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

10:15Patrick Wendell:Yeah, I do. I was reflecting on the deep mind story of the departures there and the question of 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 LL? Because that was heralded as a very magical technology. You would, you know, 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.

10:57Patrick Wendell: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 LM and say, hey, why don't you generate me a podcast of two scientists explaining this at a high school level and take it into college level?

11:24Grant LaFontaine:Tyler in the YouTube chat says, love Notebook LM. Use it weekly.

11:28Patrick Wendell:Use it weekly.

11:29Grant LaFontaine:I always thought that I would have used it when I was in college.

11:32Patrick Wendell:Yeah.

11:32Grant LaFontaine: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.

11:47Patrick Wendell:Yeah.

11:47Grant LaFontaine:I did that for a history exam. Wow. It was like a vocab lesson. It went through. Okay. Yeah.

11:53Patrick Wendell:middle-aged history i think wait oh you used notebook lm yeah it generated podcast so i

11:58Grant LaFontaine:basically fed in a vocab list okay of like dates and various things then i had it wait and was it just a general how did you do on the test uh it was really easy i think i probably aced it wow

12:09Patrick Wendell:there we go

12:13Patrick Wendell:he needs a better confidence monitor um but i was i was uh i mean first off i i'm i'm 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 Sparknotes or something. But I was interested in the evolution of notebook LLM because it's this like, there's this collapsing of capabilities where Sam Altman was recently sort of dragged a little bit for saying like he would use Chachapiti work to generate a podcast about what's going on on his calendar and the family life and stuff.

12:58Patrick Wendell: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 Chachapiti work to generate you that podcast or will the voice mode and the memory feature have enough context to just sit there and talk to you like it's a podcast on the fly. Like, yeah. And getting these functionalities for free.

13:21Grant LaFontaine:Like live voice.

13:22Patrick Wendell:Yeah.

13:23Grant LaFontaine: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. Maybe it's, maybe, maybe it thinks you understand too much or too little. Whereas voice, you can be like, go down. That's like, exactly.

13:40Patrick Wendell:Exactly. It's a choose your own adventure. It's a, it's an expert call. It's instead of notebook LM, it's Tegas LM, basically. I mean, you're talking to an expert and you can just guide the conversation wherever you go. So it will be interesting to see where this goes, what the reception is like. I mean, huge, huge delta divergence between the social media pushback for ChatGPT 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?

14:21Patrick Wendell: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, the launch of this device will be very interesting to see how things come together. You can see the ChatGPT work, ChatGPT codecs, ChatGPT 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 codecs instance and writing you software and doing the more advanced things that are required just to accomplish some tasks.

15:06Patrick Wendell:Like you can go to Chachapiti and ask it to pull down an image from the Internet, restyle 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 generate an image based on that and take it on the go, but I wanted to be able to close my laptop and still be able to access it. So I had to copy the context window into ChatGPT, just the normal app, so then I could access that information and continue to transform it.

15:55Patrick Wendell: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 like the full capability of what you can do because so many things, so many tasks instead of just knowledge retrieval require actually firing up a browser, scraping it, writing some code, downloading things, 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.

16:30Patrick Wendell:Anyway, let me tell you about Cisco. Critical introduction for the AI era. Unlocks 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 TBPN 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.

17:25So they're up$900 million.

17:27Patrick Wendell:They're very close to a billion dollars. And the numbers are going to get bigger from here. At least they're going to try.

17:32Grant LaFontaine: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 to social media as a child was awarded six million 4.2 million against meta and 1.8 million against google um and 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're like i was like no way and it's like the jury has a has has a verdict yeah to set you know talking to the biggest companies in the world, you must pay$6 million.

18:15Grant LaFontaine: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.

18:23Patrick Wendell:New Mexico is not the biggest state in the union. It's not the biggest state.

18:26Grant LaFontaine:But there was also one in May 2026, 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.

19:13Tell us about tobacco master's agreement.

19:17Patrick Wendell: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.

20:02Patrick Wendell: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.

20:22Grant LaFontaine:I'm the good cigarette company.

20:24Patrick Wendell: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.

20:33Grant LaFontaine:Are they still in business with the cigarette company? Oh, yeah, printed. They're doing great. Who are they?

20:37Patrick Wendell:Look at Victor.

20:39Grant LaFontaine:I've never heard of it.

20:40Patrick Wendell:Yeah.

20:41Grant LaFontaine:Last name Victor?

20:42Patrick Wendell:Yeah, they were literally the Victor.

20:43Grant LaFontaine:They won.

20:44Patrick Wendell:They won, yeah. There's more nuance to it than that, but that's like one way to tell a 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. So the 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.

21:22Patrick Wendell: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 battles between the states and the big tobacco companies.

21:52Patrick Wendell: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 in social media. Facebook generates roughly$200 billion in revenue every year.

22:31Patrick Wendell:although if they got hit with a$200 billion fine, that would be existential. But what 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-cigarette products.

23:08Grant LaFontaine:Well, and that just naturally makes sense. If less people are buying cigarettes, less people are going to have health issues. Exactly. So I brought it up because I think that we could be heading in that direction with social media.

23:21Patrick Wendell: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, OK, 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 298 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.

24:02Patrick Wendell: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.

24:37Patrick Wendell: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.

25:01Grant LaFontaine:You know what I'm going to hit. Overnight success.

25:04Patrick Wendell:Yeah, for sure.

25:05Grant LaFontaine:The exact opposite. Slaving away for years and obscurity.

25:09Patrick Wendell:But 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 is the all-in-one intelligent cloud provider. User-favorite agent to deploy web, servers, databases, and more, while Railway automatically takes care of scaling, monitoring, and security.

25:29Grant LaFontaine:Semi-analysis chimed in on the DeepMind news, not just chimed in. I think the term's posterized. Grave digging?

25:39Patrick Wendell:No. Not grave dancing.

25:41Grant LaFontaine:No, they're... Grape digging? They're digging the grave. Yeah, for DeepMind.

25:45Patrick Wendell:They're putting DeepMind in it, and then they're dancing on it at the end.

25:48Grant LaFontaine: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, Gnome leaving earlier was like a canary in the coal mine.

26:33Grant LaFontaine:Obviously, these are not the actions of people excited about Gemini 4 Pro. Jeff, Sanjay, Kwok, and Oriole are just the latest in a long string of high-profile departures from DeepMind. Jeff Dean is the undisputed goat of Google engineering, co-founded Google Brain, and started the TPU 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.

27:10Grant LaFontaine:Wow. The issue with Google was not Jeff Dean nor Noam Shazir, but rather their 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.

27:24Patrick Wendell:That's so aggressive. Wow.

27:25Grant LaFontaine:And do the thing that will make you more money. becomes demoralizing as many of the great technology leads have left.

27:32Patrick Wendell:Wow.

27:33Grant LaFontaine:And Tay Kim 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.

27:45Patrick Wendell: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 in 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.

28:21Patrick Wendell:In all, we estimate that over 250 billion additional TPU bookings could be added to GCP RPO 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 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 barbell approach as opposed to playing in the middle race is maybe ultimately the right thing to do.

29:04Patrick Wendell: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 they've been rewarded for it. Yeah.

29:31Grant LaFontaine:I don't know. Still, wild series of events. They obviously had effectively a version of ChatGPT internally. They didn't ship it. But Tebow, who's now running Chat Codex, was there working on that product, which is really wild. Sebastian Maliby says, semi-analysis is excellent, but this argument strikes me as paradoxical.

29:52Patrick Wendell:Oh, he messed up the tag, though. Semi-analysis underscore.

29:56Grant LaFontaine:It argues that Google is out of the AI frontier race and that, too, Google's AI revenues will meaningfully accelerate because Google is allocating compute to its Google Cloud customers. I wonder. in 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 self-compute to multiple customers, would this make OpenAI 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?

30:36Grant LaFontaine:does he have something here no we were talking about this before the show this idea that um i guess the question is like like the the like this race is all about compute allocation yeah you want to be allocating compute to training so you can maintain your lead or extend 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 to, uh, 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.

31:15Patrick Wendell:I think the number was 15 % was for GDM relative to the overall cloud.

31:21Grant LaFontaine:Exactly. Compute. Yeah.

31:22Patrick Wendell:So yeah, it was like, That must be frustrating, but still a lot. I mean, there is a world where you could sit this round out and then grow your company, grow your compute, and then rug all the labs, have all the data centers. The Tyler Cosgrove, keep the chips for yourself model, that could happen in 2028. and then every other lab is compute poor because Google just said, 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 a flywheel and needing an RL loop around the code and the use cases and the rollouts. So it'd be very, very tricky.

32:10Patrick Wendell: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 else has, and they have a lot of it loosely.

32:20Grant LaFontaine: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?

32:30Patrick Wendell:Yeah, that is tricky.

32:31Grant LaFontaine:Yeah, it just seems like Google leadership has a very different idea of where value accrues in AI than Demis or other labs. It's not actually the model itself. Yeah. It's the infrastructure, GPUs, cloud business.

32:48Patrick Wendell:It's interesting because you can run back the old Demis quote about when he was selling DeepMind, he talked to Mark Zuckerberg and was like, what are you excited about in the future? Are you excited about AI? And Mark Zuckerberg apparently, according to this exchange that Sebastian Maliby 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 Demis was like, no.

33:14Grant LaFontaine:I don't think he even said that. He was just equivalently as excited.

33:16Patrick Wendell:Yeah, yeah, excited. And he was excited about a few other things. And Demis 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.

33:42Grant LaFontaine: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 like really going to.

33:48Patrick Wendell: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' moment to be like, ah, maybe I shouldn't.

34:13Grant LaFontaine: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 just this idea of, like, there are multiple ways to move the needle and put points on the board in just the successful rollout of A, G, I, A, S, I.

34:56Patrick Wendell: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. I think if you talk to the folks at Meter, for example, they don't feel like they're sitting out AGI. They're very important in that story, in that role. They have less of a financial 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.

35:35Grant LaFontaine:Google's ownership in Anthropic is capped at 15%. They, I believe, have roughly 14%. Weird.

35:42Patrick Wendell:How is it capped?

35:43Grant LaFontaine:I think Anthropic just didn't work.

35:45Patrick Wendell:Oh, we don't want you to have 90%.

35:46Grant LaFontaine:They don't have any voting rights. They're not even a board observer. They don't have a board seat. They basically are just a purely financial backer.

35:56Patrick Wendell:Let me tell you about Console. Console builds AI agent fit, automates 70 % of IT, HR, and finance support, giving employees instant resolution for access requests and password resets. And let me also tell you about public investing for those who take it seriously. We've got stocks, options, bonds, crypto, treasuries, and more with great customer service. A branding mogul's 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.

36:33Patrick Wendell: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 LaGorche Island. Is that how you pronounce it? LaGorche? 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 Wood Houses 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.

37:13Patrick Wendell: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 LaGours. LaGors. Thank you. LaGors. Well, Authentic Brands Group is a very interesting lifestyle platform, I guess. I don't know exactly what you would call it.

37:35Grant LaFontaine:They have some truly tier one assets.

37:39Patrick Wendell: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?

37:49Grant LaFontaine:Let's start at the top, the cream of the crop. They own Tap Out. They do. Iconic brand.

37:56Patrick Wendell:Tap Out Tees. Iconic brand.

37:58Grant LaFontaine:And if you guys ever run into John on the weekends, he's almost certainly head-to-toe Tap Out.

38:03Patrick Wendell:It was one of their first purchases, Silver Star and Tap Out. 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.

38:17Grant LaFontaine:They own Ruka, the surf brand. They own Neiman Marcus. They own Prince. They own Brooks Brothers. They own D.C. Shoes. Yeah. They own Sperry's. They own Barney's. They own Saks Fifth Ave. They own Sports Illustrated. Wow. They have the Elvis Presley NIL.

38:34Patrick Wendell:Yes.

38:35Grant LaFontaine:They have the Muhammad Ali NIL. Yes. They own Forever 21. Yes. They own Roxy. They own Volcom. And what other celebrity Volcoms? Volcom, again, to me, if I, you know, Tyler, I know you're still, you're pretty much head to toe Volcom at all time. Volcom, maybe some Billabong thrown in there. Well, they also own Billabong.

38:55Patrick Wendell:Yep, they own it all.

38:57Grant LaFontaine:And so they own Lucky, they own Eddie Bauer.

39:00Patrick Wendell:They also own Shaquille O 'Neal's likeness.

39:03Grant LaFontaine:And Kevin Hart's likeness and David Beckham's.

39:07Patrick Wendell:Wait, the A-Star Venture Capitalist? Kevin Hart's?

39:10Grant LaFontaine:No, no, I don't think they could afford his NIL.

39:12Patrick Wendell:Oh, okay.

39:13Grant LaFontaine:But the actor, comedian, tequila entrepreneur. Yeah, I think it's so funny.

39:19Patrick Wendell: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 saw it during the World Cup.

39:41Grant LaFontaine:David Beckham was in every other ad. And it's because he did a big deal to basically sell all of his. and so he's basically he basically pulled forward yeah years and years and years of like

39:55Patrick Wendell:nil revenue but how does that work if he actually needs to be on site to like film a commercial

40:00Grant LaFontaine:probably has some obligation like you need to be available this many days wow that's very

40:04Patrick Wendell:interesting uh 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

40:13Grant LaFontaine:T-Z-H says, ABG is a graveyard for iconic brands.

40:19Patrick Wendell:It's the bending spoons of brands.

40:20Grant LaFontaine:No, it really is. I mean, it's somewhat sad because a lot of these brands, 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.

41:07Grant LaFontaine:and so

41:08Patrick Wendell:do you think the surfing industry needs a federal backstop

41:10Grant LaFontaine:I would push for one certainly yeah

41:13Patrick Wendell:couple billion dollars from the treasury directly

41:16Grant LaFontaine:to get Volcom Quicksilver, Billabong back to the top yeah we're on to something here this is our new platform

41:26Patrick Wendell: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 chat is in full support of uh regulatory capture for

42:22Grant LaFontaine:ski brands yes dc shoes yeah do you think there should be sort of like an fda dc shoes it's only right that Washington, D.C. would take a position.

42:34Patrick Wendell:Do you think there should be sort of like a skate brand FDA? So if you're coming up with a new tap-out tee design, it has to be reviewed by a federal authority?

42:44Grant LaFontaine:Tap-out safety.

42:45Patrick Wendell:Yeah, exactly. To make sure it's not too extreme, too aggressive. Yeah, scare the children. Yeah, because you don't want to inspire a young skater to take a 12-stair when they're not ready.

42:55Grant LaFontaine:Yeah, and some of these brands, sales are in decline, And if they knew that the government would effectively provide that demand signal, they could ramp up production, reinvest in campaigns and many of the athletes. Yeah, this is our new platform. We stay out of politics.

43:15Patrick Wendell: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. at it should be like if you're going to 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 crowd strike your business is ai their business is securing it crowd strike secures ai and stops breaches our next guest is samir call from coastal adventures his general partner and he's the latest backer of discovery loop samir how are you doing what's going on good doing great yeah i can imagine you got you got a stake in the next uh jeff dean the first jeff Dean company.

43:55Patrick Wendell:How did that come together? How excited is the firm? Tell me about the thesis behind Discovery Loop.

44:01Samir Kaul:Well, look, I mean, we've known Jeff Dean forever. You know, Vinod, when he was a 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? Did you guys need to look at the deck?

44:30Grant LaFontaine:No, no. There's been all this talk about his deck. I was like, why did you even make a deck?

44:37Samir Kaul:We're co-leading the round and I haven't seen a deck. So who's seen this deck?

44:42Patrick Wendell:That's very funny. But I think what stuck out to me was if you dig into the blog post and you look at how Jeff is thinking about the impact that AI can have, 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 everyday 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, this is a new company.

45:29Patrick Wendell:There's going to be a lot of exploration. Let's keep the aperture really wide.

45:32Samir Kaul: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-open 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 didn't see...

46:07Grant LaFontaine:That, but also the, sorry to interrupt, but I've always thought about the competitive dynamic. frontier lab comes out with you know 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 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, 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?

46:51Samir Kaul: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 mode they create. And what Jeff and his team are doing first of all they're really that's a they're a a one-on-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 it's clearly suggests that um they've decided this is something very meaningful otherwise why put their legacy at risk it you know 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?

47:43Samir Kaul: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 a 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?

48:21Samir Kaul:That's a good answer short term. And I think that's what Jeff and his team are trying to do with research also, is prove that what they're doing actually has value in a short cycle so that you can then improve upon it.

48:35Grant LaFontaine:How important do you feel like the work is in general right now? If you look back at the breakthroughs over the last couple of weeks, 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...

49:05Patrick Wendell:Don't forget, they also accidentally hacked a whole bunch of systems.

49:08Grant LaFontaine:Yeah, yeah. That's another one. Viruses. Accidental hacking. Math problems, all impressive in their own way, but certainly not going to get anyone...

49:19Samir Kaul:Well, the locusts haven't come yet, so I think we're still okay for a little bit. Yeah, good point. 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, it's still at less than 100 bits a second. but a GPU processes data at 8 trillion bits a second. So how is it, 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.

50:03Samir Kaul:On the virus side, that's scary. And that's a perfect example of why we can't regulate our US 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 over-regulate US companies and give the advantage to our adversaries where we don't know how to defend ourselves.

50:30Patrick Wendell:I'm interested to hear a little bit about the shape of Kostla, the strategy. And it'd be interesting to ground it in the shape of value add 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? I imagine Jeff Dean has not had to run payroll ever or deal with hiring a great HR lead or a great CFO. And if you, through your network, can sort of build out the rest of the shell very easily, that feels actually incredibly impactful.

51:15Patrick Wendell:But how are you thinking about helping a company like Discovery Loop in any way you can?

51:20Grant LaFontaine:I think when Jeff Dean is in the presence of payroll, it just runs itself.

51:25Samir Kaul:I was going to say, I think Jeff could probably, 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's probably right. 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 I'm very proud at our firm. 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.

52:13Oh, nice.

52:14Samir Kaul:I got a gong. That's an air horn.

52:17Grant LaFontaine:We'll save the gong for later.

52:19Samir Kaul:Okay, great. All right, Airhorn. 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, branding, et cetera, 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 boards for advice. I think Jeff didn't want people that were just going to sit back and cheerlead him.

53:00Samir Kaul:I think he wanted people that were going to push back on him and help him shape it.

53:06Patrick Wendell: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 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.

53:48Patrick Wendell: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.

54:01Samir Kaul: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, Windsurf, Scale AI, where they've been pseudo acquisitions, where the investors have not gotten anywhere near what the headline price is. 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 acqui-hire is going to be the outcome, then you're going to be you're going to lose. And and who cares about returning capital?

54:45Samir Kaul:You know, the beauty of our business is that we can only lose one times our money.

54:49Patrick Wendell:Yeah.

54:50Samir Kaul:But on companies like OpenAI or other companies, we can make a thousand times our money.

54:54Patrick Wendell:Yeah.

54:54Samir Kaul:And so, you know, we never invest being like, hey, well, let's invest and at least we'll get our money back. 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, you're not taking enough risk to justify the risk premium that our investors take when they invest in funds like ours.

55:16Patrick Wendell:Yeah. Jordy, please.

55:19Grant LaFontaine:How do you see the current private market dynamic playing out? Yeah, it's I've been very I've been a little bit concerned lately because, you know, 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.

56:00Grant LaFontaine: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 many of the LPs that were in all the bad ones were in SpaceX in some way 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?

56:46Samir Kaul: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. 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 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 when the upside has now moved for a billion, just in the last, when was Unicorn coined?

57:32Samir Kaul:15 years ago? 16 years ago, maybe? Yeah.

57:37Grant LaFontaine:Yeah, and around that time, DeepMind was, Demis was doing like a 50 % dilution round at like a low single digit.

57:45Samir Kaul:YouTube was acquired for$1.8 billion. That would be a trillion-dollar company today. 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. 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 average is.

58:29Samir Kaul:They care about how many dollars do we give you and how many do you give us back? And if it's better than three or four X and better than a 20 % net IRR, we're going to keep giving you money to do what you're doing. And the only way, what I worry about most, Jordi, is that people aren't taking that type of risk. They're not going in, taking big risks, owning 20 % of the company, helping build it, as opposed to just putting all of their fund in these party rounds, these companies that are valued tens of billions of dollars. I don't believe acquihires are going to be effective at all at returning capital to people versus saying, like, what we're doing is we'll take a portion of our fund.

59:14Samir Kaul: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, 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.

59:47Patrick Wendell:We're getting another sound effect. There's the gong.

59:51Samir Kaul: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 50, 60 percent of their assets and putting it in these large party rounds, these billionaires, I'd be shorting that all day.

1:00:09Patrick Wendell:How do you think the skill set or valuation chops of venture capitalists is changing or needs to change? Commonwealth Fusion is 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 CAC and LTV and 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 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.

1:00:52Patrick Wendell: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?

1:01:17Samir Kaul:I don't think so. You know, we promote and want people at our firm who are generalists because there's so many of the principles carry over. Let me just list a few. In the end of the day, it's the team. The company you build is the 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. All those secondary things are a function of the team. How you advise the team, how you help the CEO recruit, brand, market, et cetera, is all very similar.

1:01:55Samir Kaul:I also think specialist funds do really well in boom markets for those specialties. So 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, the Tomo Bravos and the Vistas of the world were just soaring through the moon. And then now what's happening? So you have to be – we've always been very consistent. We started the firm almost 22 years ago. Bold, early, impactful. You've got to have a technology edge. We don't take market risk. If you have a product that's 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.

1:02:47Samir Kaul:And that's worked for us.

1:02:49Patrick Wendell:If you're hiring generalists, what does it take to make it at Kostla as 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?

1:03:08Samir Kaul:We're very collaborative. I would say 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. 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, Swen, Vinod, David, everybody.

1:03:47Samir Kaul:You're going to get the best of all of us. What works at Kostla 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.

1:04:24Patrick Wendell: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?

1:04:39Samir Kaul: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-founder, 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 OpenAI, go there with the purpose of learning, getting more conviction in your idea, and ideally finding a co-founder.

1:05:15Samir Kaul:And when you do, leave and go do it.

1:05:17Patrick Wendell:Yeah. That makes sense. Jordy, do you have anything else?

1:05:20Grant LaFontaine:I'm sure you do. Yeah, I'm curious how 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 seed 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, we'll maybe throw in a token amount that says we're invested.

1:05:50Samir Kaul:Well, that's, that's, 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, doing pro rata by default is scandalous. It's the worst thing you can possibly do. I tell people they either should come in pounding the table to do three times pro rata or a third of pro rata or a fourth of pro rata.

1:06:30Samir Kaul:because we have the ability in private markets to change our bet midway through. Like, Jordi, if you and I had a bet on the Super Bowl and I said you can change your bet at halftime, you'd be a fool not to at least evaluate changing the bet. 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 we have to do pro rata to support the round. Other than that, we should be doing 3x pro rata and piling in money or a third pro rata and cooling our jets.

1:07:13Grant LaFontaine: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 a round 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 three to five X would be nice. But 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 it?

1:07:56Samir Kaul:I think that's between the angel investor and the founder. If an angel is removing money in a round, I'm coming in. Unless it's an angel investor I know who I feel like has deep pockets and shouldn't need the capital, it doesn't bother me much. It's a fine line when the founder sells. 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 a swing for a bigger fence right those are the things you have to kind of uh evaluate what's your founder is taking out 50

1:08:36Grant LaFontaine:what's your limit is it like you know it's like beyond 10 it's hard beyond 10 is unacceptable

1:08:41Samir Kaul:under any situation because you don't you to me it's like that five million dollar 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'd have, I would have to really understand what with hell was going on.

1:09:00Patrick Wendell: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, you don't always need. Yeah. Uh, yeah, there are plenty of different financial instruments for various moments in life, but yes, uh, that's 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.

1:09:21Samir Kaul:This was really fun. This was a lot of fun. Thanks, guys. We'll talk to you soon. Great to hang.

1:09:25Patrick Wendell: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, 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? What's happening? Glad to have you on the show. Long-time listener, first-time caller.

1:09:57Patrick Wendell: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. internally, but having a little lay of the land might be helpful.

1:10:16Samir Kaul:Yeah, absolutely. Have you guys had any Databricks folks? Oh, yeah. Any of the founding team yet?

1:10:20Patrick Wendell:Oh, yeah, yeah, yeah.

1:10:21Samir Kaul:Ollie. Yeah, I think twice.

1:10:23Patrick Wendell:But then we've also hung out with him a few times.

1:10:25Grant LaFontaine:To be honest, some of my favorite moments of podcasting have not actually been podcasting. We hung out with Ollie recently for like two hours. It was amazing. We were just all three of us ranting. Yeah. It was incredible.

1:10:41Samir Kaul:Awesome. Well, Ali and I are co-founders, so I'm one of the founding team. We left UC Berkeley. It was a research group. There was 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 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. You know, now it's evolved into like AI, basically just deep learning techniques. But, you know, today we we build data and AI infrastructure for a huge fraction of sort of the global 2000.

1:11:23Samir Kaul:You know, we have we have 20 ,000 customers, I think, as of our latest announcement. And we just basically help. Yeah, thank you. We 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. Sure. And, you know, we have more than 10 ,000 employees. 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.

1:12:06Patrick Wendell:Yeah. So take me through that journey.

1:12:08Grant LaFontaine:You're the guy the CFO comes to.

1:12:12Patrick Wendell:You're token maxing? Yeah, I'm the guy where he's like, what's this?

1:12:18Samir Kaul:Like, how do we project these costs?

1:12:19Patrick Wendell: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 ChatGPT 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 cloud codes and the codexes. What's been the journey inside of Databricks in terms of actually getting value, and how have you been measuring it?

1:13:03Patrick Wendell:Just walk me through some of the journey.

1:13:06Samir Kaul:Yeah, so the first product market fit in Gen.AI was these more personal chat type use cases. And that did translate into the business. A lot of the early AI companies, the foundation models built an enterprise version of their initial chat product. And it was somewhat useful. It could kind of 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 sort of 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.

1:13:49Samir Kaul: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.

1:14:13Grant LaFontaine:How do you talk about ROI with coding models to maybe other engineering leaders, your customers? And how do you talk about it with, for example, Databricks' CFO? right because a lot of people will will look every engineer will tell you like yes this thing makes me a lot more productive uh but at the same time people will try to dig down into the data and be like okay there's a lot more um 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 at the same uh at the same speed so how do you where how do you kind of like wrestle with that and prove roi month to month

1:14:57Samir Kaul: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. Now, 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. And none of those is independently perfect, but they can give you a sense in 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 size team.

1:15:37Samir Kaul:And then in certain teams where they've highly optimized it, they're 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 the beginning, we had the opposite problem. No one wanted to try the new stuff. I was going and bugging everyone. We tried it and we tried it and we tried it. And we never got to the token maxing kind of thing. But I do think that arrived out of an actually well-intentioned thing of just, like, trying to get people to try the new stuff.

1:16:10Samir Kaul: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 so we started seeing basically this 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 your revenue if left unchecked.

1:16:55So we actually hit a point where the costs were threatening to kind of reverse the purported

1:17:04Samir Kaul: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 around that time, I also talked to a bunch of other, 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.

1:17:39Samir Kaul: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 keeps costs, you know, constant or on a per head basis, roughly constant, even as we have more and more consumption.

1:17:56Patrick Wendell: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 trade-offs on the Pareto curve of different levels of intelligence at different costs. But there's an internal change management coaching that happens where 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.

1:18:39Patrick Wendell: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.

1:19:09Samir Kaul:So this is 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 tide. 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 cost. So those are our favorite type of changes because they don't require any user behavior change.

1:19:47Samir Kaul: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 a week or one every couple of 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.

1:20:28Samir Kaul: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 as 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.

1:20:55Grant LaFontaine:So 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?

1:21:05Samir Kaul:Ooh, 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, remains software engineering workloads. 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.

1:21:47Samir Kaul:and these AIs can just iterate on the software, 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. You know, they might be a knowledge worker that's, you know, 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.

1:22:24Samir Kaul: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 various products around that at Databricks. 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 a lot of other types of knowledge work job families, I think, can get a lot of productivity wins.

1:22:55Patrick Wendell: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 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 storyboarding or design exploration. Yeah.

1:23:27Samir Kaul:Totally.

1:23:27Patrick Wendell:I don't know. But on the coding side, what we did is we actually took a lot of these

1:23:32Samir Kaul: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. 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 we have this Unity AI gateway, which lets – and we have thousands of customers using that now.

1:23:56Grant LaFontaine:How do you see the routing market evolve over time? You have you guys, OpenRouter. There's a bunch of other companies. It sounds theoretically incredible to let there just be this absolute dogfight 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.

1:24:31Samir Kaul:Yeah, that's certainly our view. I mean, like, we've been pulled into this by our customers, actually, 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, 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 that area has no high fixed costs. You know, like just to do the routing itself, you don't need to buy a gazillion GPUs and you don't need to sort of have like a huge amount of capital expenditure.

1:25:14Samir Kaul:So it's a very asset light kind of business model when you're just doing this optimization on top.

1:25:20Patrick Wendell:Unless you accidentally use the God model to route the queries.

1:25:24Samir Kaul:Yeah, you 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.

1:25:34Grant LaFontaine: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 as you guys have this massive sales force, these deep integration, you know, deep relationships with many of the most important customers already. So, yeah.

1:25:56Samir Kaul: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 focused on making the models themselves. We're a lot unfocused on all the practical issues of using the models, 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.

1:26:18Grant LaFontaine:We've got to talk to the rest of the founding team.

1:26:21Patrick Wendell:Yeah, you've got to make a roundtable with everybody. I've 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.

1:26:31Grant LaFontaine:I keep one here just in the chamber. I honestly rarely drink it. I'm comforted knowing that it's there. And then maybe I'll drink one on the way home.

1:26:41Samir Kaul:Jordy, you kind of nurse it over there.

1:26:44Patrick Wendell:What you don't see is that before the show, I drink two to three Yerba Mates from Mataina, Andrew Huberman's podcast in a can. I also recommend those.

1:26:54Samir Kaul:Okay, so the Diet Cokes just keep things, they kind of just keep things moving.

1:26:57Patrick Wendell: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. All right. Well, thanks, guys. Thanks for having me, guys. Yeah, great to meet you.

1:27:10Grant LaFontaine:Let's do it again soon.

1:27:11Patrick Wendell: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.

1:27:18Grant LaFontaine:Now who should do that?

1:27:19Patrick Wendell:Data bricks. 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 to finish. We have a surprise guest. Surprise guest. We got a massive round. We got to warm up the gong. How are you doing? What happened? Tell us about it. Introduce yourself. Sorry. We're very excited. We have Grant from Whatnot. How are you doing? Hey, how's it going, you guys? We're doing well.

1:27:47Grant LaFontaine:Great to see you.

1:27:48Patrick Wendell:Great to see you. Give us the news. What happened?

1:27:50Samir Kaul:Good to be back.

1:27:52Grant LaFontaine:I guess the news, we just raised a series year round for$500 million.

1:28:01Grant LaFontaine:I couldn'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.

1:28:10Patrick Wendell:So what's driving the growth? Because this isn't an AI story. This isn't an AI build out 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?

1:28:29Samir Kaul: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.

1:28:52Patrick Wendell: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 uh you know a doug dumero on youtube where it's a whole company that's built on there's reliable stream of content happening what do the most mature whatnot creators look like do they have teams they have staffs have they raised money what does that side of the business look like

1:29:16Samir Kaul:yeah i'd say the most mature businesses um are sort of like medium-sized enterprises they may have anywhere between, you know, a couple of people working with them all the way up to 150 or 200 folks. They'll have pretty sophisticated logistics, sourcing, multiple streamers, and, you know, they're running a really legitimate operations.

1:29:38Patrick Wendell:And what's the shape of the content? In YouTube, there might be like series of formats, like Doug DeMuro 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?

1:30:00Samir Kaul: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, it's fun, is a seller called eFishco. And they sell fresh fish from San Diego. So they're 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 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.

1:30:32Patrick Wendell:Yeah, that makes a lot of sense.

1:30:34Grant LaFontaine: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 um we uh 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 uh 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 we didn't have this sort of like, well oiled machine yet.

1:31:18Grant LaFontaine: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? What is the guidance that Whatnot gives as a platform? Or what are you seeing working?

1:31:41Samir Kaul:Yeah, I mean, I think what works does span the spectrum. Sometimes the people who are starting these businesses are already used to creating content on social media, in which case they're 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 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.

1:32:13Samir Kaul:And then maybe for like bigger businesses, you're 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.

1:32:24Grant LaFontaine: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.

1:32:41Grant LaFontaine: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. you know how do you answer how have you answered that kind of question that i imagine you've gotten

1:33:00Patrick Wendell:at every single round to date um because you're now bigger than some of the public companies that

1:33:06Samir Kaul:zuck has cloned look for six and a half years we've always had competitors uh 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 going to be absolutely enormous. No matter what, we've grown every single year, basically at least doubled the business every year. And 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 the things better than any individual business who's doing a hundred different things.

1:33:44Patrick Wendell: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 the most mature whatnot content will look like in a decade? Is this going to turn into, I don't know, we've seen the Mr. Beastification of YouTube where he's basically creating game shows at a higher budget than what's on network television. But where do we go? Do we get soap operas like the original story of the soap opera was like soap companies went and created this whole genre uh how how cinematic is content going to get or is the is is raw authenticity something you see as like durable and going to stay around for a long time um i think look no

1:34:36Samir Kaul: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 is a trust-based decision so i think authenticity is 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 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.

1:35:15Samir Kaul: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.

1:35:29Grant LaFontaine:How do you think about where WhatNot 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?

1:35:59Samir Kaul:Yeah, I think the only thing we're really precious 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 what our customers wanted.

1:36:21Grant LaFontaine:What about streaming on smart TVs? I think most people are surprised when they realize how much streaming on YouTube is happening on televisions. I can imagine people putting whatnot on the TV and then being ready to buy just on their phone. Is that happening already? Am I off?

1:36:46Samir Kaul:No, I mean, a lot of people are Chromecasting on their TVs. We haven't built any native app yet. Definitely be on the roadmap at some point in the future. It's not on it now, but we know people do want to lean back. They watch with friends. And so it is sort of a natural median to do it well on a big screen.

1:37:02Grant LaFontaine:You don't think you could afford to make a native app yet?

1:37:06Samir Kaul:Well, look, it's always just about you need a deep amount of focus to do anything well. And there's about 100 different things that we can do. 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, improve 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.

1:37:45Patrick Wendell: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. Yeah, I basically am.

1:38:27Patrick Wendell:But how am I filling out a full live stream if I have a smaller product catalog is basically the question or a less visual product?

1:38:37Samir Kaul:yeah i mean i think so look i don't think diet coke's gonna be making live streams anytime soon okay um that that said we do see a lot of success from people who do have smaller uh product catalogs um and so a lot of it depends on can you make the show interesting yeah um as well as like there are a lot of people who come to whatnot and so you can still drive people into the show So, yeah, 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 SKUs. They're still successful in the mall because you have a bunch of people who are coming in.

1:39:13Samir Kaul:They're looking at it, discovering it. So that happens on whatnot as well. But, yeah, if you have one SKU, 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 to die at Coke store at the mall.

1:39:29Grant LaFontaine: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 SKUs 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 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.

1:40:10Grant LaFontaine:Flagship, yeah. But yeah, I saw a brand like True Classic that, you know, 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.

1:40:22Patrick Wendell:That's cool.

1:40:23Samir Kaul: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 the right one.

1:40:48Grant LaFontaine:But that would be 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.

1:40:56Patrick Wendell:And I think they have done like the world of Coca-Cola activations with the polar bears and the Santa Claus because they 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 whatnot amongst the creators?

1:41:38So I'd say the power law exists,

1:41:41Samir Kaul:but the monetization is an order of magnitude better than any existing platform because you don't need a ton of money. of audience. And so, um, there is a, 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 of times a week and had consistent products to sell, you would, you very easily do hundreds of thousands of dollars a year in sales.

1:42:12Patrick Wendell: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.

1:42:28Grant LaFontaine:Three figure YouTube entrepreneur.

1:42:30Patrick Wendell:Three figures. That was me in 2021.

1:42:32Samir Kaul:I was looking pretty recently at the sellers who earn over a million dollars a year at what? And 75 % of them get to a$500 ,000 run rate within 90 days.

1:42:47Grant LaFontaine:wow that's that is insane you look at you look at shopify is 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 it's fantastic if you didn't get 50 sales in your first show you'd probably be

1:43:07Samir Kaul:doing it wrong on whatnot is there you guys explicit you guys explicitly like if you yeah Since people know you. But even like many early shows have lots and lots of sales and they'll make thousands of dollars.

1:43:20Grant LaFontaine: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?

1:43:31Samir Kaul: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 uh seattle and then we have a bunch of

1:43:49Patrick Wendell:overseas offices very cool yeah we got a bunch of good ideas in the chat everything from a coke factory tour to tbp and merch and whatnot i think we should sell game drank diet cokes just the

1:44:03Grant LaFontaine:empty cans empty cans sign i don't think anyone wants that it's gross i'm i'm thinking they'd go for at least five bucks.

1:44:10Patrick Wendell:Maybe, maybe.

1:44:11Grant LaFontaine:We'll figure it out. Great to catch up. Congratulations. Amazing progress.

1:44:14Patrick Wendell:Thank you so much for coming on the show. Thanks so much for having me on the show, guys. Have a great rest of your day. Have a great weekend. We'll talk to you later. Goodbye. Steve Aoki, big winner in whatnot. He was a Series A angel in that company. Yep.

1:44:27Grant LaFontaine:Absolute dog.

1:44:28Patrick Wendell:Absolute dog.

1:44:29Grant LaFontaine:Absolute dog. Also, Y Combinator Company,

1:44:32Patrick Wendell:Winter 20, went through, right? I think winners at the end, maybe at the beginning. So maybe COVID company. fascinating business. Anyway, thank you for tuning in to TVPN on this Friday. Jordi, is there anything else in the timeline that you want to cover before we get out of here? Is there anything key?

1:44:49Grant LaFontaine:Very niche post from Alad Gil. 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 root if someone frees time.

1:45:03Patrick Wendell: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 with one another using this sort of neural ease uh to to communicate but very funny post only 25 likes go

1:45:21Grant LaFontaine:like it and a more fun post yeah before we head out for the weekend sean frank we were talking about yesterday baseball caps with tin foil uh hidden on the inside um 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 got

1:45:47Patrick Wendell:to keep going uh 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 deca-billionaire.

1:46:13Grant LaFontaine:My takeaway, everyone when they turn 54 should go to Russia, acquire four riverboats.

1:46:20Patrick Wendell:The implication that he went to Russia and didn't start there. is particularly hilarious. I mean, it's not a...

1:46:27Grant LaFontaine:It's never too late. It sounds like a... Is that not a Norwegian name?

1:46:32Patrick Wendell:Yeah, maybe. He did work in the cruise industry for 23 years before founding this company. People are calling the Jeff...

1:46:38Grant LaFontaine:Yeah, he went to the Norwegian Institute of Technology. He 100 % went to Russia with his last 200 bucks, bought four riverboats, and then ran it up to 25 billion.

1:46:49Patrick Wendell:So you're calling him a Nepo cruise? No, I'm not calling him a Nepo.

1:46:53Grant LaFontaine:I think he went to Russia with his last 200 bucks. He bought four river boats and he ran it up.

1:46:59Patrick Wendell: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 cruise industry. Anyway.

1:47:15Grant LaFontaine: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

1:47:27Patrick Wendell:NASDAQ's up 1.14 % I mean the big market news Is that the Jobs data came back weak The US economy lost 23 ,000 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

1:47:55Grant LaFontaine:and to close out the show round of applause for Satya and the Microsoft team up a cool 29 % in the last month headed back to 4 trillion great news

1:48:12Patrick Wendell:we'd love to see it congratulations to everyone over there on the Microsoft team they needed a win

1:48:18Grant LaFontaine:folks it's been an honor and a privilege to podcast for you this week yes and i can't wait

1:48:23Patrick Wendell:for next week wait is there something else ben no you're good okay we'll be back in the ultradome we're gonna have a lot of coverage this weekend too around uh our new some of our new uh initiatives

1:48:35Grant LaFontaine:getty you may have been seeing some of our getty images yeah you might be seeing some more yeah

1:48:40Patrick Wendell:we're working on it we'll see but have a great weekend we'll see you monday see you monday Leave us five stars on Apple Podcasts and Spotify. Sign up for a newsletter at BPN.com. Goodbye.