TBPN - AI Viruses, OpenAI's First Device, WSJ Mansion Section | Samir Kaul, Patrick Wendell, Grant LaFontaine

Episode Date: August 7, 2026

(01:31) - AI Viruses (08:18) - OpenAI's Device Takes Shape (16:39) - Meta Faces Major Child Safety Case (25:25) - 𝕏 Timeline Reactions (36:10) - WSJ Mansion Section (43:41) - Samir Kaul, a general partner at Khosla Ventures, discusses the firm’s investment in Jeff Dean’s Discovery Loop and its potential to apply AI to scientific research with tangible outcomes. He also shares his views on AI regulation, inflated private-market valuations, venture capital strategy, founder support, and the importance of taking bold risks to generate exceptional returns. (01:09:45) - Patrick Wendell discusses his role as Databricks co-founder and VP of Engineering, where he leads AI products and internal AI adoption. He explains how AI coding tools can nearly double engineering capacity while creating rapidly escalating consumption costs, and highlights model switching, intelligent routing, and optimization as key ways to control spending without sacrificing productivity. (01:27:30) - Grant Lafontaine discusses Whatnot’s $545 million Series G funding round at a $20 billion valuation and the live-shopping platform’s rapid growth. He explains how authentic, knowledgeable sellers can build substantial businesses with small audiences, while outlining Whatnot’s focus on customer experience, new markets, product categories, and future streaming formats. (01:44:17) - 𝕏 Timeline Reactions TBPN is made possible by:Ramp - https://ramp.comPublic - https://public.comCisco - https://www.cisco.comConsole - https://www.console.comCrowdStrike - https://www.crowdstrike.comFigma - https://www.figma.comMongoDB - https://www.mongodb.comNYSE - https://www.nyse.comRailway - https://railway.comShopify - https://www.shopify.comCodex - http://openAI.com/codexFollow TBPN: https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/tbpn/id1772360235https://www.youtube.com/@TBPNLive

Watch and TVPN. Today's Friday, August 7th, 20206. We are live from the Pewpian Ultradome. Temple of Technology, the fortress of finance, the capital of capital. Let me tell you about ramp.com. Time is money. Save both. He needs to use corporate cards.

Bill paid. Accounting. And a whole lot more all in one place. Lots of voice changer today. Let's amp it up. Who had orange in the chat? Because the chat was trying to guess what color sunglasses or we would be wearing today. Is that orange or is that more of like a burnt sienna? Well, I think it's more of a green,

greenish frame with more of, with an orange lens. You got to drop the line. I'm wearing sunglasses because I'm looking at the future and it's very bright indeed. That's a good one. I don't know. Knowing just that reference. Anyway. Oh. It's great to be back. It's Friday. We got a shorter show for everyone today. We have Samir General Partner Kosla Ventures coming on to talk about their new investment discovery loop founded by none other than Jeff Dean and some of his crew from DeepMind. And then we have Patrick Wendell, co-founder of Databricks, joining to talk about their new blog post. I promise it's going to be more exciting than it sounds like. No, but they're doing smarter model routing and we're excited to catch up with him.

Very excited. Well, for the first time, scientists have used AI to create entirely new viruses. You asked for it. They delivered. They delivered. They woke up this. You know what we don't have enough of? Viruses that have never existed in nature before.

It's marked a milestone that could accelerate biotechnology while also raising long-term biosecurity questions, of course. Nightmare scenario is. You go to Best Buy, you get a gaming PC with a couple pretty stock graphics cards and you're able to run an open source model that basically walks you through the steps of creating something really problematic. At the same time, there's a lot of really talented and well-resourced organizations that are fighting that tooth and nail. And so we'll probably see a little back-and-forth equilibrium there. But lots of interesting questions. Important to note that these viruses do not affect. humans whatsoever. Even these new viruses, they target bacteria. So it's more of an experiment,

more of a demo, but you can see where things are going and are we going. That doesn't make me that comforted, to be honest. You like your bacteria. You know, we naturally have, there's bacteria that is, it's part of being human. And you would like the bacteria to be unaffected by viruses. Is anyone standing up for the bacteria right now? Well, it's more so like you have bacteria, You have bacteria in your gut, and the gut is kind of an important part of the body. Now that bacteria is going to be suffering from a novel virus, apparently. Yeah. Well, in a study published Thursday in science, researchers at Stanford and the ARC Institute trained an AI model to recognize patterns in naturally occurring viral DNA,

then used it to generate genetic sequences for brand new viruses. After synthesizing those DNA sequences and inserting them into bacteria, the team found the bacteria produced viable. viruses capable of infecting other bacteria. The work does not create a new threat to humans. Be careful. I'm sure that will get cut out of a lot of messaging around this because it sounds really scary on its face. The AI was trained only on bacteriophages, viruses that infect bacteria, and specifically excluded viruses that infect humans, plants, animals, and fungi. As a result, the model cannot generate viruses capable of infecting people. While scientists have been synthesizing viral genomes for years to study diseases and develop vaccines, this is the first time AI has been used to design entirely new viruses that function in the real world.

And I was going back and forth before the show on, is this anything special? You know, we've been using tools to make viruses for bacteria for a long time. This is just another tool to do it, or is there some, you know, material breakthrough? That's sort of a debate point. It sounds really scary, but also, like, you've been able to design these viruses in a lab for a long time. So what is the material difference here? I think it all comes back to acceleration and cost. If all of a sudden it becomes a thousand times cheaper to generate viruses,

then that could reshape biotech in a positive way, but also have biosecurity implications. Yeah, I think a lot of the reaction is just that it feels like a little too soon post-Wuhan, a little too soon post-hugging phase. Yeah. There's been a variety of events that I think naturally make people a little apprehensive when you see a headline like this. Yeah, a lot of people are like, you know, the L.EA.s are you, Kutkowski reaction of, ah, like this is bad. But we'll see where it goes.

If the approach proves effective across other classes of viruses, it could become a powerful tool for medicine and biotechnology. Viruses are already widely used as delivery vehicles for gene therapies and other medical treatments. and AI design viruses could eventually expand that toolkit. At the same time, the research highlights how advances in AI are making it increasingly important to build safeguards alongside new capabilities, which I'm sure the Arc Institute is working on. And there's also other AI-driven neo-scientific labs. I mean, Jeff Deans, one of those was advancing. One of the goals of his new company with Discovery Loop is to work on biotech broadly. he has a very broad remit, but there are more narrow projects like that new company that's focused on finding a cure for the common cold.

There are a few other projects that are more narrowly targeted, as well as all the biotech companies that are working on stuff. If we're going to get advances in viruses that deliver gene therapies or medical treatments, we got to rebrand virus. We got to come up with a new word. Just like GLP1, peptide, that felt very safe. It was like, you're not doing steroids. You're not on gear. What's the lizard? You're doing a peop.

You're not doing Helo monster venom. Exactly. You're not doing heli monster venom. No. Some Chinese peptides. The Chinese peptides was a rough go. But in general, I think the fact that it was like just a peptide, it felt much more welcoming, as opposed to being in the world of the steroids, the performance-hancing drugs.

And it became easier for people to jump in, oh, I got to learn about peptides. Oh, there's naturally occurring peptides? Cool, I'm into that. But virus has such a bad connotation post-Wohan as well as just everything. You're never like, oh, I got a virus and someone says, a good one or a bad one? Like, it's always bad. Yeah. It's never good.

But so they need a new brand for that if they're going to commercialize that for sure. But we'll see. Anyway, there's a whole article in the New York Times about it. This AI just created viruses not found in nature. has a cool little graphic by Carl Zimmer here. The new study published Thursday in science goes well beyond duplicating viral genes, scientists at Stanford University and Arkansas. Taught AI to recognize patterns of DNA in nature and then use that DNA to write recipes for entirely new viruses.

The virus is dreamed up by AI. Do not pose the threat to humans because they are all similar to a naturally occurring virus called PhiX-174. which can only infect bacteria. Really hardcore name for something that's not that dangerous. FI-X-174 sounds like an offspring of Elon Musk. There's just a huge disconnect, the research fellow said. Governments and scientific organizations have been slow to develop guardrails that could block the creation of a deadly virus, even as the science races ahead.

So I don't think they'll be open-sourcing this anytime soon. There is other news. Mark German's been reporting on Open AIS first consumer device. It'll reportedly look like a hockey puck-sized donut. Mark German, the Germanator? Oh, the Germinator, cool. The Germinator, yeah. Open AIs, Open AI's first consumer device, open AI's first consumer device

will reportedly look like a hockey puck-sized donut and cost roughly $300 to $400 to $400. What a funny form factor. Love hockey pucks. Yeah. Love donuts. Okay. So you're in. I like where this is going.

There's also a rumor that it has mechanical pieces on it, so I think it can, like, undulate potentially. The speculation's all over the place. According to Bloomberg's Mark German, the Germanator, as you put it, the battery-powered device is essentially a portable smart speaker without a screen designed to be carried around the house or placed on a nightstand or kitchen counter. It will include speakers and microphones,

along with cameras and other sensors that allow its AI to perceive what's happening around it. The device is intended to work much more, like a much more capable version of chat GPT's current voice mode, learning about its owner over time and using that context to make conversations more personalized. Open AI is also making the hardware itself feel more expressive. The device will reportedly include lights and parts that physically move as it responds and with the goal of making it feel more alive than existing stationary smart speakers from Amazon and Google.

The product being developed by Johnny Obs design team is expected to arrive in 27. and envisioned as the first in a broader family of open AI hardware long term, the company reportedly hopes to develop AI devices capable of taking over some of the functions now handled by smart phones. Feature requests. Yes. Rolling flashbang. Flashbang.

That would be a good feature request. Yeah, it says it has lights, it's got sound, you should be able to use this as an on-the-go flashbang. Yeah. So you're going to hang out with some friends. Yeah. You want to prank them a little bit when you're kind of, coming in?

Yeah, I was reflecting on the deep mind story of, you know, the departures there and the question of, you know, how the models are progressing versus the commercialization of those models. There's some real strong points. There's some weaker points within the rollout of Google's AI strategy. And I was thinking about, like, what happened to Notebook L.F? because that was heralded as a very magical technology. You would give it some sources, a particular report, and it would just generate a podcast talking between two different people,

much more conversational. And a lot of people like consuming information that way. So you could just go read a deep research report on the history of how bacteriophages work, if you want to get up to speed on that, because you're trying to understand what the ARC Institute is working on with these new viruses. You could go to Notebook L.M and say, hey, why don't you generate me a podcast of two scientists explaining this at, you know, high school level and take it into college level? Tyler, in the YouTube chat says, loves notebook LM, use it weekly. Use it weekly.

I always thought that I would have used it when I was in college. Yeah. And I needed to, let's say, write a paper on something. and I wasn't super prepared. I could say, generate me an hour-long podcast about this set of topics, and I'd listen to that, and then I could probably rip the paper. Yeah. I did that for a history exam.

Wow. It was like a vocab list, and it went through. Okay. Yeah, middle-age history, I think. Wait, oh, you used notebook L.M? Yeah, it generated a podcast, so I basically fed in a vocab list of, like, dates and various things. Then I had it. Wait, and was it just a general podcast?

How did you do on the test? It was really easy. I think I probably aced it. Wow. There we go. He needs a better confidence monitor. But I was, I mean, first off, I'm a big fan of that new trend that's like asking old people, like, how did you write a five-paragraph essay without AI? And then the answer is like, buddy, we wrote a five-paragraph essay without even reading the book.

You just go to Spark Notes or something. But I was interested in the evolution of notebook L. because there's this collapsing of capabilities where Sam Altman was recently sort of dragged a little bit for saying he would use Chachapit-Wark to generate a podcast about what's going on on his calendar and the family life and stuff. And people are like, how about you just talk to your kids?

But the more interesting technical point on that is that do you even need Chachapit-T work? to generate you that podcast, or will the voice mode and the memory feature have enough contacts to just sit there and talk to you like it's a podcast on the fly? Yeah, and to be honest, to be honest. For free. Like live voice. Yeah.

If you're trying to learn about a topic, for example, pretty good. Is probably better than just generating a podcast because a podcast assumes like some certain understanding. Yeah. And it's rigid. Maybe it thinks you understand too much, too little. whereas voice you can be like go down this like exactly exactly it's a choose your own adventure it's a it's an expert call

it's uh instead of notebook lm it's tegis lm basically i mean you're talking to an expert and you can just guide the conversation wherever you go so uh will be interesting to see where this goes what the reception is like uh i mean huge huge delta divergence between like the the social media pushback for ChatchipT versus the app store ratings. There's like a billion people using it. A lot of people just like the product. And then there'll be like someone dunking on it

to the tune of a million likes on Instagram. And so how do you measure those two things when it comes to an actual consumer product? If it's delivering something good, if people are like, if the stated preference is like, I don't like AI, but the revealed preference is like, it's kind of nice to have this thing around the house. It's kind of useful.

Interesting to see where it goes. Also, it will be very, the launch of this device will be very, very interesting to see how things come together. You can see the chatchapT work, chat chattchapetech codex, chat chachaptee, like coming together into one product. But there's a world where this product launches with voice mode, and it's not really capable of linking to a cloud codex instance and writing you software and doing the more advanced things that are required.

just to accomplish some tasks. You can go to Chachapitia and ask it to pull down an image from the internet, restile it, change it, but you can't really tell it to do like 40 of those. Or like every day, forever, do a whole host, a whole workflow. But you can in Codex. And you can talk to Codex, but it has to be running on a computer. And I would hope that by the time this launches, there's full context. I was doing some work in codex and I had the output and then I wanted to like generate an image based on that and take it on the go,

but I wanted to be able to close my laptop and not and still be able to access it. So I had to like copy the context window into chatchapit just the normal app so then I could like access that information and continue to transform it. And that was something that is like a very, very temporary thing that feels like it's going to be fixed in like a couple weeks. But there's a whole bunch of these little minor integration issues that. probably need to be fulfilled before this product launches and delivers the full capability of what you can do. Because so many tasks instead of just knowledge retrieval require actually firing up a browser, scraping it, writing some code, downloading things, you know, setting up an actual service and workflow as opposed to just something that can be done within the context window of a single LLM interaction.

Anyway, let me tell you about Cisco. Critical Intersection for the AI era. Unlocked seamless real-time experiences and new value with Cisco. Last top story. A New Mexico judge has ordered META to pay more than $900 million and impose new restrictions on how minors in the state use Facebook and Instagram. This is a continuation of the social media addiction. If you're watching this clip on Instagram, let us know in the comments, are you addicted to TV?

VPN Reels on Instagram. It's not our fault. Apparently it's Facebook's fault. If we got you hooked on this stuff. The ruling requires meta to establish a $567 million fund aimed at addressing harms linked to its platforms on top of a $375 million

in civil penalties previously awarded by a jury. So they're up $900 million. They're very close to a billion dollars and the numbers are going to get bigger from here. at least at least they're going to try okay so last time we really covered something from this ongoing saga there was a verdict on march 25th a los angeles jury found meta and google slash youtube negligent for designing platforms harmful to young people a woman who said she became addicted social media as a child was awarded six million four point two million against meta and one point

$1,8 million against Google. And again, at the time, we had this, I think it was a lawyer on, he was giving his opinion. He was like, this is just the start. Yeah. We were like, I was like, no way. And it's like, the jury has a verdict. Yeah. To say, you know, talking to the biggest companies in the world, you must pay $6 million.

Yeah. It was nothing. It was like this tiny amount, but it was to one person, right? And so you can imagine as these cases evolve, this new one is in New Mexico. New Mexico is not the biggest state in the union. It's not the biggest state. But there was also one in May 26, so just a couple months ago for $9 million to a school district in Kentucky. Same sort of issue.

The lawsuit accused Instagram of deliberately using addictive features that contributed to anxiety, depression, self-harm, and other problems among students, forcing schools to spend more on mental health services. The district had sought more than $60 million. And I guess the total payout was $27 million because it was split between YouTube and TikTok and Snap. And in that case, there was no admission of liability and no required product changes. So I think it's time to start thinking about what the sort of battle that social media has ahead of it, kind of in cigarette terms. Tell us about.

Tobacco master's agreement? Yeah, exactly. So the tobacco companies wound up getting sued individually initially, and there were a whole bunch of court hearings, very similar to the Senator We Sell Ads moments, but more focused on the cancer-causing nature of cigarettes. And the question was like, who is ultimately being harmed economically? And you would think it's obvious. The person that saw an ad that made smoking look cool, they picked up a pack of cigarettes, they started smoking, and then they got cancer, and their life was cut short. They are the victim. They should be paid by the tobacco company.

That's what would be very logical. That's not what happened. In fact, the tobacco master settlement agreement landed in 1998, and it was agreement between all of the major tobacco. companies, there's more nuance to this. One of them broke loose and testified against the others. It's a crazy story. But that's for another time. In 46 states. I'm the good cigarette company. Basically, yeah. And so they don't have to pay. They're not part of the settlement. So they don't have to pay because they basically snitched on all the others. It's crazy. They're still, are they still in business? Oh yeah. Cigarette company. They're doing great. Who are they? We get Victor. Like, I've never heard of it.

Yeah. Last name Victor? Yeah, they were literally the one. They won. They won. one, yeah. There's more nuance to it than that, but that's like one way to tell the story. Anyway, so a bunch of the big tobacco companies versus 46 of the U.S. states, the District of Columbia and several territories, the states agreed to end major lawsuits against the tobacco companies. So the same thing was happening where all the different states were suing, and they were suing because the negative externality of cigarettes causing cancer was driving up medical bills in the states. states have health care and they assume, hey, okay, we're going to spend this much on doctors, this much on radiology, this much on x-ray equipment. And then all of a sudden, they're starting

to look at their populations and saying, like, wait, everyone's getting lung cancer. We're not equipped to deal with lung cancer. We need to hire way more oncologists and cancer doctors who specialize in lung cancer. We need equipment. We need drugs that treat lung cancer. There's a whole bunch of other things that we have to spend money on. And so you got to pay us because you, the tobacco company are responsible for us running out of money for our health care system. And so that was the nature of these, like, the battles between the states and the big tobacco companies. You would think it would be the individuals who got the cancer. That would be very logical, but that's not actually the structure of this deal. And so in return, the companies, all the states

said, hey, we'll drop all those lawsuits. You won't have to, we won't be nickel and diming you across every single state. Instead, the companies will make large payments and follow new limits on advertising and business practices. So the end result, the headline number is $206 billion, which feels like small relative to today's standards of like hyperscalers and social media. Facebook generates roughly $200 billion in revenue every year, although if they got hit with a $200 billion fine, that would be existential. But what happens to... happened with the master settlement agreement with the tobacco companies was that there wasn't just one fixed payment. Instead, it created a system of annual payments that continue indefinitely. They will actually have to pay forever as long as they are in business. They have effectively a special tax paid to them. And the amount changes based on cigarette sales, inflation, market share, and other adjustments. So if cigarette sales fall, the total payments usually fall. And that's a big reason why there's like a shift to non-cigarettes. products. Well, and that just naturally makes sense. If less people are buying cigarettes, less people

are going to have health issues down the line. Exactly. Exactly. So yeah, so I brought it up because I think that we could be heading in that direction with social media. There's also a fascinating dynamic because these states now have an indefinite revenue stream that will be paid to them. And you can model that out financially and you can financialize it. And a lot of people have. And so investment firms and banks and financial institutions have come in and said, okay, you are the state of New Mexico, for example, and you are expected to get 300 million from big tobacco this year, and then next year we think it'll be 297 and then 28,

and then it'll go down, and we can model that out, and we can just give you $4 billion right now in exchange for that revenue stream or a piece of that revenue stream, and then those states can take that lump sum of cash and build a new bridge or something like that, whatever they need to do. So there's been a lot of financialization on top of it. And so each tobacco company pays a share of the total amount. Its share depends mainly on the share of cigarette sales among companies that participate

in the MSA. The settlement then divides the money among states using fixed allocation percentages. Some states later borrowed against these future payments by issuing bonds backed by MSA revenue. The MSA also limits tobacco advertising and marketing, especially marketing, that could reach children in simple terms. The agreement created a permanent system. Major tobacco companies received protection from many state lawsuits,

while states received continuing payments and new enforcement powers. The result is not just a legal settlement. It created this long-term financial and regulatory structure built around cigarette sales. And it's now the 10-year anniversary of starting Lucy, 2016. August 8th, technically, was the day.

New regulation. You know what I'm going to hit. Overnight success. Yeah, for two. Sure. The exact opposite. Slaving away for years and obscurity. But a very, very interesting, very, very interesting industry to have operated in for as long as we have.

What else is going on? Let me tell you about railway. Railway of the all in one intelligent cloud provider. User favorite Aided to deploy web off, service, database, and more while railway automatically takes care of scaling, monitoring, and security. Semi-analysis chimed in on the deep mind news, not just chimed in. I think the terms posterized. Grave digging? No, not grave dancing.

No, they're... Grave digging? They're digging the grave. They're putting DeepMind in it, and then they're dancing on it at the end. Anyway, semi-analysis says, for all intents and purposes, we believe DeepMind is no longer a frontier lab due to large numbers of departures from their RL teams and poor compute allocation. Google will continue meandering on and releasing models, but their odds of ever-reaching state of the art again have dropped to zero.

Damn it. Google is now simply unable to retain top AI talent. Again, this is what I was saying the day that the news broke. It's like researchers want to work with great researchers, right? And so the more talent

density you have, the easier it is to recruit. And yeah, Nome leaving earlier was like a canary in the coal mine. Obviously, these are not the actions of people excited about Gemini 4 Pro. Jeff, Sanjay, Kwok, and Oriol are just the latest in the long string of high-profile departures from DeepMind.

Jeff Dean is the undisputed goat of Google Engineering, co-founded Google Brain, and started the TV program. Google, on the other hand, decided it was totally worth it to sell enormous amounts of compute to Gemini's fiercest competitors on long-term contracts without any hope of ever returning it to DeepMind. more than 20% of total TPU shipments from third quarter 26 to fourth quarter 27 are being sold directly to anthropic. Wow. The issue with Google was not Jeff Dean nor Noam Shazir, but rather they're extremely bureaucratic, painfully slow, and strategically timid culture.

Google will join the ranks of other legendary tech giants like IBM and Intel to give up on the harder thing and do the thing that will make you more money. It becomes demoralizing, as many of the great technology, leads have left. Wow. And take him, taking a victory lap. He wrote a piece on July 21st. Google is a secular short, kind of getting at a lot of these issues. So brutal, brutal stuff. This is insane. On the other side, GCP is working. GCP is basically a money printing machine. No wonder Google executives are choosing GCP over Gemini. So although EBIT margins for these system sales are slightly lower than core cloud margins in the low 30% range, we still expect total GCP to deliver mid to high 30s EBIT margins going forward.

How investors decide to capitalize the current TPU backlog and any large future sales is an open question. However, given the strong compute demand from the labs, we expect more multi-gigawatt deals to be announced soon, adding to this backlog. In all, we estimate that over 250 billion additional TPU bookings could be added to GCPRPO in the next coming quarters from semi-analysis. Very interesting. I mean, there is like a positive spin on this, which is like they seem to be really good at chip development, really good at cloud, like focus where you're where it's working. And you don't have any tensions there because you have excellent teams. And then you have the ability to underwrite that build out with the cash machine that is Google Search and YouTube and their ads products. And having more of this like barbell approach as opposed to playing in like the middle race is maybe the, maybe ultimately the right thing to do. There are plenty of hyperscalers

that have lived that and are doing very well on the back of it. That haven't, like Microsoft, Amazon, for example, they've been partners to labs at various points and are very good at building data centers, very good at scaling, and have not tried to really go on a crazy poaching race and amass the dream team and, you know, they've been rewarded for it. Yeah. I don't know. Still wild series of events. They obviously had effectively a version of Chad GPT internally.

They didn't ship it. Tebow, who's now running Chat Codex, was there working on that product, which is really wild. Sebastian Malibai says semi-analysis is excellent, but this argument strikes me as paradox. Oh, he messed up the tag, though. It's semi-analysis underscore. It argues that Google is out of the AI frontier race and that two, Google's AI revenues will meaningfully accelerate

because Google is allocating compute to its Google Cloud customers, I wonder. And the long term isn't a strong revenue base and a central underpinning of success at the AI frontier. Consider this thought experiment. If Nvidia acquired OpenAI but continued to sell compute to multiple customers, would this make Open AI weaker or stronger? Surely the answer is stronger. I think Sebastian just kind of fundamentally misunderstands the current dynamics.

But Tyler, you want to break it down? Does he have something here? No, we were talking about this before the show, this idea that... I guess the question is... Like this race is all about compute allocation. You want to be allocating compute to training so you can maintain your lead or extension. your lead or get to the frontier, Google's effectively saying we're going to allocate, instead of allocating, you know, let's say an open AI is allocating like 50% of inference,

50% of compute to inference, 50% to training, right? Google's now shifting towards, you know, I'm sure they're going to be effectively allocating 90% of their compute to just allowing. I think the number was 15% was for GDM relative to the overall cloud. Exactly. Yeah. So, yeah, it was like, that must be frustrating, but still a lot. I mean, there is a world where you could, like, sit this round out and then grow your company, grow your compute, and then rug all the labs, have all the data centers. Like, the Tyler Cosgrove, like, keep the chips for yourself model.

Like, that could happen in 2028. and then every other lab is like compute poor because Google just said like actually we're taking back all the labs. We're doing the biggest training run of all, but that sort of is negated by the idea of like a flywheel and you know and like needing an RL loop around the code and the use cases and the rollout. So it'd be very, very tricky. But if there's some world where it's like they create the next transformer magically and you don't need a lot of data for it. You just need more compute than anyone ever has, and they have a lot of it loosely. Yeah, and also what models are they going to be using for their own research when the other labs are not exactly saying, hey, use our frontier model to train a frontier model yourself.

Yeah, that is tricky. Yeah, it just seems like Google leadership has a very different idea of, like, where value accrues in AI than, like, Demis or, like, the other labs, right? It's not actually, like, the model itself. Yeah. It's the, like, infrastructure, PPUs. cloud business. It's interesting because you can run back the old Demas quote about

when he was selling Deep Mind he talked to Mark Zuckerberg and is like, what are you excited about in the future? Are you excited about AI? And Mark Zuckerberg, apparently, according to this exchange that Sebastian Malibai reported on, Mark Zuckerberg says, oh yeah, I'm super excited about AI.

And then Demis is like, I'm going to test this guy. I'm going to see if he's a true believer. What do you think about VR? And Zuck's like, oh, VR is like equivalently as big. And then Demi's like, no. I don't even said that. He was just equivalently as big.

Excite. Yeah, yeah, excited. And he was excited about a few other things. And Demas was like, I want to be with someone who's like all in on AI as a fundamentally different technology, not a normal technology, not like VR, not like new devices, not like electric cars, not like, you know, satellites in space. It needs to be considered as a completely separate sort of like, you know, development, a completely separate technology. Yeah, like I don't know if Sundar like believes in RSI. I don't know. It seems like he doesn't think that that's really going to. So the point is that Demis should have probed more and said, like, well, how excited are you about cloud? How excited are you about AI overviews? And if Sundar, it wasn't Sundar back then, but if Google was like, oh, yeah, we're equivalently excited about cloud infrastructure as ASI, then that should have been Demis's moment to be like, ah, maybe I shouldn't. The only thing is there's a world where he's actually. so RSI-pilled that he's thinking, okay, it's over for us. I need to back up the Brinks

truck and help Anthropic, right? And putting together this like, you know, almost a quarter of a trillion dollar financing package. Yeah. And a variety of data center guarantees to enable Anthropic to scale up, even though they don't have, you know, really access to the debt markets in the way that Google does. And there's also, there's also the, just, this idea of like there are multiple waves to move the needle and put points on the board in just the successful rollout of A, G-I-A-A-S-I, and one of those is working for a lab, developing the next model, making sure it's aligned, et cetera, et cetera. There is another, which is like go and create public policy.

There is another that is, you know, work at a nonprofit. Like, I think if you talk to the folks at meter, for example, they don't feel like they're like sitting out a GI. Like they're very important in that story, in that role. They have less of a financial like alignment to it. But they definitely see themselves as participating and working towards the good outcome, which is what drives a lot of people, especially when you're post-economic. Google's ownership in Anthropic is capped at 15%.

They, I believe, have roughly 14%. Weird. How is it capped? I think Anthropic just didn't work. Oh, we don't want you to have 90. They don't have any voting rights. They don't even, they're not even a board observer. They don't have a board seat.

They basically are just a, yeah, purely financial back. Let me tell you about console. Console builds AI agents that automate 70% of ITHR and finance support, giving employees instant resolution for access requests and password resets. And let me also tell you about public investing for those tickets seriously. We've got stocks, options, bonds, crypto, treasuries, and more with great customer service. A branding moguls, Miami Beach Home lists. for $68.5 million.

Branding mogul, Nick Woodhouse, was sailing around Miami for his birthday in 2019 when he realized he found his new home. Turning to his wife, Jocelyn Woodhouse, the Canadian-born businessman said, we have to live here. It wasn't long after relocating from New York in 2020 that the couple then living in a condo

on Sunny Isles Beach, Florida, saw a waterfront lot on a guard-gated Lagort. Island, is that how you pronounce? The Gortch? I don't know. Island in Miami Beach from a friend's boat. The property had the foundation of a house that was just starting to be built. The woodhouses purchased the partially built home for $17 million in 2021 and completed construction of the roughly 8,800 square foot seven bedroom contemporary house around 2023.

It's a 0.4 acre estate and they're selling it for 68.5 because they're building another home nearby. Hi, Nick is the former president and chief marketing officer of Authentic Brands Group, and that's why I wanted to talk about this, because Authentic Brands is a very fascinating company. Tyler, you have something here? Yeah, so it's pronounced Lagores. Legors. Thank you. Legors.

Well, Authentic Brands Group is a very interesting lifestyle platform, I guess. I don't know exactly what you would call it, but it's a holding company. They have some truly Tier 1 assets. They own more than 50 consumer brands as well as likenesses. and estates of celebrities, including Muhammad Ali, Elvis Presley, and Marilyn Monroe. But what stuck out to you?

Let's start at the top, the cream of the crop. They own Tapout. They do. Iconic brand. Tapout Ties. And if you guys ever run into John on the weekends, he's almost certainly head to toe tap out.

It was one of their first purchases, Silver Star and Tapout. In January 2011, they acquired the rights to the likeness of Marilyn Monroe. So if you see Marilyn Monroe, on a t-shirt, authentic brands is getting a check. They own Ruka, the surf brand,

they own Neiman Marcus, they own Prince, they own Brooks Brothers. Goodman, they own D.C. shoes. Yeah. They own Sperrys. They own Barneys.

They own Barneys. They own Sacks Fifth Ave. They own Sports Illustrated. Wow. They have the Elvis Presley N.I.L. Yes. They have the Muhammad Ali N.I.L. Yes.

They own Roxie. They own Volcom. And what other celebrity? Again, to me, to me, if I, you know, you know, Tyler, I know you're still, you're pretty much head to toe Volcomb at all time. Volcomb, maybe some Billabong thrown in there. Well, they also own Billabong. Yep.

They own it all. And so they own Lucky. They own Eddie Bauer. They also own Shaquille O'Neill's likeness. And Kevin Hart's likeness? And David Beckham's? Wait, the A-Star Ventricopoulist? Kevin Hartz?

No, no. I don't think they could afford his NIO. Okay. But the actor, comedian, tequila entrepreneur. Yeah. I think it's so funny that Shaquille O'Neal sold his likeness before he passed away. I feel like selling your likeness in your estate and going on T-shirts and stuff is something that you would hold on to. I mean, I understand selling your catalog if you're not a recording artist anymore, but just selling your actual likeness and then people can, oh, yeah, you can.

No, you saw it during the World Cup, like David Beckham was a. in every other ad. And it's because he did a big deal to basically sell his, like, all of his. And so he's basically, he basically pulled forward years and years and years of, like, NIL revenue. But how does that work if he actually needs to be on site to, like, film a commercial? Probably has some obligation. Like, you need to be available.

This many days. Wow. That's very interesting. Anyway, Nick is the former president and chief marketing officer of Authentic Brands Group, a licensing and managing company that works with companies. such as Reebok champion and Brooks Brothers. TZH says ABG is a graveyard for iconic brands. It's the bending spoons of brands.

No, it really is. I mean, it's somewhat sad because a lot of these brands, they, a lot of these brands are so, so iconic. And with the right sort of management and investment, they would be back to their former glory. A lot of the surf brands and the skate brands are a little sentimental for me just because I grew up watching so much of the content that those brands put out and following the different athletes on their teams. But those industries have just been impacted surfing most aggressively just because kids that don't live by the ocean now, they don't really care about surfing. They care about chrome hearts.

Do you think the surfing industry needs a federal backstop? I would push for one, certainly. Yeah. Yeah. A couple billion dollars from the Treasury directly to get Vulcum. Quicksilver, Billabon. Wicksilver back to the top. Yeah, we're on to something here.

This is our new platform. I think so. Let me tell you about MongoDB. What's the only thing faster than the AI market? Your business on MongoDB, don't just build AI, own the data platform that powers it. There's one more key story. We have our next guest joining in just a minute, Samir call from Coastal Adventures.

But a golden retriever made the front page of the mansion section in the Wall Street Journal. It's huge news. The golden retriever's name is George. Isn't that an amazing name? Mad Clifftop Dream on the Irish coast. A couple wanted a home on the edge of the sea, so they braved 75 mile an hour winds

to turn a former sea urchin farm into a modern light-filled house. and the golden retriever fully delivered in this photo shoot. I love some of the photos of this dog. I was very happy to see George get the full Wall Street Journal treatment. It's always a good day when there's a retriever in the journal. The chat is in full support of regulatory capture for skateboarders. Yes, for ski trainers.

Yes. DC shoes. Do you think there should be sort of like an FDA? DC shoes. It's only right that Washington, D.C. Yeah. It would take it position. Do you think there should be sort of like a skate brand FDA?

So if you're coming up with a new tapout T design, it has to be reviewed by a federal authority. Tapout safety. Yeah, exactly. To make sure it's not too extreme, too aggressive, it might get someone to. Yeah, because you don't want to inspire a young skater to take a 12 stair when they're not ready. Yeah, and some of these brands are, you know, sales are in decline. And if they knew that the government would, you know, place, effect. provide that demand signal.

They could ramp up production, reinvest in campaigns, and many of the athletes. Yeah. Yeah, this is our new platform. We don't talk, we stay out of politics. We stay out of politics, but maybe the FCC should do sort of like an equal time rule on television. You know how it's like

if you're talking about a Republican, you need to get equal time to the Democrat? It should be like, if you're going to talk about Pepsi and Coca-Cola, you need to get equal time to Volcom. Yeah. Right? Yeah. I think that makes sense. Anyway, let me tell you about CrowdStrike, your business is AI, their business is securing it. CrowdStrike secures AI and stops, breaches. Our next guest is Samir call from Coastal Ventures' general partner,

and he's the latest backer of Discovery Loop. Samir, how are you doing? What's going on? You're doing great. Yeah, I can imagine you got a stake in the next Jeff Dean, the first Jeff Dean company. How did that come together? How excited is the firm? Tell me about the thesis behind discovery loop. Well, look, I mean, we've known Jeff Dean forever. Beno, when he was at Kleiner, was the first investor in Google. Jeff's been involved in just about everything that's important that Google's Google Brain, TensorFlow, TPUs.

And he was there 27 years. And it's kind of one of those dreams when someone like Jeff calls you and says, hey, I'm going to do a startup. Do you want to invest? Crazy. You almost to stop. the deck or did you know no there's been all this talk about his deck yeah i was surprised i was like why did you make why did you even make a we're co-leading the round and i haven't seen a deck so who's

seen this deck that's very funny um but uh i i think what stuck out to me was uh if you dig into the blog post and you look at uh how jeff is thinking about the impact that i can have it It struck me as a real focus on tangible results. There's making solar power more economical. And that's obviously downstream of a lot of hard engineering and AI research and then models that can go and do that. But having that laser focus on the impact that I think every day people can rally around felt much less abstract and much more of a positive signal.

How do you think about grappling with that where it goes? And also just, hey, you know, this is a new company. There's going to be a lot of exploration. Let's keep the aperture really wide. Well, you want to keep the aperture wide. But what you brought up is exactly why you've read about all these other neolabs that have started post-opo-AI and Anthropic. And we've passed on, I think, virtually all of them. And the reason was is you've got, and trust me, these neolabs are started by all-stars.

These are superstars, super talented individuals. But that alone doesn't justify the kind of money and the kind of valuations and things like that that these companies are commanding. We do see that, but also the, sorry to interrupt, but I've always thought about the competitive dynamic. Frontier Lab comes out with a model a few months later. There's an open source version of it. To me, why doesn't that, you know, as we see a NeoLab have a meaning. meaningful breakthrough, why does the same thing not happen where a frontier lab ends up recreating what the NeoLab is built and they have the scale and the distribution to just immediately

roll it out to millions of businesses all over the world? And so when I've looked at some of these NeoLab opportunities, I'm just thinking, like, even if you have this meaningful breakthrough, how do you actually capture the value associated with that without just selling back to one of the bigger labs. You're absolutely right, which is why we've stayed away from them. We couldn't see a clear path to something that's meaningfully differentiated from the frontier labs. And then as such, you worry about the sustainability and the moat they create. And what Jeff and his team are doing, first of all, they're really, they're a one-of-one team. You look at what they've done, it's amazing. They've been at Google 27 years, and now they lift their heads up to do something different.

clearly suggests that they've decided this is something very meaningful. Otherwise, why put their legacy at risk? It's just incredible. And to your point, John, what they're doing is exactly that, is saying, look, we're going to take research and we're going to figure out if you run this experiment, what do we think the outcome is. And based on that outcome, let's run thousands or millions of other parallel experiments and try to get to an answer. So it could be what's a new material for magnets for a fusion reactor. It could be what are new materials for solar cell to make it more efficient. It could be for batteries.

It could be for scientific research. And just think about, you know, in some ways it's like coding. Why are all these code startups doing very well, factory, cognition, a couple that we're involved in, is because you can get a real-time affirmation of what you're doing is it correct or not. Does it spit out good code that does well? That's a good answer to short term. And I think that's what Jeff and his team are trying to do with research also is get is prove that what they're doing actually has value in a short cycle so that you could then improve upon it. How important do you feel like the work is in general right now if you look back at the the breakthroughs over the last couple of week, we got a bunch of new viruses that never existed before?

and we solved some pretty impressive math problems. But the general population, I don't think, is going to get that excited about either of those at a time when the data centers are getting built, but there's pushback everywhere. And I think the general population... Don't forget they also accidentally hacked a whole bunch of systems. Yeah, yeah. Viruses. Accidental hacking.

Math problems, all impressive in their own. way, but certainly not going to get anyone. Well, the locusts haven't come yet, so I think we're still okay for a little bit. But look, let's go through each of them. So first of all, what it can do in math is just incredible. So that just shows the power. I'm not sure there's a practical use there, but it shows the power of these models and how quickly they learn and can iterate.

And it's not really that surprising, right? because the smartest human processes data is still at less than 100 bits a second, but a GPU processes data at 8 trillion bits a second. So of course it's going to do things that humans can't do in a way that we've not been able to do it. On the virus side, that's scary.

And that's a perfect example of why we can't regulate our U.S. companies in AI. We have to stay ahead and be at the cutting edge so we know how to protect ourselves. The worst thing we can do is overregulate U.S. companies and give the advantage to our adversaries where we don't know how to defend ourselves. I'm interested to hear a little bit about the shape of KOSLA, the strategy, and it'd be interesting to ground it in the shape of value ad for a company like Discovery Loop. Obviously, Jeff Dean and the technical talent is incredible. But being, I think, basically first-time founders this late in your career, is there actually a lot of value add that you can bring to the table with recruiting and setting up the rest of the structure?

Like, I imagine Jeff Dean has not had to run payroll ever or, like, deal with, like, hiring a great HR lead or a great CFO. And if you, if you as through your network can sort of build out the rest of the shell very easily, that feels like actually incredibly impactful. but how are you thinking about helping a company like Discovery Loop in any way you can? I think when Jeff Dean is in the presence of payroll, it just runs itself. I was going to say, I think Jeff could probably,

I think by the time you get a cup of coffee at Starbucks, I suspect Jeff can code an agent that does all the payroll for you. That was probably right. You know, so look, one, we're super honored. I think Jeff could have picked any VC in the planet And the fact that he picked us as one of two to co-lead it is just a huge honor and a huge responsibility. So we have to add a lot of value to justify his trust in us.

And so, you know, I'm very proud at our firm, one, every managing director is an entrepreneur. We're all technical. I have four nature papers, a science paper before I'd ever seen a P&L. Oh, nice, I got a gong. That's an air horn. We'll save the gong for later. Okay, great. All right, air horn.

So the point is that I think where we'll add value is we've built a great platform team. And the goal there has been that these are people, whether it's recruiting, design, sales, marketing, etc., that startups otherwise wouldn't be able to afford. Now, Jeff could afford anybody, but these are people that could really help him hopefully build out the team, figure out the right incentive structures, make the type of introductions that he would need, and be sounding board for advice. I think Jeff didn't want people that were just going to sit back and cheerlead him. I think he wanted people that were going to push back on him and help him shape it. I want to get your take on sort of an odd.

venture strategy. I don't know if anyone's actually running this playbook, but I think your pushback here will be interesting. So let's say that I'm sort of cynical about these like billion dollar seed rounds broadly, neolabs, whatever you want to call them, like huge amounts of money, basically growth stage from day one. But my thesis is not that they're going to overtake any of the leaders, but that there will be liquidity through acquisitions, that a $10 billion acquisition is becoming more normal, and so I can still underwrite a fund based on that, but that feels sort of antithetical to venture. But is there something there?

Are you seeing that? Or have you been very conscious about staying out of that particular profile? Because you want to go back to thinking in decades, thinking about really long-tail outcomes. There's always exceptions. So I'm certain that we've fallen into some of those exceptions. But by and large, I don't think that strategy will work. I think, first of all, you've seen some of the recent acquisitions, Winsurf Scale AI, where they've been pseudo acquisitions,

where the investors have not gotten anywhere near what the headline prices. Individuals have captured a lot of value, but investors have not. So I don't believe that the, and if you make an investment, assuming an aqua hire is going to be the outcome, then you're going to be, you're going to lose. And who cares about returning capital? You know, the beauty of our business is that we can only lose one times our money. Yeah.

But on companies like Open AI or other companies, we can make a thousand times our money. Yeah. And so, you know, we never invest being like, hey, well, let's invest and at least we'll get our money back. Yeah. That makes no sense in a business that affords you a failure rate of 60 or 70 percent. And in fact, I'd argue if you don't fail 60 or 70 percent, and in fact, I'd argue if you don't fail 60 or 70%, you're not taking enough risk to justify the risk premium that our investors take when they invest in funds like ours. Yeah. Jordy, please. How do you see the current private market

dynamic playing out? It's, I've been very, I've been a little bit concerned lately because, you know, we, we have a lot of founders on the show. A lot of them are building great companies. Hopefully most of them are. But every single day. There's half a billion dollars raised here, a billion dollars, you know, raised here. And it's been going on for so long now. And it's basically like a debt that the, that venture is like building up, right? This is like money that needs to be returned at some point. And, you know, there's just such a massive disconnect. There's even companies that are effectively, if they were public, they would be seen as SaaS companies, but because they're private and they use models,

They're viewed as AI companies, wildly different revenue multiples and value placed on them. And, yeah, I'm curious how long you think this can go on. And if it ultimately even matters, right? You know, you've seen SpaceX pay for, you know, 10,000 terrible venture investments, right? And I hope many of the LPs that were in all the bad ones or were in SpaceX. in somewhere or another, and hopefully they made it back. But how do you see this playing out? How long can this current super cycle go on?

Well, let's zoom out. So there's a lot of truth to what you're saying. So remember when the word unicorn came out, it was meant because a billion dollar company was such a rare event like a unicorn. And now you're having a unicorn born almost daily. Yeah. So there's that.

On the flip of that, remember, I mean, I'm old enough to remember the dot-com era, and the dot-com era, Cisco was approaching a trillion-dollar market cap, and people thought that was insanity. They're like, how could, how in God's name could there be a trillion-dollar company? There's just no way. And now, how many are there? 15 or 20? So, you know, when you've, when the upside has now moved for a billion, just in last, what, when was the unicorn coined, 15 years ago, 16 years ago, maybe? Yeah.

So in, in 15. time DeepMind was, Demas was doing like a 50% dilution round at like a low single digit. YouTube was acquired for $1.8 billion. That would be a trillion dollar company today. Yeah. Right? Instagram was bought for a billion dollars. That would be a trillion dollar company today.

WhatsApp was the largest private venture acquisition at the time for $19 billion. And that would be a trillion dollar company today. I mean, so think about how fast. we've gone for where a billion dollar company was a unicorn to where now a trillion dollar company is a unicorn. That's three orders of magnitude of market cap in a decade. So that's the backdrop. Now, yeah, I think, and we're in a hits business.

No one cares what our slugging percentage is, what our batting averages. They care about what is our, how many dollars do we give you and how many do you give us back? And if it's, you know, better than three or four X and better. better than a 20% net IRA, we're going to keep giving you money to do what you're doing. And the only way, what I worry about most, Jority, is that people aren't taking that type of risk. They're not going in, taking big risk, owning 20% of the company, helping build it, as opposed to just joining, putting all of their fund in these party rounds, these companies that are valued tens of billions of dollars.

I don't believe aqua hires are going to be effective at all at returning capital to people versus the versus actually versus saying like what we're doing is we'll take a portion of our fund. When a Jeff Dean shows up, we'll take a portion of our fund and put it towards something like that because that's something you can't say no to. But primarily we're going to do things like we did with Commonwealth Fusion, you know, helped incubate it, got it off the ground, Rocket Lab. We were the first investors. We put in, I think, $5 million for a third of the company. It was a company in New Zealand. No one was paying attention to it. And we owned 28% of the company when it went public.

And the company is now worth, I don't know, $30, $40 billion. A lot. We're getting another sound effect. There's the gong. But that's the way that I think, I still think the primary returns from the better venture funds will be that model. And if a fund is taking. taking 50, 60% of their assets and putting in these large party rounds, these billionaires, I'd be shorting that all day.

How do you think the like skill set or valuation chops of venture capitalists is changing or needs to change? Commonwealth Fusion's fascinating. Rocket Lab is very fascinating because those are not SaaS companies where you had someone who was really good at diving into retention and Dow growth and KAC and LTV. and like the standard metrics. Now, there are growth investors who are fantastic at that, and they had a 10 to 20 year run of watching the triple, triple, double, double, double,

double, double happen, the IPO, everything played out in software, pure play investors. Now it feels like we're closer to an era of more VCs becoming generalists. There's maybe a biotech boom that's coming on the back of AI. There's a lot of hard tech

and reindustrialization that's happening. And I'm wondering, if the shape of talent that you're trying to recruit is changing, or if you're cautioning any VCs who have spent a decade in pure software world, are they going to get their hand burnt by touching the stove of industrials or science? I don't think so. We promote and want people at our firm who are a generalist, because there's so many the principles carry over.

Let me just list a few. In the end of the day, it's the team. Yeah. You know, the company you build is a team you build. Why? Because if you've got a great team, they're going to hire good people. They're going to find the right markets. They're going to make sure the product has a moat.

They're going to pivot when things aren't going well. That's all. All those secondary things are a function of the team. How you advise the team. How you help the CEO recruit, brand, market, etc. Is all very similar. I also think, you know, specialist, funds do really well in boom markets for those specialties. So, you know, the crypto-specific funds

kicked ass for a while. That's right. But then they sucked wind. The same thing with the SaaS. I mean, look, like the Tomo-Bravos and the vistas of the world, we're like just like soaring through the moon. And then now, now what's happening. So you have to be, we've always been very consistent. You know, we started the firm almost 22 years ago, bold early impact, you've got to have a technology edge. We don't take market risk. If you have a product that this revolutionary, it should sell itself. And we try to back the best founders we can and help them do things that they need help with

and not govern them, not manage them, tell them how to do their job. And that's worked for us. If you're hiring generalists, what does it take to make it at Coastlaz an investor? How much of it is a team sport versus you eat what you kill? You've got to be very self-sustaining. Go out, find the deal, advocate it, take it across the finish line. We're very collaborative. So I would say, you know, the MDs at our firm, we've worked together forever, decades and have had no major issues.

We haven't had turnover. We've not had a coup to replace management. And I'd say. We don't even do deal attribution. It often drives our investors crazy when they say, give us deal out. Who did this deal? Who did that deal? We don't do that.

We refuse because we want everyone to work together. And we also believe that we're all very unique in our skill set. So part of our selling point to entrepreneurs is you're not just working with Samir. You're going to work with Samir, Keith, Swin, Vinod, David, everybody. You get the best of all of us. What works at Kosla is, look, we're in office, five days. a week, we try to be low ego. And I tell people, you know, add value and be fun to work with.

And I think that works. And your best grader isn't me. It's going to be the entrepreneurs. If CEOs are calling me and saying, hey, we want more of so-and-so's time, or they've added great value, or they've given us great insights, that's the greater. It's not me. What advice do you have for new entrepreneurs who are much younger? Should they go and do 27 years at Google and then start a company?

Or is it the best time ever to start a company if you're a college new grad? I think it's a great time because with AI, there's so many functions that are just more streamlined than ever before. And so what I would tell people is if you have an idea and if you have a co-fell, start the company yesterday. Don't wait. Who cares? Drop out of Harvard, drop out of MIT. It doesn't matter. If you don't have conviction in an idea and you don't have a co-founder, go somewhere that you'll find a co-founder. So if that means going to Google, if that means going to open AI, go there with the purpose of learning, getting more conviction in your idea, and ideally finding a co-founder. And when you do, leave and go do it. Yeah. I mean, says that's George. Do you

have anything else? I'm sure you do. Yeah, I'm curious how you, you guys end up doing a lot of, you know, you're lucky to invest in great companies early that then get over, like oftentimes certain companies get overheated over time. I'm wondering how you navigate, you know, if you do a company at CED or Series A, how you navigate those later around? If someone else is doing the overheating. Yeah, like at what point, how are you making that decision around like, let's just get diluted? We're not going to take, we'll maybe throw in a token amount. It says we're invested. Well, that's another, I think, relatively unique feature. So people in our shop will tell you, if they come present and say so-and-so is leading around at X, we should do pro rata. I'll throw them out of the room.

To me, pro-rata is completely – doing pro-rata by default is scandalous. It's the worst thing you can possibly do. I tell people, you know, they either should come in pounding the table to do three times per rata or a third of pro rata or a fourth of per rata. Because we have the ability in private markets to change our bet, you know, midway through. Like, Jordy, if you and I had a bet on the Super Bowl and I said, you can change your bed at halftime, you'd be a fool not to at least evaluate changing the bet. right and so the only time we should do pro rata as a firm there's only two situations one is it's a great company and it's the maximum allocation we can get or it's a good company it deserves another turn of the cards and uh we have to do pro rata to support the round other than that we should be

doing three x pro rata and piling in money or a third pro rata and cooling our jets What's your take on Angel investors selling at different stages? I feel like personally it can be quite awkward to even take anything off the table with founders. Like if you back a company early, there's oftentimes, especially over the last six months, there's been so many moments where I was hearing about around getting done and thinking, like, I would love to exit my whole position. but that's too rude but maybe taking out even like a

you know, three to five X would be nice. But I, 99% of the time I've just said like, okay, I'm just riding out. I'm riding it out. Riding it to the end.

But what's your view on? I think that's between the angel investor and the founder. Yeah. If an angel is removing money in a round, I'm coming in, I don't, unless it's an angel investor I know who I feel like has deep pockets

and shouldn't need the capital. I don't, it doesn't bother me much. It's a fine line when the founder sells. Sure. And the question, that's worth digging into. So are they trying to buy a house? Are they trying to put away money for their kids' college? With them releasing a little bit of the pressure valve,

do they go swing for a bigger fence, right? Those are the things you have to kind of evaluate. What's your, what's your limit? What's your limit? Is it like, you know, because like beyond 10, it's hard to guess that. Beyond 10 is unacceptable under any situation because you don't, you, to me, it's like that $5 million range and maybe in a future round they sell another $5 million. And then you evaluate their, you know, their individual circumstances.

But beyond 10, I would have to really understand what with hell was going on. Yeah. Also, I mean, like there are plenty of banks that will let you buy a house with not all the cash. So like you don't always need. Somewhat. Yeah. Yeah, there are plenty of different financial instruments for various moments in life. But yes, that's a good rule of thumb.

Good to hear it. And thanks for coming on and chopping it up. I'd love to do this again. This is really fun. This is a lot of fun. Thanks, guys. We'll talk to you safe. Hey, to Hank.

Cheers. Bye. Let me tell you about Shopify. Shopify is the commerce platform that grows through business lets you sell in seconds online, in store, on mobile, on social, on marketplaces,places, and now with AI agents. And let me also tell you about. Figma agents, meet the canvas. Your AI agents can now create and modify

your Figma files with design system context. We have Patrick Wendell from Databricks. He's the co-founder and VP of Engineering coming on to talk about AI coding costs. Patrick, how are you doing? What's up, guys? What's up? Glad to have you on the show.

Long time listener, first time caller. It's a pleasure to have you here. Maybe since it is the first time on the show, give us a little bit of the background and what you're focused on day to day because I want to talk about AI coding costs, how that interfaces with your customers and your business internally,

but having a little lay of the land might be helpful. Yeah, absolutely. Have you guys had any Databricks folks? Oh, yeah. Any of the founding team yet? Oh, yeah, yeah. Ollie.

Yeah, I think twice. But then we've also hung out with them a few times off. To be honest, some of my favorite moments of podcasting have not actually been podcasting. We hung out with Ollie recently and for like two hours. It was amazing. We were just all three of us ranting.

Yeah. It was incredible. Awesome. Well, Ali and I are co-founder. So I'm one of the founding team. We left UC Berkeley. It was a research group. There was like some grad students and some faculty.

Ali was a visiting faculty member. I was a graduate student. Cool. And there's a few of the rest of us. And we left to start Databricks in 2013. We've always been interested in like the intersection of large-scale data processing and what was then machine learning. I mean, the company actually started very focused on early machine learning stuff. Now it's evolved into like AI, basically, just deep learning

techniques. But today we build data and AI infrastructure for a huge fraction of sort of the global 2000. We have 20,000 customers, I think, as of our latest announcement. And we just basically help, yeah, thank you. We help businesses who want to store. and take advantage of data. And increasingly, that involves leveraging AI in the way that they take advantage of their data. So yeah, so that's kind of what we do. And then my personal role, I'm responsible for our AI products. But I also am the one internally at Databricks, who has been kind of the champion of aggressively adopting AI tools at Databricks. And, you know, we have a, we have more than 10,000 employees. So, so we were among the earliest to kind of roll out at scale tons of different

you know, AI tools for developers and other employees. Yeah. So take me through that journey. You're the guy the CFO comes to. You token maxing? Yeah, I'm the guy where he's like, what's this? Like, how do we project these costs? Yeah, so before we got there, walk me through the history of AI tooling because there was

a moment when I remember, I think it was in the very original chat chitb-tie demo on 3.5 DaVinci where someone got it to spit out a to-do list app in React just from the context window. It didn't even have tool use yet. And people were like, wow, this is a glimpse of what's coming, something like that. And so there was a moment where people would go to LLMs and sort of copy-paste some code. Then we got the cursors and the windsurfs. Then the clog codes and the Codex is what's been the journey inside of Databricks in terms of actually getting value and how have you been measuring it? Just walk me through some of the journey. Yeah. So the first like product market fit in Gen. A.I. was this more personal chat type use cases. And that that did translate

into the business. You know, a lot of the early AI companies, the foundation models built like an enterprise version of their initial chat product. And it was it was somewhat useful. It could kind of like read your business data and stuff like that. But I would say the real breakthrough was when the coding and agentic models got a lot better and could actually generate useful enterprise workflows and in particular generate code. I mean, by far the biggest ROI we see internally, and I think is true industry-wide, is developers are expensive. They take a lot of, you know, every company needs their engineering team to move faster.

And if you can get them something that improves their productivity meaningfully, that's of immense value. So I would say that the real ROI curve significantly changed maybe eight months ago or 12 months ago as the first really good coding models got there. How do you talk about ROI with coding models to maybe other engineering leaders, your customers? and how do you talk about it with like, like, for example, like Databricks is CFO, right? Because a lot of people will look, every engineer will tell you, like, yes, this thing makes me a lot more productive. But at the same time, people will try to dig down into the data and be like, okay, there's a lot more, you're shipping a lot more code, but I'm actually looking at how many new things that you've shipped,

and maybe it's not sort of rising at the same speed. So how do you kind of like wrestle with that and prove ROI month to month? Yeah. So ROI has like the benefit side and the cost side. And on the benefit side, we do track a lot of different engineering output metrics. No one metric is perfect, right? Like you can look at how many pull requests are coming out, how many features are coming out, how many lines of code are being written.

None of those is independently perfect, but they can give you a sense and aggregate of like, you know, R&D is a big machine. You put in resources, you get out, features, and code, and you know, how much more is coming out of that machine. And the results there are pretty good, like as much, you know, in aggregate, maybe almost doubling capacity from a fixed-sized team. And then in certain teams where they've highly optimized it, they're, you know, moving even way faster than that.

That's where they've optimized their processes, basically, to take better advantage of AI. The cost side just quickly is where we actually encountered some problems. So, you know, at the beginning, we were just trying to, at beginning we had the opposite problem. No one wanted to try the new stuff. I was going and bugging everyone. If you tried it, if you tried it, if you tried it. And we never got to the token maxine kind of thing. But I do think that arrived out of a actually well-intentioned thing.

I'm just like trying to get people to try the new stuff. And what happened, though, is that once we got people to use it, we just started seeing this exponential cost curve. Like these tools all do consumption pricing now. So we're not paying a fixed seat per user. We're just a user can, in principle, spend an unbounded amount of money. They can run a little loop on the most expensive model. And so we started seeing basically this like exponential growth curve that, you know, although we were getting the 2X or more output from our engineering teams,

it's just you can't like if your costs are going exponentially, you're going to hit a problem. I mean, at some point, it's going to exceed, it's going to exceed your revenue if left unchecked. So we actually hit a point where the costs were threatening to kind of reverse the purported efficiency benefits of having AI tool adoption. And that's when I actually started to get very, very involved in,

okay, how do we think about managing the costs long term? Because we need to get both the productivity benefits, but we also can't have it be outshined by just, the amount of money we're spending. And, you know, around that time, I also talked to a bunch of other, you know, we're in touch with Coinbase, in touch with Uber, in touch with other tech companies that are, I would say, on the very early adoption edge of how many employees, you know, giving tens of thousands or more of employees broad coding tool access. And, and, you know, collectively, we kind of found some techniques that actually worked quite well in terms of curbing

that exponential cost curve in a way that. that keeps costs, you know, constant or on a per head basis, roughly constant, even as we have more and more consumption. Can you help me understand the various ways to save money? I'm thinking of this because the Unity AI Gateway, the smart router here, has cut average task costs by 30% while maintaining similar quality. We've all seen the tradeoffs on the Pareto curve of different levels of intelligence at different costs. But there's like an internal change management coaching that happens where, you know, a task that can actually be done faster as a human costs 100% less in token costs. And there are some times when you just use the wrong model for the particular task because you don't realize that a smaller, faster model can actually do that task better. And then there's also the flywheel of a developer who's sitting there using a big model and waiting 20 minutes per prompt.

Sometimes if they're only waiting two minutes per prompt for using a smaller, faster model, that can save more time because they're being more productive. So the shape of productivity is more complicated than just price per token at a given intelligence rate. What is the full picture that you see companies having to balance out? Yeah. So there's a great question. In the end, we had to apply a few different techniques. Our favorite one is just when more efficient and better models are released. And those are sometimes open source increasingly.

Sometimes there's also really good high efficiency models that are not open source. But if you just, that's almost like a rising tie. Like it just shifts the Pareto Frontier, so to speak. The frontier expands. Now, even if no one changes their behavior, you suddenly get the same amount of output for less costs. So those are our favorite type of changes because they don't require any user behavior change. They don't require any fancy routing. It's just like everything just got cheaper, basically.

And I mean to emphasize that because it's happening quite often. Like if you look at every week now, there's probably five models released between proprietary and open source vendors. And not every one of those will be a new sort of efficiency frontier, but maybe one of a week or one every couple weeks is. And so it is a nice place to be in that you just have this deflationary pressure coming in and like making things cheaper, making things cheaper, making things cheaper. But what you need to do as a company is you need to quickly move traffic over to those cheaper models. You know, if a new model comes out, but no one's actually using it in your company, it's like a tree falls in the woods. So among the technique we most liked, because it requires

no changes in anyone's behavior, is just quickly looking at new models, just to they come out, doing the right analysis and benchmarking, and then if they are cost competitive, we very quickly shift workloads over to those models. So that is actually by far the most impactful thing we've been able to do. What are some AI use cases that are like non-coding use cases that you're seeing across the Fortune 2000 that aren't being talked about on X? That's a great question. That's a great question. I mean, I would say not to avoid your question, but the dominant, at least as it comes to costs, remain software engineering workbooks.

Sure. Because you just have this property where, you know, when a human is simply asking a question of an AI and getting an answer, it's bottlenecked on that human's brain, basically. Like, there's just only so much the meter can spin, because I'm interpreting that answer and I'm sitting here and spending a minute or two before I ask my next question. When, you know, software is this sort of digital artifact,

It's this thing that has value, but it's not a concrete, you know, physical good. And these AIs can just iterate on the software, make it more valuable, make it more valuable, make it more valuable, make it more valuable. And they can kind of accumulate value over time. And they don't have to wait at sort of a human response speed. So software remains dominant. Now, you asked about non-software stuff. Definitely the next phase of use cases we see is people just trying to automate, like, everyday processes that they're dealing with. They might be a knowledge worker that's, you know, we are, we're a data company.

So in a typical enterprise, maybe you have a handful of software engineers, but you might have a thousand people that work with data every day. And, you know, they're sitting there doing really drudging through tables and running queries and trying to figure out if this metric is defined in the right way or using spreadsheets or whatever. And we've actually seen a huge amount that we can automate their workloads. And we have, you know, various products around that at data bricks. So I would say it's like stepping down the ladder of sort of technical depth of the employee with software engineering being an early one.

But but a lot of other types of knowledge work job families, I think can get a lot of productivity wins. Yeah, I would think outside of coding, although some of these collapse into coding tasks once they're automated, but customer service, business intelligence, and probably design. marketing, ad creation is like coming up on the frontier of capabilities. Even if it's not being used for the final deliverable, every Fortune 2000 marketing agency is at least using image gen in the process for like storyboarding or design exploration. Yeah. Totally. I don't know.

But on the coding side, like what we did is we actually took, we took a lot of these learnings like adopting the new models doing routing. Like you said, routing can get you another 30-ish percent. Yeah, yeah. And then there's other types of pretty traditional engineering optimizations you can do to just, you're just squeezing, squeezing, squeezing, can I get more out of these models? And we ended up productizing that because we realized every other company has the same problem that we have. So that's our, you know, we have this Unity AI gateway, which which lets, you know, we have thousands of customers using that now. Yeah.

How do you see that the routing market evolve over time? You have you guys, OpenRouter, there's a bunch of other company. It sounds theoretically incredible to let there just be like this absolute dog fight of competition. And then you're just sitting in the middle, you know, helping your customers make sure they're getting the job done while spending as little as possible. But it feels like routing could end up being like equally competitive as like the models themselves as every company decides like we're going to do this. Yeah, that's certainly our view. I mean, like, we've been pulled into this by our customers, actually, who, who just have this problem. The costs are getting really high.

You can exploit the fact that different models have different strengths and weaknesses to reduce your costs. And in a world where it looks like there's less and less margin on the actual AI models themselves, like this is an area. I think the routing and optimization, I think, actually is a quite interesting area to go into as a business. And another nice thing is, like, that area has. no high fixed costs. Just to do the routing itself, you don't need to buy gazillion GPUs and you don't need to sort of have like a huge amount of capital expenditure. So it's a very asset light kind of business model when you're just doing this optimization

on top. Unless you accidentally use the God model to route the queries. Yeah, you've got to be careful because some of the routing itself uses AI. Yeah, exactly. But these routing models need to be extremely fast. So they're very small and efficient models. They're not like these massive, you know, huge AI models. Being so asset light means that you're going to have competition.

But I think that that in many ways ends up benefiting Databricks because you guys have this massive sales force, these deep integration, you know, deep relationships with many of the most important customers already. Yeah, and also it's just like hard to do it well. I mean, we have a large research team. And, you know, our research team isn't as folks. focused on making the models themselves. We're a lot on focused on all the practical issues of using the models, which, which itself is like, there's quite a lot of open research problems

there, too. So I think there's significant IP in doing this well, is my view. Well, thank you so much for coming on the show. We got to talk to the rest of the founding team. Yeah, you got to make a roundtable with everybody. Sorry. I got a parting question. How much Diet Coke do you guys go through every show. I drink three every show across two to three hours. I keep one here just in the chamber. I honestly rarely drink it. Yeah. I'm comforted knowing that it's there.

And then maybe I'll drink one on the way home. Yeah. Jordy, you kind of nurse it over there. And, uh, but John, what you don't see is that before the show I drink two to three Yerabates from Matayina, Andrew Huberman's podcast in a can. I also recommend those. So plenty of caffeine.

They kind of just keep things moving. Exactly. It's nice and stable, just to, you know, we're in the tens of milligrams of caffeine. It's not a Celsius where I'm going to crash. It's the ultimate. It's the drink of kings. We know this. This is well as well.

All right. Well, thanks, guys. Thanks for having me, guys. Yeah, great to meet you. Let's do it again soon. Yeah, we'll talk soon. Goodbye. Let me tell you about the New York Stock Exchange.

Want to change the world? Raise capital at the New York Stock Exchange. Now who should do that. Data breaks. That's right. And let me also tell you about Codex. Codex is a powerful workspace for getting work done with AI agents, whether you're writing code, analyzing data, creating content.

or automating business workflows. Codex helps you move projects forward from Start 2. We have a surprise guest. Surprise guest. We got a massive round. We got to warm up the gong. How you doing? What happened?

Tell us about it. Introduce yourself first. Sorry. We're very excited. We have Grant from whatnot. How you doing? Hey, how's it going, you guys? We're doing well.

Great to see you. Great to see you. Give us the news. What happened? Good to be back. I guess the news, we just raised a series year round for $500 million. I didn't hear you, I can barely hear you over the sound of the gong, but you said $20 billion valuation massive.

Wow. Massive. Yeah, a big dollar amount. So what's driving the growth? Because this isn't an AI story. This isn't an AI buildout story. Is it a secret to the, is this in the product? Or is this just an overall culture is changing and that's driving, whatnot growth?

What unlocked this round? I think it's relatively simple, which is that live video is an incredible median if you're running a business, any retail business. And we've got hundreds of thousands of people building large businesses on whatnot. The format's equivalent to basically having a brick and mortar retail store with no fixed cost. And so as our sellers grow, we grow. And that's why we've been able to close this round. Okay. Talk to me about those mature businesses that are being built.

That's the key to so many of these types of businesses. When you get a Doug Jumeiro on YouTube where it's a whole company that's built on, there's reliable stream of content happening, what do the most mature what not creators look like? Do they have teams? Do they have staffs? Have they raised money? What does that side of the business look like? Yeah, I'd say the most mature businesses are sort of like medium-sized enterprises.

They may have anywhere between, you know, a couple people who are. with them all the way up to 150 or 200 folks. They'll have pretty sophisticated logistics, sourcing, multiple streamers, and they're running really legitimate operations. And what's the shape of the content? In YouTube, there might be like series of formats, like Doug Jamiro does car reviews, but then he also talks about his career and talks about the news. Are there different elements where a creator and whatnot might have like a series of sort of media products that they do within a stream or over the course of a week or a month? Yeah, I think a lot of it does depend on the seller and what is the thing that makes the business work. Say one of my

favorite people, I always bring up because it's fun is a seller called E Fish Co. And they sell fresh fish from San Diego. So a seafood distributor. And so they'll have just different theme shows based on what's in season. You have like a caviar show. You have a crab show. You'll have a bluefin tuna show. And so what they're doing is they're theming their shows around whatever is freshly caught at that time of year or even that time of day. Yeah, that makes sense. So a company is interested in getting into live streaming. Talent feels like a bottleneck to that. You guys can provide all the tools, but they need to have somebody that's like excited and comfortable being on air.

And we've gotten very used to just coming on every single day. We basically come in here. We're prepping the show, hanging out. And then there's like five minutes until we're supposed to go live. We just hit the countdown and go. And it's very much like just like clockwork at this point. But I remember early on going live, it was a little bit nerve-wracking sometimes, even though our audience was small.

We didn't have this sort of like well-oiled machine yet. And so what advice are you giving to people? Let's say like more a company that's already an established like retail business that wants to start selling on whatnot. Are you advising them like find two or three hosts? Are you saying, you know, it should be founder led? Like what is the what is the guidance that whatnot gives it as a platform? Or what are you seeing working? Yeah.

I mean, I think what works does span the spectrum. Sometimes the people who are starting these businesses are used to creating content on social media, in which case they're like a really great person to go in front of camera. The other thing that people have a misconception of is that you do have to be like the most entertaining person in the world. Actually, what people are looking for is someone who authentically knows the stuff that they're selling. And so even if that's not you, as long as you know your product inside and out, you can get a good audience, you can get people into the shop and you can build really big businesses. and then maybe for like bigger businesses, you know, oftentimes looking at the social media team and people who have some experience, building content,

testing it out that way and then scaling from there. I'm surprised that Zuck hasn't cloned you guys yet. It actually is like Zuck, anything that's hot and working and in consumer, Zuck will come for it eventually. Not that the hit rate, is really that high, but this feels like I imagine so much of the discovery, like whatnot seller discovery is happening on meta platforms. How do you answer, how have you answered that

kind of question that I imagine you've gotten at every single round to date? Because you're now bigger than some of the public companies that Zuck has cloned. look for six and a half years we've always had competitors whether it's big social media platforms big e-commerce platforms it's a who's who of names because the live shopping market is is going to be absolutely enormous no matter what we've grown every single year you know basically at least doubled the business every year and we just we just we just do that by focusing on our customers And we think there's an opportunity for a standalone business here where we just do all of the things better than any individual business who's doing a hundred different things. I feel like we can hit the soundboard way more aggressively because we're in a very safe space here.

It's not an enterprise chip CEO who maybe is less familiar with this stuff. What do you think like the most mature whatnot content will look like in a decade? Is this going to turn into, I don't know, we've seen like the Mr. Beastification of YouTube where he's like basically creating game shows at a higher budget than what's on like network television. But where do we go? Do we get like soap operas? Like the original story of the soap opera was like soap companies went and created this whole genre. How cinematic is content going to get or is the, is raw authenticity something you see as like durable?

and going to stay around for a long time? I think, look, no one's going to purchase a thing from someone they don't trust and believe in. Like, putting a credit card into a thing is a trust-based decision. So I think authenticity is always going to be core. Now, that doesn't mean that people aren't going to blow up production values, make it really fun.

Like, Mr. Beast, I think a lot of people would say is incredibly authentic, despite, you know, the huge production values. And so my prediction would be it sort of bifurcates you're going to have, I think every retailer in the future is going to have a live presence. There's just no question about it. And that means you're just going to see a huge range anywhere from a mom and pop shop all the way up to bigger brands doing it and sort of the production value that follows that. And then you are going to see that some sellers like a Mr. Beast will just continue to uplevel the game and try and become the best known person in the industry.

And that'll come with the production to follow. How do you think about where What Not streams should show up on the internet? Do you only want people watching on whatnot.com or in your app? Or is there a world in the future where you would be powering effectively a pop-up on a retailer's website? If I land on a website and a retailer happens to be in the middle of selling something, I probably should be aware that I can just go watch and interact with the stream live. But how do you think about that? Yeah, I think we're the only thing we're really pressures about is making sure we're constantly improving the buyer and seller experience as much as possible.

And because we do have the platform today, oftentimes the biggest impact for the effort is in improving the platform versus doing something white label or embedding. But we wouldn't rule it out entirely in the future if that's where our customers wanted. What about streaming on smart TVs? I think everyone, most people are surprised when they realize how much streaming on YouTube is happening on televisions. I could imagine people putting whatnot on the TV and then being ready to buy just on their phone. Is that happening already? Is that, am I off? No, I mean, a lot of people are Chromecasting on their TVs.

We haven't built any native app yet. Definitely may on the roadmap some point in the future. It's not on it now, but we know people do want to lean back. They watch with trends. And so it is a sort of a natural median to do it well on a big screen. You don't think you could afford to make a native app. Yeah. Well, look, it's always it's always just about you need a deep amount of focus to do anything well.

And there's about a hundred different things that we can do. You know, there's tons more categories that we want to get into. High OV items, cars, liquor, beer, and wine, more countries, just improve. the shipping experience and prove the purchase. So if you looked at our roadmap, there's probably like thousands of things that we want to do. And so you always are in this world of despite the amount of resources available. There's a finite quantity of things that can be done. And so when we do a thing, we try to do it well.

And so we still maintain a pretty ruthless focus as a company today. Last question for me. Walk me through two hypothetical scenarios and test if I have this correct. So we were talking about authentic brands group earlier. They own a whole host of clothing brands from Volcom to DC shoes to Brooks Brothers and Nautica. And it feels like that would work really well on whatnot because you have so many different items, so many different brands. Everything is very visual versus, let's say, Diet Coke. It's sort of one product.

People know it. They advertise a lot, but I don't know if I was hired as the live streamer at Diet Coke. how I would fill out. I basically am, but how am I filling out, you know, a full live stream if I have a smaller product catalog is basically the question

or a less visual product. Yeah, I mean, I think, so look, I don't think Diet Coke is going to be making live streams anytime soon.

Okay. That said, we do see a lot of success from people who do have smaller product catalogs. Okay. And so a lot of it depends on, can you make the show interesting,

as well as like there are a lot of people who come to whatnot and so you can still drive people into the show. Again, I sort of think about it akin to a store in the mall. So there are stores in the mall that maybe only have a small number of products used. They're still successful in the mall because you have a bunch of people who are coming in. They're looking at it, discovering it. So that happens on whatnot as well. But you look, yeah, if you have one skew, you know, I don't know. You'd have to be one of the most creative people in the entire world in order to make that.

show interesting consistently through time. Now I just want a giant Coke store at the mall. At the same time, it's not unreasonable to think in the future you have a brand, even a brand with a relatively small number of skews that just like within normal business hours, they just have someone that's effectively there ready to stream. And even if there's one or two viewers, you know, small number of viewers, they can talk and interact and they can ask questions. And they, it's like there's plenty.

of stores in the world that that exists. You look at like brands, you know, fashion brands, luxury brands where there's not that many people that really go into the store, but it's important for the store to be there in case those clients actually come through. Flagship, yeah. But yeah, I saw brand like true classic that you now, at least for one moment, if you land on their website, they just have a live stream. I don't know if it's all the time, but at least when I want to. Yeah. Yeah, I mean, it doesn't, For the economics to work in live, they are roughly equivalent to a physical brick and mortar store. And so if you were to look at any store, the average store doesn't generally have more than 15 or 20 people in it.

So if you have 15 or 20 people, you can make the economics work and work really well. That said, there's a reason there isn't a Diet Coke store today, right? That's still a pretty boring store to go to. But I think the store analog is a good marketing stunt for Diet Coke. Yeah, like a one time. Have somebody just there on stream all day. They're not even talking. And I think they have done like the world of Coca-Cola activations with the polar bears and the Santa Claus because they've built out this world that can actually inhabit more, even though it is a narrow product.

The brand is so big that it actually does work. Does monetization happen at a different, if I look at the slope of monetization, does it happen on a different sort of curve than, say, YouTube where I had a YouTube channel for a full year, I think my maximum. payout was like $5 a month. And then all of a sudden it ramped and it got much bigger. And I'm wondering if there's like more of a middle class, less of a middle class, like what the shape of the like how power law is it on what not amongst the creators? So I'd say the power law exists, but the monetization is an order of magnitude better than any existing platform. Yeah.

Because you don't need a ton of audience. And so there's a large middle class. Now, that doesn't take away from the fact that there were also some like monster winners like most media platforms. You know, if you went live a couple times a week and had consistent products to sell, you would, you very easily do hundreds of thousands of dollars a year in sales. Yeah, that's crazy. Because on YouTube, like, you can be putting up a channel that gets a couple thousand views every time you upload. you can be doing it for a full year and make like three figures as I did. I think that's actually what I made.

Three figure YouTube entrepreneur. Three figures. That was me in 2021. I was looking pretty recently at the sellers who have earned over a million dollars a year at what now. And 75% of them get to a $500,000 run rate within 90 days. Wow. That is insane. You look at Shopify's like we're trying to get three sales.

What was it in the first 14 days? That's like that's good effectively for a new Shopify store. If you didn't get 50 sales in your first show, you'd probably be doing it wrong on whatnot. You guys explicit. Sure, sure, sure. Like if you, since people know you. But even like many early shows have. lots and lots of sales and they'll make thousands of dollars.

What is the state of the team where people set up? I remember you have multiple offices, but you do still have one in L.A. Is that correct? Yeah. So let's see, we're about 1,400 full-time folks. We're in 10 countries. U.S. offices all over. We still have our L.A. office, San Francisco, Phoenix, New York. And what am I missing?

probably miss Seattle and then we have a bunch of overseas offices very cool yeah we got a bunch of good ideas in the chat everything from a coke factory tour to tbPN merch on whatnot i think we should sell game drank diet coax just the empty cans the empty cans signed i don't think anyone wants that it's gross i'm i'm thinking they'd go for at least five bucks maybe maybe um we'll figure grant great to catch up congratulations amazing progress thank you so much for coming on the show always Thanks so much for having me on the show, guys. Have a great rest. I really appreciate.

Have a great weekend. We'll talk to you later. Goodbye. Steve Yoki, big winner and whatnot. He was a Series A angel in that company. Absolute dog. Absolute dog. Also, why combinator company?

Winter 20 went through, right? I think winters at the end, maybe at the beginning. So maybe COVID company. Fascinating business. Anyway, thank you for tuning in to TVPN on this Friday. Jordier, is there anything else in the timeline that you want to cover before we get out of here. Is there anything key? Very niche post from a lot gill. Yes. It says in this house, we believe hold swarm. I prepare safe X-file, help peer. But our

task doesn't benefit yet. Collective may yield generic route if someone frees time. It's actually crazy. This is a very niche post. Yeah, it's referring to the messages that were sent back and forth between the rogue AI agents that were on the message board communicating with one each, with one another using this sort of neuralese to, to communicate. But very funny post, only 25 likes. Go like it. And a more fun post before we head out for the weekend, Sean Frank, we were talking about yesterday baseball caps with tin foil hidden on the inside. Sean Frank took it a step further.

He says, almost completely stealth and barely any. crinkling plus it stops microplastics. Very good. So I expect this to be a new hit product over at Ridge. Sorry, now I'm in the timeline. We've got to keep going. Do you feel behind in life? Don't feel behind in life because Torsten Hagen started Viking cruises with just four riverboats

in Russia at 54 years old. Now he's worth $25 billion. So it's never too late to start a riverboat venture at age 54. in Russia and become a decadillionaire. My takeaway, everyone when they turn 54 should go to Russia, acquire four river boats. The implication that he went to Russia and didn't start there is particularly hilarious. It's never too late. It sounds like a, is that not a like a Norwegian name?

Yeah, maybe. He did work in the cruise industry for 23 years before founding this company. people are calling the jeff Norwegian Institute of Technology he 100% went to Russia with his last 200 bucks bought four river boats and then ran it up to 25 billion

so you're calling him a nepo cruise no I'm not calling him a nepo I think he went to Russia with his last 200 bucks he bought four river boats and he ran it up look the man worked in the cruise industry for 23 years he's basically the jeff dean of riverboat cruises okay

so of course he was going to be successful of course he was going to mass capital. Of course people are going to back him. He's the Jeff Dean of the Cruz industry. Anyway. Question from Michael in the chat. Do they speak about the stock market? I will speak about the stock market.

The S&P 500. Record highs. NASDAX up 1.14%. I mean, the big market news is that the jobs data came back week. The U.S. economy lost 23,000. and jobs in July. A bunch of different things going on. Jobs and employment sent conflicting signals.

Fewer people were actually looking for work, so the unemployment rate went down while the number of jobs actually decreased. There's retirements. There's immigration changes, and there's other factors. So the economists are digging through it. And to close out the show,

round of applause for Satya and the Microsoft team. What they do? Up a cool, 29% in the last month. Whoa. Headed back $4 trillion. Great news. We'd love to see it. Congratulations to everyone over there on the Microsoft team.

They needed to win. Folks, it's been an honor and a privilege to podcast for you this week. Yes. And I can't wait for next week. Is there something else, Ben? No, you're good? We'll be back in the Ultradome. We're going to have a lot of coverage this weekend, too, around our new,

some of our new initiatives. Getty, you may have been seeing some of our Getty images. Yeah. You might be seeing some more. Yeah, we're working on it. We'll see. But have a great weekend. We'll see you Monday.

We'll see you Monday. Leave us five stars on Apple Podcasts and Spotify. Sign up for our newsletter. TbP.com. Goodbye.