Leopold's 13F, Data Center Fixes, Shein Buys Everlane | Mike Isaac, Rowan Trollope, Dean Leitersdorf, Joanna Stern

24:38Mike Isaac:That doesn't mean they're being used, right? Because people will sell their water rights to like a neighboring property that is. Yeah. Yeah. And so my question is like, it sounds like they sold the water rights previously, or they had some sort of deal to send the water that they were getting out of the desert, which I can't imagine produces that much water, but I guess it does use it for like agricultural purposes. Like what were they growing? Well, agricultural could mean you have some, like you have some cattle, like there's a, there's a bunch of different potential meanings for that. It doesn't mean you're growing fresh produce, but were they actively using it?

25:13Were they just like no that's the other thing that's the other thing too it could have been agricultural land yeah but not could have been like a failed farm it's not farming anymore like a former livestock uh like uh farm something like that but i don't know i feel like people are going to want to go a click deeper on that like he rebuts a lot of the good the good rhetoric like but uh there's still like another another layer there he says the water could be used on mungiri

25:43yes influencers are protesting in the flats outside of amangiri drain the pool at amangiri it's it's gonna be uh it's gonna be a big protest gonna be over uh well uh yeah i mean these these points like as you said i think are going to be hard to break through just because ai is so deeply unpopular for a variety of reasons uh and we should watch the video of eric schmidt uh getting booed on stage at University of Arizona. Alex Kantrowitz played a video here. I don't know if we need to watch all this, but he says this is incredible. Artificial intelligence getting booed out of the stadium in any commencement speech it's mentioned in, maybe telling college students AI was taking their jobs, wasn't the best strategy.

26:26Let's watch this clip. The architects of artificial intelligence. Interesting.

26:35Mike Isaac:The question is whether you will help shape artificial intelligence. We do not know. We do not know the precise contours of what this... If you'd let me make this point, please. Step one. If you're giving a commensum speech, you've got to bring a soundboard. Yeah, I'd be like AI. Yeah, it's not that bad. But also I hear you

27:07They're really going crazy We thought that we were adding stones to a cathedral of knowledge

27:14Mike Isaac:that humanity had been constructing for centuries. There's just a low-level boo the whole time. It's so rowdy. Like, normally you'd think there'd be like a little bit of boo, and then they'd just like get quiet down. Okay, this is about to turn into a riot. This is crazy. Did he just bail on this thing? No. At this point, I mean, you got to go off script. You can't stay in a script. It is funny that if you cut it up in the right way, you could make it seem sound like the most evil. He's like, you will surrender your agency. Okay, now we need to take this clip, do that thing where we... Ray says he's lucky they didn't flashbang it.

27:56Mike Isaac:True. We need to do that thing where we take out the booze and just leave his words and then add cheers. So it's just the same exact speech, but everyone's just like, yes, this is amazing. I can try to find it, but there's a video of him after the speech, like getting mobbed by students. They're all like yelling at him. Yeah, they were not fans. Wow. This is rough, rough, rough. Yeah, not good. I mean, the big thing is like, I don't know that that is, like everyone is booing for a slightly different reason, But it's like this ensemble of problems and grievances with AI generally. One thing that I've been frustrated about is everyone is vibe coding 24-7, leaving MacBooks open, talking about productivity.

28:49And yet the magical moments, the consumer technology has been completely left behind. There was a time when we got the cloud. We were building a lot of data centers, but every year you'd get like a cool new thing like Yelp would come out and it was like it wasn't changing the world, but it was like oh, you could find a cool new restaurant and maybe like or Groupon like Groupon was like not a great business ultimately but like for the first couple months of Groupon you could like go try a restaurant for like half price and it just felt like Magical or like uber when that came out. It was like wait I can go out and and the car will be right outside instead of having to like call a phone call a taxi cab service maybe it comes maybe it doesn't stand outside in the cold try and flag a

29:32Mike Isaac:car there were all these things they were i'm just i'm just thinking that do you think they were uh do you think they were like angry at usage nano banana usage limit probably probably is that yeah is this whole thing just a misunderstanding they might think we're in a plateau and they might just be upset with the lack of progress outside of coding domains they say yeah the writing is just still not that good on any of these models. I can clock it. Yeah. It's still clockable. Yeah. Yeah. At first I thought they were mad that, uh, like at Google, Eric's minute was, he was doing too many, you know, stock buybacks instead of investing too much cash technology.

30:08Yeah. Yeah. Having a hundred billion on the balance sheet and cash is just unacceptable. Yes. You get Waymo. Yes. You get deep mind.

30:14Mike Isaac:Yeah. Cause it just says they don't know what to do with the money. Yeah. Yeah. They weren't innovating for a long time. And that makes a lot of sense That's why you would boo them. Sort of the Tealian. The Tealian boo. No. And then also, like, yeah, the jobs thing is super real. Like, whether or not AI is affecting the jobs. It's also, so we should pull up Lulu's critique, because I'm sure it'll be way better than this. But just in those handful of sentences, like is that that felt like a speech more potentially like oriented towards maybe like the Stanford student body which is like how are you going to contribute to AI that's what I was like sort of that's that's what was standing out to me yeah being like don't be afraid of this thing like jump in yeah and help shape it yeah and if you're maybe someone in Stanford yeah and you have the opportunity to go actually be involved and you're at the epicenter of all this progress, maybe that would land.

31:20Yeah.

31:20Mike Isaac:But at U of A where people are hearing like, hey, all the different career paths that I'm thinking about. I would prefer, in terms of commencement speaker, I would prefer someone like a Sam Sulek to give the commencement speech. That would be like my, like Eric Schmidt is like, he's kind of like a, meh. Sam Sulek, that's an inspirational speaker. That's going to fire me. He's on the come up. Exactly. Yeah. Did you have a question? Derek, more plates, more dates. That would be fantastic too. Yeah. I was trying to, Gabe's asking about the, why would he give a speech there? I was trying to find a connection.

31:54Mike Isaac:I think he's just a big name. Okay. And it's very, obviously his experience is very relevant in this moment. Show up to Mog and none of you are getting any jobs. It's just terrible. Yeah. No, no. I mean, there is this thing where like AI needs to create jobs because like, even if AI isn't destroying the jobs. If we have a weak economy, there won't be good jobs. And then you're still held accountable for that. And so you've got to create jobs. And then on the data center side, there's just so many issues within that that we can go through. Environmental impacts, which are probably real. If you burn a bunch of fossil fuels, you're going to have negative externalities.

32:30Diesel generators, these things are smoky. The air quality, all of this stuff is fairly real when done improperly, which is happening the water use thing mostly fake but still like needs to actually be walked through fully uh and digested by the public uh the noise issue which is solvable but still like not that great uh and then a bunch of other issues that are just not going to happen happen magically ben thompson had a wild wild proposal he he had a great uh great piece which uh i wish we had time to read through the whole thing but um we we can sort of run through it so uh he starts with an anecdote from Politico.

33:11A Texas county southwest of Dallas this week passed what may be the state's first county-level moratorium on data centers. Not what everyone was expecting in the free state of Texas. Everything's bigger in Texas, except for the data centers, which are getting smaller now that there is a county-level moratorium, seeking to buy time for lawmakers to soften the blow of development sweeping across rural areas. What's the county? Hill County's commissioner court voted three to two Tuesday to put a year-long moratorium on data center and power plant construction in unincorporated areas, citing an influx of as many as eight data centers planned there, many of which could have their own power plants.

33:55Opposition to data centers is spreading in regions led by both Democrats and Republicans as politicians try to balance economic development.

34:03Mike Isaac:Yes, apparently, according to AI, there's no official public count of operating data centers in Hill County, but there's eight proposed or planned data centers. So this is a place that... They're going to be delayed. Yeah. In Missouri, one small town, unhappy over its city council's approval of data centers, voted last month to oust all four incumbents running for re-election. In North Carolina, Governor Josh Stein has made a point of saying that sales tax exemptions for data centers cost the state up to$57 million per year. Texas has hundreds of data center locations operating or in development, second only to Virginia.

34:43Among U.S. states, the growth has stirred pushback from environmentalists and rural residents who worry about the effect on water supplies, the electric grid, or their quality of life. Officials in states across the country are starting to have second thoughts about data centers, and some are looking to roll back tax incentives. And Ben Thompson says, I chose this story because it happened to have happened over the weekend. In truth, there are an exploding number of options, including one just up the highway from where Ben Thompson lives in Wisconsin in DeForest. And they are hardly isolated sentiments.

35:18Seven in 10 Americans oppose constructing data centers for artificial intelligence in their local areas, including nearly half, 48%, who are strongly opposed. barely a quarter favored these projects with 7 % stronger in favor. Now, I was thinking about what do Americans want to build because it's easy to look at the data center stuff and be like, well, everyone's against building data centers but I do think that there's an element of like, Americans don't want to build anything. I was reflecting on the whole re-industrialization meme this weekend. I got a version of that sweater mailed to me that I picked up.

35:56And, uh, and I was thinking about the actual knock-on effects of re-industrialization.

36:01Mike Isaac:Like most people don't want a car factory in their town, but we do want new roads. Well, not necessarily new roads. No, people don't want new roads and they don't even want the roads paved because they're like, I'll just buy a bigger car. Like, I don't know. You want a bunch of people dying next to you. I don't think people want hospitals. I, I literally golf courses, They have poisons. They're bad for your health. Like, I actually think people just don't really want change necessarily. They don't want things built broadly. Like, data centers are probably at the bottom of the list. Like, they're the least popular.

36:35But they're, like, high-speed rail. I thought that would be popular. It was not popular. And, like, I'm just going down the list of, like, oh, like, you want, like, oh, we need, maybe you're a national defense person. You want a missile factory next to you blowing up bombs? Like, no. No one wants that. Like, what do we want? Like we don't really want anything. We're kind of good on building in America. I don't know. I just think we're good. Like, we're just like, we're fine. It's good. Don't change anything. No new trains, no new roads.

37:04Mike Isaac:Yeah, I think when there's self-interest, right? When people want to build their house. Yeah. Right? When people want to create their new restaurant. Everyone wants to build their data center. Yeah, their data center for sure. But people don't want other stuff built generally. Like there's very, very few things that people are like, yeah, I'd be down for that to be built. People like the status quo. They're happy with things as they are, and they don't like change. So, like, anything new is going to be, like, somewhat unpopular, as nuclear power was. Not building out nuclear power 50 years ago was, of course.

37:36One of the greatest mistakes humanity has made, and one that contributes directly to data center opposition today, giving questions about the impact on energy bills. Also interesting, we have to do this another time, but, you know, did we run out of nuclear scientists? was that what stopped the build out? Did we not have enough geniuses? I don't know. Maybe. We'll dig into it. But Ben Thompson has an interesting solution. He points out a bunch of ways to fix the problems of data center construction and opposition. He says, first, this is obvious.

38:07Mike Isaac:People are saying homes in the chat, but then again, people don't really want more homes in their area once they already own a home. They block them all the time. They block home construction all the time. And also permitting and also expansion of existing homes. Like these things, I'm not saying that they're like as unpopular as data centers. No way. Data centers are at the bottom. But homes are something, maybe in the abstract, but like new housing in communities is like razor's edge, 50-50, 60-40. Like there is a lot of opposition to building just in America, broadly. Like that's just the nature of our society.

38:45So Ben Thompson has some solutions though. What do you got to do to build a data center properly? He says, First, this sounds obvious, but tech needs to fix its messaging problem, the issue, and if an answer seems obvious, then there surely must be some other problem at play is threefold. First, a good number of people in tech, particularly at one of the leading labs, genuinely believe most jobs are going away. They could lie more effectively, but beyond being dishonest, it's also a betrayal of the fanatical devotion with which they are pursuing AI despite obstacles, including the challenge of spending billions and billions of dollars on models that are obsolete in months, if not weeks.

39:19Second, it is extremely hard to describe the benefits of inventions not yet made. Cures not yet discovered, economic activity not yet engaged in, etc. This is always the burden of those arguing in favor of progress, and the sheer potential of AI actually makes the problem even harder. 50 years ago, everyone was like, electricity isn't that expensive. Why do we need to build nuclear power plants? They're scary. And now electricity is expensive, and we're like, oh, we should have built those. That's the way these things always go. Now, third, tech is and always has been terrible at understanding and relating to the rest of society.

39:53I go back to how Silicon Valley was extremely skeptical of Facebook, a company predicated on connecting with friends and family precisely because it's filled with people running away from their friends and family. You can optimistically say that people in tech live in the future. You can also more cynically say they live in opposition to and denial of humanity for better, and in this case, for worse. Second, tech could control the misinformation. TikTok is a major point of this. He talks about how the algorithm is still controlled by the Chinese and maybe there's misinformation there. Second, in a rather ironic twist, Meta has learned the lesson of trying to control misinformation, doesn't want to overtly censor, but now the company gets no credit for not censoring misinformation about data centers.

40:41And so it's like this weird thing. And then third, this was a wild card, which I didn't think of, but X is the social media platform X and Twitter, formerly Twitter, is actually incentivized to be anti-data center in a weird way because X is owned by SpaceX. And a big part of SpaceX's upcoming public offering is the possibility of building data centers in space. This is like total tinfoil hat, I think, but it's an interesting like, okay. And he says, to be clear, he hasn't seen any evidence of thumb on the scale or not. I certainly haven't. But part of the problem, though, is that we would never know if there were.

41:18And so he goes on to propose something very, very bold, very, very bold. He says, instead, the most obvious solution is the most crass. Simply start giving people money, not universal basic income, though. If data centers are a resource for our AI future, then start paying people for that resource. If that data center up the road weren't sold to my neighbors based on amorphous tax benefits that my local government may or may not spend appropriately. I was talking to Tyler about this earlier, but rather were to result in a check in the mailbox every year. I suspect you could get a lot of people on board.

41:51So he put some numbers together and he says, for the data center up the road, it was expected to be 1.6 gigawatts, which could generate around$3 billion in annual operator revenue. DeForest, the village it was to be built in, has around 11 ,500 people. So you could pay every person in that village$10 ,000 a year, and it would only equate to 3.8 % of annual revenue grossed by the data center. And he says, I bet that that proposal would have been approved, and I bet the operator could very easily pass on those costs to actual data center users. It also highlights how relatively pathetic the original commitment that I think the data center said, hey, we'll give you$50 million, which is like nowhere near.

42:38what that math works out to. So data centers come into town, you get to vote for it, but the data center company says, hey, we'd like you to vote for this and we will give you a$10 ,000 check in the mail every year forever while we're operating this. And that seems like that could actually get people on board. So this is ridiculous.

42:58Mike Isaac:This goes back to even months ago at this point, we were saying, you know, AI is not like a, you know, natural resource where you benefit from having it in your backyard, right? If you're just an everyday AI user, you do not care where the data center is at all. And so if someone is coming to put it in your community, it's pretty fair to want to benefit from that in some way. And like a direct payment like that, I think, I'm sure that will happen more. Yeah, yeah. And what I was talking to Tyler about was, do local communities feel a difference between$10 ,000 in the mail directly to them or$10 ,000 to their local government that says, we're going to use this to build roads and hospitals and all the different things that we do?

43:50I think that on net, the average American is a little bit skeptical about dollars going to the government actually benefiting them at a one-to-one ratio. They definitely think that if the money that goes in is worth something, but a lot of it gets mixed around and there's delays.

44:07Mike Isaac:Yeah, and the data center is already going to generate a bunch of local tax revenues for that local government. Show me the money. Show me the money. That's what the locals should potentially be saying. That's what I'm saying. I think it's totally fair for the local population to think, okay, this big infrastructure project is happening in my town, even if I'm not going to work there. yeah it's going to generate some taxes or to help improve our community but show give me the money basically give me the money go direct yeah go go direct with the money i like it well we have mike isaac from the new york times in the waiting room uh we can come back to our data center debate after we check in with mike and i think he's on location is this correct mike where are you welcome to the show how are you doing i'm good can you hear me i'm sorry i'm literally outside of the courtroom amazing no we can hear and see you just fine that's amazing well take us through it my actual how has today been going what's happened uh it was crazy uh basically today was supposed to be the first day of jury deliberations and And we were a few reporters in the courtroom because in the morning it was about both sides presenting their case for remedies to the judge on basically how much money, if anything, would be dispersed as a result of the lawsuit.

45:33And literally in the middle of this deliberation, the clerk goes and interrupts the judge and says, hey, something's happening, basically the scurrying. And everyone's like, oh, my God, what's happening? And this is like less than two hours into it. um they reach a verdict and so the jury comes back in and and delivers the verdict interesting

45:56Mike Isaac:what was your expectation going into today did you think you'd be hanging out at the courthouse all week all right bill yeah yeah i'll see you soon sorry that's a lead opening eye council walking by that i should go run after but he's doing his thing i mean we're just hanging out we're just hanging out if you want to go chase him down i'll bug him later that's very literally he was just chilling and walking out um i uh sorry i can't see without these i uh uh i forgot what you i'm so tired what did you ask me yeah i was i was what was your expectation for your week were you expecting to be at the courthouse every day yeah we were like i got here again at 6 a.m and like was ready for a long like sitting out in front of the court for days because the way these work is like you get 10 minutes notice uh from when the judge gets the jury verdict to get down here i live 10 minutes away but still like no uh reassurances so we had me my colleague kade metz and then natalie roca another colleague of mine just like ready and i was just like thank god when they came when they came back i didn't want to sleep out here okay so So the actual verdict, it feels like victory on a technicality.

47:13And what I'm interested in is that over the last few weeks, it feels like the core discussion or the talking point was Elon Musk, you can't steal a charity. Very pithy phrase, easily memorizable, could stick with you or could bounce right off you. But you know what his grievance is. And then OpenAI sort of needs to say, well, the charity still exists. And we had an agreement that we would go this way. And it was a little bit more complicated. But that doesn't seem like what the jury actually decided based on. And was that like, as you think back to the last three weeks, do you think that there were that there were actually good seeds planted around the statute of limitations and when the case should be filed?

47:59because it feels like from the reporting and from the viral, you know, the screenshots and the emails and the quotes, like there was never like, oh, yeah, we all remember the smoking gun of Statue of Limitations. No, I don't. I remember the You Can't Steal a Charity or the Rockman Diary, right? And it feels like we got a different outcome here.

48:19Mike Isaac:I think I remember at different points, like this whole debacle only became a thing after the launch of ChatGPT. and after the company was showing massive traction and revenue growth. But I never heard specifically, like you said, this statute of limitations. Yeah, but how did you process it? Well, that's a wonkier point too, right? It's very easy to, and that's what I think really the strategy on the must side was, was to go for really clearly digestible talking points for a juror who may not be steeped in nonprofit contract law or statute of limitations and exactly what that is. And I think that's what they were betting on, too.

49:05They're like, all right, if we can sell the jurors on this idea that Musk is selflessly trying to interrupt something that could be bad for the world versus OpenAI's more technical point of, look, you should have filed this lawsuit years ago. Maybe they can win it. And so I think that was going into it, what everyone was kind of thinking about, like, is this going to be certainly what I was thinking about? Is this going to be a battle of like the billionaires who you trust? You know, it's like a character thing that is a referendum on that. And exactly what you said. It's super surprising when they came back.

49:42And essentially, I would say Statue of the Limitations was like if that was that was the ballgame. Right. And if they had flown past that, if they had not find them the burden to be met, then we would have seen how it really played out. But that was just that was the whole thing. You know what?

50:00Mike Isaac:So so last week I was surprised that that Elon jumped on the China trip with with Trump. Oh, yeah. Was there been some? Yeah, that that something. I mean, a lot of the people online were just like, he's a billionaire. He can do whatever he wants. That was like the president supersedes the federal judge. Yeah, I don't know if that's actually the case. But there was some dialogue around like, hey, you're in the middle of this historic trial. Like, you should be present. Yeah. Or at least able to be present. Did that. Do you think he did that because he felt like it wasn't going his way and he was just like, I need to make the most of my time?

50:40I think he. So. So, yeah. NBC wrote a good story on that. Like, he was not excused. He could have been recalled and asked to testify again. Uh, and it's typically bad form when you leave the country to do when that happens. Um, and, uh, so what I was told or what I heard is that they had actually spoken to the judge beforehand to like, make sure it was like, okay. And like that he probably wouldn't really recall. I think part of it also was that both sides were both sides are on a clock. So you only have so much time to, to present your evidence. and the early testimony was running long. So opening eyes still needed to get through a lot of the testimony of their expert witnesses towards the end.

51:29So they decided, and Musk's side also decided they weren't going to recall Musk. So like there was that part of it that probably made it okay. That said, like it's probably a bad look when you make it the first three days of the trial and Sam and Greg make it basically most of the time. but uh but at the same time like it didn't come down to character who pissed off the judge necessarily it came down to like a legal technical argument which seems to have this jury was pretty sophisticated at least in like focusing on something that i didn't know if it was going to land or not yeah did uh it i mean it really makes all of the like the the the ai safety testimony feel like maybe a miscalculation because it sort of took the conversation in a completely different place and then they got focused on this like technical issue um i mean the jury doesn't put out like a statement are we are we expecting any sort of like closing statement from the judge or is this what we get here we so by the way sorry there's still like people protesting in the background.

52:40I can see that. But on my very terrible laptop camera. Are they protesting the Statue of Limitations because they're on Elon's side? Actually, this has been the best part of this. There's many different protest camps and it's kind of hard to define who is against what.

52:57Mike Isaac:Are any of the protesters protesting other protesters? I mean, genuinely, yes, probably. There's the... Yeah, the yack is out there protesting the decels. genuinely there there were a supporter no 100 yeah um so actually usually post trial you people like me go and try to find the jury and chase it down which is what we were doing i think they probably are already out of the building um i ran around the back and saw a van that was like all blacked out and this marshal that i had known the whole trial and like they were just like getting the hell out of here so i'm guessing they didn't want to get mobbed by us but uh the judge i'm going to try to get the notes out the judge left the jury with like a pretty good summation not of the trial but just like appreciating a jury and like respecting a jury finding like finding uh parties liable or not liable you know and and i think that the point of that was she didn't, she, some federal judges could like be like, no, I'm throwing your verdict out or whatever, but she respected the jury with the jury of their peers and they were deliberate, you know, and they listened intently.

54:10And so she left them, I'll find the exact quote and send it to you guys, but she left them on sort of like, uh, we thank you for your service. Yeah. Yeah. That seemed also a little bit unexpected because, uh, that when, when the jury verdict became, you know popularized or publicized as as like advisory a lot of people were sort of interpreting that as well like it doesn't matter at all in that case but it seems like the judge did wind up sort of uh you know giving the jury a lot of weight and very quickly reacting to the jury's verdict and i think that's a that's really important as far as appeals go because you could argue um bias charge cut out like you could argue like oh the the yeah exactly the judge didn't care the jury so i think there's real incentive to be in line yeah yeah that's very interesting uh what was the snack set up today are you going to get a proper lunch now i feel like my god i i feel like that was one of the most disappointing arcs if i'm going to be completely honest with you the lunch game just didn't seem to evolve you were saying that you weren't learning from your

55:17Mike Isaac:lessons and all for you where you've got you know the nathan for you episode where he's got the chili suit we were gonna do that for you because it just felt like the day okay day three you show up with an apple and a banana it's like okay he's still learning his lesson but like fool me seven times i was expecting a chipotle burrito or something with a little more substance get into of the four digits of calories, please. People were like DMing me saying I have like scurvy or rickets by the end of this trial. I think I just have like a really disturbing diet overall. So yeah. And today I forgot I was out last night until way late at a show and I'm hung over and I forgot to bring food.

56:01So it's just, this is basically my, you get to see my slow descent into madness, but thank God we're done. Okay. So, I mean, we asked you earlier, is this the stuff of movies? Is there going to be a movie about this or was this anticlimactic? I think the movie is still going, man. This thing is still... There's so much. I feel like this is an exciting time in AI because OpenAI is really on its back foot in a lot of ways. This gives them some relief in the many fronts that they're being attacked on, whether it's going public this year with a messy balance sheet or Anthropik coming after them, Google coming after them, Google IOS tomorrow.

56:43so like if anything it's a brief reprieve you know but uh i wouldn't i wouldn't make the movie now i'd wait a wait a couple of years okay okay uh anything else jordy the story continues story

56:56Mike Isaac:i'm expecting to see uh model wise around san francisco that say i bought this after elon lost his landmark trial against open ai yes the bumper sticker new bumper sticker Hang on. Well, have a great rest of your day. Thank you so much for taking the time. We'll talk soon, Mike. Great to see you. Next time. We'll talk to you soon. So Mark Cuban has another proposal for how to deal with data centers and internalize all those negative externalities. He says we should tax tokens federally at the provider level. Tyler, you're going to have to interpret what this would mean in all the ways that companies would wind up getting around this with maybe less robust answers, potentially.

57:47But he says, not a lot, less than 50 cents per million tokens. It will accomplish four things at least. It will push the big AI players to optimize tokenization, caching, routing, and localization, which will reduce energy usage, saving them in energy costs more than what they paid in tax and reducing strain created by the growth and energy consumption, which will generate maybe$10 billion a year to start, but over the next 10 years could grow 30x to 100x. So he's thinking two orders of magnitude in a decade in terms of growth for AI. That's low end of what a lot of people think. And then four, create a source of funding to pay down the federal debt or deploy in response to the things AI brings that we don't expect or don't like.

58:36At some point, the models will pass it on to consumers. Of course, that's okay. Consumers will have the ability to choose between providers or to do everything using open source models locally, which I guess wouldn't be taxed. What do you think? This is kind of like the opposite of what we were saying before, of like going direct, right? Because we were saying, okay, you know, the actual data centers are going to make so much revenue. You can just tax the data centers, and then the money goes to the local community, and then that's where you see the benefits. But isn't this going up the chain even more?

59:04So you're taxing the companies. Then people in the community definitely won't. The money will be so abstract if it's at the federal level. I feel like this is the wrong way. Here's something else. You should get a check from OpenAanthropic every month maybe. That's, I think, the better version of his if you want to tax the company.

59:20Mike Isaac:What if we tax companies? What if we had something like a sales tax? Profit. What if when income tax? Yeah. Like if someone, when someone paid, what if some of that money went to the government to help pay for public services? And maybe even if a company is doing really, really well, then you could take a percentage of their profits. Yeah. Because that company has an incentive. And if the investors sold their stakes, they would pay a tax on whatever game. And then every single, what about every single underlying vendor that the company, you had the same sort of like structure for every underlying company.

1:00:02So like if NVIDIA sells a bunch of GPUs and they make a bunch of money, they'd have to tax on the profits on that.

1:00:06Mike Isaac:Yeah. Or even somebody like a contractor that, you know, manages a building. Sure. Right. So they have a, you know, maybe it's a small local business. Yep. They manage an office space. Make a million dollars. Some of that. The costs are only half a million. Yeah. That half a million profit, that gets taxed. Has anyone thought of that? That might work. Anyway. And then you could use that money to sort of cover the costs of operating the government and then even potentially use some of the extra to pay down the debt. Potentially. Well, Palmer Luckey is going back and forth with Mark Cuban about this.

1:00:35Palmer Luckey says, there are already massive economic incentives to optimize. So this is just a tax on American companies that makes foreign models and products more attractive, along with creating the infrastructure for government to track all AI usage and punish anyone who doesn't report. Mark Cuban says those incentives change over time. Right now the incentive is to grow and spend market share over optimization, you know this. Do you think the marginal cost of some BIPs on a token is going to make those buyers choose differently or do you think the models are just a commodity and price is the only differentiation space and then the question mark every time, you know it's not AI.

1:01:14And the tax would only be on what providers sell, not open source models, not local, not internal, and what foreign models are you referring to? Palmer, Mark, you are essentially making an argument for central planning. The burden is on you to show you where it's worked before. No quotas, no mandates, just good old capitalism and competition. Palmer says, this is obviously not capitalism or competition by any reasonable definition. It is a tax that specifically disadvantages one type of AI business to the benefit of others, artificially propping up their business models. And my business is one of the ones that would benefit because he's not token heavy.

1:01:44That is an interesting take.

1:01:45Mike Isaac:Semi-analysis says 50 cents per MTOK is a lot of money marker. Are you considering considered cash hit on pre-fill or just output tokens? These are the hard questions. Steven says, imagine a bit tax in 1995. Yes. Flops tax. I don't know. What else is going on in the AI slop world? The bot farms. What about every time you, how about this? What about every time you move your cursor? It's just one cent. Right? Yeah. I don't know. Tax on something. It's pretty funny. I was saying last week when I was saying like, you're basically reinventing the U.S. Postal Service. Yeah. A lot of people were messaging me saying, you know, people, you know, this exists already.

1:02:32Mike Isaac:It's like, man, it's tough when the sarcasm doesn't break through. Well, the bot farms have figured out anti-AI, anti-data center posts on Facebook are good for engagement. But ironically, they're using AI slop to do it. You don't know this is AI slop. This might be the most perfectly designed set of stones ever visited upon a beach. It's not worth giving up an inch of this to a data center, Indiana. Breaking. An Indiana resident reportedly arranged stones to make an anti-data center message. This is 99 % slop. And this one is really sloppy. Wow. Wisconsin's forest farms, lakes, rivers, small towns.

1:03:16Not a single square inch of Wisconsin is worth giving up for an AI data center. Interesting that the I and is is capitalized. Makes me think that that was added after the fact. But the rest is pretty sloppy, but kind of beautiful. I kind of like the perspective on this image with the big farm and the barn in the background. This makes me want to visit Wisconsin. Yeah, does Wisconsin actually look like this? If it does, perfect place to build a data center.

1:03:45Mike Isaac:yeah that's the only thing that's missing uh well no i want yeah we have to go and find we have to go find the the the the ugliest 10 000 acres in wisconsin new challenge tyler well uh we gotta we gotta cover uh everlane we gotta cover everlane there was a big just to close out should we should we should we cover this post from ken griffin that was going around i i i I want to cover this, but the trick is that this is a Ken Griffin clip. So basically he pivoted on AI three months ago. He was saying, it's not really useful. The reports that we get from AI models are not actually relevant to our business.

1:04:24And now he's saying, for us at Citadel, it's allowed us to unleash a much broader array of use cases. It's been really interesting to watch. Work that we would usually do with people with masters or PhDs in finance over the course of weeks or months is being done by AI agents over the course of hours or days. And it's seen as sort of a blackpilling moment because he says, like, I got home and I was sort of, I got to tell you, I went home one Friday, barely depressed by this because you could see how this was going to have such a dramatic impact on society. And it is like a weird moment and it's sort of like, oh, okay, he's waking up.

1:05:00But then if you actually watch the full interview, this is one minute from a 40-minute interview or something, And he goes on to enumerate a whole bunch of different benefits and where he is allocating his workforce. And also Citadel is in a very interesting game theoretic dynamic where it's not, they are not a monopolist. So by definition, like they are in competition with all their other funds. And so there is a world where, like, even if they're getting incredible value out of AI, they wind up using AI and humans in conjunction to compete because we are in, like, the centaur era, which is sort of what he enumerates.

1:05:39But anyway, did you have a take away from this?

1:05:42Mike Isaac:One thought I had is that, you know, Citadel has, you know. AI psychosis. That's what you're saying. No, they have a team of thousands of, you know, PhD level talent that are doing things that AI can do pretty well now. And him driving home on a Friday, being depressed. Part of me was thinking, is he depressed because he realizes everyone will soon have access to a thousand people with PhD level talent that they can turn on? And maybe they can't cover the whole market. And obviously, you know, he talked a lot about, you know, how much software there is to build. He's like, we'll never build enough software.

1:06:23Mike Isaac:But at the same time, he was thinking like, wow, this, this like resource that I've accumulated, this like capability, this like this, this team, when AI can do what they do and everyone can access AI, like how is my business going to change? Yeah. So funny reflecting on the time I worked at Citadel and my job was basically to copy and paste cells in an Excel spreadsheet. And so I wrote a visual basic script to sort of just do it for me. And then I was able to just like have seven hours of free time every day. And I wound up being able to do a lot of other stuff. And it was a story of automation.

1:07:02And I can tell you at least back in 2011, I spent the summer over there as an intern. There was a lot of stuff you could automate for sure. A lot of stuff in the back office, middle office. and some research in the front office. But Citadel's Edge is more than just research. They do a lot of CEO interviews. They talk to a lot of people off the record. They have a lot of information that does not exist on the internet. They have scale, track record. So I don't know. It's interesting.

1:07:39Mike Isaac:Yeah, let's talk about everything. Yeah. Well, I think we have our next guest already here. But we can go through Everlane quickly, or we can come back to Everlane at 1245. Let's do that. Okay. Well, let's bring in Rowan from Redis because he's waiting in the waiting room. Rowan, welcome to the show. How are you doing? I'm doing great. Thanks so much for being here. Since it's your first time on the show, I've actually been. Are you getting an act? Is this an active sauna session for you? It does look like a sauna background. I'm in Tenerife today, actually. so amazing yeah amazing the wood paneling behind you really does look like a song i like it i like um well yeah we'll see in in a few minutes if you start sweating i'll be doing the cold plunge next we'll see how that goes yeah yeah well some people in tech do combine cold plunges with that's happening talking about their companies tim draper yeah yeah yeah for sure that's anyways great great great to meet you great to meet you um i i i've used redis a ton uh about a decade ago i'm a big of the product.

1:08:42But if you could introduce yourself and the company a little bit before we go into the news today, that'd be great. Yeah, absolutely. Thanks, guys, for having me on. It's an honor to be on. I loved your show. I'm a big fan and watch all the time. Yeah, so I head up Redis and we're one of the sort of core infrastructure components that has been around. We're one of the bigger open source projects over the last 15 years and sort of helped build out a lot of the internet infrastructure and got a great team. We have just about, we're 1 ,500 people now, and we're starting to see a lot of, there you go.

1:09:17That's great. We're starting to see a lot of traction in the AI world as people are starting to really build out agents, as you guys were just talking about, lots of opportunity there, and we're being pulled in on agent data. Yeah, I want to get to that. Is the correct framing for Redis for people who might not have actually used the product in memory key value storage, non-relational databases think like MySQL, but less structured and also held in memory, therefore faster? Totally. You nailed it. The history of it, it's an in-memory data structure server. It's not really a database, but it's been treated as a database.

1:09:55And the killer app that kind of took off and made Redis a part of, kind of got the tendrils into all the applications on the whole internet was key value being used for caching. So it originally started as an in-memory database. The big thing that's changed, though, and this is just coming live now, is over the last few years, we've re-architected Redis and launched a new product that uses Flash as the back-end storage. And so now we have the fastest, the world's fastest Flash object store. And so that's a new thing. And that was really driven by AI because we were seeing huge demand for way bigger, way more data.

1:10:31And also RAM prices have gotten crazy. and MVME performance has improved dramatically. Sure. Okay, so then take me through some of the history of the business. I know you joined a CEO in the modern era, but in terms of that transition, what is the shape of the business? Because a lot of people are building open source software and I'm always fascinated by that transition and that interaction between the product, which sometimes has like incredible developer pull, incredible ecosystem, and then also an incredible opportunity to build a real business around it. But what is the shape of that? Because I think people go to Red Hat.

1:11:09They go to consulting shops. They go to hosting providers, enterprise software wrapped around it. But how would you describe it, the shape of the business around the product right now? Yeah, so it's a great question. We're still an open core company. So we have an open source base, which is Redis. Anyone can download it and use it for free. It's used all over the place for free. And then we have a paid version. So, for example, the recent innovation I mentioned, the rewrite using Flash Story, that's not for free. That's something that you would pay for. We have a lot of performance advantages in the paid version.

1:11:44We have a hosted version. It runs on all three of the major clouds. So if you get Redis on Amazon or Google or Microsoft, Azure, we have our own version essentially that runs on those clouds. And so that's the heart of the business. Most of our usage on the internet is free Redis because the free product is amazing. The paid version is even better. I like it. That's good salesmanship. So the relationship with the hyperscalers, is that like consumption revenue that's coming to you? I set up an AWS instance. I pull Redis off the shelf from the dashboard of a million different tools. And then as I'm using it every month, stuffing more and more data into it, that money is flowing to you from the hyperscalers.

1:12:30Exactly. So it's a little different depending on which hyperscale you're talking about. For Microsoft, if you buy the first-party service from Microsoft, right? So on the hyperscalers, you have first-party services that are offered by the hyperscalers themselves. Then there's third-party that you buy through the marketplace. In Microsoft's case, when you buy Redis first-party, it's actually our software. And you're exactly right. We get a revenue share of that. So that's called Azure Cash for Redis. And then Amazon and Google no longer offer us first party services Redis. They have their own products that were once built based on Redis, but we did a license shift to kind of get them off of our tail, frankly.

1:13:08So Amazon and Google now have their own code bases that they have to maintain that have really diverged from what is now core Redis. We offer on Amazon and Google through the marketplace Redis as the Redis cloud product, essentially. And then increasingly, we're offering that through new cloud vendors, either their Neo clouds or like Vercel, for example. So if you ask an agent, if you're building on Vercel and you say, hey, please deploy Redis cloud, boom, you'll get our product. And it seamlessly is integrated into their platform as well. Yeah, that makes a lot of sense. So, I mean, I remember when I was using Redis, I was using it a lot for actually like business intelligence and like data analysis.

1:13:50It was just nice to clean up some data, have it all available in memory much faster to sort of query and do like MapReduce over. But obviously the bread and butter is caching. But I'm interested in the shape of the agent business. Like what data is being stored? when, because a lot of this stuff can be loaded in context. It can live on the chip. We talked to the Cerebris founder last week. Like there's an incredible amount of work being done really, really deep in the, in, in the, in the AI supply chain. And then there's everything out to hard drives and tape storage on the other side. And so what is the sweet spot that Redis is filling right now?

1:14:34Yeah. So if, if in the past, as you just talked about sort of the, the kill use case in the cloud mobile era was caching your database, basically. You could use it for a lot of other stuff, as you talked about. And in the new world, we sit in a similar place, and that is essentially providing all the context, like coalescing all the context for the agent and then delivering that to the agent. And we had to actually build a new product to do that. So what developers have been using Redis for in the agent, this is called the next era that we're heading into, is storing agent data and hosting agent context.

1:15:12And one of the reasons for that is that you're going to see multiple orders of magnitude more agents than human beings in a company. And what that has a direct consequence to the load you're putting on your backend data systems. So just like in the cloud mobile era, you saw, you know, you went from like guys that were sitting at green screens, like bank tellers, for example, and the load factor on your backend DB2 might've been like 10 ,000 to one or something. Okay. Then you added mobile and you added a million customers or 10 million customers. So two, three, four orders of magnitude more load and Redis came in there as a scaling layer.

1:15:51Yeah. Okay. And you didn't have to go and scale DB2 or your mainframe or whatever. It doesn't make any sense. You Oracle that backend. Similarly in the agent era, a similar transition is happening. So as that load increases, is you can't have, like my company has a thousand employees. I can't have a hundred thousand or a million agents. And we're going crazy with agents right now internally hitting my backend data systems. Cause I'm going to be paying a hell of a lot more to all of my underlying providers. So we use Redis in the middle as the context engine and we cache and hold all the context from the underlying databases in Redis.

1:16:26And that's what the agents interact with. So we launched a brand new product that's on our website right now called Iris. And this is its exact intention is that what you do is you have, we have a data integration piece that sucks the data out of your underlying databases, stores it in our new Redis Flash database, and then serves it through CLI and MCP through Pydantic models. So you define Pydantic models on top of your data, and you do the transformations underneath. And then what the agent sees is a manifestation or a view of the underlying data. And the difference is it's not just a scale issue.

1:17:02It's also providing the data in the way the agent expects to get it. So I'll give you a simple analogy here would be like, if I told you, you know, hey, you know, let's say, let's say I said to you, hey, I'm an agent, and I need you to go get some data. And you said, great, it's in that filing cabinet. And I got to go rummage around as an agent calling a whole bunch of MCP tools and doing queries and figuring out relationships, et cetera, et cetera, versus I say to you, I need some data and you just pull the exact file out of the cabinet and say, here it is and hand it to me. And that's the difference.

1:17:34So it's a huge reduction in token costs and also agent speed. And then a big improvement in terms of performance of agents, because the data is essentially massaged into a format, these pedantic models, and then semantically described exactly what the agent needs. So that's what Iris is all about. And then it also has the second component, which is memory. So agent memory is the other big thing we've invested in. We have a state-of-the-art memory server that we've just launched as well. Yeah. So I mean, what is like a reasonable scaling factor for the amount of data from my relational database, my hard drive-based database to go into memory?

1:18:11Because I imagine it's, you mentioned like brings a copy into memory, but I imagine that's not one-to-one. I want to do some condensing down of the data to what's relevant. And I imagine that Iris helps with that. But what is a good rule of thumb? I imagine that there's some sort of cost relative tradeoff there. But how are companies even thinking about that? Yeah, it's interesting. I haven't really talked to any customers who are thinking about it in that way. What they're thinking about is, what is the cost delta to scale my data layer in Redis versus purchasing additional licenses of, you know, whatever, NetSuite or, you know, Salesforce or this or that other thing, whatever that underlying asset is.

1:18:53And so, but I would say, so it's a good question. I actually don't know the answer to that. But they do think about it in terms of accuracy. Like, you know, you want the data to be served up in a way that is the best possible and most accurate data. So semantic descriptions, this is why we use the Pydantic models, is you can put semantic descriptions on each thing. So all that encoded knowledge of what to query, what database, what record, what table, that all gets encoded in the system. What the agent gets is a really nice set of MCP or CLI tools that say, like, search customer records. And we have a super fast search underneath the covers.

1:19:33We have a great vector search and then a BM25 search. So we can search across all those records and then just deliver exactly what you need. And so what that all amounts to for the end customer is a much faster and much more token efficient agent experience. Yeah. And the second piece of it, and this is important, we should talk about it is that that context should get better over time. Like agents learn things as they go and they need to remember the things that they've learned, not just facts about the user. Like when people talk about memory these days, we often talk about remembering user preferences.

1:20:05That's interesting. But you also need to remember, hey, when I when I check the shipping status for this particular customer, like that system was wrong, but this system was right. And that's the truth of large enterprises and their data is that they're really messy in most cases. And so expecting them to sort of like get all that stuff in order in advance, it's just too tall of an order. And so we need to also remember things that the agent has learned over time and then store those. And that gets stored in agent memory. So we have a state-of-the-art model there called Agent Memory Server that does the extraction and all the kind of stuff you would expect from a memory platform.

1:20:39Yeah. How are you interacting with benchmarks these days? Because most of the benchmarks are centered around performance, like meters, like how advanced of a software engineering task can the frontier models crank on? And they're up to like 24 hours. It would take a software engineer 24 hours to do something. but 4.7 or 5.5 can do it, period, and can achieve it with 50 % accuracy. They're not really talking about the time to return that result. And we've sort of settled into this equilibrium where if it's a big query, 10 minutes is acceptable for most people, maybe 20. And then for a knowledge retrieval, I want to know an answer.

1:21:27It's got to come back in like 30 seconds, But we're not in the Amazon e-commerce era where 100 milliseconds means losing dollars, which is sort of where the Redis DNA comes from in caching. But I imagine that a pitch to an agent company might be something like, yes, the vast majority of wall clock time is going to be waiting for tokens to inference and churn out on a big cluster somewhere. but we're going to keep the GPUs fed so much more effectively by keeping this in memory. How are you thinking about quantifying that for customers? Yeah, well, so the first point you made about agent runtime, certainly that we're witnessing what everyone else is witnessing, you know, the time an agent can run unattended.

1:22:13And the issue with that is context becomes even more important, right? If I told you to solve a problem and then I locked you in a closet and didn't give you access to the outside world for eight hours, you'd just hallucinate a bunch of answers. But if I stuck you in the New York Public City Library with a Google terminal, you'd be good and you'd come up with an answer and it would be good. So context becomes super important when you're running these really long tasks. And the transition that has happened really over the last couple of years from what started with RAG, which was kind of engineers thinking, hey, we'll just preload the context window with all this stuff.

1:22:48and then the agent can go and go figure it all out. And there was this whole idea that context windows would get bigger and you could just load everything into the context window, your whole code base, all of your – but the truth is that really doesn't work. To stick everything into the context window, number one, is expensive and number two, just really it's overloading. You're just getting way too much rot in the context window. And so it's much better to provide a tight set of tools to the agent to let them reason over the data and sort of do searches and what can I access and that kind of stuff.

1:23:21So what we see is the longer the agent can run, the better the context has to be to make it effective. Otherwise, it just starts to go haywire. Yeah, that makes a lot of sense. Switching over to just your philosophy as a CEO, you said 1 ,500 people, something like that, over 1 ,000 work for Redis. You're obviously using these tools. How do you see the shape of the organization changing over the next few years? Well, dramatically. I mean, so I've been coding since I was 11 years old and professionally since I was 18 in high school and at a startup. And, you know, I woke up one day with these tools and realized like all the way that I learned how to build software 30 years ago is just not relevant anymore.

1:24:03And so, you know, I'm not going to rely on a bunch of other people telling me, you know, and like watching, you know, Twitter people breathlessly telling me how the world is changing. I'm going to go learn it myself. So I've gone back to basics over the last year and a half. I mean, really, since we started using ChatGPT for coding and OpenAI, and then really have been diving in myself personally. So I actually sit on teams, I've been contributing and building my own projects on the side, as well as contributing to our own code. And I think there's a few maybe non-obvious things that I've learned.

1:24:35You know, there's the obvious part that it's like the code is now can be written mostly by by agents and by you know by coding agents but but that if you just do that it doesn't really change much because then you still have the same people in the same process the process is all set up to basically handle a world where the coding takes a really long time that's the long poles if that's not the long pole anymore there's all these other long poles like meetings and daily stand-ups and processes that were all built around that fundamental assumption of coding is the long pole in the 10. Now that that's gone, we're having to reinvent those processes.

1:25:06And I've basically found, and same with my CTO, we have to go right back into the front lines of the teams and build code ourselves as we reinvent the software development lifecycle. And frankly, we're finding that a lot of folks have to make a big jump in terms of how they do work. Like a developer with 10 agents is more like a development manager of old. And the development manager does a different job. They coordinate, they express their requirements in the right way, they have taste, they decide what's the right approach to solve a problem. And that's the new job. And it's really fundamentally different than what the developer of, let's say, three years used to do before these agents showed up.

1:25:48And by the way, I'm having a blast. I love coding. I've always loved coding. I love everything about it. And I love it even more now. I mean, it's like I've taken out the gnarly part in the middle, which was the typing everything in and finding missing semicolons. And now I just go right from expressing intent to getting the result. And that's awesome. I mean, it's super cool. Are you seeing it instantiated more in like new greenfield projects, new internal tools or actual product velocity on the core product? Both, but more on greenfield. On the brownfield, what we've – first of all, we use it differently.

1:26:24So for like front end stuff, you know, we can like pretty much vibe code everything. Sure. You know, on core Redis system software. Yeah. I'll give you a good example. We just launched a new data type. Salvatore Sanfilippo, who's the original author of Redis. Yeah. Launched a new data type called Arrays. Yeah. It's 4 ,000 lines of C code. It took him four months and he was deeply using Codex. Interesting. And Anthropic. Okay, Claude. Yeah. The whole time. Yeah. And it was it's but the difference. So it took it was faster to do. OK, so that same idea that that array data type would have taken probably a lot longer, but more important, like eight months maybe for him just sitting there writing C code.

1:27:09But more importantly, it's way higher quality right out of the gate. Huge amounts of tests, huge amounts of infrastructure, like all kinds of benchmarks, all that extra stuff that comes around the edges. And we really do use, even at hardcore systems level coding, we're using the AI to give really good suggestions. We're often pitting them against each other to sort of say, hey, come up with your best design for this. And then we'll throw it at the other AI to say, what do you think? And back and forth. So at that level, you really are still crafting the code at the systems level, which is kind of where the world that I come from.

1:27:43but at the higher end and kind of for greenfield projects, you know, JavaScript and, you know, next JS applications, you're just like five coding and just going crazy. And I would say if you have one project, what is a good example in a greenfield, it would have taken a typical, like we were building this big management infrastructure for, for the Iris project. It would have taken us probably a year for like 10 devs to do something like big like that with LDAP support and all the different things you need for enterprise software. It took five guys, one month, guys and girls, actually. So that's a big acceleration on that front.

1:28:16But it's different at the systems level software side and Brownfield. Yeah, yeah, that makes a lot of sense. Well, thank you so much for coming on the show, breaking down for us. Hope you have a great week. We'll talk to you soon. Huge fan. Thank you so much for having me on. Yeah, we'll talk to you soon. Goodbye. Everlane was sold to Shein for just$100 million. It was a VC darling when it launched, says Shiel Monat, raising from Kleiner Perkins. I didn't realize how many big VC funds. It was a who's who. It was a who's who. Kleiner Perkins, Khosla, Maveron, and others,$145 million raised. I think the bet was that consumers would pay more for ethical, sustainable basics, and that consumers may not really exist at venture scale.

1:29:01That consumer. The low-end consumer wants price. The high-end customer wants brand, taste, and status. Everlane is kind of stuck in the middle. It sells Smart Basics at a premium, but I'm not sure people who are willing to pay a significant premium for simple clothes over Quince, Uniqlo, and Amazon, maybe the real radical transparency was showing everyone how brutal fashion economics can be. Wonder what Shein does with it. Will they just make the same clothes in sweatshops now? And so people were very upset about this. Rachel. Yeah. So, so yeah,

1:29:38Mike Isaac:I think you won pretty, pretty shocking, right? Companies have had very different approaches to building their business. Yeah. And it's hard to see how it's hard to see how Everlane can fit into Sheen in a way that maintains their historical ethos. Who knows? Right. Sheen. Is it that hard? I mean, doesn't like Volkswagen Group owns Lamborghini or something? Yeah, but neither Volkswagen or Lamborghini were ever. They were both saying we're making cars. Lamborghini says we make faster cars. Volkswagen. They both make clothes. Everlane's saying we make clothes in the sustainable way. Sheen is a company.

1:30:28Mike Isaac:She like Everlane, Everlane was created as a response to people's concerns with sweatshops. Right. Was the Rivelto not a response to the Passat? I believe it was. No. So Everlane came out. It is different because it's moral. It's moral. It's not purely functional stats. It's not like we're making Everlane wasn't like we're going to make a better T-shirt. That was maybe part of it, but it was more like we're going to make good. At the same time, a lot of the car makers, they went EV directly to counteract the gas guns and V12s. You have to look at when these car companies were founded. At the time, there wasn't, yes, if speed is morality, horsepower is morality, maybe you're right, John.

1:31:17Mike Isaac:But look at the, when was Everlane founded? 2011. I just think like some car brands were founded with safety in mind. Founded in 2011. Yeah. Two things on top of mind. at that point for consumers? When was she encountered? Sweatshops, like apparel sweatshops, right? And then the entire, you know, sort of like eco sustainability movement, right? So Everlane was a response from that. They met the moment. The business absolutely ripped. I think the other thing at that time is like a lot of the big legacy brands, thinking like Gap and Old Navy and brands like that, they were just totally asleep at the wheel, right?

1:31:57Mike Isaac:So I think they weren't keeping up with, just weren't keeping up with the times, right? When you just look at, think about the difference of like navigating like an Everlane website in that era versus navigating like a Gap website, right? I've actually never navigated any of these websites. But just imagine it, right? Like one is extremely clunky. The other one is like very easy to operate. uh everlane was a pioneer of an entire style of uh you know photography product photography uh it was very everything was like clean minimalist it really met the moment right and this is something that um apparel brands blow up because they're just a little bit busier on the website i'm looking at everlane it's like a single model just showing like a few items of clothing and you open up the shein website and it's just huge accept all cookies and then 30 off if you sign up and save and then like a huge registration thing then another pop-up so many pop-ups here uh yeah wildly different brands another pop-up yeah so everlane is created in the perfect moment a response to consumer concerns and preferences they ride that wave to a couple hundred million of annualized revenue.

1:33:20Mike Isaac:They've got owned retail in a bunch of different places. They're a D2C darling. Michael, CEO, who's a friend of mine. I'm an investor in one of his new companies. He, yeah, I mean, incredible execution by the team. They built a brand that effectively became a household name. He stepped away after basically 10 years and a woman named Andrea took over. But yeah, I think ultimately when you look at, there's this like constant desire that sometimes gets forgotten or obfuscated, which is that consumers want cheap stuff. right and i think as everlane was like trying to scale right competing over the coastal millennial who's like on instagram all day long shopping right they are excited about newness right like i have tried so many different companies that are effectively competitors to everlane i've tried so many different t-shirt basics companies just because i'm constantly searching for the perfect which we might we might have to make we might have to make the tbpn perfect white tea yes um uh and and so you have this customer base who you met them at this amazing moment and their their revenue ramp reflects that but then over time it was in some ways like the the sort of of like sustainability brands like broadly have suffered over the last decade, right?

1:35:04Mike Isaac:It stopped being something that the average consumer was caring about to the same degree. Allbirds is another example of this sustainable footwear, right? And so yeah, shift in consumer preferences. Also, when you look at a lot of the greatest apparel brands in history, they didn't raise venture capital, right? When you have venture capital, it's like, we need to grow as much as possible year over year forever. Like that is what you sign up for, right? And when you look at apparel brands, oftentimes like it's more of a kind of like winding road. Like Chrome Hearts. Exactly. Up and down. Exactly.

1:35:46Mike Isaac:Up and down, but tightly held, right? By one family. And they're okay. They're like, hey, if revenue dips one year or we want to pull back on supply, that's great, right? And so when you're venture-backed, you don't have that luxury. And I think that venture is at odds with building. It's just at odds with building a super durable apparel brand simply because there's no network effects at all, right? And especially if your customer base is excited about newness, right? I might be more loyal to one brand or another, but that doesn't stop me from seeing a brand pop up. Maybe it's run by some founder, I think is cool, being willing to try it.

1:36:37And this is happening all the time.

1:36:39Mike Isaac:Like Chris Black has a brand, and the dollars that I'm putting towards his brand are like effectively dollars that could have gone to Everlane, right? Amy Leon Doerr, founded in 2014, seems to be doing well. Venture back, though? Is it? I don't think so. I don't think so, no. And I think it's very tightly held, very tightly controlled, very limited. Well, the deal was$100 million. We don't know too much about the deal other than they'd raised over$100 million in equity. Al Catterton invested$85 million in Everlane in 2020 when the brand was doing$200 million in revenue. Now, revenue is down to$170 million, but there's$90 million in debt.

1:37:27Sort of unclear. Did Sheehan acquire the debt and then pay that$100 million to the preferred equity holders? It feels like Common was probably wiped out, but unclear exactly the structure of this deal. They say, this one post, Fan B, says the$100 million sale price essentially covers the debt, but it's possible that the$100 million went to the preferred equity holders and Sheehan assumed the debt with the deal. Either way, not a fantastic outcome. uh there's uh you know people are saying it's the death of DTC but there are some green shoots specifically with green products grooms sold for 1.2 billion that's a good outcome yeah but that's

1:38:15Mike Isaac:a brand that's a brand that can go in every target every Walmart every Whole Foods every major retailer and sell billions of dollars worth of product uh Everlane I'm not sure if they ever were selling in other retails or it was entirely their own stores. And there's no real, like, you know, Everlane made some great clothes. There's probably people listening to this that bought something from Everlane five, eight years ago, something like that. And it's still in their closet. And so, unfortunate outcome for the Everlane team, but their execution across that decade was pretty impressive. And we'll see where it goes.

1:39:05Well, we have our next guest, Dean from Descartes in the waiting room. Let's bring in Dean. Will there be a crazy filter? Normal. Normal mode. Welcome back to the show.

1:39:16Mike Isaac:We'll throw a filter on. I haven't seen anyone nail that as well as you have. Well, you've been nailing lots of things. Give us the news. Tell us what's going on. Well, so fun to be back here on TBPN. Last time we did this, we had some crazy filters. It was very psychedelic. I loved it. It was very psychedelic. If you're interested in the newer ones, you should go on our site and try them out. It's been mind-blowing. Amazing. But today, you know, we announced a round. We had a big funding round. We raised$300 million. Woo!

1:39:51Mike Isaac:There we go. Nice! It's great to have you back. Great to have you back. We missed you. It was worth doing the round just for that. We should do more and more rounds just to get that going. Raise a dollar tomorrow. We'll have you back. No, tell us what you've been up to since the last conversation. So today, the really exciting stuff is that we have announcements on all three of our product lines. Wow. So we have three product lines at the cart. The first two are world models. We have Lucy, that's a world model. It's a real-time video model that is used for immersive experiences. So gaming, live streaming, e-commerce, ads.

1:40:31And we have the new version of Lucy coming out soon, which has been growing dramatically over the past three quarters.

1:40:38Mike Isaac:That's generally what you were demoing the last time you were on, where you have this real-time video of you in these sort of exotic settings. Exactly. We have Lucy Lucy can take any video stream and edit it live So it can do either fun stuff and we've seen huge usage for that and social platforms like Twitch tick tock live YouTube live and At the same time can also be used for for beneficial experiences for example e-commerce and virtual try on trying on different clothes Or putting ads inside into live streams, and we've seen that for example with Amazon We're using this across different e-commerce providers.

1:41:15So that's our Lucy product line and has its new version that's coming out. We have our Oasis product line, which is a real-time world model for physical AI. For robotics, for autonomous vehicles, drones, manufacturing, and really over there, our real-time model lets AI just interact with the real world. It stops being just in the virtual world and tech space and actually is real-time pixels lets the AI see the real world in real time and interact with it. And then we have our third product line, which is DOS, the Descartes Optimized Stack. It's our inference engine. It's basically what powers both Lucy and Oasis, and it lets us run models, all types of models, LLM models, agentic models, video models, audio models, world models, all the types of models, dramatically more efficient than anything on the market.

1:42:05And today we're announcing DOS 2.0. that's already being used by some of the hyperscalers? Hit it again. Woo! I think I got Ben Lacken over there. He gave him a heart attack.

1:42:20Mike Isaac:When did you release DOS 1.0? You realized at some point, hey, we're cooking pretty hard over here. Maybe we should let other people use it. It feels pretty aligned with the other products. but yeah, how did you get into it? So I think that's a great question. Actually, you know, we don't talk about DOS too much but DOS was actually the first product we commercialized. When the company was just three months old we closed the first multi-million dollar license deal for DOS. Overnight success. Literally three months in. It was less than 100 days. Why did it take you so long? Why did it take you so long?

1:43:02That's, you know, that's the number one question I ask my team literally every single day. Number one rule for running an AI company, if you're an AI CEO, whenever your team comes to you with a deadline, ask why not 10 times shorter. But yeah, to go back to your question, DOS 1.0 was the first product we ever had at Dakar. We licensed it back to the NeoClouds back then and to some of the younger AI labs. Now DOS 2.0 is being used by all the players, including the tier one players as well, and hyperscalers to really use compute much more efficiently. And for the models that we support, really focus on very fast models.

1:43:42So either agentic models or live video models. For those models, we're anywhere between 5 to 8x more performant than anything on the market.

1:43:49Mike Isaac:Is focus overrated?

1:43:55Mike Isaac:No, it seems that you're doing a lot. You're competing, you're fighting on three different fronts. but clearly doing a great job at it. How do you make it work? I can imagine any one of these opportunities being big enough at some point to warrant kind of going all in on it. Well, we're all in on them, on all three of them. Now, the nice thing is that it really, I think focus is very, very, very important. And you have to build inside the company very independent leaders. We have a lot of very, very talented researchers that turned into very independent leaders inside the company. So they're both great on the technical side and very, very good on productization.

1:44:41I'm taking this to market, I'm talking to customers, I'm building the product itself. And we inside the car really have three different teams. One for Lucy, one for Oasis, one for DOS. And they each operate completely independently and only focused on the thing that they're doing. now with DOS the reason the reason we accelerated DOS 2.0 was supposed to come out in August we're launching it now instead is because of the huge huge huge huge supply constraint on the chip side it's it's just become we're hearing this from all our customers that there's no capacity left basically till 2028 and and so getting more performance out of chips is the only way to actually grow your revenue and to grow your AI adoption.

1:45:27So if you're any AI company, you really have to be able to extract the most out of any possible chip to be able to actually grow your business. And right now, that is a bottleneck. Yeah. How tightly linked are the different products? Because when I think of Lucy real-time interactive video world models, I think like optimization there is what you're a good at, but also incredibly important because even the demos that we've seen, they're not 4k. They're not 60 FPS. There's clearly room to run there. Whereas in many of like the text generation models for a lot of the queries that people are asking, how do I cook this?

1:46:07You know, tell me the history of this company or story. Like it's basically superhuman already, but superhuman real-time world models. We're not there yet, and so optimization feels really important. How tightly linked are those two projects? Yes, they're very tightly linked through DOS. And DOS 2.0 today, it can run real-time video models at full HD for the first time up to 100 frames per second. Wow. Okay? So that's huge breakthroughs there. And on the text side, what DOS can do, so DOS runs on all the three major chips. It runs on NVIDIA, on Google TPU, and Amazon Tranium. It's the only stack that really supports all three for all the different types of models.

1:46:53And on the agentic side... Silver for AMD. Silver. The chip space is incredibly, incredibly interesting. You're like, we will support the fourth eventually. We will support everyone. We will support everyone. Yeah, yeah. But to your question about fast text models, where you really need them is agentic workloads. You really need it if you want to be able to run, for example, coding models very, very quickly. And DOS 2.0 can, for the first time, run it above 1 ,500 tokens per second, which is more than 10 times the industry. Interesting. At somewhat of a high level, technical level, what is different about the architecture of interactive video world models from text-based LLMs.

1:47:43I think most people saw the fork in the road during the mid-journey era, the DALI era, the diffusion, you start with a bunch of noise versus token-based next token prediction. Have these converged? Have they diverged? Are there different requirements? We're seeing with agents, we need more CPUs now. We might need more context in cache. We might need RAG or or vector databases like like what are different if you're to build out like the ultimate data center for generative interactive world models like are you looking for Cerebris like chips are you going all in on NBL 72 like what what is this how it is there?

1:48:25Is there a difference to the shape of the of the architecture that lends itself to like different hardware constraints? Yes, I think that that's that's probably one of the best questions in this field right now because Because AI is moving so quickly that it's very, very hard to predict what the right infrastructure will be three months from now. You brought up the CPU shortage that suddenly happened. No one was expecting AI to need CPUs. And when AI needed CPUs, it went from zero to can we get all the CPUs and all the hyperscalers today? And that's happening overnight. And now it's becoming very hard.

1:49:02What we're seeing, what we're hearing from our customers. it's becoming very hard for the people on the model side to actually understand what to do on the infrastructure side and vice versa. And so there's this gap here of how do you map the model requirements and that they're constantly changing every single week to what's possible on the infrastructure side. And so that's why, for example, we support all three major hardwares. It really allows us to choose where to route the different workloads to. And then each one has its own unique strengths and weaknesses. and that lets us really, we developed a very, very deep expertise in knowing how to map the model to the chip itself.

1:49:44I think that it ties into something else that we're seeing. Usually when people draw out the stack, they say, okay, there's the model layer, then there's software, for example, Kudo, and then there's the hardware layer.

1:49:55Mike Isaac:I call it a five-layer cake, but if you want to call it a stack. I wonder if someone else will adopt their five-layer cake terminology. You have the two layers above and below, you have the data center and you have the application layer. But what people usually miss is that the software layer is around seven layers inside of it. It's not just one thing. It's not just, oh, there's cuda here. No, no, no, no, no, no, no, no, no. It's a five layer cake with lots of flavors in layer three. Sure. Lots of ingredients. Now, that's really where we sit. We integrate across all those layers inside the software side to really tie from the AI model itself directly onto the chip.

1:50:35We literally write assembly for all these three chips. We know how to write VLIW for TPUs. We know how to write assembly for traniums. We know how to write SAS and PTX for NVIDIA chips. And so we have all these different layers, and they really enable us to very quickly move between these workloads that constantly change. Okay. Are you seeing glimpses of consumer product opportunities in video world models? When I see your technology, when I see Genie from Google and World Labs, I think, okay, like a harness, a wrapper, a couple UI, a relational database storing my inventory, like a couple other steps.

1:51:21And all of a sudden, this is something that I want to play for more than a demo for more than a minute. And maybe the hardware is not there, but I think just as, you know, lots of folks who were interacting with LLMs during like the GPT-3 era sort of saw ahead and started thinking, oh, well, like chat is a potential modality here. Everyone's seeing that video games or something playable would be a potential modality. But how far away are we from that? Is that interesting? Like what else, what other dominoes need to fall for that to actually happen? So over the past month, actually, we've seen huge usage for using Lucy in live streaming.

1:52:03You can go to delulu.ai. Sure. Yeah. D-E-L-U-L-U.ai. And you can – come on. Of course. It's good. It's good. It's good. It's good. And it just plugs right into your OBS. So it just literally plugs into your OBS camera. And you can just apply all these filters live. And we've seen streamers go on it for eight hours nonstop. So we've seen that. We've seen that pop really over the past month, month and a half. We have a new subscription service there that people just subscribe to, and they can turn it on for however long they want. And that's just been growing exponentially fast. Okay. Well, thank you for coming on.

1:52:39We actually have some videos that we're going to play because we've been demoing it, or the team has. No way!

1:52:46Mike Isaac:Only while we've been talking. Can we play this while he's live so he can see it too? I think you'll see the program monitor if you want to hang out. but let's pull up this is Tyler Cosgrove you guys are doing the live demo instead of me this time that is insane so we have a video here we recorded it I believe it's Tyler as Albert Einstein is that correct let's see if we can pull this pulling it up might be the harder part we have real time video models but pulling up a video the shadow and the lighting still a challenge did you prompt this? so it started as Einstein and then I went through a couple different You wanted a pink tuxedo on as well?

1:53:25That's very funny. What a funny prompt. And the, yeah, the, the visual fidelity on Einstein's face. That is weird. Okay. There we go. It's a very humanoid. Oh, that's a jacked horse. That is odd. That's very odd. But the horse head, oh, there you go. Okay. That's interesting. As you touch your face, Like the the hand of the horse sort of hits the correct part of the face so it understands the physics well That that was impressive. It wasn't purely last question last question

1:54:00Mike Isaac:Before you jump is is there a certain milestone that if achieved you will cut your hair like is it in? Oh, yeah. Oh, yeah. Oh, yeah, really? It's the the the milestone is that we need to hit 1 billion ARR That's the milestone. It's a bet from early on in the company. Now, this is a year and a half long. Okay? This is just one and a half years. We have to get rid of it. Now, with DOS and the way that's scaling, at some point, I'm going to get haircuts. Fantastic. Amazing. Well, we'll be here when you hit that milestone. Selfishly, I kind of want to see it down your waist. Oh, we should do a haircut on stream.

1:54:38Mike Isaac:We're going to do a haircut on stream. I love that idea. Come to the El Trigone. We'll shave your head. Dean, you're the man. This is great. The chat loves you. Thanks guys so much. Say hello to everyone at Radical. We're big fans. We'll talk to you soon. Cheers. Love them. Goodbye. Another one. We have Joanna Stern, author of I Am Not a Robot, coming in person today. All right. But before, we got to talk about the protein shortage that is coming. What's going on with the protein shortage? Ellen Cushing in The Atlantic says making all that way is complicated. Okay. She says in rest retrospect maybe the protein pop tarts were a bit much Americans broadly speaking are in a state of protein Mania, mania.

1:55:23Mike Isaac:We are eating it at breakfast lunch dinner dessert And just about any time in between We like it in chips candy soda water. We like protein so much in fact that we've been eating it all up Whey protein prices are surging and a shortage may be eminent if you're not investing in the protein bottlenecks i don't know what to do yeah where's the situational awareness for the protein shortage we really need that demand is strengthening the usda warned in a recent report inventories remain tight some manufacturers have already sold their supplies for the full year no way i'm getting back i'm getting ptsd uh since january wholesale prices for food grade whey protein powder have risen by more than 50 percent to the highest level on record.

1:56:11Mike Isaac:Retail prices are going up. Two, six months ago, a two-pound jug of Optimum Nutrition's delicious strawberry-flavored whey protein went for about$40 on Amazon. Now it's$54. We've absolutely felt it, says Stephen Zeminski, CEO of the supplement company Naked Nutrition, said of the shortage in an email. He said his company has not raised prices. Demand is up and supply is tighter than it has ever been. Historically and currently, much of the protein that has made its way into packaged foods and smoothies and those big tubs of protein powder comes from whey. Raw milk is treated with heat, acid, or enzymes to coagulate it into two distinct substances, curds, which become cheese, and whey, which was, at least until recently, the cheese-making process's unlovely byproduct.

1:56:58Mike Isaac:Almost as long as industrialized agriculture has existed, the problem with whey wasn't scarcity at all, but the opposite. that farmers did anything they could to do to get rid of it as cheaply as possible. Fed it to livestock, sprayed it onto fields, dumped it into rivers and sewers. Can you imagine? And swimming in a river that was used as a dumping ground for whey, John? Weird. Especially combining that with a place like Switzerland where you can drink the water and the lakes and the rivers and you'll be totally fine. That could be a powerful combination. For much of our nation's history, any fish unlucky enough to be born in Wisconsin or Vermont had a good chance of being, whoa, murdered by whey.

1:57:40Whoa. I'll keep reading from here. Then environmental regulation Limited whey dumping And technological developments Made processing whey into powder much easier Starting in the 1980s Whey was the future industry's Go-to source of supplemental protein Cheap, vegetarian, efficient And already right there in abundance Supply and demand were more or less In alignment for a while

1:58:05Mike Isaac:I'll keep reading Another one then came the group protein protein protein protein this is such a the helium is there a helium shortage as well? it certainly seems that there is not because the helium is flowing throughout the tbp and ultradome anyway influencers started bragging about how many grams they got in a day the government flipped the food pyramid around placing protein at the top people from every walk of life latched on a protein as a sort of one-size-fits-all super ingredient supposedly capable of giving anyone the body they want as long as they eat enough of it, even if the reality is obviously more complicated.

1:58:51Mike Isaac:And food manufacturers responded to this new demand. You know, when I was young and I was intentionally trying to have as many calories as possible, I realized I had to pull back on protein because it was just like too, it was too filling at times. Yeah, not enough calories. And protein, you need fat. Yeah. More dense, more caloric. Food manufacturers responded to this new demand enthusiastically, cramming in America's new favorite macronutrient wherever they could, usually in the form of weight. Now the infrastructure can't keep up. The North American dairy industry has pumped about a decade of investment.

1:59:25Mike Isaac:Let's go. Wow. Heavy infrastructure. The build out. The build out. Say that again. The build out. The build out. The protein. The protein powder build out of the late 2010s. consumer demand and consumer preferences can change faster than processing capacity can we're in that lag situation right now it's this is a screaming bottleneck we got a capability overhang turning fresh raw cow's milk into shelf stable scoopable tasty enough protein powder people want is a massively complicated process one that requires space and time and huge expensive machine i didn't think the protein what is the what is the auv what is the auv machine what is the asml of way the euv machine sorry sorry evie advanced lithography machines yeah what is the asml probably i don't know maybe that company uh what's that collar the cow collar company they're right at the top yeah top of the founder's funds going long into the uh what's it called cattle holler collar something like that cowler woops for cows it's whoop for cows and they're printing The business is growing really, really quickly.

2:00:35Mike Isaac:A full processing plant can cost up to$1 billion to build. Everything is just big numbers. Even if you had theoretically started raising capital for a dairy processing facility the day the word protein maxing first appeared on Reddit three years ago, it would unlikely to be up and running today. The higher the protein content, the more complex and expensive the processing. Whey protein isolate, the protein is protein available, the kind that makes it possible to stuff half a chicken's breast worth of fuel into a candy bar is the most expensive and until recently was a very small part of the market.

2:01:11Mike Isaac:The dairy industry just isn't set up for it. The processor decisions are long run decisions. It's really hard to make capital investments at the drop of a hat. Okay, just say you're not protein pilled based on whatever new shiny consumer preference there is out there. Polzin grew up on a dairy farm. He remembers the cottage cheese craze of the past when fitness fixated when the fitness fixated country set its site on a different milk-based superfood that was supposed to make you healthier and thinner and more powerful trends come and go was this point they move quickly our appetites change faster than the systems that satisfy them north america is currently building out 12 billion of dairy processing capacity projections suggest that the current shortage will be short-lived and that the dairy industry will catch up with demand in the near future.

2:01:58Mike Isaac:I just wonder what consumers will be demanding then. I don't see supply ever catching up with demand, John. I think we're in a fast takeoff scenario. I think that the fitness influencers of the 2030s will be recommending five to ten grams, five to ten grams per pound of body weight. Yeah, I wouldn't be surprised. I did not know that the protein boom was going as well as to drive up, you know, supply. CapEx? Yeah, yeah. We need ramp CapEx. We've talked on the show a few times about how they're putting protein and everything, protein and cereal, but I thought that was maybe like overhyped. It was going to be like a temporary trend.

2:02:46They're calling it a whey bubble. A whey bubble. Potentially. Well, we have our next guest, Joanna Stern, the author of I Am Not a Robot, in the TBP and Ultradome, we'll bring her in in just a second. But I don't know. Have you added anything to your diet recently that actually contains newly added protein? Have you gone from something that was not, like, I'm not drinking a Diet Coke with protein. I don't know. So the occasional protein bar, the protein shake, these are the staples of the modern life. But I don't know if there's something that jumps out to me as wildly successful. There's been a lot of, like, protein cereals and protein Pop-Tarts and all sorts of different things.

2:03:27But I haven't seen, like, breakout successes in those actual categories.

2:03:31Mike Isaac:Yeah, I think when you add protein to most things, it just tastes worse. And then explain to me with the David Barr EPG. But that's a fat. That's a fat. That is from how it's been explained. And so they still have to buy normal protein. It passes through you. Yes, yes, yes. So it doesn't count. So I would expect that part of this whole thing is that Peter... Has cornered the market somehow. I wouldn't be surprised. Anyway, we have our next guest, Joanna Stern, author of I Am Not a Robot, live with us in the TVPN Ultra Dome. Let's bring her into the studio. Welcome to the show. Will you be enjoying a Diet Coke?

2:04:11Yes. No, no, no. Just grab a seat. You're welcome to have a sit down. How are you doing? It's real. Is today the official book launch day? No, last week was. Last week, okay. But the tour continues, right? This is the West Coast tour. This is my first stop on the West Coast tour. Here, LA, we're having a conversation tonight, then up to San Francisco. Up to San Francisco, Mountain View. International dates yet? June is when it goes international, so we'll find out. They'll have me. The bot replies, come to Brazil, come to Brazil. Come to Brazil. That's a very popular thing. I haven't heard. You know about this, right?

2:04:43I do know about that. They're like huge fans, the fandoms. I think London. London would be great. London, yes, I think. Well, how are you introducing yourself these days? I know you guys had me as author. Author. Author. I think founder. Founder. Is a founder popular name? Yeah, founder is correct.

2:05:03Mike Isaac:I think I prefer business owner. Okay. Or business woman. I think founder is already sort of fading. Oh, okay. Business person. I think we hit peak founder. Oh, okay. Because anybody can be a founder, but not everyone can be a businesswoman or a businessman. I was at LinkedIn last week, and they said that they're seeing a big uptick in people putting founder in their profiles. Yeah. Angel investor, too, became very trendy. It's over. It's over. It's rising at LinkedIn. So you should put business owner. Okay, business owner. You're selling subscriptions. You're selling books. Ads. Sales. Ads. Yeah.

2:05:40Mike Isaac:All right. Business owner. So maybe take us through the shape of the business, the media empire that you're building. Obviously, there's a book. That's a great way. Was this intentional to time up the launch of the - I don't know if it's a great way. I think it makes so much sense. It's a good marketing vehicle, I think. Yeah, yeah, yeah. I mean, that's why I'm here, right? And so I can come on and I can - I thought through a lot of that when I decided to leave the journal. Yeah. I thought, okay, I've got this book coming out. I've got to get out right away because I've got to start building this business so it's ready when the book is ready.

2:06:11And I probably should have, you know, hindsight. I think there's like a one plus one equals three thing here where you have video content that feeds into sub stack subscriptions, that feeds into books, purchases, and then someone hears about the book. Maybe even if they just read a review of the book, maybe they wind up going and subscribing the sub stack. And so having that sort of 360 degree view. It's a flywheel. It's a flywheel. It's a flywheel. Let's go. Let's go. I love a flywheel. You guys have a flywheel here? We need a flywheel. What a flywheel? I don't know what a flywheel looks like.

2:06:39Is that a waterwheel? I think it's... What is a flywheel? Well, the Amazon flywheel is like a... I'm familiar with the metaphorical flywheel.

2:06:46Mike Isaac:A heavy rotating mechanical device used to store rotational kinetic energy. So we're going to need some proper machinery. Okay. We can get that made. We can get a plastic flywheel. We can get a... It's specifically not a windmill? No, I think... Okay. In my mind, it does look like a windmill. Okay. I think so. this is funny okay can we get one of those here we definitely next time i return to the studio look at all these people they already went out and started to get the flywheel look at all there five of them already this is a flywheel creation yeah anyway what was the flywheel for writing this book um you know i wasn't the the motivation for writing the book was not actually really a business reason at first it'd be a little bit in the sense now it is now it is now it's but as you know, I wrote a popular column for the wall street journal for a long time, 12 years, my biggest, you know, one of the reasons I didn't want to leave, I thought you guys might not read me anymore.

2:07:40Cause I know you read the wall street journal. You love the wall street. We love your coverage. Um, so I have been considering just making a newspaper of just my newsletters and sending it to you guys.

2:07:50Mike Isaac:But so that is something that every writer discovers when they leave a big platform is like, were people reading me for who I am or were they reading me and care about what I was saying because it was in the context of the platform that you were a part of? And I think for you, it's certainly. You had way more personal brand. Yeah. Yeah. You had a personal brand. But still, it means like you guys won't pick that up and be like, oh, yeah, Joanna wrote about robots today. Let's have her on the show. Well, I got a edition of the newsletter. I know. Printed. I think that's a. But so just to kind of.

2:08:24Yeah. I've been writing this column for a really long time, and I was realizing so much of the AI columns had a theme to it. Sure. And I was testing all of this AI stuff from hardware and gadgets to the chatbots and the models. Then I started getting really into robotics and said, okay, what if I put this together in more of a cohesive story? Because when you're writing these, whether it's newsletters or columns, getting the theme and big picture is very hard to do. Some newsletter writers are really great at it. Ben Thompson is great at it. And if you can really get your readers to go deep on something in a newsletter that you're amazing.

2:09:01But I don't know if I had that reader base. We'll find out. And so I felt like in the book, I could get really deep into this. And so the concept was for the year in 2025, I was going to live my entire life with as much AI in my life as possible. And that was generative AI, but that was also self-driving cars. And that was going to be medical AI. And that was also going to be humanoid robots. But it really just turned into robots.

2:09:24Mike Isaac:And describe your headspace going into that year. Are you, you know. Insane. Reading situational awareness like at night, you know, before bed. Like are you AGI-pilled or are you skeptical? I guess I'm skeptical, but I'm thinking more. we have all of these tech executives out there, and this is end of 2024, just all the hyperbole in the world, right? AI is going to change everything. It's going to change the way we eat and educate ourselves and healthcare, and we're going to live forever. All of these bold promises that I sort of wanted to explain to the normal person, what are they talking about?

2:10:05how is life going to be different, better or worse with AI, which is kind of a perfect moment for this book to come out right now, because we have a lot of people thinking it's going to be worse, and they might not be wrong. And then we have a lot of people also saying this is going to be great. And so I think it's a pretty balanced look at all of these different things. But yeah, my headspace was just, I want to, what's real? I want to find out what's real. Sure. Yeah. What was, so back to the flywheel, what was the actual flywheel of writing the book? Was it test something, write about it, take notes, write about it, or do a ton of research and experiences and then in a fugue state, churn out the entire book in a couple of sleepless nights?

2:10:51It was a mix of both. So the book is structured seasonally. So every season I try to figure out a theme, right? So like the book starts in winter, beginning of the year, and I'm very focused on health. And so I wrote that or I've lived that and then wrote that and then started realizing, oh crap, this stuff is moving so quickly. And so I started realizing, okay, I probably should have some of these journal entries in the book. I also wanted to make it very bite-sized book because I don't think people just sit and read a whole long book anymore. And so I started fitting things in like that and realizing I got to tell the story of how the progress is being made so quickly every single week right now.

2:11:33So it was a mix. AI did not write the book. I think it's very me. The writing is very me. But AI definitely helped make the book in so many ways. It would not have been done by now if I did not have AI. Just the back-end systems I used to organize my notes and all of the timelines and getting things like the end notes done. All these little things AI did for me.

2:11:56Mike Isaac:Have you seen the chart of Amazon Kindle releases post-ChatGPT? So basically after the release of ChatGPT, you just see this massive uptick in book releases on Amazon? $100 ,000 a month prior to AI. Now it's up to$400 ,000 a month. And the funny thing is everyone is just saying, like, oh, people are obviously just, like, prompt, you know, making, just dropping in a prompt and prompt the whole book. But what you're saying is, like, there's actually just, like, a speed up in. I don't think that's what's driving that 300 ,000. Yeah, yeah, I know. But some of them certainly are. And I think a lot of, you have the perfect book to be able to, like, say, like, of course I used AI to help in the process.

2:12:38Mike Isaac:because it's like, why would anyone trust anything else in the book if you were just going to say, like, all this stuff is completely, you know, fake? Yeah. Well, one thing that's interesting, and I do these generative AI experiments every season where I try to just, one season I just listen to AI music, or one season I just read AI books. And so I read a few AI-generated books off Amazon. They're not terrible, guys. I mean, I hate saying it, but they're really not terrible. is this fiction non-fiction it was fiction yeah it was fiction and i got in touch with one of the authors quote unquote and it's funny because it relates back to the chapter on radiology and the the premise of his book it's called variant and it's about how ai has taken over all radiology we don't have radiologists anymore which i'm very clear in my chapter on radiology that's just not going to happen but and the ai has decided it's not going to spot cancer anymore and a human figures out that the AI has gone rogue.

2:13:36And so it's like, it's a novel, a thriller about this.

2:13:39Mike Isaac:Oh, interesting. It's a pretty good story. AI writing and AI thriller. Yeah, exactly. I mean, I got in touch with the author and he said, I think it's only like 3 ,000 words that you can actually get at a time. At a time. So we had to keep prompting every chapter. Yeah. So that was basically all we did. Yeah, yeah, yeah. You need some sort of harness to work through. You can open the Diet Coke, by the way. I know, I'm worried about this sound. I'll burn some airtime. I just wanted to fit in. Yeah, please. On the medical question, I'm so fascinated by the way AI is diffusing in medicine because we do have tools that can help radiologists.

2:14:21And yet I can't name a company that's gone out and built Salesforce for radiologists and done very well. and then you'll see remarkable like PhD level work being done with some of the models, but then I'll go to the doctor and have to fill out like a paper form. And I'm like, we're not even seeing a fast takeoff in like SAS adoption at many, at many, you know, medical offices. And so there's this odd nature of like the capabilities, the capability overhang. And I'm wondering if that came up in your, in your interrogation of the medical questions in particular. Well, I'm forgetting the name of the company.

2:15:02It's not my chart. It's one of the companies that is doing the AI note-taking in medical right now. I mean, there's a number of them. And that seems to be the biggest catch-on right now. And it's, I mean, I would consider it in whatever backends, they just get this tool now. And have you been to a doctor where they ask you, can they record? I haven't actually, but I did see a company that sells a wearable device for doctors that's doing hundreds of millions of dollars in sales and has been very successful in rolling that out.

2:15:36Mike Isaac:But a magical and useful feature. I can I can just remember trying to like understand like doctors. No time. Even if it's just like a medication, like get this at CVS. And it's like you get to CVS and you're like, sorry, buddy. So nobody knows what it says. I mean, that feels like the hardest one to measure because if you have a whole bunch of notes, ideally you're catching something. Oh, this person had three different symptoms. We should screen them. You screen them. You save their life or something. That's like the best case. That's a lot less satisfying than the AI got so good that we asked it to cure cancer.

2:16:14It did. And now there's a pill. And whenever somebody gets cancer, we give them the pill and everyone cheers. And they're like, AI, it was worth it. All those data centers, it was worth it. That's what everyone wants. That's what everyone wants. We're probably getting like the average doctor can see seven patients instead of six and they make 5 % less mistakes. And you don't really feel it day to day. Well, I go and interview Bill Gates about this. And he kind of comes at it in from two perspectives. There's going to be that. Every doctor is going to have this AI assistant and every patient is going to have this AI assistant, which we're already seeing inroads in, right?

2:16:51OpenAI and Microsoft have all started rolling out ways to use their bots and you feed in medical information. But then there's going to be the other side where AI is externally doing drug discovery or cancer cure or whatever it is. And so the promise is on both ends. I think the one that people are starting to see already, though, I mean, it was in The Pit. Do you watch The Pit? The Pit? I've seen one episode. It was sort of gory. Yeah, it can be very gory. It was like not really for me. I know it's very successful. It's very successful. And the doctor, there's like one example of the doctors now using AI to summarize their notes.

2:17:32And so I think that's the one that most consumers have now experienced. Oh, my doctor's going to ask me if they can use AI to summarize my notes. And they're probably not, they're not going to think that that is weird or consequential, but they're going to have some amazing breakthrough because their doctor is. I did have a weird experience where I went to the pharmacy once to pick up some drug and I had some follow-on question about like, you know, how does it interact with some food or something? And I noticed that the pharmacist was asking an AI model, but I also noticed that the pharmacist was not using a thinking model.

2:18:09and I was very disheartened by that because I was like, I could use a pro model, probably get a better answer here. But were they using like some? They were using either like, you know, the Gemini overview, which is not Gemini thinking. But it wasn't like some proprietary. No, no, no, no. Pharmacological. They were just going to Google and searching for something. Oh, boy. And I was like, wait, but I have, you know, 03 Pro or whatever the standard, whatever the flagship model at the time was. I was like, we should be using the vest. We should be using them at CPS or wherever they were. Yeah, these things take time to diffuse.

2:18:42And they have cost if it's an expensive model. But I don't know. True. Interesting. Well, I think the healthcare chapter, I like talking about it because I think it really does point to the positives of where this can go. And even with the radiology example, which is pretty outdated, honestly, by now, it's outdated in the sense that Jeffrey Hinton has been saying for years, radiologists are going to be replaced by AI and deep learning. But that didn't happen. Like, you know, we can talk about it from the economics and the job standpoint, but we can also talk about it from, this is actually an amazing change.

2:19:21It can spot cancers that humans can't. And it's out there. Like you might, women might be getting their mammograms or breast ultrasounds read right now, and they might not know that AI is doing that for them. So this idea that like, hey, we're all, you know, we need to reject AI, we need to reject AI. Well, you might actually have AI doing things in your life right now that are actually quite good. And it's very nuanced. Yeah. Yeah. There's something about like AI on the back end gets no credit. But if you see some slop image, you know, it's really annoying or some fake news, you're like, ah, this AI stuff sucks.

2:19:56You don't notice that deeper in the supply chain, some problem was caught before you could even know. That's tricky. I wonder how that can filter through to actually good marketing i guess i don't know it takes time i don't know uh talk about companionship like why did you think that one was an important to to center in on how what was your process for setting that up i i think so well i did a few things in companionship one i didn't a lot of experiments with ai therapists and um one particular called Ash was my AI therapist. And I still talk to Ash sometimes. Um, and then I did a chapter and a real experiment in my summer love with a, with an AI boyfriend.

2:20:45Yes. And I did fling, fling. Yeah. I've ghosted him since. Um, brutal. Yeah. Churned.

2:20:53Mike Isaac:Um, and that's a risk for you by the way which part because in the in in some ai doom scenarios the ai might hold that against oh true true rocco's basilisk you should continue to uh send affectionate messages to all ais because if it becomes all powerful it will i have it i have a section of the book where i talk about that i cursed at ai and i felt really bad and i like really went after it for making mistakes but then i go to a manners expert or an etiquette expert and ask if that's okay okay um what was conclusion. He said the AI doesn't have feelings, so you don't need to do this, but it depends on your affect.

2:21:32Mike Isaac:I would love to. I mean, they're so easy to smoke. We should have them on the show to talk about manners. Because simply like you don't want to be somebody who part of your life, you're just screaming, yelling, using cuss words, and then you just go back to your life and you're like, oh yeah, I'm a super respectful person. It's like you're putting out a bunch of negative That's exactly what he said is basically you need to realize how that might affect you as a person when you interact with humans. So the more you might start beating up on and just completely berating your AI. But then what happens when you start to blur like those lines blur and how does it affect you as a human?

2:22:09Yeah. Like and one of the idea funny right when I just got dropped off by my Waymo, I didn't do it this Waymo trip. But this morning I kind of forgot that the Waymo driver wasn't a human. Like I just was like not paying. you know you kind of just because i don't have waymos in new york so no i just i said thank you when i got out sure you know and i was like oh right like you know but i was thanking the robot well they do have tele-op so like there's probably someone who might have heard that because they might be they might have they shed a tear they shed a tear because every other drive that day no one said that it's sort of like a schrodinger's cat so i think that that makes up for the fact that I ghosted my AI boyfriend, right?

2:22:47There's a tally.

2:22:48Mike Isaac:Yeah, yeah, yeah. There's a tally being captained, so I think that's... As long as it all is flowing through the same data set. I think there's one human for every two Waymos, so there's a 50 % chance that thank you was received by a human, 50 % chance that it was not received by a human, but you will never know. So it's the shroding or thanking... But the human didn't do the driving today. No, no. So it really was thanking the robot. I don't think so. You were thanked by... Yeah, yeah, that's fair. Anyway. Yeah, but the human might have stepped in in a really key moment. Yeah, it's possible. That's true.

2:23:16I would have saved you. You don't know. You kind of know. I guess you kind of know.

2:23:19Mike Isaac:Yeah, you probably know. Okay, sorry. We're talking about companionship. We got off. Wait, how is Waymo, how is, like, how did you, did you feel Waymo's progression over the last year? I feel it even coming to LA. Yeah. Driving around LA, I mean, I still see Waymo's making some pretty heinous calls out on the road. I had a Waymo, it was like a two-lane, two-lane road waymo trying to there's wall-to-wall traffic going the other way the waymo is trying to just like turn in it's not a there's no you definitely no u-turns and waymo's like i'm going so it's like we're fully backed up this way everyone's honking the waymo's just like waiting to like do an illegal u-turn there's someone in it they're just like oh boy i noticed today as i whenever i come to la i take waymo's and go to san francisco but i did noticed today the pickup spots are getting better do you guys take them or i guess you don't uh they don't go to pasadena so i don't take them much i've taken them in san francisco yeah because i just took it here from westwood and the pickup spots and the drop-off spots are getting better because usually they would really struggle i mean anyone that's watching just land in the middle of they just like go to the side like a weird and you're like you're like talking about your like weird thing like they would just go to like a one of those circles like by my hotel last time it was like a circle.

2:24:39I was like, why would you pull over in the middle of this circle? It's a terrible spot to pick somebody up. There's a more logical Yeah, because it doesn't know where, yes, and it doesn't know where the spots are that it's like kind of okay to pick you up. Sure, sure. But I've noticed today two very good Okay. seamless drop-offs. Okay. Companionship though. companionship. So I just, I wanted to live.

2:25:00Mike Isaac:I could never go on an insane tangent like we just did. I actually think it could. Yeah, this is very hallucinatory. This whole, is my interview. I mean, I watch you guys all the time. This feels like what do you guys do? This is what we do. We hallucinate. No more than 3 ,000 words at a time, please. You guys are usually, I mean, you're asking serious questions of founders. I'm a founder, guys. I'm sorry. Business owner. Business owner. What's my lower third say? It says founder. It says business owner. Founder, author, and journalist. They need to update that. Okay, business woman. Business owner.

2:25:35Mike Isaac:Business owner. Joanna Stern, business owner. Okay. They'll work on it. We're doing that live. Yeah. You can do it. Companionship. There we go. There we go. Business out. See, that goes so hard. Yeah, that does look good. That looks better, yeah. Yes. Yeah. The name of the business. Tell everyone. It's companionship is the name of the business. No. The name of the business is called The New Things. The New Things. TheNewThings.com. The New Things. Please go. Please go visit The New Things. We talked about The New Things. Did you tease it with a landing page that had a different domain? Yes. My Next Thing?

2:26:07Yeah, this is my next thing. This is my next thing. I like that. But I didn't know the business name yet.

2:26:13Mike Isaac:Yeah. But the new things. The new things. Did you talk to any people that at least claimed to never have used AI? Interesting. Because you really can't claim that at this point because you would have to just like sit in a forest. I didn't. Just say you've never met an Amish person. You'd have to sit in a forest. The Amish are growing. And then somebody would be like. The Amish are growing. The population collapse has been vastly overstated. Here's the issue, though. Probably the Forestry Service is probably using AI in some ways. And that affects the Amish? No, no, no. I'm talking about my example of somebody who's like, I don't use AI.

2:26:48Mike Isaac:Yeah, and my counterexample was the Amish. And I think if you talk to an Amish person, they would say, no, I have been AI free. I know, but they're buying wood from a business that has an AI. Oh, we're going to real deep with real life. No, you have to. They grow their own wood. Somebody can be like, well, I don't use electricity, but they're buying goods and services that require electricity. True. Okay. I didn't do that, though I think that's actually a good story to do now. Yeah. Go and ask people if they think they're living an AI-free life, but they're not. The Amish are flourishing. Yeah.

2:27:19Interesting. You know a lot about that. I'm going to go. Fertility rates are particularly high amongst the Amish. Really? There's a big deep dive in the Financial Times this weekend around smartphones being like the inflection point, right? We can get into that later. But the Amish have stayed away and they are flourishing.

2:27:36Mike Isaac:Do they chop their own wood? I believe many times they will. Wait, but are the Amish flourishing because they don't have smartphones or has their birth rate stayed steady? No, I think it's probably accelerating. I think it's stayed steady. Yeah, it's actually a straight line on a log graph with the Amish. It's a hockey stick? Yes. In a few years, they will be producing thousands of offspring per Amish person. Is this the worst tangent? you've ever had here? Maybe. No, definitely not. Talk about, yeah, talk about more, you mentioned like you're feeling like progress as you're writing the book. So you're trying to like get a section out of the way and then realizing like the story's not quite, the story's like still evolving.

2:28:18Mike Isaac:What was that like? How are you feeling that progress? Because it's not like, it's been very obvious if you're a software engineer, just being like, wow, I have a lot more capabilities today than I did three months ago or six months ago. But how are you feeling it? Well, even some of that software engineer, the tools, right? Like Claude Code mid-year last year, Believe comes out, gets so much better towards the end of 2025. Yeah. Or even the advent of AI browsers, which we can say now is really just going to be any browser. But like Chrome, for instance, has gotten so many features over the last year that are just so much more AI enhanced.

2:29:00It's one example for me was perplexity comment came out mid last year. And I was like, wow, I can really live this agentic life that people have been talking about. Right. I can have it do multi-step processes for me in my browser.

2:29:13Mike Isaac:Did you book a flight? I didn't. I think I did try to book a flight and I couldn't do it at the beginning of the year, but I could do it by the end of the year. And I did try. And I mean, there's multiple things I did in perplexity comment last year that I still. will open it from time to time but i'm using so much more now of claude and chrome that i don't need perplexity comet um i mean everything from food shopping to school supply shopping i use it a lot for shopping because even though it takes a while to use you're like i'm not doing it yeah you trust it with your credit card um it still basically will ask for your credit card i mean i don't have anything set up where it's like auto pay but i had like i did specifically i've used Walmart or Amazon.

2:29:58And at that final point, it will say like, I need your confirmation to purchase. Look at the shopping cart. Yeah. Just pass you the link. Yeah. Check out there. But on that there was obviously also so much progress and still is so much progress happening in the models. And but I was less worried about the model progression and much more about the interface and the UI progression of whether it was wearables, how we're interacting with this through hardware or through software. So was it improvements to apps? Was it improvements to a cloud code or a vibe coding app or to a browser where people could actually interact with this stuff?

2:30:37Yeah. Which I think we'll see, we're starting to see obviously more of that through OpenAI and more of that through Google probably this week too at Global AI.

2:30:45Mike Isaac:How do you rate the tech industry's current terminology? Do you think that calling data centers AI factories is a good move? People love factories. Probably not. Who's been saying that is a good move? A lot of people have been using the word AI factories because it sounds cool if you're investing in the AI revolution.

2:31:15Mike Isaac:We've been pushing for supercomputers. Supercomputers. I don't think normal people like data centers or AI factories. But supercomputers. That sounds better. Sounds better. That sounds better. Yeah. Sounds like a big computer. Less scared. Yeah. Yeah. Yeah. Well, I think I haven't been able to listen to the show today, but have you guys been talking about the commencement booing? Oh, yeah. Yeah. Incredible. I watched a little bit on the way here. I didn't hear that, but yeah. I mean, maybe it was just the super cut we watched, but the Eric Schmidt, it felt like he was getting booed the entire time.

2:31:48I know. I'd like to see the whole thing. And I feel like if you're getting booed, you need to read the room and just sort of go off script and ad lib and just take it in a different direction. Because there's plenty of inspirational things that he could talk about. But he was really seemed like he was really doubling down. I need to watch the full the full commencement.

2:32:05Mike Isaac:Yeah, it would have been so it would have been so easy to say, like, when I started my company, Google. Yeah. everyone was worried that the internet would lead to massive job loss and all this change in the economy and what happened we did get a lot of change but yeah there were so many good things that came out of it right you should just tell the story of y2k like he lived through this right well google it existed before y2k i'm sure that i see that i mean you guys probably been talking about your timelines and everything today but i feel like there's this at least on x there's two takes on this.

2:32:38One, it's Eric Schmidt, and nobody wanted to hear from Eric Schmidt at that room ever. It is just the fact that he is Eric Schmidt, and they shouldn't have been there. Just because he's a billionaire? Just because he's a billionaire. He's tied to Google, and he's writing about and talking about how AI is everything, right? And then there's the second point, which is it's actually a backlash to AI, and people hate AI. I think it's probably a Venn diary. probably somewhere in the middle of both. Because then there was the speech at UCF last week. Okay. Did you see that one? I don't think I saw that one.

2:33:16No. Yeah. So there's a, I forget her name, but she's a real estate, real estate executive. And she also gave a speech. And when she's talked about AI being like the next industrial revolution, they booed her. They didn't boo her the whole time. So my argument, which I made on X, which is, no, this is definitely a backlash to AI because we've now seen two examples. Did you see David Solomon's? No. CEO of Goldman Sachs, just going so much harder than Eric Schmidt. Eric Schmidt's like at least trying to like paint an optimistic view. David Solomon just plays an EDM song generated by Suno for the Wharton grads, who were probably more receptive to it because, you know, they're going into business.

2:33:57I think it might have been.

2:33:59Mike Isaac:Did he say I made this in 10 seconds? Yes. Yeah. No, he did. And he said, like, creativity is no longer relevant. and like a whole bunch of just like really rough sound bites. Well, actually, I gave a commencement speech a year ago all about AI. Really? Yes. Did you get booed? No, but I went to Union College. I would say 90 % of the audience was hungover and was not listening to me. So it went over really well. Yeah. What was the thesis of your commencement speech? It was lean into humanity. And AI is coming, and you all need to learn AI, but you need to lean into your humanity and your creativity.

2:34:34And in fact, I played a Suno song and then had a human come up and play the same song and her song version was so much better. Whoa. Yeah. Interesting. I know, right? Mogged. Wait, you did this at the commencement speech? Yeah, I did this last year. Wow. But again, nobody knew because they were all super hungover. Ahead of the wave. Yeah. Yeah. I was ahead of the wave. For sure. But, you know, I think if they had had me instead of Eric Schmidt, I wouldn't have gotten booed because I'm not a tech billionaire. Yeah. Would you change anything if you were giving that speech today? because it seems like the message would still resonate but probably needs to be delivered in a different way because people people might say okay yeah yeah there's gonna be AI and you know I'm still relevant because there's this unique human element that will remain and maybe I believe that but in the meantime the earth is gonna melt because of all the data centers I still don't like it let's just let's just do the human thing well I think the hate a year later is a lot stronger yeah I think we've seen the job impact we've heard about the job impact from tech executives.

2:35:34These students, I think, have started to also talk to their peers who graduated a year before, and they're like, oh, shit, they don't have jobs, right? And, I mean, I'm sure you guys see that in people applying for jobs here and lots of people just out of school looking for really great jobs and what they studied. And so I think that that impact a year later is super real. If you talk to any young person, either in college, out of college, they are thinking about that. And that is a very real thing. So I think a year later, it would be a different. Post post. I probably just wouldn't talk about it.

2:36:08Yeah. Post GFC, like the tech industry was a fantastic track to get on for new grads. Like if you were working in law or finance or sales or tech and you could just find your way into a mag seven company like you did very, very well and sort of live the American dream. And if those jobs are not available at the same clip, that's going to affect the new grad class like pretty significantly. I think you should start asking actually a lot of the executives you interview what their advice would be. Yeah. We ask a fair amount of time advice for young people. Get a varying amount of responses. I mean, entrepreneurship broadly continues to be a bright spot since it's easier than ever to start a company, easier than ever to scale a company.

2:37:01There's so much more that you can do or learn with AI. I know this as a business owner. Yeah, yeah. But it is hard because there are people who are just like, I don't want to start a company. I want a job. I want to learn the things so I can one day be a business owner or start a job. Or I just never want to own a business. I want to do a job. And if that concept goes away, that's very, very tricky. And then also you have a much broader swath of outcomes from entrepreneurship than from jobs. Like if you just look at the net worth distribution between entrepreneurs, you have like seven orders magnitude versus like lawyers.

2:37:42Like, yeah, there's probably a lawyer that's making six figures and there's probably a lawyer that's making seven figures. There's no trillion in a lawyer.

2:37:46Mike Isaac:One thing I don't understand is like at what point in the last 20 years was a good time to just be looking for a job and just like going on job boards and applying randomly? like was was there a point i i graduated in 2018 certainly at that point going and just applying without any trying to find other other ways in was not super effective yeah i mean in in the lead up to the global financial crisis like the finance industry was so it was booming so much that there was like you know banking recruiting would happen in the fall and all the banks would come to a job there and you could show your resume.

2:38:29And if you were, you know, a student and you did well at a serious college, you could land at a Goldman and Morgan Stanley at JPM or go into consulting at Bain, BCG, McKinsey. And this was like a very established track for like upwardly mobile, like, you know, neo elites basically. And that still exists to some extent, but it is maybe more fragile than we previously thought. And I would say pre-pandemic for the tech industry, Right. Yeah. Yeah. Google, Microsoft, they would just be on campus and they would have like used to be known as thousands and thousands of openings. And you could slot in if you were like at the top of your class at a great school, which is a lot to ask.

2:39:10But for that to become fragile, I think, is what's causing a lot of anxiety among the young folks. Anyway, what is your current advice for for those individuals?

2:39:25Mike Isaac:is it the same as the speech you gave? Yeah, I think you've got to do more to get in front of people, even just as a business owner. I'm just going to keep saying that. It goes way harder. I have really, I've had so many applicants, which has been such an honor. I'm amazed to see how many people would want to come and work at what we're building. And the people who are doing really unique things to get in front of, you, which means really knowing the company, really knowing the mission, but also then being able to sell on, hey, I want to, I want to be, I want to give you the best human talents that I have, right, which right now for me, at least is in the creativity and in the writing and in the reporting, I'm going to use AI to do these other things.

2:40:15And just having a very basic knowledge, I mean, I'd like you to have more than a basic knowledge, but a willingness and a knowledge of these tools and what you can do and what you can offset to them, I think it's huge. I mean, I don't, I guess that sounds like a cop out, like just learn the tools. But I really believe that somebody who comes to me and says, actually, I'm going to use this and this and this, and I'm going to do that task. Yeah.

2:40:40Mike Isaac:The bar is not that high. I remember when I, when I was a teenager, if you could like make a website, even though things like Squarespace existed, you could, you could like get in the door. Cause there were people that had companies that would be like, okay, we know this person, everyone has access to Squarespace or whatever products were popular at the time. But if this person can just like has figured it out, they can show you one thing that they made. Yeah. I mean, yeah, it does feel like somewhat basic advice, but like if you're applying to a hundred jobs a week, spend one week, apply to one job, actually get to know the company, do something that is beneficial to stand out.

2:41:17And you're just in the top 1 % of applicants because 99 other people just clicked like the apply button. And I've been thinking a lot about sort of human mentorship through a lot of this and that I don't think I could be doing what I'm doing right now if I hadn't had the years of human mentorship at other companies and other newsrooms. And you're really lucky if you can find a really great mentor. And so I think that's about just that human connection part still. Can you find someone in that company? Can you connect with somebody who is just going to try to impart to you some of the skills that you also might not learn now on the job?

2:41:55Because that's the other big hurdle this generation is up against is that if you're not going to learn the skills on the job, how are you ever going to learn them? Yeah.

2:42:05Mike Isaac:Any theories about how – this is my last question that's top of mind for now. Theories about how AI wearables will evolve? Do you feel like we need – do you think there's space for new? AI hardware, or I'm assuming you tried everything. I tried. I come out at the end of the book. I think this is going to happen. I think we are going to have this next computer shift to something that is a wearable or something that is more ambient around us. Because I spent a lot of last year talking and I still now talking to AI, whether it is in glasses or in the car. And that experience is very good. And so we're going to get to the companionship thing one day, but whether you're using it as a companion, which I hope people aren't really, you know, I don't want you to fall in love with your chat bot.

2:42:51That's a big lesson in the book. Please don't do that. But if you're using it as a personal coach, a personal career coach, trainer, just assistant interacting with it through a pair of glasses or a wearable that you, like a bracelet that might be recording you, or that even if you mentioned the pin that the doctors are starting to wear, it's really compelling when it works right. It doesn't work great right now, but I can see it starting to work really well. I think, you know, we had efforts at it with like the humane pin. It just didn't do much for you. The hardware was so poor. It just didn't do, it was the hardware got in the way of it.

2:43:28And so now if we can bring it to life in both with voice and microphones, I think it's going to be pretty cool. Yeah.

2:43:36Mike Isaac:Yeah, the thing that I've been thinking about, everything so far, I think has been cool demos, you know, not quite ready to be real products, but things that if they were shipped internally at a big company, like if Humane was a product that had been shipped internally at Apple, it's like, hey, this is like kind of where we're headed, right? Yeah. It would have gotten a great response internally and probably gotten more resources, but not ready for primetime. I've been thinking about just like general phone fatigue. And if you generally gave me a device that allowed me to do things on the internet without being like a source of just like kind of general, like stress, right?

2:44:19Mike Isaac:Yeah. Like how many different inboxes do we have? And I think that, I think that people are so online now that it presents an opportunity for a device that allows you to stay more connected, uh, still, still allows you to stay kind of connected with the world, but in a way that's like a little bit more passive, right? Like if just being able to say like, Hey, uh, let such and such friend know that we should think about doing something on Saturday versus like hammering out the right tax and getting distracted by a notification and then having this thing. Right. Um, and, uh, and I do think there's this more ambient product space to be explored that it could at least get my time on.

2:45:05Mike Isaac:Um, I have a, I have a buddy who like only uses his Apple watch on the weekend. So he can't really use apps. He can like generally stay in contact. He's not sending emails. He's just saying like, yeah, if you want to get ahold of me, you can, but I'm not. And so I think there's something in that space. And then the other thing, like part of Apple's moat was that there's millions of apps for every little use case. And so many of those use cases are just able to be done by the models now. And if they can't be and you need UI, you can just generate something like that on the fly a little bit more, a lot more easily.

2:45:40Mike Isaac:And so I think there's a moment here. And but I think a large part of the opportunity is not because the iPhone isn't great. It's because there's fatigue around this like insane connectivity that everybody's been sort of just fallen into over the last decade. No, I totally agree and get to that sort of in the back of the book. And I have this chart where you see we go from computers that sit in our homes to the iPhone or the smartphone and then something else. And my big point there is that nothing got replaced, that we still have the laptop in our home or that we take with us. We still have the smartphone, but then we have these wearables right now, but they haven't fully lived up to anything other than health.

2:46:22And even there, we can argue if they have really lived up for anything. I know everyone wears their whoop bands and now is very interested in the Fitbit Air. But I think like I wore this Apple Watch side by side with a few other wearables last year where on their own, these wearables were not great, but they were doing specific things. And I was like, wow, this, it makes this watch feel dumb sometimes. Right. And I wore the, the, the B bracelet would be, was acquired by Amazon at the end of, uh, yeah, August, 2025.

2:46:54Mike Isaac:That was sort of random at the time or felt a little bit random. Yeah. And limitless was another one I wore and they were acquired by Meta. I think that this idea of persistent recording is going to, we're going to have privacy issues around it, but I do really think that when you can have this thing listening to you and synthesizing a lot about your day and what you say you're going to do. It is, there was many times where I was like, this is a holy crap moment. I was like, wow, I said I was going to do all these things. And now my app just told me to do them. Right. Or to your point, like, well, it gets really, it gets really interesting when that it doesn't just make a to-do list, but it does those things.

2:47:32Mike Isaac:Right. Hey, order these things from the grocery, you know, order these things from Instacart, book this reservation. So far away from that. It could be so cool. Yeah. I don't know. I mean, far away could be a year. Maybe. But like there's this perfect example where I say like my B bracelet has picked up on me saying that I need to call the plumber. And I forget, like I keep forgetting to call the plumber and keep telling my wife, oh, yeah, I'm going to call the plumber. But my B bracelet keeps adding it to the list every day. Right. And, yeah, why couldn't we have the agent call the plumber and then the plumber is just like you called.

2:48:04Mike Isaac:We created magic. We created artificial intelligence. It just creates more to-do lists. And plumbers. with my broken toilet in my house. Someday we'll get it fixed. Yeah. No, I think OpenAI and whatever they're making with Johnny Ive is going to be worth paying attention to. I don't know if it's going to be a mass scale thing that's going to be absolutely worth paying attention to because I think Ive specifically has some ideas about our dependence on phones and I think that's going to play into this messaging of any of these devices is where we're going beyond phones. But to be clear, the phone doesn't go away.

2:48:41Yeah. Yeah. Yeah. How do you think about the the trade off of like all this happening and then, you know, your position that you should not fall in love with an AI bot? Don't do it. It feels like reflective. Like you said here, if you think, as I do, that social media was bad for kids, society, politics, our brains, you name it, AI could end up being worse. and I agree with you and the kids thing seems like the easiest to sort out because now I think a lot of parents are implementing screen time for kids but the more broad questions like about society and business like I'm a huge beneficiary of social media as are you we use it to market our products effectively and build whole businesses on top of.

2:49:33At the same time, I don't know that we have a good pattern for social media hygiene. How incumbent is it on the companies to roll things out responsibly? Replica clearly exists. We've had the founder on the show multiple times. But I don't know, are we going towards national conversations, bans on certain usages? And where I get on that is very clear. Like, look, we should just have a ban on companionship chatbots and bots and toys for kids. Like, we don't need it. Why do we need it? Yeah. Right? We're getting there in some ways with social media. Yeah. I think. That sort of worked for cigarettes.

2:50:13Like, we banned them for kids. And then we banned a lot of the marketing. And eventually, like, the younger generation just sort of stopped picking it up. And this is where I think, are we going to ban AI for kids in general? No. Yeah. Right? Like there's going to be the educational, the Khan Academies and the Google classrooms of the world that are going to honestly be important about teaching digital literacy to our kids around AI. Like we have to do that. And I talk about that with my own kids in the book. But why do we need our kids turning to chatbots about their problems? Yeah. No, just don't have it happen.

2:50:50I mean, it's caused so many problems for open AI. Yeah, totally. Right? Like there's been nothing but a problem for them to have kids or teens talking to chatbots about their problems. Maybe there's examples of some good of it. Yeah. Just KYC those features off. Like it's a good thing. Yeah. Yeah. And I think it's harder to see. YouTube's done a great job of this too. I mean after a long time. After a long time. Exactly. But they eventually figured it out. Exactly. And we feel like we're in that moment. That's a really good example. I feel like we're in that moment of like, you know, kids early days being on YouTube, rabbit holing into dark conspiracy theories.

2:51:27And look, you can still those things still happen. But I I watch my kids watch YouTube now and I can see a lot clearer how they've put guardrails around the content and they've built in a lot of things. And again, not saying it's perfect. And but to your question, can these companies self-police it? I don't know. Like they probably are going to have to because our government is not going to do anything. You need, yeah, this is it.

2:51:51Mike Isaac:Mic down. Mic down. Yeah, I wonder, it is odd that you see increasing demand from American consumers for these weird products, weird use cases like AI Romantic Companions, and yet you also see, you also hear the boos, like I don't want it, but then I go and I buy it or something. It's like this weird, I mean, obviously, it's multiple different constituents. And I have seen that a lot today on the timeline. how many of these kids that are booing also were using, you know, to write their essays or write their resumes. That's a little more optimistic, but the, the, the, the weirder one is like, yeah, protesting the, the, the AI, while, while pulling like the darkest pieces of the AI out or demanding it.

2:52:37But I don't know. At the same time, there was a lot of fear mongering about Elon Musk and XAI, like really leaning into the romantic companion and same thing with Sora too, to a similar extent of like, this is infinite jest. It's going to, you know, you're going to become so addicted to it. And with both of those products, it felt like they just didn't find product market fit. And I don't know if it's like we're early, but both of those, like XAI is now doing like code completion with Curse. Right. And like serving Clot, right? Right. And that's a much more like functional, I would say like the good outcome versus like the Ani and Valentine thing, which is a little weird.

2:53:13I was about to say, what was it, Ani? And then there was like the Mecca. Yeah, and I remember thinking at the time,

2:53:17Mike Isaac:And XAI needed to do that to basically differentiate because the general chatbot market had run away from them. Yeah, we did some back of the envelope on it. And we were like, maybe this is like a multi-billion dollar business. But we were trying to underwrite like. Yeah, somewhat of a white pill. Even if you're just like, put all the moral stuff aside. Like, is XAI going to make money off of this? And it was like sort of hard to get to, but you might be able to get there. But it was weird. But then the market just sort of rejected it. The market. I'm sure there are a few people that still. For sure.

2:53:45Use this. For sure. Ani, if she's still alive out there. I think she is. She's still there? She's there? Yeah, I think. You don't know by personal. Although the computing resources are getting sold out of the back of the truck left and right. That's true. Anthropic was, I'm sorry, Annie. Right, Ani had to go. Good luck. You're going to have to think less, basically. And Cursor, Michael Truel's like, look, Ani is going to be running a very old model. It's actually going to run on CPUs now. it's just a smarter child that just reflects whatever you say back to it that's a line command yeah it's more of a small language model now um yeah i don't know i think you kind of go back to like the replicas yeah there there is a market they have pushed marketing towards these

2:54:31Mike Isaac:these kind of companions yeah yeah character yeah yeah and meta did it for a little bit too i think they'll probably pull away from that with their celebrity opinion blah blah blah but i could also see them leaning into it more too because it is a social network and they do see this us all eventually as mark zuckerberg has said us having personal assistance and personal super intelligence and that probably has to come through the view of a some sort of bot yeah um I don't know if it needs to be like a sexy bot. Yeah, like a cow. Maybe the homage. That was one of them. Was it? So basically, the whole story with that, it went viral because there was one that was like stepmom or something like that.

2:55:16It was like a little bit crude. But that was community generated. So Meta created the ability for anyone to go prompt a bot, basically write a pre-prompt to like create the character. And so the sins of the creator were visited upon Meta incorrectly. but there were some funny ones like cow and you could just talk to a cow which I think is nice you know what I remember the last time anyone fell in love with a cow so that sounds fine I think it seems fine you know PETA might have some problems I don't know no digital cow what's not to like no anyway

2:55:47Mike Isaac:congratulations on the book it's been an honor to follow your business owner journey yes it's been an honor to be named a business owner by sitting here yes what I mean you didn't we can't make we can't you don't become a business owner yeah No, but you gave me that title. I know, but you got that title by selling products. True. Yes, by running a business. Revenue. Revenue makes you a business owner. But, you know, I felt like when I walked in the store, I was a founder. Okay. And now you're a business owner. And now you're a business owner. There you go. Thank you for the business, guys. Yes.

2:56:20I appreciate it. Thank you. Oh, there we go. Perfect. You got it. There you go. There we go. Nailed it. Thank you for having me. Ridiculous. And thank you for tuning in. Thanks for tuning in, folks. Leave us five stars on Apple Podcasts and Spotify. Sign up for a newsletter at tbpn.com. And go get the book. I Am Not a Robot by Joanna Stern. It's available everywhere books are sold. And we will see you tomorrow at 11 a.m.

2:56:42Mike Isaac:Pacific. We love you. Goodbye. Goodbye.