of like internal facing, so design is more of an afterthought. But you have to imagine that if the software is valuable and provides growth a growth vector for the business, at some point, you're going to wind up with design challenges and trade offs. Is are are you thinking that this will be like a tool that's eventually dropped on top of like, a a a vibe coded system, or do you think this was more of, like, an entry point into a company building new tools internally?
Speaker 7:So all three types. Right? Like, let's say let's say the first type, an existing company, big product, let's say, you know, like Spotify or someone else like Dropbox. Yeah. They have an existing product.
Speaker 7:They can they can use the tool to build their next feature. Yeah. The vibe coding, if you let's say your site you're doing a site project, you vibe coded something on Lovable or some other some other white coding tools.
Speaker 2:Sure.
Speaker 6:You can
Speaker 7:build your you can bring in your project here almost instantly and start designing and working on it better. And you have the third one. You're starting from scratch. You can, of course, like, start from scratch very easily on tool and and then and then build your product. So can we kind of support all entry points?
Speaker 7:It's a very multipurpose tool that way.
Speaker 2:How are you thinking about business model? It this feels like very logical for seat based, and yet there's been so much pushback around the seat based model. You're sort of starting from scratch so you can pick your your your monetization method. What are you thinking of for the next couple of years?
Speaker 7:Yeah. I think right now, at least, like, we've we've been we're working on the pricing model. We're talking to a lot of customers to understand, like, what works for them. Yeah. We don't wanna break their budgets.
Speaker 7:Right? Like, there are certain budgets assigned already for this. So TBD, you know, we'll we'll soon publish our pricing on the website when we show the product as well. So very, very soon, you'll see you'll see the product go, you know, on on the website and the and the pricing going live.
Speaker 2:Very cool. Awesome. Thank you so much for taking time. Congratulations
Speaker 1:on round together. And we will talk to
Speaker 7:you soon. One You've a thing. Like, also have a I I got a Gong.
Speaker 2:Oh, yeah. You have a Gong? I have a gong for you. Hit that gong.
Speaker 7:Because we've
Speaker 1:I couldn't hear you.
Speaker 2:I think Zoom I think the Zoom noise cancellation just completely killed the gong head. We'll hit the gong again. We'll hit our Yeah. No. It's the next week.
Speaker 2:Thank you.
Speaker 1:Thank you. It's it's great to have you on. I'm sure you'll be back on.
Speaker 2:We'll talk to you soon.
Speaker 1:We'll talk to
Speaker 7:you soon.
Speaker 1:Congrats to
Speaker 5:the whole team.
Speaker 7:Thanks, John.
Speaker 2:Have a good rest of your day. Name a street. We are counting down the minutes. How long do we have? Twenty nine minutes.
Speaker 2:WordPress still in
Speaker 1:the Still at number one at a 100
Speaker 2:Very excited.
Speaker 1:$35,000.
Speaker 2:Our next guest is Zach Shore from Hermes. He's returning to the show with some massive news. Zach, how are you? Where are you? What's up?
Speaker 9:I'm great. Thanks for having me, guys. This is your
Speaker 2:second outdoor guest today. It's fully spring. Spring.
Speaker 1:Spring.
Speaker 2:Riley was in San Francisco. I assume you're in Georgia?
Speaker 9:No. Close. I'm in Virginia. I'm at the Defense Action Forum, the JP Morgan
Speaker 2:Oh, cool.
Speaker 9:Event. So good place to be when you're announcing a $350,000,000 unicorn round. There it is. That's what I was looking for.
Speaker 2:There we go.
Speaker 9:Thanks, fellas. And congrats to you as well.
Speaker 2:Thank you. Thank you.
Speaker 9:Big moves for the the TBPN fellas. Fellas.
Speaker 2:Big moves. Big moves.
Speaker 1:What's new? What's it's it's been a minute since you've been on the show. Yeah. Give us Yeah. Give us all the updates.
Speaker 9:Yeah, guys. A lot. I mean, obviously, we've got the raise, but the raise is a function of of the milestones. So, you know, we flew our second aircraft in nine months, which is pretty unheard of. The first one we flew last year in, like, May '25.
Speaker 9:Yep. And then we just flew our mark two aircraft. That's an f 16 sized unmanned aircraft. So, you know, fighter jet speed, fighter jet size, thousands of pounds of payload, thousands of pounds of thrust. We're slated to fly it again on Friday.
Speaker 9:There you go. Exactly. That was out in White Sands. Wow. And, you know, imminently pushed this thing to supersonic and and really just start really start building the heavy systems that the country needs.
Speaker 9:The second aircraft, which is a Mach two aircraft, is in production right now in Atlanta. And then we we just announced also that we're expanding our headquarters out to Los Angeles in in the Gundo. Nice. And we're gonna build our platform out there. So yeah, we'll
Speaker 2:be neighbors. I'll come see you guys. That's amazing.
Speaker 1:Alright. What with with autonomous jets is how how does how is the development and just like r and d process different? I imagine I imagine there's a bunch of advantages because you're not worried about a human life. Obviously, there's still a bunch of risk and you don't wanna, you
Speaker 7:know Yeah.
Speaker 1:Crash crash the thing that the team worked so hard to build. But the the iteration cycle feels insane based on on how you've described it. And so I'm curious how
Speaker 9:Yeah. I mean, you you kinda nailed it. Right? I mean, taking a person out allows you to take a lot more technical risk. Just like full stop.
Speaker 2:Yeah.
Speaker 9:I can lawn dart something intentionally, right, just to push the envelope on a vehicle to run What is
Speaker 2:the lawn dart?
Speaker 1:Is that Yeah.
Speaker 6:Just like
Speaker 2:Yeah. I guess.
Speaker 9:If we need to, that's not
Speaker 7:our goal.
Speaker 2:Yeah. Yeah.
Speaker 9:You could. Right? If I really want to find the edges of performance and there's nobody on board, you you have that you can take that kind of risk. And then you can iterate faster. There's also I can take all of the systems that exist on an aircraft that are there for human survival, the oxygen, the ejection seat, all the command and control capabilities, the the human human machine interface screens, the the stick, the throttle, all that.
Speaker 9:I can pull that all out, and I can put in more payload, more fuel, and just continue to drive more capability for the warfighter. I mean, we just saw that incredible mission to to rescue those f fifteen pilot and copilot in in in Iran. And, ideally, you know, you have a vehicle like this. You don't have to do a rescue mission. We don't even have to put ourselves in those positions and ask American men and women to to take that kind of risk.
Speaker 9:So there's, you know, operational utility to the unmanned platform and there's a significant accelerant to development because of the risk we can take.
Speaker 2:Yeah. Take us through the different aircraft that you've built so far because the and then remind us of the goal
Speaker 3:of Yeah.
Speaker 2:How fast are we going? Is like miles per hour the correct benchmark for each subsequent test? I imagine that you're trying to make each one faster than the last, basically.
Speaker 9:That's that's correct. I think, you know, we we speak in terms of Mach, right? So Mach one being supersonic. Yep. But so the first aircraft was not really an aircraft.
Speaker 9:We called it Turkey. It was Mhmm. Sort of a actually, Before that was Emu. Excuse me.
Speaker 2:Emu.
Speaker 9:A flightless bird. Yeah. Right? So that had a jet engine, and it had a bunch of the avionics and the sort of radio links to just show that we could build an integrated team, build some hardware, hook up the engine, and get this thing sort of taxiing down the runway. We did that in in '24.
Speaker 9:In '25, we built Turkey, which was a flying bird, but turkeys don't aren't meant to fly. So that aircraft flew at Edwards, and we demonstrated we could rapidly build a jet powered aircraft. It was a 10,000 pound airplane. It had fixed landing gear. It was a GE j e five engine Mhmm.
Speaker 9:Which is the same engine that you see on the jet trainers that American men and women train on. Mhmm. And that was in May '25. And now we're on mark two, and we call that aircraft Eagle. And this is where it gets kind of fun.
Speaker 9:Right? This is where you start to see what I would call product utility. So this aircraft is the size of an f 16, maybe a little bit bigger, fully unmanned. It's got a 30,000 pound thrust engine. To give you a sense of comparison, like the CCA program, those engines are roughly at 3,000 pounds of thrust, so you're looking at 10 x more power, about 10 x more payload, and just a totally different problem space that we're working in.
Speaker 9:And the first aircraft of this series, we're building three of these mark two eagles. The first one we flew that that's what you showed the video of. This one will go supersonic. So the premise of this aircraft is demonstrate that the the the vehicle design, the shape, they call it the outer mold line, can get through something called transonic. So transonic is that that window right before supersonic, and there's a lot of very unique things that happen, with physics, for lack of a better term, right before you go through that supersonic window in terms of shock waves and stability for the platform.
Speaker 9:And so you really wanna demonstrate that your plane can make it through that, you know, point nine nine Mach to 1.1, 1.2 Mach window. That's a huge risk window that we're gonna unlock Yeah. Here shortly. The next vehicle, Mach 2.2, will have some additional pieces of proprietary technology on it. Our proprietary precooler, which is a technology that sits in front of the engine, will be on that next aircraft.
Speaker 9:That aircraft's being manufactured right now in Atlanta, And that will allow that airplane to do Mach two plus. So now we start to really get into that really, really high speed regime. As an example, you know, the f 15 is the fastest fighter jet in the world right now. That aircraft in a dive with nothing on it will do maybe 2.5. Maybe maybe Mach 2.5.
Speaker 9:So we'll do we're gonna go for that number straight and level with this aircraft. And then the third aircraft in this series is going to be Mach three. And that aircraft is gonna be manufactured in the new El Segundo facility and and will be flying somewhere around the '27.
Speaker 2:Talk about the actual technology.
Speaker 1:Speed is just insane. Yeah. Speed of r and d. It's what
Speaker 9:The iterative design, guys. I mean, right? Like, continue to build hardware so that as I am build as I am flying the current airplane, I am building my next airplane. Right? And so on and so forth.
Speaker 9:I mean, is SpaceX over and over again. Right? This is SpaceX for aviation, or as we say, SpaceX sideways. So, you know, that's how you can take this kind of this hardware risk and continue to go. And and to your original question, our goal is Mach five.
Speaker 9:Right? That remains our goal. But the key technical unlock in here is actually Mach three. Because in order to unlock our next propulsion approach, we need to demonstrate that you can get a turbine engine, this case, the f one hundred two twenty nine, the f 16 engine. We need to demonstrate that I can fly that engine at mach three for a period of time.
Speaker 9:And so that's what this series of aircraft are gonna do. And then we've also got some pretty exciting, you know, capabilities that we're gonna be able to offer to the warfighter with this platform at at the same time.
Speaker 2:How focused are you on the on the on the defense industry specifically? Because there must be demand from commercial. There's demand from the AI world for this technology. How are you thinking about the trade offs there?
Speaker 9:Yeah. Great question. So commercial is one of those things where, yes, this technology eventually will naturally lend itself to a commercial application, but we're a ways away from that. I mean, if we think about just aviation historically, you start with the the defense environment. Think about how jets and planes were even adopted.
Speaker 9:Mean, the Department of Defense is going to take more risk and going to, you know, help develop inherently just by operating these systems, these technologies to lower the complexity, lower the risk on them so that they can be eventually adopted in a commercial environment. But the other problem is when you work into commercial aviation, the the flight certification requirements for a new commercial engine or a new commercial airframe are steep.
Speaker 5:Sure.
Speaker 9:For good reason. Right? We're putting people on board.
Speaker 2:Yeah.
Speaker 9:So to have the economic viability to pursue that certification process requires you to have a stable business that's got robust economics.
Speaker 2:Yeah.
Speaker 9:So for us, even if, you know, we do eventually wanna go after commercial, you have to build a viable defense business first just to have the economic scalability, not to mention the expertise on the platforms. And so for us, you know, I certainly wanna do commercial work eventually, and I think these propulsion systems will lend themselves, but we are a defense company. Right? Yeah. That is our bread and butter.
Speaker 9:That's where we're focused. We're not interested in some of the, you know, the energy plays on the propulsion. We are really just true north unmanned high mach, high altitude systems for the warfighter. And as those systems come online, we will be, you know, the arguably the best aircraft manufacturer in the world, and that we'll start lending that to other aircraft problems.
Speaker 2:Talk about the actual technology that enables you to go Mach three, Mach four, Mach five, Ramjet, scramjet. What what is the what's the lineage here? How much of this has been used in the past? What are you inventing from scratch? What are you pulling off the shelf and leveraging?
Speaker 9:Great question. I mean, a lot of what we're doing has been done before. Mhmm. We're trying to stay out of the world of science problems, which is where you get into the scramjets mach six seven and stay in the world of engineering problems.
Speaker 6:Mhmm.
Speaker 9:And science problems, things have to be invented that don't exist yet. Specific materials, production processes. Ramjets have been around since the fifties. NASA did a lot of work on this. You see these on missiles currently and all over the place.
Speaker 9:And so ramjets are very well understood and and well tested. And so what we're doing is taking a different approach with the propulsion system and using something called the turbine based combined cycle or TBCC. Mhmm. And this is an engine type that's a mix of multiple propulsion cycle propulsion systems. NASA sort of led the way on this, and we demonstrated this propulsion cycle on the ground in about 2022.
Speaker 9:And I think DARPA is the only other group that's done this, and so us and DARPA are only people who've demonstrated this propulsion cycle.
Speaker 7:It's
Speaker 9:got basically three components to it. You got your inlet, and the air comes in. And and the first thing that happens is we've got a proprietary precooler that that cools the air down and and slows slows the flow. It then hits the turbine. So in this case, the f one hundred two twenty nine, the the jet engine.
Speaker 9:So we're not building a new jet engine. Now the challenge has been with ramjets, for a ramjet to light, the air has to be moving through at mach three. So how do you get the system? How do you get that air flowing in mach three? Typically, we've seen it in missiles with rockets, you boost it.
Speaker 9:Right? Use a solid rocket or liquid rocket, but that has a couple problems to it. Number one, you have to really harden the system to handle all those g's, and you're not going to have big wings because of drag. So you're really looking at systems that are not really optimized for flight, and they're just one way. So with an aircraft, you can have a more graceful acceleration.
Speaker 9:We are able to basically tune that jet engine, that to that f 100 to get mach three airflow. It goes through the ramjet, and then I can light the ramjet. Now once I light the ramjet, I could coon off the turbine engine. I route the air around it directly into the ramjet. Now I can fly mach three to mach five.
Speaker 9:Mhmm. When I decelerate, I do that whole system in reverse. I open the doors, the air comes through the turbine engine, the ramjet shuts off, and the traditional jet engine takes over and takes me from Mach two back down to the ground. And this is why it's called the turbine based combined cycle, because I'm combining these two propulsion genres. And it allows us to use mature technology to unlock these sort of these flight conditions.
Speaker 9:And you won't get much above Mach five. That is hypersonic is that line at Mach five, and we don't need to get much five. Above There's two reasons. One, survivability and and the sort of analysis we've seen is it's overkill, and you're gonna find yourself in sort of physics land that's gonna cost you more and take you a lot more time to run up that curve. And, also, you get in the mach six seven world, now you're in science problem world.
Speaker 9:That's scram jets, which are still kind of more new. That's CMCs for very bespoke material sciences. Right? I can have a hot end a hot vehicle that's titanium or inconel or steel, and I can mass produce that to handle the the heat and temperatures. And so what we're doing is taking a lot of old information, we're and modernizing it.
Speaker 9:And for that matter, the the s r 71 had an aircraft called the d 21. You can Google this. It was a drone that sat on top of the Blackbird between the the right on the back between the engines. And once the aircraft was above Mach three, they turned that aircraft on. It was only a ramjet, no moving parts.
Speaker 9:The air flowed through that ramjet. They lit the ramjet, the aircraft flew off, and it went Mach three plus for about 3,500 nautical miles. And so in this way, we can start we can start accessing those conditions again just like we did in the fifties
Speaker 1:and Were was the d 21 like a single use designed to fly like reconnaissance or
Speaker 9:to fly reconnaissance. Yep. Exactly.
Speaker 5:Then it would just ultimately
Speaker 1:crash and burn?
Speaker 9:It would it well, it was supposed to return. They didn't end up going the full distance with it. They had a couple successful test flights. They also had some bad flights where they had some challenges. You can look up the history.
Speaker 9:But more importantly, this concept was executed and validated in the sixties. Right? And so we can take modern practices and all these learnings and sort of bring bring the past forward and say, you know, speed is in vogue again. You know, the in the introduction of ICBMs and stealth technologies really took America's focus away from high speed systems, and that's why nobody really worked on these things for about sixty years.
Speaker 2:Question from the chat. There's a claim that China has a system that can go Mach 20. Do you know anything about that? Does that seem realistic or propaganda
Speaker 9:or It like South China morning news if anybody's aware of that
Speaker 2:Okay.
Speaker 9:That that that newspaper. There's lot of claims. So I mean I'm not privy to anything but I would call I'd call shenanigans on that.
Speaker 2:Okay. Last question. Talk about the decision to expand to El Segundo. Incredibly cool community at the same time three time zones away. Feels difficult to manage a team.
Speaker 2:Is it about talent? Is it about Yeah. Resources? What's the thesis?
Speaker 9:Yeah. It's talent. It's it's talent talent and tacos. Talent and tacos. Right?
Speaker 9:You you've got the core engineering talent that knows how to iterate on hard heavy hardware, heavy high speed hardware
Speaker 7:Mhmm.
Speaker 9:Is really resident there and nowhere else. And, you know, ultimately, as much as the hardware we're building is exciting and innovative, the sort of the team we are reconstructing reconstructing is really the unlock for this business because aviation has not seen this pace of iteration or these flight conditions in a generation. So it's not like we can go and hire somebody from insert company that's done this before. We have to effectively take the best we can find from, you know, the the closest parallel and then, you know, bring them into the the aircraft world and say, take what you learned from, you know, innovating and you know, and and and working quickly on rockets and now apply that to aircraft. And so if you really want that talent and you want to draw that talent, the best place in the world to be is El Segundo.
Speaker 2:Well, congratulations on the round. Congratulations on the progress. And enjoy the rest of the conference. We'll talk to you soon. Very
Speaker 9:so much.
Speaker 2:Have a good one.
Speaker 3:See you.
Speaker 2:Goodbye. Up next, we have Hongwei Liu from Madapan in the waiting room. Let's bring him in to the Ultra Dome. We're still figuring out the transitions between gas. We're working it.
Speaker 2:How are doing? Welcome to the show.
Speaker 8:Thanks for having me.
Speaker 2:Thank you so much for joining. First time on the show. Please introduce yourself and the company.
Speaker 6:Sure, John. My name is Hongwei. I'm one of the founders here at Baffonton, and we are mapping all of the indoors, one building at a time. Okay. Up from Waterloo, Canada.
Speaker 2:How are you mapping it? What what is the sensor?
Speaker 6:So look, there's low tech and there's high-tech. Mhmm. You can download the map and scan app, grab any iPhone, grab any three sixty camera these days and just walk through buildings. Yeah. Everyone thinks that that's what you have to do and you don't.
Speaker 6:The the amazing thing is that 70,000 people have now mapped, you know, all sorts of stuff, schools, their own house, offices, malls, just by scanning in the piece of paper that's on every wall. I bet somewhere in in Yeah. In that room of yours, there's an emergency escape map on the wall somewhere in the studio. Oh, okay. You can take a photo of that, and you can get it in.
Speaker 6:The problem, of course, is it's a it's a picture. And so how do we turn that into vector data? How do we make that interoperable and useful to all the other apps that you already use and take for granted? That's what we're trying to do here at Matten.
Speaker 1:So what are all the different use cases for indoor mapping data?
Speaker 6:So the one that, you know, I've become known for because I've been at this for a while is, you know, that touch screen in the mall that you guys probably use at Santa Monica Place and stuff Yeah. That gives people directions? Yeah. That's us.
Speaker 5:No way. So we
Speaker 6:do that for yeah. We do that for a third of the malls in the world. We do it for the Super Bowl four years in a row. We do it at LAX where you guys are trying to make that airport experience a little bit better. Yeah.
Speaker 6:We think we touch about a third of Americans a year Cool. With our products. They probably wouldn't know it's us, but we're we're trying. And now increasingly, we're starting to be embedded in safety applications. We've mapped thousands of k to 12 schools now in The United States, unfortunately, because when something bad happens, need a map of the inside for the good guys to know how to run inside.
Speaker 2:Yeah. When when I think about those customers that you mentioned malls, the Super Bowl, LAX, I feel like they have reasonable budgets. So is is it about cost savings to use an image based on a floor plan as opposed to just walking around with a three sixty camera? Because that doesn't feel that cumbersome when I think about the the price of an Insta three sixty or a GoPro or even your phone. Like, it feels like the data collection shouldn't be that cumbersome.
Speaker 2:But what what is motivating the the desire to sort of go go lighter on the data collection side?
Speaker 6:Yeah. Fair question. And and first, I assure you they all negotiate very
Speaker 1:hard to
Speaker 2:see any
Speaker 6:customers listing. They they got a good deal. Okay. Yeah. But I I I think the hardest part about mapping the indoors is not mapping it once, but keeping it up to date.
Speaker 6:Okay. You know, the the goofy example is like Santa Claus moves every year in the At Christmas.
Speaker 2:Oh, yeah.
Speaker 6:Right? So if you want to know where Santa Claus is going to be this Christmas, the only person who knows is the person on the ground planning Christmas at the mall in that off in that back office. Right? And if you wait until that's already happened and then you somehow try to scan it, it's too late. Never mind that it's private property and, you know, someone would escort you outside.
Speaker 6:Yeah. So a lot of managing and mapping the indoors for you and I and for everyone else who needs that information is getting ahead and being able to plan ahead and managing that constant change. The you know, you can scrape the outdoors with a with a LIDAR sensor or with a satellite with a car. It's good for about five years. If you've even if you manage to scrape the 100,000,000 buildings that are privately owned indoors, it's good for about five days.
Speaker 6:So how do we how do we enable those folks to plan ahead?
Speaker 2:Yeah. So I mean, the the tagline is Google Maps for the indoor spaces. Are you are you gonna partner with Google? Are you gonna partner with Apple Maps? Is there an API that you can just expose these things to?
Speaker 2:Because I imagine if I'm LAX, I'd I I pay you, I'd want the data to be as available as possible to my customers and patrons.
Speaker 6:I wish I could use that tagline. I'm glad you did Yeah. So I don't have to. But, look, I I think from from their perspective, and obviously, I can't speak for Google and Apple. Yeah.
Speaker 6:But, you know, Google wants better data so that they can serve more users. Yeah. Apple wants better data so they can sell more phones. They I think they're generally pretty happy when someone does all the hard work of mapping the indoors and makes that information accessible and standardized. So we publish a lot of data on behalf of our many clients, the LAXs of the world, the, you know, SoFi stadiums of the world, two platforms like that.
Speaker 6:Mhmm. I can't speak specifically to which ones and who because they're all pretty sensitive about, like, this is my private property. Sure. You, mister Big Tech, can't have it. Yeah.
Speaker 6:But to your point, you know, consumers need this information. It's it's on the wall. So we're we're just about standardizing the pipes Yeah. And enabling building owners to publish their information.
Speaker 2:Have how do you think this interacts with the potentially coming robotics boom?
Speaker 5:I've been getting a lot
Speaker 6:of calls about that. It wouldn't surprise you, of course. So I think there's enough problems to solve outdoors for robotics that I'm, you know, I'm still kind of holding my breath for when this becomes more real indoors. There's more constraints. I'll just say that.
Speaker 6:If you if you you know, we're only now solving for self driving cars outside. It's been, what, twenty years since Yeah.
Speaker 7:That we've
Speaker 6:been talking about it. And that's actually a much simpler problem. Right?
Speaker 2:Mhmm.
Speaker 6:Like, streets, buildings, lampposts, pylons. Yeah. There's, like, you know, far fewer things you have to recognize outdoors to be able to move around. Indoors, there's way more. And and the training data is not actually easily available because unless you're a Roomba, you can't just scan people's houses.
Speaker 6:And even if you could, it's incomplete.
Speaker 2:Yep.
Speaker 6:So, you know, we're we're building up, we think, a pretty large training dataset. We've, you know, seen our technology now deployed for Department of Homeland Security, various fire departments and police departments throughout The United States. But going you know, I I guess I'm sometimes accused of being too Canadian in that we don't we don't sell ahead of reality. I think we're a couple years out of of You have be like, we're going
Speaker 2:to map the inside of Saturn's moons soon. You gotta think, like, fifty years ahead.
Speaker 6:How about Mach three jets for starters? I'll I'll do that first. Yeah.
Speaker 2:Yeah. Yeah. Maybe maybe airplane hangars. You know?
Speaker 6:Yeah. We're headed that way. I'll I'll say this. If if we don't pull it off, I don't know who would. Yeah.
Speaker 6:We have by far the most amount of training data at this point of the indoors, but we're we're doing it on behalf of our clients. And I really do think that the indoors belongs to the landlord
Speaker 4:Yeah.
Speaker 6:Belongs to the people operating it. And and so it's about who can enable them to realize that future.
Speaker 2:Yeah. Yeah. And to help their customers. Makes a ton of sense. Tell us how much did you raise?
Speaker 1:I love how you've you just got a third of the market. Like, I just like, it is a it is such a such a large Yeah. So much market share and and those early early pitches. Yeah. It's a it's a fascinating market overall.
Speaker 1:But anyway
Speaker 2:Tell us about the round.
Speaker 6:Yeah. Well, my fiance hates that I I don't like going to malls anymore if you would believe it. It's really not fun. Oh, go to feels like it's working. Yeah.
Speaker 6:Oh, dude. Alright. We raised $24,500,000. Congratulations. That's a lot bigger than the sales Gong we have in our office.
Speaker 8:So thank you guys.
Speaker 7:That's a
Speaker 2:huge one.
Speaker 1:Awesome. Well, thank you so much for
Speaker 2:coming on the show. Congratulations on the progress and we'll talk to you soon.
Speaker 6:Love you guys.
Speaker 3:Have a good one. Love you.
Speaker 2:Love you is a great sign off.
Speaker 8:That's a
Speaker 1:new exit.
Speaker 2:Our next guest is live here in the TBPN UltraDome with us, Zach Kukoff. Thank you. Welcome. Thanks for having me.
Speaker 1:Telling
Speaker 2:Welcome to the show. How you doing? Thank you.
Speaker 7:Thank you.
Speaker 4:For you guys.
Speaker 2:It has been far too long since you've been on the show. Last time, we were talking
Speaker 1:Why are you in
Speaker 2:Beautiful.
Speaker 1:Why are you in LA? Why is a man like you in Los Angeles?
Speaker 8:What does a man like me have to gain in Los Angeles? A nice tan, a little relaxation. Everyone
Speaker 2:who's joined the show has been outside. I mean, a few people, but it's spring is fully in.
Speaker 8:It's beautiful.
Speaker 2:Yeah. In in full swing. Did you get snowed in in DC? Did you go crazy blizzard?
Speaker 8:We had Snow Creek. So we were
Speaker 2:Snow Creek. What's that?
Speaker 8:Snow Creek, I had never heard of this before. Washington Okay.
Speaker 2:It's the
Speaker 8:only East Coast city
Speaker 2:Yeah.
Speaker 8:I've ever seen. They haven't figured out how to plow snow. Okay. Because the snow here's the problem with Washington.
Speaker 2:Yeah. The
Speaker 8:snow lands, everybody just sits there and there's a wait for it to melt. Okay. So their only plan is to like help it gets warm.
Speaker 1:Work smarter, not Yeah.
Speaker 8:Except neither. They just let it sit there and it didn't melt and it stayed really cold for a week and it merged into like a weird hard soft hard soft, the water and the snow and somebody who's smarter than we can do like chemical But basically, once it melts and freezes over like four times in a row
Speaker 2:Yeah.
Speaker 8:It becomes this thing called snow creep and you're basically stuck and you can't leave your house. So we couldn't like drive basically for the better part of like two weeks.
Speaker 2:It was Brutal.
Speaker 8:Brutal. Yeah. It was wonderful.
Speaker 2:But how is business broadly? Reintroduce yourself. Re re re describe your role and then we can go into some of the hot topics.
Speaker 8:Yeah. Yeah. Okay. I run a lobbying firm.
Speaker 2:Yeah.
Speaker 8:A lobbying firm. I run the tech practice of a lobbying firm. Firm's called Lewis Burke. We do science, tech, education. Wow.
Speaker 8:That's so nice. Wow. That should be in every room I walk into. They should always applaud for me. We do science, tech, education, health care.
Speaker 8:Dude. I'm from the tech side of the house.
Speaker 2:Yeah. Exactly. You're like I was watching you
Speaker 4:guys on the way over.
Speaker 2:Maybe the
Speaker 1:most like straightforward explanation. I really like jazzed
Speaker 7:it out.
Speaker 1:I was
Speaker 4:like really
Speaker 8:into it. Anyway, I run the tech side of the house. So I lobby for venture firms. I lobby for private equity. I lobby for high net worth individuals mostly who come out of venture private equity.
Speaker 8:And then I lobby for a whole bunch of tech companies.
Speaker 2:And specifically on the federal side?
Speaker 8:On the federal side. That's right.
Speaker 2:So we
Speaker 8:do everything at the federal level.
Speaker 2:So give me your sort of postmortem on big beautiful bill. That was the last thing we talked about. Yeah. Wow. What were the key decision points?
Speaker 2:I know that the government was shut down for a while. There's a lot of back and forth.
Speaker 7:Like, how
Speaker 2:did this all shake out?
Speaker 8:Okay. Basically, every this is it didn't used to be this way.
Speaker 2:Yeah.
Speaker 8:It used to be in Washington that things operated. I wouldn't say smoothly. But like go back to the nineties, West Wing optimism
Speaker 2:Yeah.
Speaker 8:Newt Gingrich contract with America, Bill Clinton, like Yeah. Yeah. We get a sound effect for that one. That's nice. I think it's pretty function pretty well.
Speaker 8:Now in Washington, basically every time something happens, it sets up the seed for the next issue. It's like if you only had the Treaty of Versailles over and over and over again. Okay? So big beautiful bill comes out. Yeah.
Speaker 8:It happens after big beautiful bill. You lead up to the big conflict which is around homeland security, ICE, and enforcement. Sure. And you basically have a variety of issues that come out most recently. You guys I'm sure were tracking
Speaker 2:Yeah.
Speaker 8:Christine Ohm out Yeah. Right at DHS. Yep. Others may be coming out soon too. Right?
Speaker 8:You know, AG, many others in the case too. A lot of this stems from the inability to get the entire government funded. Right? Big beautiful bill and by the way, reconciliation reconciliation as a whole Mhmm. Guaranteed funding for border enforcement for ICE.
Speaker 8:Right? So when the Dems later come back and say, hey, I wanna be able to stop some of these things that are happening in Minnesota and things like that.
Speaker 2:Yeah.
Speaker 8:The only lever they have to pull is to stop funding DHS as a whole.
Speaker 7:Sure. That's why you get
Speaker 8:these airport shutdowns. Yeah. That's why you get these super long lines at TSA and so on and so forth.
Speaker 2:Yeah. But from a tech perspective Yeah. How many like, all of that, like, flows through to whatever tech leaders want to happen in Washington just is slower. But what was on the top what's on the top of the the the stack in terms of to dos in Washington for Silicon Valley broadly
Speaker 8:these days? Mean, I will tell you it's less of a policy to do and the biggest political issue right now is probably the data center stuff. Yes. You guys are, I'm sure, tracking. I'm sure people aren't talking about Yep.
Speaker 8:You saw the thing in Indiana. Yeah. Right? City councilman. It was horrible.
Speaker 8:Yeah. Terrible. I had 13 shots in his house. Yeah. Okay.
Speaker 8:Putting aside how horrible that was Mhmm. There is like a very broad bipartisan emerging consensus Mhmm. That data centers rise energy costs Yep. Water and all sort you know, create pollution and whatever. You saw, like, they, you know, increase heat temperatures for, you know, parking lots.
Speaker 8:A lot of that's not true Yeah. But because the perception of it Yeah. Is real. Yeah. You have this big, huge armed, basically, opportunity for candidates who are populist sometimes, but opportunists always to come in and run on that issue in '28.
Speaker 7:So the
Speaker 8:big the problem with tech right now in DC is you have a bunch of tech money coming in. You guys know Leading the Future is the OpenAI associated super PAC. Sure. And public action or or public first, something along those lines, is the Anthropic Alliance super Both have been putting tons of money into races like New York twelve
Speaker 6:Mhmm.
Speaker 8:I think with Flores. Right? Mhmm. All sorts of people who have been either pro or anti data center and AI development as a whole Mhmm. There are now hundreds of millions of dollars of tech money
Speaker 7:Yeah.
Speaker 8:Going to try to arm those. That's the big issue for tech. Like, you want to get anything else done
Speaker 2:Sure.
Speaker 8:You basically are saying, how do I play now in midterms, but also looking ahead to '28. Yep. Even if I'm not talking about data centers directly, to make sure my preferred candidates get in to actually open the doors for the things I want to be able to do.
Speaker 2:Yeah. And how much of the data center question is about research education on those issues? Like there there was a full back and forth on the water issue. I think that one landed in a pretty good place with energy less so because no one debates that these data centers use a ton of electricity. I mean, they're measured in electricity.
Speaker 2:That's how we refer to how big they are. It's a gigawatt or a megawatt or
Speaker 8:Well, it's it's a proportionality problem.
Speaker 1:Right?
Speaker 8:Like the data center issue is, yeah, do they use a lot of electricity? Sure. Yeah. But in comparison to things like growing almonds Yeah. Right, or raising a cow
Speaker 6:Sure.
Speaker 8:It's actually not that much. And it turns out we love cheeseburgers and we find cheeseburgers like have huge value in America Sure. And so we accept the trade off that in order to have cheeseburgers, we have to pay a little bit for electricity. Yeah. Right?
Speaker 8:It turns out there's a lot of value in AI. By the way, this is not a winning political argument. I wouldn't go up and down and make the argument that, hey Yeah. Everyone's gonna have to get used to paying little bit more to pay for AI.
Speaker 5:No one wants that.
Speaker 1:No. Who who
Speaker 8:would want that?
Speaker 2:And that's the backbone of the ratepayer protection pledge. Correct?
Speaker 5:That's right.
Speaker 2:That's right. How is that going? Because that is a pledge right now
Speaker 6:Yeah.
Speaker 2:But it feels like it could be codified into law at some point.
Speaker 8:I don't know that I'm super bullish on it being codified, what I'll tell you is anything that tech can do Mhmm. To get in front of the issue like, you guys know the account on Twitter, More Perfect Union? Yes. Okay. I think they are the most effective messengers, by the way, in politics today.
Speaker 5:Sure.
Speaker 8:They have one narrative they push, it's very, very well done, which is look at these great local small towns, salt of the earth people fighting back against the evil tech firms who want to do things like build data centers. Right? And so the more that you see that and the more salient the issue becomes, and it's already so salient as it stands today.
Speaker 2:Yeah.
Speaker 8:You guys saw Leading the Future played in the sort of two Illinois races that just happened recently during the midterm cycle. They won one out of the two. If you look at what they ran on, in neither case do they run ads saying, we love data centers. Please fund data centers. Right?
Speaker 8:The ads were about saving democracy and it's great to have Jesse Jackson junior and the other candidate and so on and so forth. Like the more the tech can come out and ahead of these things and then change the topic to the variety of other issues voters care about Mhmm. The better position we are in. The more that we just try to take this on because we don't need thirty more years. Right?
Speaker 8:We need to have a window of time Mhmm. Where we can come in and get data centers built and actually start to operationalize a lot of the future value of AI. Mhmm. If you wait too long, there's a window where our adversaries pull ahead of us and the opportunity for American AI to dominate goes away. And if we're if we're too aggressive, right, the other inverse of this is we risk really alienating a lot of the communities that are local.
Speaker 7:So you need
Speaker 8:to thread the needle on getting out ahead with things like the pledge, right, Making sure we can come out and show that we're listening to constituent needs while also at the same time actually delivering on some of the positive benefits that are not just more doom around AI is going to take your job and kill your horse and burn down your house and whatever. Sure.
Speaker 1:What what has messaging been like around the the bent like, I I think for a lot of people they're like, okay, data center in my area Yep. What does it do for me? Yep. They're like, am I still going be able to use LLMs or video models? They're even if it doesn't go in, they're like, yes.
Speaker 1:So okay. So what what are you gonna do for me? Yep. And so I think like one of the best one of the best arguments for it today has been like tax revenues. Is there any is that can be, you know, repurposed for a bunch of other things.
Speaker 1:Seems to be pretty significant based on some of the numbers I've heard. But Yeah. Is that kind of messaging resonating or are people still just saying, you know, flat out not not in my backyard.
Speaker 8:Yeah. It is I would say it's very NIMBY. I don't think the tax stuff is breaking through to people and the reason it's not breaking through in part is because for every person like you and me and John who says, of course, these things are gonna throw off cash. How could you not look at them and think you can fund an entire school district Yeah. With one data center.
Speaker 8:Right? You have somebody else who goes, well, that doesn't logically track to me because you have five employees manning these things and they're gonna be more and more automated as time goes on. And more to the point, why not put them somewhere else? We're gonna have to deal with it and see the negative externalities. Like, the messaging thing that tech hasn't figured out yet, and partially we do it to ourselves.
Speaker 8:Every time you have somebody come out and say, AI is gonna take your job, it's gonna totally disrupt society, it's gonna end. You didn't have the people who built NAFTA weren't selling NAFTA by saying, hey, NAFTA's gonna ship all of these jobs overseas and be horrible. And by the way, NAFTA, whatever you think about it, did set up the conditions for a lot of jobs moving overseas. Yeah. Like tech has to get out of its own way a little bit and stop saying things even if there is some some tail chance of it being true.
Speaker 8:Like we've left the context bubble. Right? We're not in I I lived in SF for seven years. Like we're not in Berkeley right now where we're having a great conversation in front of the light cone or whatever and having some in-depth intellectual discussion.
Speaker 2:Yeah.
Speaker 8:We're in persuasion mode, and you can't come out and say that.
Speaker 2:Yeah. What about the just taxes broadly? Because
Speaker 6:Mhmm.
Speaker 2:When I hear a data center will throw off a lot of taxes, I think, well, maybe corporate taxes wherever that company is headquartered. Yep. And they'll certainly pay real estate taxes. Yep. But it's a very small real estate footprint.
Speaker 2:And so are there any local local regions that have figured out how to rethink the tax base to actually capture some of the value and say, look we're down but you're going to have to pay and here's the actual deal and let's let's about it more in those terms to make sure that we're actually internalizing the value.
Speaker 8:In some ways you're a Georgist. Right? You're like Yeah. I'd like to have a land value tax.
Speaker 2:Yeah. Yeah.
Speaker 8:Yeah. If we just capture some of the improvement we've created Yes. Which I'm very sympathetic to. Yeah. I hear the argument.
Speaker 8:The big tax conversation today, it's been a little bit back and forth. And the back and forth has been between some people who are saying, hey, we need tax breaks to lure in data centers. Like, for all that we hear about local community hates data centers, there's a huge swath of like offline people who are saying things like actually I would like to have any job in Right? My Interesting. I'd love to have any good construction job.
Speaker 8:Yeah. Yeah. Any job running these things. Yeah. So that's okay.
Speaker 8:So one side of the issue is Okay. Do we have people who are saying we need tax breaks or tax incentives to lure? Right?
Speaker 6:Yeah.
Speaker 8:Yeah. And and that's actually a wedge issue even within Republicans too, by the way, who say, hey. Some of whom say, hey, you're putting this in my backyard. You're destroying the character of my community. Very sort of the classic NIMBY arguments we've heard.
Speaker 8:And some of whom are saying things like, gosh, I would love to have more industry in my community. Okay. So that's one. The other side of it on the tax side are people who are saying, okay, we already have them. Right?
Speaker 8:And so what are the other things that we can levy? Sometimes it's land improvement. Sometimes by the way, it's a consumption tax on energy. Right? Okay.
Speaker 4:So you can
Speaker 8:actually like there are people who are saying, look, should we craft more narrowly targeted energy consumption taxes commercial in their orientation which is not a perfect And
Speaker 2:it's not something we've historically done because Correct. If I'm using energy to That's right. Do my dishes and you're using energy to not not watch Netflix, we don't typically put a value on that
Speaker 8:That's right.
Speaker 2:Differently, but maybe extraordinary circumstances require mean,
Speaker 1:many many have pushed for, you know, podcast tax. Taxing. Energy consumption.
Speaker 8:Podcasts are the backbone of America. Okay. We cannot tax them. Yeah. And so you see this back and forth in Georgia.
Speaker 8:Like, I would tell you
Speaker 6:Mhmm.
Speaker 8:Okay, Virginia, which is I think the largest concentration of data centers in the country, in part, the reason Spanberger, the Democrat, won the new the recent gubernatorial race in Virginia Mhmm. Is because she campaigned on the sort of very kitchen table issue of your energy cost has gone up.
Speaker 2:Yep.
Speaker 8:I am going to do the things to make it go down. Yeah. One of which is slow down data centers. Right? And in Georgia, if you look there right now, I would tell you the best chance the Dems have of flipping the Georgia gubernatorial race in the last twenty something years is running on they, by the way, they flipped some of the Georgia Public Utility Commissioner seats, which are like super nerdy, low salience, but they flipped them on this question of, I am paying more for my energy.
Speaker 8:I don't want that to happen. How do we prevent these data centers from going on? So it's it's a big problem. And the super PACs are doing a good job, but they could be doing a lot better of a job of articulating, by the way, non AI related messaging Yeah. To support AI candidates.
Speaker 2:What about zooming out to just energy broadly? Because I feel like, well, the AI companies might be and the tech companies might be narrowly focused on data center construction, a lot of them do have bets in solar and nuclear, and a lot of venture capital firms have funded solar and nuclear efforts. And that feels like potentially a more pro bipartisan issue. How do you see that breaking? How do you see the like, when we talk to nuclear founders, we get extremely excited, and then they give us their timelines.
Speaker 2:And it's like, it'll be online in 2030. And I'm wondering if there's anything that the government can do to pull that Stop offering. Forward. Are there any efforts or any reframing? Like, if you were to put on your strategist hat on, like, how do we I mean, how do we just get excited about clean energy?
Speaker 2:Because that feels like it's longer term, but it's potentially the release valve for everyone makes everyone happy.
Speaker 8:So okay. I'll say two things. One, and I should disclose that we lobby on basically all these issues. So Sure. Everyone should just count appropriately
Speaker 2:Yeah.
Speaker 3:Yeah. Because I'm
Speaker 8:talking my own book.
Speaker 2:Okay.
Speaker 1:Yeah.
Speaker 8:One is you can think about what are the ways
Speaker 12:Thank you very much.
Speaker 2:Thank you
Speaker 8:very much.
Speaker 12:Thank you
Speaker 8:very much. One is we could think about what are the ways that we can co locate, by the way, data centers with currently stranded sources of energy. Right? So if have like, there's there's two components to energy. There's production and there's transmission.
Speaker 2:Yeah.
Speaker 8:And the government can do a lot. The federal government can do a lot on from both the research side
Speaker 12:Mhmm.
Speaker 8:And some of the permitting side on the construction consideration. Mhmm. The transmission side is a lot more nuanced and and sort of a boring conversation. But suffice it to say, like, there are very limited ways which federal government can really make a big, impact on transmission. Mhmm.
Speaker 8:And so you might think to yourself, okay. What are the ways where we can take places we've already built energy? Right? Everything from all of the above. Right?
Speaker 8:From nuclear to solar to coal to natural gas and build data centers where it already exists. Same thing, by way, that crypto mining did, right, for many many years. Call that door number one. Door number two is I am very bullish on nuclear and things of that nature and partially because we we do lobby for it. But also, like, if you're thinking about what are the ways in which nuclear moves forward, what you actually want is for the federal government to think about what are ways that we can centralize authority over permitting more and more.
Speaker 8:Mhmm. Because you don't want to have, like, the local permitting group up in arms saying, we don't want a three mile island. What you actually want is for, like, a much more centralized one stop shop authority.
Speaker 2:Sure.
Speaker 8:And so in that way, you're not you're call it industrial policy, call it big government, call it whatever you like, but you're getting back to the idea that the government plays a much firmer hand in actually driving where these things go over the short and medium term. Mhmm.
Speaker 2:Is the data centers in space thing bullish or bearish for building more data centers on Earth? Because it feels like a get out of jail free card a little bit. It's like Totally. Now that we can build them in space potentially Right. Let's just not build anymore here.
Speaker 8:Well, it's my position that America owns space too.
Speaker 2:Okay.
Speaker 8:Let's just start there for a second or at least a little bit of space. Yeah. Okay. In all seriousness, the honest answer is I find it hard to believe that the economics of building data centers in space flip before we have a government that needs, that is more flexible and more amenable to people who want to build locally. Like, part of the challenge is this.
Speaker 8:You saw the here's a quintessential example. Okay? The Germans get very excited about decommissioning nuclear energy. Right? They they have lobbied for it for years and years.
Speaker 8:They have the famous tweet you've all seen of the Green Party candidates, you know, announcing the shutdown of the last reactor. Then a crisis happens, in this case, Russia, Ukraine.
Speaker 2:Yeah.
Speaker 8:And suddenly Germany is saying, gosh, I wish we had nuclear energy. Any source of energy we would take today. K? You have the strait getting closed. You're saying to yourself, gosh, I wish we had any source of energy.
Speaker 2:I think oil is at 140 a barrel right now.
Speaker 8:Yeah. I don't know the exact, but that sounds
Speaker 1:about right. Where it was at when The Russian Ukraine
Speaker 4:Ukraine invasion.
Speaker 8:That's right. Okay. What's the common thread across all these different things? Government is reactive and people Yep. Are reactive to crisis.
Speaker 2:That's true.
Speaker 8:And so it is I don't you would never root for a crisis. You don't want a crisis to ever happen.
Speaker 7:Don't let it
Speaker 2:go to waste.
Speaker 8:But don't let it go to waste, to quote Rahm Emanuel. Right? And so you're far more likely to say, hey, what's what's more likely to me on a short medium time horizon? The economics of building in space rapidly flip possible, but I don't know how likely. Mhmm.
Speaker 8:Or something happens on Earth, and there are millions of things that could happen Yeah. Such that people now are newly incentivized to build and allow for building at home. Mhmm. And I hope it doesn't require a Sputnik moment. Right?
Speaker 8:I hope that by the way, another Sputnik moment because maybe DeepSeek was already one. Yeah. I hope that's not the outcome. But if it is, the outcome will be people are much more amenable to building, I think, locally here on Earth and in Thank
Speaker 2:you so much for coming on and breaking it down.
Speaker 8:Yeah. We appreciate you. I appreciate Congratulations, guys, again.
Speaker 2:And we will talk to you soon. Can you We have some breaking news. I can take you through while we bring in Thomas Laffont from CO2. The alley has officially been auctioned fully. The naming rights to Riley Walls' Alley have just sold to Notion for a $140,000.
Speaker 1:It's now came in.
Speaker 2:The Notion way. It does seem like they sniped it. The Notion I like that in
Speaker 1:What was WordPress do it?
Speaker 2:Called it the notion way. Yeah. WordPress was asleep at the wheel. They let it get away from them for just 5,000 more.
Speaker 1:Do not pay. Just just absolutely get it.
Speaker 2:I like that someone was trying to make it Bag Street. Core Automation Inc the way also was there.
Speaker 1:Road.
Speaker 2:Someone went back and tried to keep it named Dirt Alley for a $111,000. Gumroad was a good one. Well, we can bring in our next guest Thomas Laffont from CO2. He is here live with us in the TBPN UltraDome. Thomas, great to see you.
Speaker 2:How are you doing? Thank you so much for taking
Speaker 1:the long.
Speaker 2:It has been too long. I wanna I wanna actually begin at the very beginning. Can you tell us where you grew up?
Speaker 5:Yeah. I was born in Paris in 1976. I'll be turning 50 and Congratulations. Actually about a month and Success. Thank you.
Speaker 5:Yeah. And really split my growing up between The US and France. Yeah. My father was an executive who kind of moved around. So between Paris and New York, did a back and forth twice.
Speaker 5:Was kind of used to moving around.
Speaker 2:Yeah.
Speaker 5:Settled in New York in 1988. Mhmm. One of the first questions I get is why I don't have an accent
Speaker 2:Yeah.
Speaker 5:When my brother does. Yeah. And I think it's really related to our kind of where we grew up and our difference in ages when we moved to The US. But obviously incredibly grateful to have moved to The US. Yeah.
Speaker 5:What I do remember from France is the feeling of a country that kind of felt stuck in neutral. Sure. And so coming to especially a city like New York with the dynamic economy and just the the feeling of life just in the buildings, construction Yeah. Was incredibly motivating. I went to a really international school in New York that had a lot of different types of people.
Speaker 5:It was a French language school, so you had your kind of classic expats. You had a lot of diplomats from all over the world since French is a diplomatic language in a lot of countries. So I was really grateful to that exposure.
Speaker 7:Mhmm.
Speaker 5:Then I went to Yale, I studied computer science. My junior year, I realized what a good programmer was
Speaker 4:Yeah.
Speaker 5:And that I wasn't one of them. Wow. Because what would take a good programmer, you know, an hour would take me six days. Wow. So that was kind of sobering and I thought, okay, gotta think about something else.
Speaker 5:Yeah. And I love movies. I always watched a ton of movies. It was kind of the peak for I think kind of the movie business. We were about to roll into the DVD era
Speaker 2:Yeah.
Speaker 5:Which if you think about it now as an analyst was essentially the studios monetizing a library Yeah. Again Yep. At virtually no cost. Yep. Everybody's building DVDs, media's at the peak.
Speaker 5:You had Mike Ovets on the cover of Newsweek. Yeah. So I learned as much about that industry kind of reading the New York Times on Mondays, which was kind of the digital edition, reading Vanity Fair and Premier Magazine and anything I could get my hands on. I said, okay. Well, Hollywood sounds like a lot of fun and CAA has this training program.
Speaker 2:Mhmm.
Speaker 5:I don't know anything. I don't know anybody. I've never really been there. So getting trained sounded pretty good.
Speaker 7:Yeah.
Speaker 5:I went to my alumni house and I we had these binders and you could look up industries and there was one that said entertainment. And I saw there was one agent who had gone to Yale who was at CA, so we're now in my senior year. I called her every day for six months at the same time. Wow. And I got to actually know her assistant pretty well because agents have to pick up the phone.
Speaker 5:Yeah. Right? Because that's how their business is built.
Speaker 2:Wait. What time of day? Like early morning? Late? No.
Speaker 2:How did you settle on one particular time? Because even
Speaker 5:3PM.
Speaker 2:By default I would like mix it up and try I knew
Speaker 5:first thing in the morning.
Speaker 1:No. It's kind of an interesting thing. Like if you just get a random call here or there, you're not really paying attention to it. But if every single day at 03:00 you get the same call
Speaker 2:Exactly.
Speaker 1:By the third or fourth day, you're like
Speaker 5:I I knew she was take my call first thing in the morning.
Speaker 2:Sure. Too busy.
Speaker 5:Yeah. Exactly. Yeah. So I'm like right about right after lunch.
Speaker 2:Yeah.
Speaker 5:Right? It's like the mid morning Yeah. The mid afternoon nap, maybe I'll hit them
Speaker 2:in So weak
Speaker 5:I got to know the assistant and we would kind of joke around and but finally, one day I got a callback from her. Her name was Sally Wilcox. She was a book agent. And she said, well what's it gonna take for you to stop calling me? I said, well I want an interview.
Speaker 5:And she actually gave me, I thought an amazing answer to that. She said, well if you agree to move out and you call me after you've moved out to LA, I'll get you the interview.
Speaker 7:Mhmm.
Speaker 1:She wanted you to move
Speaker 2:move before you even get the interview. That is crazy.
Speaker 5:I realized what she was doing was she was kind of testing my conviction. Sure. Right? And she probably got a lot of calls from people who said, oh, I want to do this, I want to do that. Yeah.
Speaker 5:And she's like, well, if you have the conviction in yourself to move out with no job, that shows you really kind of want it. It was probably a filter on her part.
Speaker 2:Yeah.
Speaker 5:So I did. And it was my second time I think in LA and I called her. Mhmm. And I only had one egg in the basket. There was no other egg in the basket.
Speaker 5:This was the only egg in the basket. So I called her. Said, well, remember? You told me if I moved you would give me the interview. And she did.
Speaker 5:I interviewed I think on some I moved out May 22 Mhmm. I think after I graduated. I got here June and by July 7 was my first day Wow. Of 1997 in the CA mail room. In the mail room.
Speaker 5:And I think you guys were just maybe there. Right? Was just this iconic place and a lot of people I kind of looked up to had started in the mailroom. Ron Mayer had started in the mailroom. David Geffen, Barry Diller.
Speaker 5:So I'd read about all these legends of the business kind of starting.
Speaker 2:There was a dress code back then too?
Speaker 5:What's that?
Speaker 2:There was a dress code back then too.
Speaker 5:Oh, absolutely.
Speaker 2:Because yeah, there's still a dress code today. That I think that's the thing that sticks out the most about the mailroom is just the number of talented young people that you have in a pretty small space Yeah. And they're all dressed perfectly.
Speaker 4:Yeah.
Speaker 5:Which is just And every experience you have Yeah. In that mail room is kind of unique. Mhmm. So I'll tell you guys this story. I don't think I've ever shared this one publicly but we did a lot of work for Ralph Lauren.
Speaker 5:And this is back kind of in the Friends era. If you remember Jennifer Aniston's character on Friends worked at Ralph Lauren. Yeah. So he's coming in and he's doing a taping. And so I'm asked to go pick him up at the Beverly Hills Hotel and just escort him for the day while he's shooting the scene.
Speaker 5:And if you remember the scene, it's in an elevator and Jennifer's character Rachel bumps into Ralph and it's like a twelve second scene. You can look it up on YouTube. So it took like three minutes to shoot. So we get on set at nine. He, by the way, I think he's in denim on denim, just classic Ralph.
Speaker 5:Right before he goes on, he's like, collar up or collar down? I'm like, call her up.
Speaker 1:Let's go. We're rolling.
Speaker 5:We're rolling with this. And so it takes like three seconds. And so we arrived at nine and like 09:08 and we're kind of done. And Ralph says, well, I didn't think this would be that quick and my next meeting's not till 04:00, so why don't we go and spend some time together? And I'm really kind of interested to go where you shop.
Speaker 5:Mhmm. Oh, interesting. Oh, gosh.
Speaker 1:Ready? He wanted to jump right into market
Speaker 2:Yeah.
Speaker 5:So we spent the whole day going together, shopping around. One memorable one was going to Fred Siegel, like when Fred Siegel on Melrose was every new brand was kind of getting broken into there. I just watched him walking around and the way he engaged with every single salesperson, never talked down to him, to your point did market research. Why are people buying this style, not that one? It was just amazing to watch.
Speaker 5:Mhmm. And how just curious he was and how much he wanted to learn. So we finish and I'll get to the end of the story, but at the end of the day he's like, look, gotta ask you something, it's really bothered me the whole day. I'm like, yeah. He's like, why aren't you wearing Ralph Lauren?
Speaker 5:And I said, look, honestly, the cut's not great and the store on Beverly Drive is a little old and then there's a lot of wood. It doesn't really feel kind of new. And he's like, man, you're so right. But he's like, you really should be wearing Ralph's, so go there and just tell him I sent you and you can get anything you want. Wow.
Speaker 5:So we kind of parted ways and he was he was really lovely. But I debated whether I should go or not. And the next week I go and I go and I introduce myself to the very pretty lady at the counter and I said, look, I'm sure you get this all the time. You're gonna think I'm a crank. Mhmm.
Speaker 5:But Ralph sent me and he said I could get whatever I want. And she paused for a minute and she looked me up and down and she said, oh, we've been waiting for you. No way. And I kind of spent the, you know, an hour kind of going through the store. But, you know, the exposure that you got to people through that job was really amazing.
Speaker 2:Yeah.
Speaker 5:Watching, you know, actors, watching directors, watching entrepreneurs like Ralph. So I was really grateful for that opportunity.
Speaker 1:Talk about you you had a we were catching up yesterday off air and you had a story about you can just talk generally about your what what what maybe entrepreneurs could learn from actors and actresses that are breaking in through Hollywood and what they have to go through from a competitive standpoint to actually break out. I'm sure you got to see a bunch of different stars over the years, but the, you know, everything from, you know, the rejection to to the the constantly having to, you know, constant hustle because, you know, as soon as a project ends, it's like, okay, what's the next thing?
Speaker 5:Yeah. I think I think people underestimate first of how hard it is to be an actor and how competitive it is. First of all, especially in the movie industry, right, you have to kind of find a new job every, you know, six or seven weeks. Mhmm. So you're constantly unemployed.
Speaker 5:You're constantly having to search the new job. Not only that, when you go and you actually interview for a job, you might run into 10 other people that look exactly like you. Right? All of your competition, like imagine if I was pitching an entrepreneur and I'm like, oh, there's Sequoia and Andreessen and Benchmark and we're all kind of sitting lined up next to each other waiting. That's kind of what actors go through when they audition.
Speaker 5:And then by the way, when we give you feedback, it's not even feedback on your business, it's on you. Don't like how you talk,
Speaker 9:how you look.
Speaker 5:Yeah. You're tall.
Speaker 6:Or it's
Speaker 1:your ears.
Speaker 6:Your ears are Right.
Speaker 5:I I represent represented Jordana Brewster who's a friend now and is married to a friend of mine. But one day on one of the casting sheets it said, hey, a Jordana Brewster like actress for this role. So I called and I said, well, what about Jordana Brewster? This is literally who you said. They're like, no, no, no.
Speaker 5:We just want someone like her. I said, well, what about her? Right? But that that is the kind of stuff. And obviously the competition is intense.
Speaker 5:Yeah. Right? And it actually reminds me a little bit of what it was like to be an entrepreneur in China. Right? Very similar like you would have if you had a ride sharing company.
Speaker 5:There were a 150 other ride sharing companies that you had to kind of get through Mhmm. Just to then win your city to then go compete with all the other cities to then at the end compete against Uber in China as an example. And Didi kind of won that. So it's an extremely competitive kind of industry and I relate to that. As someone who worked with actors, you would sometimes talk to an actor and say, how'd the audition go?
Speaker 5:They would tell you, I nailed it. It was just so good. And then you'd call the casting director or the director and they would say, that was the most unprepared, bad audition. And so you have to figure out how to communicate that feedback in a way that's constructive to the client. Right?
Speaker 5:Because just telling them, oh, you did great but you didn't get it isn't necessarily useful. Yeah. But in a way that doesn't also, you know, is detrimental, right, to their mental health and things like that. So it's it's very much a people, a reputation kind of business. Mhmm.
Speaker 5:And I really enjoyed it for the seven years I did it.
Speaker 2:Yeah. What was the process of getting out of the mailroom? I imagine that you have, you know, a few really iconic stories from the mailroom but there were plenty of days that were just photocopying. Is that roughly correct?
Speaker 5:Yeah. I mean we did we did shopping for groceries. Oh, sure. We we copied scripts. We delivered scripts.
Speaker 5:Yeah. So there was a whole set of kind of stories on that and honestly we could we could fill a lot of podcasts. Yeah. Just the different things that we kind of did. But look, it it rewarded hard work and rewarded attention to detail.
Speaker 5:Yeah. Ultimately, and you got invited to the retreats, right? And CA did these retreats every year and after one of them I had some thoughts, I wrote them down Mhmm. And I hand delivered a letter to the managing partner saying, I was at the retreat and here are my thoughts. Right?
Speaker 5:Wish I still had it. I don't know what I said. And then I didn't hear anything for a long time. But when I came off what was called the runs where you delivered scripts, you then waited to be picked for a desk. And only the top five got to interview for desks to try and not keep people jammed there too long.
Speaker 5:But the desk O'Brien Lord opened up and he was the co chairman and is now the CEO. And he asked to interview me because he had read my memo and he said I want to interview the kid from the memo even though he's not in the top five, I don't care. So I went up and I'd never really met him or spent any time with him before. But we sat down and somehow we got talking to about John Steinbeck which was my favorite writer and I was reading a biography of him at the time and we spent thirty minutes talking about John Steinbeck. Nothing about business or how do you answer the phone or what he's looking for in an assistant.
Speaker 5:So I came back down and all the guys were like, how'd
Speaker 6:it go?
Speaker 5:I'm like, well, I don't think it went well because he didn't ask me a single question other than, you know, was talking about John Steinbeck. So I'm like, there's no way I got this job. Yeah. And then he ultimately kind of gave me the job.
Speaker 2:Yeah. That's amazing.
Speaker 5:And I worked with him for almost three years.
Speaker 2:Yeah.
Speaker 5:Unbelievable experience coming off of Mike Novich, having gone to Disney, then having flamed out and starting his own company. So much kind of turbulence in the industry. And he was an amazing guy and it was it was a great formative experience for me.
Speaker 1:Since we are in Hollywood running a a show that covers venture, was there anyone in that era of Hollywood that was from the talent side that was leaning in and investing in in in startups of any kind?
Speaker 5:No. I mean, what I remember from that era is no one really thought about the investing side of it per se. People thought that, wow, the business is going to be digitized, so let's think of creating content for these new digital channels. And so it was more on the monetization side of here's a new distribution channel called the Internet and how can we adapt our businesses to that new channel. Yeah.
Speaker 5:I had always loved kind of investing, so I was kind of trading public market stocks on the side. Sure. And my brother and I kind of started kind of doing that together and I just bought companies that I liked and Yeah. Was kind of doing it as a hobby. Eventually, I was promoted to an agent, I kind of realized two things.
Speaker 5:One is I preferred being an assistant to an agent. Oh. I I preferred being an assistant rather than an agent. Yeah. Yeah.
Speaker 5:So that was one. And then two, I kind of really like this stock thing
Speaker 2:Yeah.
Speaker 5:On the side. Right? And someone said, well, always invest in someone's hobbies because that's what they choose to do in their spare time. And so Philippe called me and this was a couple years into Cotu and said, we're kind of trading this account together anyways. Why don't you come over and do this?
Speaker 5:Yeah. And, you know, that's how I got started.
Speaker 2:And, yeah, what year did you get started at CO2? What was 2000 then? Walk us through post.comcrash. How are you feeling? What's the strategy?
Speaker 5:2003, so we're just coming off of 2000, 2001, 2002 and down 80% on the market.
Speaker 2:Yeah.
Speaker 5:O three kind of had a snapback, so the market was up 50%. We were well positioned for the downturn, not as well for the snapback. But now it's about, okay, what do the next kind of decade kind of look like? Right? The easy money's been made on the quick rebound.
Speaker 5:Right? Mhmm. Nasdaq I think was up 50% year to date or And something like we were really looking for semiconductor analysts. Mhmm. And couldn't find one.
Speaker 5:And this is something I'll forever be grateful to my brother for, but eventually he said, look, since we can't find one, he dropped a copy of the universe and this universe was a printed memo of essentially all the stocks and key metrics about each name. P. E, volume, sector, the semiconductor universe. And he said, you know, why don't you go ahead and do it? Can't find anybody anyways.
Speaker 5:And, you know, I had no real training as an analyst and, you know, I I would sit in our bullpen and there were analysts from Morgan Stanley and Goldman Sachs and I thought, man, my training was in a mail room. You know, I don't know anything. But what I started to realize is the downside is I didn't know anything. The upside is didn't have any bad habits either in terms of how so I really learned from my brother directly and I started to define how we want to invest versus how maybe you learned it at Goldman or a mutual fund or something like that. And so I kind of relearned from first principles, you know, Philippe and I kind of working hand in hand.
Speaker 5:And I started learning semis and pretty soon if you started in semis at the time, all the roads led to one company and that was in Cupertino and it was Apple. Yeah. Why? Well, because the iPod was starting to really gain traction and an iPod was a semiconductor product. It had NAND flash.
Speaker 2:Yeah.
Speaker 5:It had a processor.
Speaker 2:Yeah.
Speaker 5:So that was the gateway into Apple, which eventually led to the iPhone. Yeah. And it was kind of an iconic investment for us, and we got to know that management team really well.
Speaker 2:Yeah. Wanted to ask you about that. How much of your investing philosophy at the time was quantitative, pulling metrics, building models versus doing expert calls, talking to management teams, listening to earnings calls, the
Speaker 5:was a really sacred place for me. And because I hadn't trained as an analyst, I felt I needed to build every model myself because I didn't trust myself with someone else's work because I wasn't good enough. So I'm like, well, I'm gonna build every single cell myself. That's going to mean I'm going to understand it if I built it myself. Right?
Speaker 5:Versus if I take someone else's complex model Sure. Sure. I'm not going to understand. I'm going to rip a DC since he's number 10 for the day. So let's go.
Speaker 5:I knew when you had coffee, by the way, after dinner last night, was like, okay.
Speaker 2:Get ready for the coffee.
Speaker 8:Yeah. Yeah.
Speaker 5:So I felt like I had to rebuild every model myself because I couldn't understand someone else's model. Sure. And what happened in the process of building that model is as I would go through a sell side model and there were lines that I thought were irrelevant, I said, well, why should I add that to my model? Like this is driving no value. But it was kind of a verboten thing at the time.
Speaker 5:It was like, well hold on, the company reports it this way or Yeah. This is a revenue line and for the sake of accuracy you kind of need it But in like I didn't know enough to basically say, well, to me it doesn't drive any value to my investment thesis so I'm just going to lump it into Yeah. This other Called other. And I'm going to rename things the way I understand them. Not the way the company chooses to report it.
Speaker 5:My model. Yeah. Basically just what made sense to me and what my thesis was about. So that when I pitched my thesis, my model actually reflected what my thesis was.
Speaker 2:Yeah.
Speaker 5:Right? Not let me pitch you my thesis, but now I have a thousand line model and I have to go from row two to row seven to like the other tab then back to line 250 to kind of explain it to you, like that made no sense to me. Like the narrative was no, let me show you from the top line all the way to the bottom how it flows and what the key functions are.
Speaker 1:Yeah. What's what's by the way, our philosophy. Yeah. Is doesn't that kind of still define like a partner meeting that like, aren't you guys like, let's say you meet an entrepreneur, you're excited about them, you do the work, and then from what I've heard, you guys will spend like hours and hours and hours still just in the model, like ignoring ignoring
Speaker 5:And we will, but a lot of times you might be getting a model from the sell side. Sure. Right? Because it's faster and it's more convenient, but it might not be exactly how your thesis is being laid out, right? So one of the things I try and talk to all of our analysts and say, well, let's have a model that really reflects our simple view of what the thesis is and what drivers are.
Speaker 5:So I think a model to me is kind of a sacred place. And in fact, our Apple model, which I then passed on to Jaemean Rangwala, who's now our CIO, was kind of this sacred I didn't let anyone edit a cell on that model. I knew every single cell. I knew the color. I wanted a very specific kind of color for the background of certain cells, right?
Speaker 5:And eventually that kind of got passed on. But to me at the end of the day I learned this in actually back in Hollywood we had all the trainees one day got brought into a meeting with Steven Spielberg. Mhmm. And Steven said every great story can be pitched in three sentences no matter what the story was. And I always said, so pitch me a story or a movie and I'll pitch it to you.
Speaker 5:And no matter how complex the movie was, he understood the essence of it Mhmm. And in three sentences you got the whole movie. And what I realized is, it takes a true understanding of story to be able to crystallize it in three sentences. Right? If you don't understand something, you'll say, okay.
Speaker 5:Well, TBPN is a podcast and it's about these two guys and they do this. Well, do you really understand what it's about? Because you just gave me ten minutes of rambling
Speaker 2:Yep.
Speaker 5:Stuff.
Speaker 2:Yep.
Speaker 5:Right? And all the great investors that I've met like Stan Truckenmiller or you know my brother Philippe or Dan Loeb or some of these kind of legends of the hedge fund world. Right? They have an ability to take any kind of story and just drill it down into its essence, to what the key pivot points are that are gonna make or break that stock
Speaker 2:Mhmm.
Speaker 5:At that particular moment. And so we really try and say our thesis should be simple. We should be able to explain them very in, you know, few sentences. Right? And you should have a model that reflects that thesis.
Speaker 7:Mhmm.
Speaker 5:So on the public side in particular, then we dive into, okay, let's go into your model and let's say, okay, can Apple sell 50,000,000 phones? Can the ARPU be in the out year? Is it going to increase? Is it going to decrease? You know, when I look back at our old Apple model, I actually think we did a pretty good job on units.
Speaker 5:Where we were way off is we had the price of the phone declining five to 10% a year because that's what every consumer electronics product Yeah.
Speaker 2:Did. TVs.
Speaker 5:And in fact the ARPU doubled. Right? Yeah. I think the first iPhone was like 500. 600, right?
Speaker 5:Unsubsidized. Now people sell. And 1,200.
Speaker 2:Easily. Right?
Speaker 5:Yeah. So never would have kind of forecast that.
Speaker 2:Interesting.
Speaker 5:So, yeah. So models are are quite important
Speaker 2:to us. What was the what was the mood in the hedge fund industry broadly during that time around different strategic expansion opportunities. There's obviously a high frequency trading boom that's happening. There's more quantitative strategies. There's debt strategies.
Speaker 2:There's so many hedge fund can mean so many things. How were you thinking about defining what you would do best and where you would expand to or decline to expand to?
Speaker 5:Look, I think for tech it was an amazing environment to be in because almost every company was getting swallowed up or Yeah. So if you were in TMT Yeah. You really felt like you were the center of the universe. Correct. That makes sense.
Speaker 5:And then also we had companies going public pretty early on. Mhmm. You could do a lot of differentiated work in companies that the market cap was a couple billion.
Speaker 7:Yeah.
Speaker 5:Right? I think what really changed for us in the early two thousand tens was Meta, then Facebook
Speaker 2:Mhmm.
Speaker 5:And Alibaba staying private for longer. Yeah. We just never seen companies of that scale who were that important to our research and our market not go public.
Speaker 2:It was Meta or Facebook went out
Speaker 5:at like 60,000,000,000, I believe, something around there. Right? And right around 02/2000
Speaker 2:So if you're used to buying a company potentially at 2 or 3 or 6,000,000,000, that's a big miss.
Speaker 5:It's like a 10 x difference. Yep. But not only that, we actually were an investor in Google from pretty shortly after the IPO. Sure. And Google had this stretch post financial crisis where it kind of traded sideways for a long time.
Speaker 2:Yeah.
Speaker 5:And the reason was here comes Meta or Facebook and they're going to replicate a private internet that Google won't be able to search Mhmm. And so Google's going to be under pressure. Yeah. And we weren't able to talk to Meta, so we didn't know what they were thinking.
Speaker 2:Sure.
Speaker 5:As soon as the company went public, ironically, Google stocks started working. Yep. Because they didn't come out and tell you we want to kill Google or we're replicating the internet. We're doing kind of something different. Both stocks ended up working.
Speaker 2:Yep.
Speaker 5:So that was kind of a big eye opener to us. Yep. It felt both offensively minded Yeah. And defensively minded. Yeah.
Speaker 2:How could you tell at that moment? Obviously, it was correct that companies would stay private longer. But I'm sure you were debating the question, is Meta the outlier or the the exception that will eventually prove the rule versus there's a structural shift in private equity venture capital that will propel many more companies to stay private well into the tens of billions of dollars in market cap?
Speaker 5:We would not have foreseen what ended up happening. Sure. We had an instinct Yeah. That it might happen. Yeah.
Speaker 5:Remember that Spotify is kind of getting Yeah. Built at the same time Yeah. Right? And it's redefining music and we really, you know, as I mentioned Apple was a core thesis for us and now with here comes subscription music which goes directly against Apple's model of selling you an album. And so what's going on?
Speaker 5:They just did a round of 3,000,000,000, felt like a lot. And then Uber. Yeah. Right? So it was it was just kind of you felt an Airbnb, right?
Speaker 5:Yeah. So I would say like those two companies, the mobile internet coming out, these companies getting big in in private markets, It felt like undeniable momentum. Mhmm. Right? And so and China, by Right?
Speaker 5:The The same. So we felt like we had to participate.
Speaker 2:So what was the first private investment you made?
Speaker 5:Evernote. Evernote. I think it was one of the first. And we said, look, we're gonna do later stage deals, a 100,000,000 plus in revenue. So we did deals like Evernote and Box and ironically our most successful deal is one that broke all of the rules that I just laid out, was Snapchat.
Speaker 2:Okay.
Speaker 5:Where I think we led the series c Mhmm. In that an evaluation of about 1,000,000,001 half.
Speaker 2:Yeah.
Speaker 1:And And what was the reaction from other more traditional venture investors when you guys started leading around?
Speaker 5:I think that look, venture felt very different back then. There was fewer firms. There was more Atrified thinking.
Speaker 7:Mhmm.
Speaker 5:Right? Andreessen is just kind of starting. We actually shared a building with them. So we were kind of starting at the same time about as they were. And it felt like, wow, we're gonna bring a bit of a different competitive energy to this market.
Speaker 5:It felt very clubby. Sure. You hadn't seen like these new firms like founders that obviously you know and a bunch of others kind of really make their mark.
Speaker 2:Yeah.
Speaker 5:So it was sharp elbowed for sure. Mhmm. And still is in many respects which is probably what I like the least about that market because I love talking about ideas, love trying to be a positive some thinker which the public Easier
Speaker 1:to do in the public markets. Correct. Yeah.
Speaker 2:Did you bring the the models to private markets? Were you building financial models with a team?
Speaker 5:We did. I think we brought that. We brought analytical thinking. Yeah. We brought kind of deep research.
Speaker 5:Like I remember reverse pitching Aaron Levy at Box, a big deck that we had done and we had just done what we thought was kind of public market like research but we brought that to a private entrepreneur and he hadn't seen that kind of work before. So that was a differentiator for a minute until other firms realized, wait, we can do that. Or even better, we can outsource it to Bain. Yeah. Right?
Speaker 5:And so we had to kind of quickly kind of adapt to that. Yeah. But in the beginning it was novel.
Speaker 2:Yeah.
Speaker 5:And that was an industry that was really done in word and we were Excel thinkers.
Speaker 2:Yep. Yep.
Speaker 5:So that was kind of a very different kind of mindset that we were bringing to the table.
Speaker 2:Was there any shift required in the messaging to LPs, the fund structuring, anything that were that you had to work through in order to actually set up the fund for success in the private markets?
Speaker 5:I think our LPs first of all, LPs are not talked a lot about in venture, is kind of interesting. Like we talk a lot about the founder, we talk a lot about the companies. I would say for us, we are pretty clear that our customer at the end of the day is our LPs. Yeah. And so the trust that they give us means a lot.
Speaker 5:I have virtually no outside investments. I I do some as favors and things like that. Yeah. But almost everything I have and own Mhmm. Is in our funds.
Speaker 5:So we kind of act as entrepreneurs and as owners ourselves.
Speaker 6:Mhmm.
Speaker 5:And we asked for trust from our LPs and I think at the end of the day they were willing to give us a chance in our first fund. I don't think they held us specifically to exactly what we said we were going to do, but they're like, these guys are pretty disciplined and they're pretty smart and they're entrepreneurial and aggressive and let's see what they can do. Mhmm. Right? And so, I think over the years, what's helped us most in our business, and I think why we're still in business twenty five almost years or twenty seven plus years later when a lot of our peers have disappeared over time is we never lose sight of our investors and hopefully we've made some good decisions, but we've also made some bad ones.
Speaker 5:But I think our investors learn more about us on how we deal with our bad decisions. Mhmm. Right? And so I think we've earned hopefully some trust from them over So the I remember distinctly an investor when I called about the snap deal and saying, look, I know this is a bit off brand. This was one of the largest investors in the fund, but I just have a lot of conviction in this deal.
Speaker 5:And he said, then do it. That's what ultimately why we're investing in you. And so I think the the trust that you build, the relationships that you build with your own investors over those periods of time are really important.
Speaker 2:So relationships with entrepreneurs, building models for, you know, Apple ARPUs, you projecting units, that feels all very micro. Yep. How have you processed macro statistics and and factors like interest rates? Everyone talks about when interest rates rise, all the DCFs change. There's a pullback in the private markets.
Speaker 2:We we lived through this with, the end of ZERP. But how much are you tracking the labor market, the GDP numbers, the interest rates? And how much of a factor is that on the strategy day to day, month to month, year to year, or even like broader terms?
Speaker 5:Yeah. So data science has really become a much larger part of our business than it was back then. Sure. So we now have, I don't know, maybe 20 or 20 ish, 20 to 30 people Yeah. Something like that in data science that are just processing different types of data and alternative data.
Speaker 5:So think it's not just macro data, it's app store data, it's click stream data, it's credit card data. Sure. So we use a lot of that for our investment research.
Speaker 4:Yeah.
Speaker 5:And some of that we even make accessible to our portfolio companies. Right? So that made us smart about a trend. We were early customers of Databricks and Snowflake as an example that let us invest in those companies. Yeah.
Speaker 5:So that is way more of a presence in today's world than it was, you know, twenty years ago. Yeah. We're constantly looking at data as an example. You know, I think OpenAI is probably the most important company in the world today in the sense that it's the driver of AI both consumption and spending. Mhmm.
Speaker 5:So I look almost every day at the chart of ChatGPT users download share, how it's weathering the storm versus other competitors. You know, that's really something that wasn't available ten fifteen years ago.
Speaker 2:Sure.
Speaker 5:With this amazing data set called Onava, which actually gave you engagement data from users on phone and then Zuck bought it. No way. Turned it off. And I remember thinking like, damn that guy. That's a great move.
Speaker 5:It was the only data set that really gave you engagement data.
Speaker 2:Yeah.
Speaker 5:So we're always looking for kind of new Yeah. Data sets. Right? And then obviously so that felt like a major shift, right, going from, you know, data science enabled research. And now obviously we're getting to AI and Yeah.
Speaker 5:Agentic research and
Speaker 2:How are you thinking about AI as a category from an investor perspective versus the Databricks and Snowflakes, which to me feel it's easier for me to maybe understand the financials, the model that I would build, how I think about value accrual and competition in Databricks and Snowflake. Fantastic businesses, but feels like easier to pattern match against previous eras of software and tech innovation versus AI where you have infrastructure and CapEx and training costs and inference budgets and all sorts of different your your entire products getting copied by open source every three months. And it just feels like a different different puzzle to solve when you're thinking about underwriting those businesses. Like how have you grappled with that? Do you see it as an extension of the tech investing or is it an entirely new motion?
Speaker 5:Well, for me it was almost coming back home to what I knew Okay. Because the infrastructure layer was really semiconductor driven. Sure. Right. So I think our knowledge of semis and our team's knowledge of semis was a great head start.
Speaker 5:Mhmm. Because a lot of people just hadn't done semis. Mhmm. So we're kind of new to semis and I had a lot of relationships in the industry and that led us to leave the series being cerebris Yeah. That I think will be kind of a generational kind of company.
Speaker 5:Yeah.
Speaker 2:I love the actor he's been on multiple times.
Speaker 8:He's So been
Speaker 5:that felt very natural to us. And pretty quickly when we saw what Jensen was building and the momentum that Nvidia was building in the data center.
Speaker 2:Yeah.
Speaker 5:So that was kind of our first telltale that wow, something big is going on here. So we had seen semis before in the mobile era.
Speaker 2:Yep.
Speaker 5:So we felt very equipped when AI first came around to look at it from a semiconductor, GPUs, memory, TSMC. Yeah. I've personally been to Taiwan many times, visited TSMC. Great anecdote. I'm driving back to Taipei City with my host from TSMC and we're on the highway and there's a golf course and it's nighttime, so there's there's lights and people playing.
Speaker 5:I just very innocently turned to him and said, wow, you guys you guys play golf at night here. And he very innocently looked back at me and said, well, when do you play? And that's when I realized like that's we're in a different level of of work here.
Speaker 2:Yeah.
Speaker 5:So we saw it at the infrastructure layer first, right? Where it just became obvious you didn't have to necessarily worry about who was going to win, like the whole infrastructure layer will win. Yeah. So I think that was kind of layer one. I think layer two then came kind of the models and obviously investors in a number of them.
Speaker 5:I'd say the most complex element of AI today is you can almost talk yourself into a bulk case and a bare case for almost any name
Speaker 2:Yep.
Speaker 5:In tech. And I think software is kind of seeing that right now, So is software going to win because of AI or get displaced, So you've got that. In infrastructure, you've got the, well, when is the peak? And what multiple peaks should things kind of trade at, right? So it's both an exhilarating dynamic but also very complicated environment in the sense that like, for example, when Databricks came around, no one thought, well gee Databricks is going to put Salesforce out of business.
Speaker 5:Mhmm. Yeah. Right? It just felt like a new architecture. Yep.
Speaker 1:Yeah.
Speaker 5:There's something about AI that feels a lot more disruptive. Yeah. And what if your model, not today but in two years, can just build you a workday right off the bat? Yeah. What does that mean for workday?
Speaker 5:Does that mean their data's more valuable? Yeah. In on the left hand side or no?
Speaker 1:Does that
Speaker 5:mean they get fully wiped out?
Speaker 2:Yeah.
Speaker 5:So I think that battle and it's being played out kind of in the public market today, right, you kind of see it in in these names is
Speaker 2:How can a public company CEO actually communicate a vision for that case, the bull and bear case around AI? What effect AI will have on their company?
Speaker 5:I mean, you're seeing it. It's I I read I read something that we're we're kind of moving into a selection market.
Speaker 4:Mhmm.
Speaker 5:Right? So now like some companies are going to do well, some companies are not. I mean, look at Square, right?
Speaker 2:Yeah.
Speaker 5:Jack came out and just said, no, I'm pivoting the entire infrastructure of this company for an AI era. We think you're going to need to be remote, right, because you're going to move faster if you're remote. And so he's kind of laid out a whole vision about how he wants
Speaker 1:you're sort of generating the necessary context because you're not getting the in person interaction so you'll small teams. Yeah. Small teams. You'll more more easily be able to be AI native if you're Yeah. Basically explaining process.
Speaker 5:Yeah. Very small teams moving really quickly without a central organize or or you know, kind of like the Borg, right? No central organizing force. The model drives everything. Mhmm.
Speaker 5:Then you have other companies that are saying no, product. Well, the labs themselves, right, are all in person. And they believe, right, that you product development needs to be done kind of in person. So you're kind of seeing a lot of these different ways of, you have different models. Some people are going to charge for tokens.
Speaker 5:Some people are going to charge for data access or ingress and egress.
Speaker 7:Mhmm.
Speaker 5:So I think what we're seeing right now play out is a true Darwin like survival of the fittest where software companies are
Speaker 1:It's like the mailroom. Exactly. Right?
Speaker 5:You saw Aneel come back to Workday, right? He probably thought that I think Carl is an amazing executive and is a good friend of mine. But maybe he thought in order to make the changes I need to be have that kind of founder mindset, right? Founder mode Yeah. As Brian calls it, right?
Speaker 5:So we're seeing now a lot of these different approaches kind of compete with each other. I think it's too early to tell who's going to win. But eventually, think we should see kind of separation between winners and losers. Right? Which should be good for our business.
Speaker 5:But I think right now it's still so early that it's not clear who will win.
Speaker 2:Is it enough to look at reaccelerating top lines? I imagine we've talked to a lot of founder CEOs. Maybe they're unicorn status decade in, completely reinvigorated by AI. They come on. They see that the growth has returned.
Speaker 2:It feels like a new start up even though they're maybe coming back from a sabbatical. Maybe they're coming back in after hiring an outside CEO. Maybe they're just coming back in with a new vigor. But what what are you seeing more at the earlier stage or mid market stage around companies that are starting to show signs of being winners in the AI age?
Speaker 5:I think look. The good news is no one is head in the sand Mhmm. About this. Yeah. So I do think in prior cycles you had more of a head in the sand mentality.
Speaker 5:Mhmm. Right? So for example, if I remember when cloud got started, there was do you remember virtual cloud? Right. That was going to be the big thing, right?
Speaker 5:I can't just have my stuff in Amazon. Yeah. I'm going to have this virtual cloud and you know obviously that hybrid cloud, right? Yeah. It's another one.
Speaker 5:No. It's going to be all the big data, right? Yep. All those things basically just got torched and went by the wayside, right? So there was a lot of head in the sand.
Speaker 5:Similarly with the iPhone. You need a keyboard. It doesn't have three g. It doesn't support Adobe.
Speaker 1:Doesn't have copy and paste.
Speaker 5:Exactly. The battery life.
Speaker 2:Yeah.
Speaker 5:Right? Bengate. You may remember that one. That was a whole weekend. Or something?
Speaker 5:Whole weekend wasted on Bengate. So there was a lot more to me head in the sand in prior Sure. Investments cycles Yeah. Right? In prior tech themes
Speaker 2:Yeah.
Speaker 5:Where people were just pushing back against the idea Yeah. That this was going to work. Yeah. I think AI is one where the consensus view is it is going to work. It's not it's an extension extension level event and so the sense of urgency is high.
Speaker 5:So that does feel a little bit different to me than maybe prior cycles where I think that took time for right? The carers are like, well, not going to allow Apple to have an App Store and I don't want to be a dump pipe and Right. So they all these things that they fought.
Speaker 2:Yeah.
Speaker 5:And over time tech won.
Speaker 2:Yeah.
Speaker 5:The difference to me with this specific cycle is everybody agrees it's gonna happen and it's happening quicker and the stakes are higher than any other.
Speaker 2:Yeah.
Speaker 5:So I think every board is ultra motivated. Every founder is focused on this. Now, they're bringing different approaches and and you know, we'll see which ones win out. But I would say they're tracking token consumption, right? So how much of my revenue is token based?
Speaker 5:Right? How much of my COGS is token based? How much of my G and A is token based? How much of my spend per developer
Speaker 4:Mhmm.
Speaker 5:On Cursor, OpenAI and Anthropic is happening. Right? So that in, you know, I do sit on a bunch of boards as an observer most most of the time. So I kind of see a lot of that kind of happening. So the awareness is absolutely there.
Speaker 5:People are doing different approaches. There's some that are, no, I'm in a white box, a totally new product Mhmm. Right? That where I think I'm uniquely positioned to build it. And then there's others who are like, no, my data set is so valuable, I'm not going to allow my customers to build apps directly using my data.
Speaker 5:Mhmm. So you're seeing a lot of kind of different approaches. Yeah. Right? But everyone's awareness is at a 12 out of 10.
Speaker 5:Mhmm. So there's no convincing needed. Right? Everybody's aligned, every board member's aligned, every investor and now it's about, okay, what does that sense of urgency mean for this company? What are the things that we need to track and the things that we really need to go and execute on?
Speaker 2:What does it take to make it as a new hire at Co2?
Speaker 5:So we do and I'm assuming you mean on the investment
Speaker 7:Yeah.
Speaker 5:Staff, right? We do case studies. Very important part of the process for me. We usually pick a public name, right? Because we want to test your thinking.
Speaker 5:And my favorite types of names are names where there's a good bull case and a bear case. And whichever one the prospective analyst argues, I will vehemently argue the opposite. Yeah. Right? Just the Exactly.
Speaker 5:Understand their thinking. So that's really really important.
Speaker 2:Are you trying to pick obscure names or household names, everything?
Speaker 5:No. I mean, for a long time we used Netflix.
Speaker 4:Okay.
Speaker 5:Yeah. Right? As an example. That was a really controversial stock
Speaker 2:Yeah.
Speaker 5:Both in the DVD era then when they moved into streaming Yeah. Then when they moved into proprietary content
Speaker 8:Yeah.
Speaker 5:It was a heavily shorted stock over that period of time. So there was a lot of interesting
Speaker 2:Sure.
Speaker 5:Ways to look at that name. Right? And you could ask interesting questions like, well, if they increase, you know, price by a dollar, what happens to EPS? And what you realize is it was almost all profit. Yep.
Speaker 5:So EPS went up a lot.
Speaker 2:Yeah.
Speaker 5:So we're just really trying to test thinking.
Speaker 2:Have you ever had to revisit a candidate who made a really great bull case or bear case that the firm maybe didn't agree with and then they came back with an I told you so five years later?
Speaker 5:You know, I've never had someone kind of email me that, which surprising because we we've done a lot of
Speaker 2:case studies. Can imagine there's
Speaker 8:a couple
Speaker 2:I told you so. It like, oh, yeah. Yep. I called Domino's or whatever.
Speaker 5:And and honestly to me, it's not about whether they say the right you know, sometimes you've
Speaker 4:built to go
Speaker 5:it has to be if I say bowl of bear, it's
Speaker 1:the Yeah.
Speaker 5:Doesn't really matter. It's like how did you articulate your thinking? Did you lay out a clear model? A lot of kind of where where we were starting. Yeah.
Speaker 5:Right? And so that's my favorite part of this job is thinking through a name and the opportunity and Yeah. What could happen and Yeah. It's kind of the intellectual backbone Yeah. Of what we do.
Speaker 5:Yeah. You know, I would say that I think the key to our platform is number one, like seeking big themes and big ideas. Mhmm. That's a big one. And then the kind of the risk management piece.
Speaker 5:Yeah. Right? That's kind of kept us in business for a long period of time.
Speaker 2:How is AI changing the role of early analysts or career or analysts who are earlier in their career on the investment side?
Speaker 5:Too early to tell.
Speaker 2:Too early
Speaker 5:to Obviously, look, we use AI every single day.
Speaker 6:Yeah.
Speaker 5:I use it a lot to test my thinking, to clarify my thinking. I've always had a weird dichotomy personally where I I'm I love reading but I'm a terrible writer.
Speaker 2:Okay.
Speaker 5:And one of the things I like about AI and ChatGPT specifically is it's helped me actually write in a way that I can be proud of.
Speaker 2:Yeah.
Speaker 5:Not just sometimes I write, you know, I'll write something, an email to somebody, I'm like, this is just so badly written, you know. And it's just I don't know how to make it better. Yeah. I know it's not good.
Speaker 2:Yeah.
Speaker 5:I don't know how to improve it. Yeah. And it's so frustrating because I know what great writing is from my reading, but I just can't do it. Yeah. And at least
Speaker 1:I've had a I had a a family member send me some something that was very obviously obvious to me, AI generated. And I think people have an aversion to AI generated text
Speaker 5:I totally don't
Speaker 1:get that. But Well, can be gross. But the thing is like I was reading through it and I was like, this is very cool because I know this person would not have been able to articulate their thoughts in this way. Mhmm. But they went line by line and I know they they mean it.
Speaker 1:Right? And so they were able to communicate something that they never would have been able to communicate with text. Maybe if we sat down and spent, you know, couple hours talking through it, would have been able to get the gist. Exactly.
Speaker 5:But Some people take out the em dash because they Yeah. Right? And tell them, oh, don't want it. And I'm like, what do I care?
Speaker 2:Yeah.
Speaker 1:I don't Leave Like, it in.
Speaker 5:Yes. A lot of emails that I write are
Speaker 2:With MDAC.
Speaker 5:Helped by chatty people.
Speaker 1:It's like the Arnold Schwarzenegger line, you know. He's I smoke my stogies Oh, yeah. Everywhere.
Speaker 7:Why With
Speaker 1:the MDAC.
Speaker 5:Judge me on what I
Speaker 8:said. Yeah.
Speaker 5:And my idea and whether it's well written. Yeah. Who cares whether it was written by AI or not. Yeah. That I totally don't get that.
Speaker 2:Yeah. Or polished by
Speaker 5:the way. In fact, I hope that more people are able to communicate things that maybe they couldn't before.
Speaker 2:Yeah.
Speaker 5:Right? Yeah. Because they didn't know how or they only knew granular things, you know. And now more people can write, more people can communicate, more people can express themselves. Like, to me that's an incredibly empowering right vision.
Speaker 5:Talk about
Speaker 1:how you guys have approached investing in multiple companies in the same category or the same general category. How has that evolved over time? Were you were you mocked early for for for doing that from maybe some of the more traditional funds? And then how have you managed to make it work in practice and, you know, maintain the trust of
Speaker 5:entrepreneurs Yeah. Think and other conflicts, which is kind of what you're Yeah. Has definitely changed a lot in the Valley as companies have stayed private longer, And I think we have to be kind of precise by what we mean by conflict, right? So as an example, funding two Series A companies at the same time that are pursuing the same opportunity is an obvious conflict that I think no firm, including us, would ever do. Yeah.
Speaker 5:Right? So let's just kind of be very clear on that. I think it's quite different when now you're talking about these very late stage companies, right, that are kind of competing with each other. But look, every company is kind of competing cooperating. You know, Apple and Google are great examples.
Speaker 5:You know, they compete but they're partners. So I think the distinction and the conflicts distinction has to be, you know, kind of changes as companies and markets kind of mature. Mhmm. Right? So I think you're seeing that become much less of an issue in mid to later stages.
Speaker 5:Even by firms that, you know, would typically view conflict as core to what they do, traditional venture firms, right, not And kind of moved in that I think it's just the nature of the market. So that that's kind of would be my first point. I think the second point is the execution of it, think, really matters. So, you know, if if I view a perceived conflict between companies, even if they're a later stage, I will always let the founders know
Speaker 2:Yeah.
Speaker 5:Directly. And I'm not asking for their permission, so I think you also have to be clear with the founder. Because what if they say no and you still want to do it, then you're in trouble. You've now you've just broken your word, and I won't do that. Yeah.
Speaker 5:But I will inform them, I'll be very direct. I won't let them hear about it from somebody else or something like that and I'll explain kind of the rationale. Right? So I think communicating directly both good news and bad news, that is something that I learned as an agent. I'm not afraid to have difficult conversations because I think we can grow from them.
Speaker 5:And I ask the same of founders or employees that I work with to both come to me and say, if if you have an issue, let's just kind of talk about it. And look, I've hired a lot of people, I've fired a lot of people over the years. I've asked a lot of people to go and look for different career paths. So I'm comfortable having this those conversations. So, you know, that's not something that, you know, I think your your reputation and trust then is kind of the the second point on the execution, right?
Speaker 5:Of Yeah. We take information security incredibly Mhmm. Strongly. That's when you know where SCC registered and you know even before coming here I got like a four page memo from my lawyer about you can talk about this but not that and SCC this and so of course you know I I have to read it and You can
Speaker 2:tell the Ralph Lauren story.
Speaker 5:Yes. Yes. The lawyer specifically. By the way, the way it well, you know, so side note. I believe that meetings should be recorded.
Speaker 5:As an example. Now, my compliance will say, shit. We can't have meetings be recorded because it creates a paper trail.
Speaker 2:Yep. Insane in discovery they
Speaker 5:can take And let's just not even talk so too specific. Let's just talk an enterprise.
Speaker 2:Yeah. Yeah. Yeah.
Speaker 5:But then I say, okay, let me posit enterprise CIO that says, no, I can't have my meetings recorded. I'm too afraid. Mhmm. I'm like, okay. Let me posit two scenarios to you.
Speaker 2:Mhmm.
Speaker 5:Okay? Scenario one is and in each you have a bad actor that's doing bad things, right? Whatever that is. Yeah. You know, like belligerent
Speaker 2:Yeah.
Speaker 5:Talking down to people, whatever. So Yeah. Scenario one, nothing gets recorded. You know nothing. And ten years later, someone comes out of the woodwork and says, by the way, x y and z ten year pattern of deception, nothing happened.
Speaker 5:Mhmm. Okay. So that's scenario one, right? Scenario two is every meeting is recorded. The first time said person does something that's not right, the compliance system, right, which is always listening sends that person an email and says, hey, by the way, better you didn't do this, talk to that person that way, disclose this piece of information depending on the severity.
Speaker 5:Mhmm. Right? Second time person does it again, says, hey, I now have to flag this to IR, to HR.
Speaker 2:Yeah.
Speaker 5:Right? I would much rather live in world number two. Right? Because you know what the problem is. There's a system.
Speaker 5:Sure. There's flags that have been raised. Yeah. And eventually, you know, someone kind of gets involved and you either remediate or you terminate the person or whatever. Right?
Speaker 5:Yep. To the
Speaker 2:back and forth of he said, she said, all of that. Yeah.
Speaker 5:Exactly. And who knows? Maybe that person, if they had gotten that first warning Yeah. Might have realized, oh, wait. Yeah.
Speaker 5:You're right. I'm being abusive. Sure. Or whatever the case may be of whatever Yeah. They were they were violating.
Speaker 5:Right? So I think to me that's a better world Right. Than kind of the ignorance of while getting no feedback and then you just learn much later that kind of you had Yeah.
Speaker 2:A problem. Yeah. I mean, it certainly seems like a trend. I mean Bridgewater's written about it a lot, Ray Dalio, but then also Grimaldo.
Speaker 7:He did
Speaker 5:that with no analytics. Right? Yeah. So he so that's different.
Speaker 2:Yeah.
Speaker 5:Correct. I I think to me what will happen is the analytics are going to get so much better.
Speaker 2:Interesting. Right?
Speaker 5:Yeah. And these systems are going to know. Yeah. And they're going to be able to look at your WhatsApp and your messages and your emails Yeah. And all of your calls.
Speaker 5:And they're going to be able to just say, hey, by the way, just don't Or say did you think about this? Or maybe you could have they're going to coach you. They're going to say, hey, you told this customer to Yeah. Fuck off. Be like, well, maybe you shouldn't do that.
Speaker 5:Here's like two other ways you might have mentioned, you know, like whatever this situation.
Speaker 2:Yeah. Your
Speaker 5:frustration or the situation. Right.
Speaker 2:Yeah. No. Very
Speaker 1:interesting. Instead of the the Tokenmaxxing
Speaker 2:like Well,
Speaker 5:let me be clear. I'm talking about work context.
Speaker 2:Yeah. Yeah. Yeah.
Speaker 5:This is I'm not talking about after work. Yeah.
Speaker 2:Yeah. I I I just wonder if if that would become something that employees select into or out of for various reasons. Just like some people are huge fans of remote work, some people can't stand it. Yeah. And there's a variety of
Speaker 5:I also think there's a clear distinction between transcription and recording.
Speaker 2:Okay.
Speaker 5:Right? They don't necessarily go hand in hand to me. Okay. Right? So I don't necessarily need a system that transcribes every word that was said and keeps it in some database somewhere.
Speaker 5:Yeah. I'm not sure that's necessary. But Yeah. Key takeaways from the meeting Mhmm. What was said, what was agreed upon Sure.
Speaker 5:Sure. Like that's useful.
Speaker 4:That's a
Speaker 5:good corpus of data. Yeah. To me, just because someone's quote recording doesn't necessarily mean that it's transcribing.
Speaker 2:Yeah. It could be
Speaker 1:compressed. Yeah.
Speaker 5:I like the option of deleting. Yeah. In an ideal world, I would recommend, well, you can delete the transcript. Yeah. The transcript's not that relevant.
Speaker 5:Yeah. Because maybe you batted an idea back and forth three times and you said something that turned out not to be true but you figured that out later. So you don't need any of that. What you do need is what was said, what was agreed upon. Mhmm.
Speaker 5:Was anything done out of compliance or not? Right? So it doesn't mean it doesn't imply a world where everything you say is recorded.
Speaker 8:No. Right.
Speaker 2:No. It's funny because there's so many opinions on this, but we record everything all day and livestream it on the Internet. Right. It's What
Speaker 1:how have you processed a number of these venture funds that have become publicly listed that are taking a lot of the different names that CodeTwo is in, you know, trying to find basically the most in demand secondaries, putting them into funds? As I've watched, think what I've seen is like, yes, it's very obvious. There's an incredible amount of demand from the public to invest in these names, but the big issue is that as soon as that demand floods in, you know, supply and demand price shoots up, and then you have a bunch of people investing at effectively, you know, 10 times, what the, you know, private valuation or or the underlying asset value. But have you processed it? Do you think there's a more elegant solution over time?
Speaker 5:So we do have a fund called C Tech that I'm allowed to mention Mhmm. That addresses some of this. And, you know, people can kinda go online and research more about it. What I would say generally is people want access to these companies. Yeah.
Speaker 5:And I think there's a lot of arguments for going public. One of I think the most powerful, in my opinion, is to democratize access Totally. To companies. Let's take an anthropic. Let's take an open AI.
Speaker 5:Right? And enabling the retail investor, enabling the Trump accounts, which I think is a marvelous idea that my friend Brad Gerstner really spearheaded and I a give lot of credit for. This idea of wow, why can't we have every single new child already have be invested in the market and participate in the value creation of these companies. So I love that democratized nature of it. So what I think it speaks to is there is incredible demand.
Speaker 5:Right? Let's say you were sitting, you're not a VC investor, you're you know, maybe a dentist and you're like seeing OpenAI and Anthropic and you're like, wow. Why why am I not able to
Speaker 2:Yeah.
Speaker 5:Participate in that? Yeah. You know? Why is it just like an elite group of funds and accredited investors Yeah. And so forth and so on?
Speaker 5:That to me will have to change. Yep. And I think it should be bipartisan, frankly.
Speaker 2:Totally.
Speaker 5:Right? And I think there'll need to be some guidelines and stuff put into place and we don't want bad behavior and Yeah. You know, all that kind of stuff. But I think there is incredible demand from the retail investor base to participate in the value creation.
Speaker 2:Mhmm.
Speaker 5:And I think I think what we're learning as a society is the cost of not having broad participation is incredibly high.
Speaker 2:Completely agree.
Speaker 5:Right? And will be Yeah. Right? If you have a whole generation of young people that don't own their house and have student debt and don't feel like they're economically levered to OpenAI or Anthropic
Speaker 6:Yeah.
Speaker 5:Or even more so are directly threatened
Speaker 2:Yeah.
Speaker 5:By their technologies, I don't think that's a great future for any of us.
Speaker 2:Totally.
Speaker 5:So I'm not saying that OpenAI or Anthropica going public is the Solution but it's is like the one Yeah. Thing. Right? Obviously, there's gonna need to be a lot of things that are done. Yeah.
Speaker 5:But I do think the transparency that comes with it, the democratized nature of it Mhmm. Will make a huge difference.
Speaker 2:Yeah. Makes a ton of sense. Jordan, anything else?
Speaker 1:Last question. What what is what are Can
Speaker 5:I make also one point on in person? I'm so glad I got to do this in person. Yeah. I did not want to do this remote. Because the the tactile feedback you pick up in person, as an example
Speaker 2:Yeah.
Speaker 5:For the viewers at home who have not been to this office, the open jar of creatine just what I mean, what a bowl. I mean Open jar. Just the the lit just for everybody to describe it. There's there's a Okay. Goodie And there's just a jar of creatine.
Speaker 5:It's just wide open. The scoop's right in there. It's so inviting.
Speaker 7:If you want to power
Speaker 5:up before you get on, it's just right there.
Speaker 2:It helps if you're if you're sleep deprived.
Speaker 5:Right. That's just the kind of tactile feedback you like.
Speaker 1:Yeah. You don't get that on Zoom.
Speaker 2:On Zoom. No way. I'm really glad you could be here.
Speaker 1:This is a pretty interesting Well, I'll save the next I'll save the last question for your next appearance. Okay. Let's see what we get soon.
Speaker 2:Well,
Speaker 1:thank you, Saint Peter. I love going way going way over.
Speaker 5:Yeah. Yeah. Went way over. Delighted to be partners in company I now with you guys. I'm really proud of your success, honestly.
Speaker 5:I love hustle and people that break into industries and so congratulations.
Speaker 1:Yeah. We bring a very mailroom approach to podcasting.
Speaker 2:We do. Yeah. Can think about this. There's a lot of mailroom here. Lot of suits here too.
Speaker 2:Well, thank you for watching. Tune in tomorrow 11AM Pacific. Leave us five stars on Apple Podcasts and Spotify. Sign up for our newsletter at tbpn.com and we will see you tomorrow. Cheers.
Speaker 2:Goodbye.
Speaker 1:See you. We love you.
Speaker 2:Goodbye.