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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
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Speaker 2:You're watching TBPN.
Speaker 3:Today is Thursday, 03/19/2026. We are live from the TBPN UltraDome, the temple of technology, the fortress of finance, the capital of capital. Let me tell you about ramp.com. Time is money. Save both.
Speaker 3:Easy use corporate cards, bill pay, accounting, and a whole lot more. Don't test me with the soundboard. Don't go soundboard for soundboard with me. You know I got you. A narrative violation.
Speaker 3:I know. We're having some fun.
Speaker 2:We're we're out of control.
Speaker 3:We got a great show for you today, folks. Carl Eschenbach is Eschenbach at Sequoia. We love to see it. We had the pleasure of chatting with Carl a couple months ago, and I've always been a big fan of his, but we'll we'll let him introduce himself. Let's pull up the Linear lineup.
Speaker 3:Linear, of course, is the system for modern software development. 70% of enterprise workspaces on Linear are using agents, and you should be too. We also have Mark Cuban coming on the show. The Cuban agent. What a fantastic return to form for us because the first time we had him on the show, we discussed and we we can talk about Cuban in a second, but, of course, we have our light our Lambda Lightning round.
Speaker 3:And Alex Konrad from Upstarts Media is joining as well. Anyway, last time we had Mark Cuban on the show, we were debating ads in LLMs. And since then, we've gotten a bunch of data points about ads in LLMs. And I think that some of his takes have probably aged well. Some of our takes have probably aged well.
Speaker 3:It'll be an interesting time to reevaluate what's actually happening.
Speaker 2:There's been
Speaker 3:a lot more points.
Speaker 2:I don't know, John.
Speaker 4:We just haven't said
Speaker 2:that ads would be fine.
Speaker 3:Well
Speaker 2:And now, the world is ending. Yes. Now we add now we add
Speaker 3:ads, though. It's not because of the ads. It is it is much more complicated than that. But here's a white pill. Samsung is investing $70,000,000,000 to advance their fab capacity.
Speaker 3:They're getting back in the AI chips game. They've always been in the AI chips game. So brief history of Samsung. You probably know them from the phones, from the TVs. They, of course, are a major player in HBM, high bandwidth memory.
Speaker 3:They are a massive company, over a quarter million employees. They're close to touching a trillion dollars in USD market cap. They pull in around 200,000,000,000 USD a year in revenue, maybe $250,000,000,000 this year in revenue. Really good. All that's USD.
Speaker 3:When you look up Samsung, you get South Korean won, but I like to think in USD because I'm an American. And it's actually kind of complicated thinking in foreign currency. They're the global leaders in memory and OLED displays as well. So a lot of the displays that you see in other electronics, even it has a different brand name, still Samsung actually making that OLED display. But they're second in smartphones to iPhone to the iPhone and Apple, and they're second in the semiconductor foundry business to TSMC.
Speaker 3:Semiconductors still make up 30% to 40% of their business, and they supply HBM to NVIDIA for the h 100 and Blackwell systems. So it's not like they're sitting out the AI bull market. Are doing great. They are definitely participating. They're they're incredibly important in the AI build out.
Speaker 3:But if TSMC is bottlenecked and TSMC is sort of risk off and they're not going to be, you know, guiding to, like, insane CapEx numbers while every American hyperscaler is, well, that creates an opportunity for Samsung. And so Samsung is stepping up and they're announcing that, hey. We're gonna put another 70,000,000,000 to work on this particular business. So Tesla has been working with Samsung on the foundry side in AI for a while. So Samsung's never really been on the frontier with a direct competitor to the h 100 or the Blackwell chip.
Speaker 3:That's been more of like AMD's game, and AMD also fads to TSMC. So there hasn't really been this, like, neck and neck battle between TSMC and Samsung. But it's like you can do AI inference on a Samsung chip, and we know that because Tesla went to Samsung years ago and said, we need a chip that can take in pictures from the road, decide where the lines are, set aside.
Speaker 2:They want their chips with the dip.
Speaker 3:They want their chips with the dip and that's Samsung does too. That's all you know. And so the the the FSD system, you have a Tesla, you might be familiar with, like, h w three hardware three. That has been deployed into millions of cars, and it was fabbed on Samsung's 14 nanometer process, which is a lagging node. It were not in the three nanometer, the crazy frontier stuff, but it's working and it's on the road.
Speaker 3:And, according to a a US regulatory probe, there were 3,200,000 vehicles, Teslas, on the road in America with FSD systems that were basically all running Samsung chips inside. And so now to be clear, Tesla, just like any foundation model lab company, they have training and then they also have inference. They're a little bit different than many of the labs that you know and love because they do training in a data center using what's called the Dojo chip, and that is Fablet TSMC. But so they train the system. They take all the data in from every Tesla camera, every road, all the information that they have.
Speaker 3:Every time that there's a disengagement, that's feedback to the reinforcement learning system. It says, hey, we were in FSD mode, but then someone grabbed the wheel or someone stepped on the brakes. You made a mistake. Understand what happened to get you to that point where you made that mistake. And so that all that data gets collected in the Tesla data center, runs on these dojo chips.
Speaker 3:They do the training, and then they deploy the model onto the Samsung chips in the actual cars. So if you're driving a Tesla, you have a Samsung chip in there that was trained, and the model was trained on TSMC chips. And so the Dojo D1 is one example of their training chip. That was fabbed to TSMC on on seven nanometer, and it's completely separate from the in car FSD chip. So with the backdrop of NVIDIA's massive GTC news cycle, they've had done so much press around GTC and so many different launches.
Speaker 3:You know that NVIDIA's just gonna suck a lot of the air out of the semiconductor discussion this week. Out of the clean room. Out of the clean room, yes, which is recycling all of the air every three seconds or something like that. So Samsung dropped this update. It was pretty quiet.
Speaker 3:We were actually struggling to find it. There was one Wall Street Journal article about it, but it it has not SEO ed well. They I I mean, maybe they need to, you know, do some more podcasts or something. But but they did, in fact. I mean, Jensen's doing the whole fleet of of of, you know, shows and interviews and all
Speaker 2:sorts of says companies should podcast hard.
Speaker 3:Yes. Yes. Yes. Yes. The solution to everything is is more podcasting.
Speaker 3:Talking my book here.
Speaker 2:No. But I think this is, like, particularly Yep. Important especially this morning. The I guess the CCP put something out in the last twenty four hours basically saying, hey, Taiwan is gonna have an energy crisis Yeah. Due to the broader global energy crisis.
Speaker 3:So we need to reunify
Speaker 2:peacefully. There's an opportunity for peaceful reunification.
Speaker 3:But peaceful reunification, even if it was completely peaceful and all the Taiwanese people just say, hey, we wanna be part of China. They all vote for it democratically. That's gonna be rough for the American chip buying industry if you're a buyer of of chips that are fab there. And so having another chip on the board metaphorically to make physical chips is probably a good thing. I you know, I was writing yesterday.
Speaker 3:I'm I'm very excited about Samsung, very excited about Intel, very excited about all of the new fabs, the the Gigafab, the TerraFab is the one that Elon's talking about.
Speaker 2:Launches in five days?
Speaker 3:Oh, wait. Did he actually say that?
Speaker 2:He said seven days.
Speaker 3:Seven days?
Speaker 2:Seven days ago.
Speaker 3:Okay. Wait. Five days like the plan launches?
Speaker 2:He just said TeraFab launches in seven days. Okay. So, I don't know what launches mean.
Speaker 3:And and and Tyler, what's the lead time for an ASML lithography machine?
Speaker 5:Yeah. I mean, it's at least like,
Speaker 6:you know
Speaker 5:It's five. Three, five years. Yeah. Depending on it depends on which like tools
Speaker 3:So the TeraFab will be ready in five and and ASML the But ASML machine
Speaker 2:ASML. It's alien technology.
Speaker 3:It's possible.
Speaker 2:Elon's going up and back to space all the time. Maybe he got some of his own.
Speaker 3:An extreme ultraviolet lithography machine on the moon, on the on the backside on the dark side of the moon. They just had them stacked up there in crates potentially. So, yeah, Samsung's been doing well over the last five days. Stock's up 11% during a time when the Nasdaq is down 2.2% and geopolitical tensions continue to rise. The compute bottleneck, we know it's important.
Speaker 3:We've been discussing this constantly, and it's gonna be very constraining over the next few years. So every in increase in CapEx in the supply chain is a step in the right direction. And so Samsung gets the first Gong hit of the Great. Congratulations to everyone over at Samsung on making making a big bet. Who else is making big bets?
Speaker 3:Cursor is making big bets. Before we talk about Cursor, let me tell you about Phantom Cash. Fund your wallet without exchanging or middlemen and spend with the Phantom card. Let me also tell you about Labelbox, RL environments, voice, robotics, evals, and expert human data. Labelbox is the data factory behind the world's leading AI teams.
Speaker 3:So Cursor
Speaker 2:is out We do. With Composer two. Composer two. It is frontier level at coding priced at 50¢ per million input tokens and 2 and a half dollars per million output tokens. It's also they have a fast version.
Speaker 2:They say we're able to significantly improve the model quality and cost to serve. These quality improvements come from our first continued pre training around providing a far stronger base to scale RL. So It performed quite well on what is it? Cursor Bench.
Speaker 3:Yes. Which is A funny bench. But
Speaker 2:Which is well, yeah. Yeah. TBPN performs quite well on TBPN Bench too.
Speaker 3:Yes. It's a little it's a little silly to design the bench and then publish the bench that that your score on your own bench. But, I mean, to be fair, like, they're putting GPT 5.4 high and medium above them. So it's like they didn't it's not one of these graphs that's just like, oh, look. We made some arbitrary x and y axis and, like, we're in the top right corner, of course, because the axes are, like, good and cool.
Speaker 3:Like, we're the only ones that TBPN TBPN Bench
Speaker 2:is, technology podcast Yes. Publish at least three hours of content every week. Yes. Yes. Naturally.
Speaker 2:Exactly. Naturally, we are
Speaker 3:The right
Speaker 2:of the right top. Of the And it's actually there's no one else on there. Yes. But
Speaker 3:But, yeah. I mean, this seems fair. It is a little bit odd to read this because the cost the cost is on the x axis and it's inverted. So the further you are to the right, the cheaper you are, which makes sense because people associate an x and y graph with you want to be in the top right quadrant, and they certainly are. And it does seem like in terms of this Pareto frontier, you want to be on the frontier.
Speaker 3:You want to be pushing out across every single curve. Maybe if you are interested in sparing no expense, you'll go with the GPT 5.4 high or medium model, and you can align Cursor to GPT. I'm sort of surprised that Opus is not doing as well on CursorBench. That that that feels surprising based on, like, the general vibes around around Opus 4.6 generally. But Cursor has specific needs for specific customers.
Speaker 3:And I don't know. What else do you think is going on here?
Speaker 5:Yeah. I mean, the cost is really big. Like, this is basically like 10 x cheaper than
Speaker 3:Yeah.
Speaker 5:An Opus. Yeah. So I I think also, you know, Cursor has kind of been, like, not really a, like, dark horse, like, everyone knows about it. Yeah. But in the coding race, it's like, everyone's like, okay.
Speaker 5:There's Codex versus Cloud Code.
Speaker 3:Yep.
Speaker 5:But, like, you know, if you imagine that, you know, Cloud Code and Codex are kind of like these environments for getting a ton of, like, really good data
Speaker 3:for Yeah.
Speaker 5:For training coding models. Like, Kurzar's had that for way, way longer
Speaker 3:Yeah.
Speaker 5:Than than OpenAI or Anthropic. Yeah. So you should imagine that, like, at least, you know, in the near term, like, they actually have, like, really, really good data
Speaker 3:Yeah.
Speaker 5:That they can, you know, train these these good models on. And, obviously, like, this is a very specific model. This they've said it, like, that you're not gonna write poems with this model. It's this very like specific kind of almost like point solution model where it's
Speaker 2:it's to them, Tyler. Write a poem with the model. Poem bench.
Speaker 3:Poem bench. Yeah. I I I would be interested to know like how many sacrifices were made because it's at a certain point, like, I I remember talking to an AI researcher, actually a semiconductor entrepreneur who was saying that, like, he actually thinks he actually does believe that importing, like, the Odyssey and, like, Homeric epics is key to humanoid robots learning to walk.
Speaker 5:Yeah. Well, I I think, like, if you look back at just, the general history of, like, machine learning AI, like, the the lesson is that, like, big general models always beat these small specific models. Yes. But if if you kind of zoom in on the time scale, like Yep. You can still train, you know, GLM, some open source model on on a very specific task like accounting or something.
Speaker 5:And you can, like, hill climb and you can actually make it better than the frontier models right now.
Speaker 3:At that specific thing. And especially at cost. Yeah. Especially at
Speaker 7:cost.
Speaker 5:Yeah. Yes. Yeah. Very much so. But, like, on the long term, if you zoom out, we're actually once here it it seems like it's basically always gonna be these big Yeah.
Speaker 5:You know, general models. But
Speaker 3:And I wonder I wonder if that's true. I mean, we talk about this a lot where the big general model outperforms the smaller model. But at the limit, like if you were to think about like a Python if statement, just like flow control that is truly deterministic, like yes, if you piped the same question of, like, the if statement, like, is this number bigger than this number? You pipe that into 5.4. It's gonna get it right all the time.
Speaker 3:It's gonna be very expensive compared to an if statement, which takes, like, no no compute whatsoever. Right? But the if statement is 100% accurate, like, unless there's some bit flipped from cosmic radiation. Like, it is deterministic. And so if you're in a world where the small model that you've built, the classifier that you've built, whatever machine learning pipeline or small model you built is actually functionally at a 100%, well, then there's this upper bound that even, like, the bigger, smarter model doesn't get you any benefit at all.
Speaker 3:So you're just purely in cost control mode, I would imagine.
Speaker 5:Yeah. That's reasonable. But I I think
Speaker 3:This is not a great example because coding is more
Speaker 5:Coding, we're not at a 100% saturation on just coding.
Speaker 3:Yeah.
Speaker 5:It's literally one
Speaker 3:I mean, look at the look at the chart. Like, the the best performing models are sitting at at 65%, sixty sixty three, 64%. So there's clearly more more room to saturate this particular bench. I'm actually super interested to know about what goes into CursorBench at this point because I feel like when I see every benchmark, it's like 100% now. But that that's just from, you know, the old the old models.
Speaker 3:Legendary poster
Speaker 2:sent Kalp says all s h I t s and giggles on that headline till Anthropic or OpenAI decide to cut off their access to Cursor, referencing the Bloomberg article. Cursor is taking on Anthropic and OpenAI with
Speaker 3:a new AI coding model. Would would that matter? Like, at this point, if they have if they have Composer two and it's a small model, but it's good at writing code, and it performs well in CursorBench, and the Cursor users are satisfied with the Composer two model, and they do Cursor does get their access cut off. And when you install Cursor, you roll it out to your organization. You just get Composer two.
Speaker 3:And you know what? It's it's, you know, maybe there's taste that wouldn't pull
Speaker 2:you Yeah. We just say at this GPP point right now, I don't think we have any visibility into, like, how much of Cursor's revenue right now
Speaker 3:Yeah.
Speaker 2:Is tied to using OpenAI or Anthropic models?
Speaker 3:Well, I think, like, in some ways, all their cost is, but is all their revenue? It depends on the perception of the user base. Because the revenue might be, well, I pay for cursor. Like, I don't really care what they use under the hood. Yeah.
Speaker 3:There's a lot of people this was Ben Thompson's argument for a long time was that there's for a lot of people, they just show up to ChatGPT and they wouldn't care if the model was powered by Gemini because they're just like, I just ask it a question and get an answer. And so if you're a cursor user, it's possible that you're in the same boat where you don't really mind what happens but but like under under the fold. What else is going on here?
Speaker 2:George says, I'm hearing tons of complaints from Cursor customers at enterprise companies. A silent change put almost all models Cursor uses behind max mode. Devs, used to manage to spread out monthly credits over a month. See, all of it used up in one to two days
Speaker 3:Oh, interesting.
Speaker 2:Are furious and switchy.
Speaker 3:It does feel like there's a little bit of like an economic war here.
Speaker 2:Yeah. And then this is what came up, like, you know, earlier this month Yeah. Around the labs sort of subsidizing. Yeah.
Speaker 3:So You know who's
Speaker 2:They're not they're not in an easy position, but they're such a talented team.
Speaker 3:Yeah. Well, you know who's great at the Pareto frontier pushing models? Gemini 3.1 pro. It's here, and it has a more capable baseline. It's great for super complex tasks like visualizing difficult concepts, synthesizing data into a single view, or bringing creative projects to life.
Speaker 3:And let me also tell you about Graphite, which is owned by Cursor. Correct? Code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster.
Speaker 2:Nikita says, we're rolling out summaries for articles now. Just tap the summarize button if you wanna know if it's worth your time to read it.
Speaker 3:Yes.
Speaker 2:And yeah. It's basically, Grock, turn this into a regular tweet. I am excited about the listen button. I've had this. I you know, on on my commute.
Speaker 2:Yeah. There's so many moments where I'm like, I wish I could just have somebody read this article.
Speaker 3:Actually wound up doing this with a number of Will Menidas long form essays. I would copy them, put them into 11 Reader from Eleven Labs and have it read it to me in sort of a
Speaker 2:A silly voice.
Speaker 3:Voice a silly voice.
Speaker 2:It was a good time. Well, I was trying I was actually trying to use Grock in I was trying to use Grock in the X app Yeah. To just take an article, paste it into Grock and Yeah. Say, hey, can you read this to me? Yeah.
Speaker 2:And said, cannot find
Speaker 3:Yeah.
Speaker 2:The post. It's So like, it it couldn't it couldn't kind of is
Speaker 3:sort of is sort of crazy reflecting on the fact that there is so much software out there that, you know, we we we we talked about DoorDash. Like, how can you completely reimagine the experience with agents on the platform? And there's so many different things that you can do to, like, sort of, like, rearchitect what your product is if you've built a successful software company. But then there's all these, like, little things where, like, yes, every product probably does need an LLM that can summarize text and expand it, and that's what Grok does. And also, everyone wants text to speech, and everyone wants speech to text.
Speaker 3:And and everyone wants the okay. If there's an image, I want you to, you know, have a text version so it's searchable. Like, I've complained about if I see a funny meme on x and then I want to go search for it later. Impossible. Like, there's just no way you could ever do it because that is stored in Twitter's database or X's database as, like, image number 762542, and someone's comment was just like, this changes everything.
Speaker 3:And I'm never gonna remember what they said. But now you can run every image through a image model to understand what's actually going on and then potentially service that in search. Now that's gonna be a long project to actually implement that. Make it fast, make it cheap, make it affordable, make it, like, fit within the business model of x or whatever social platform is out there. And I mean, you can see Instagram, like, struggling through these things right now as as search becomes more important and as ranking becomes more important.
Speaker 3:Meta's already seeing the lift from machine learning applied to ad ranking and whatnot. But this is a response to every article people would post, people would always say, Grock, summarize this. And now there's just a button. I wonder if this button will be gated by x premium because I recently learned that you can only ask Grock. Like, at Grock, is this true?
Speaker 3:You can only do that if you're paying for x. And sort of underrated how well x has seemingly I don't know how big the subscriber base is, but that was a crazy idea to have a paid social network. Dalton Caldwell, from formerly YC, partner, actually launched a competitor to Twitter back, like, maybe a decade ago that was, paywalled only. And and the whole pitch was, like, better content, more sub stack model, no ads. And he never really got it, you know, to a perfect product market fit, but but it was an interesting idea and that Yeah.
Speaker 2:And I think it's because people are people are deeply addicted to x. Yeah. It is very valuable to them Yeah. To be on there, to participate. Yeah.
Speaker 2:And the paid functionality, the way that it was marketed and the way that it generally worked was like, you were gonna have a bad time on x. Yeah. Like, if x was valuable to you and you didn't pay the $10 a month Yeah. You it was gonna be like significantly less valuable to you. Probably, you know, you might you might, depending on what kind of business you're running or what you use x for, it might be the equivalent of like losing thousands of dollars a month of value or you could just pay the $10.
Speaker 2:Yep. So it was a good trade.
Speaker 3:Yep. But It was also just it was weird how the targeting never seemingly got dialed to the point where you could actually target the CEOs of companies who are on x. Like, I mean, you see Travis Kalanick on x, like replying to things. It's like, he's raising money. He's growing a business.
Speaker 3:Like, there's a lot of value in advertising to him because he's gonna be picking a corporate card soon, or he probably already has, or it might be in that market. He might be picking a payroll suite. Like, there's all these things where if you could deliver that to that audience, it would be incredibly valuable, and the CPM should be, like, through the roof. But I think for privacy reasons and for a variety of other reasons and sort of like the like, really monetizing that long tail has been very difficult across every platform. So they've just gone with scale and the products that have sold the most on social networks have been very broadly marketed.
Speaker 3:And the and the the criticism that we saw from the Oscars is always like YouTube ads are generic. It's just like for a pillow or like injury or like something that applies to every single person.
Speaker 2:Yeah.
Speaker 3:But there's always this like hyper targeted opportunity there.
Speaker 2:Yeah. The other the other thing is is the paid program with x has seemingly worked Mhmm. In that we know a lot of people that happily pay and have no plans to churn. Mhmm. But it would be a failure in the context of like meta scale.
Speaker 2:Right? Mhmm. I think the last reported number that I saw was something like they had like one to one and a half million paid subs at $10 a month.
Speaker 3:That's Oh, on x?
Speaker 2:Yeah. You're talking about somewhere in the range of a hundred to two hundred million of like ARR. Yeah. And if Mark if Zach had launched a product like that, he would just wind it down. Right?
Speaker 2:Yeah. Reels went from zero to 50,000,000,000 Yeah. Of run rate in like a handful of years. Right? That's what a that's what a home run looks like.
Speaker 2:And so Yeah. I think it makes sense for X, but it certainly is not a home run from a, you know, consumer application standpoint, and they still need the, you know, the overall business.
Speaker 3:Yeah. Olivia Moore had some extra context there around monetization of via ads versus versus subscriptions. So Neil Patel, who is the founder of NP Digital, a New York Times best selling offer, shared this is how ChatGPT ads
Speaker 2:guy, think.
Speaker 3:Okay. He said the data is from is only from five businesses, but these businesses also run Google and Meta Ads. Compared to Meta, ChatGPT's rough quality is 256% higher. On the flip side, lead quality is 49% lower than Google. I mean, seems like a miracle to be in between two hyperscalers on on, like, day one, basically.
Speaker 3:But on the bright side, due to add costs, it's substantially cheaper from a CPA perspective than Meta. And this was sort of what we were talking to the folks the good folks over at Ridge about was that at least at least in the early days, like like being being early to a new ad platform that can you can potentially scale on can drive a bunch of new conversions. But Olivia Moore said, a big story that most people are missing in the AI race for the consumer, chat GPT versus Claude, is ads. Right now, most consumer AI revenue is coming from power users who are willing to pay high subscription costs. This currently skews positive for products like Claude, but this will not be the end state.
Speaker 3:Google makes $460 per user per year in The United States more mostly on ads. I didn't know that their ARPU was so high. Meta makes around 250. I mean, I guess those Google Ads are really, really valuable, and it's so intent driven that it it it makes sense. I would argue or she would argue that Chattypetty's ad based ARPUs will be even higher as they will ultimately have deeper, more frequent user engagement Even at the $460 level, monetizing everyone in The US via ads is a 152,000,000,000 in annual revenue.
Speaker 3:By contrast, if you're able to monetize even 5% of the population at $200 a month subscription, which is a stretch, that's only 40,000,000,000. That's a that that's actually a crazy difference because $200 a month subscription is is like super high. Like, you know, you're talking 20 times like Netflix or something else that's, you know Yeah. Premium and like really important.
Speaker 2:Yeah. The $200 subscription at the time was crazy. Yeah. But even at that point, some of the people that were more kind of just like AI pill generally Mhmm. Were like, oh, it's actually possible that someday you could spend $20,000 a I
Speaker 3:I I was like, give me the $20,000 a month. And it sort of came via via API, but it was heavily subsidized. So she says, I suspect this will be even more drastic outside of The United States where users are even less willing to pay or directly pay for subscriptions. And the earliest data from a very small rollout shows ChatGP ads are already outperforming that in effectiveness. This just gets better out it just gets better over time.
Speaker 3:So interesting. The the question about Will Menidas and the article summaries, should he move to Substack? He's threatening Nikita. He says, I'm defecting to SBSTCK. He won't even type it out.
Speaker 3:He says, they pay more. And Nikita didn't reply. I think people would follow Will over there. I think people would read his articles anywhere potentially. But if you're looking to advertise, why don't you head over to AppLoveIt?
Speaker 3:Profitable advertising made easy with axon.ai. Get get access to over 1,000,000,000 daily active and grow your business today. And let me also tell you about Gusto, the unified platform for payroll benefits and HR built to evolve with modern small and medium sized businesses. So Carl
Speaker 2:says, it's time to return to the place where I know I can have the most impact. I'm beyond excited to rejoining Sequoia as a partner. Here is what I shared with the team on how I am approaching my next chapter. He wants to serve the ecosystem, fire to win. Let's see what this means.
Speaker 2:Being a servant leader does not mean I have lost my edge. In fact, the fire in my belly burns brighter than ever. The difference now is that I'm not using that fire to light my own path. I'm using it to light the spark in others, so their fire burns brighter. Leading from behind, have no interest in the view from the front of the room.
Speaker 2:I will leave that to our to great leaders, Pat and Alfred. I want to lead from behind empowering each of you. Ego less impact, contagious energy, mentor and build great leaders, always ready to serve. Carl's the man. We will have him on in just thirty minutes, so we can wait to cover more of that story.
Speaker 3:But first, gotta go to his Allen and Co photoshoot, dual wielding coffee, jump rope, and a faded Sequoia t shirt. Andrew Reed says
Speaker 2:Elite.
Speaker 3:Immediate overwhelming response to Elite. VC push up debacle. Welcome back to Sequoia, an all time great partner. That's a great that's a great photo. He's looking great there.
Speaker 3:Let me tell you about Plaid. Plaid powers the apps you use to spend, save, borrow, and invest securely connecting bank accounts to move money, fight fraud, and improve lending now with AI. Is an
Speaker 2:interesting story.
Speaker 3:This is an interesting story.
Speaker 2:Apple is way behind in AI and still making a fortune from it. Let's see.
Speaker 3:Begs the question, are they actually behind?
Speaker 2:It might not. AI revenue is set to top 1,000,000,000 this year reassuring investors wary of rivals sky high spending.
Speaker 3:And keep in mind We
Speaker 2:have a chart here showing gross revenue from Gen AI apps as well as Apple's commission. So
Speaker 3:Look at this. The the the 2025 was really the boom of Gen AI app growth. 400,000,000. Is this is this monthly app store revenue? Wow.
Speaker 3:They're really cooking. And then and then sort of a
Speaker 8:flat line.
Speaker 2:Yeah. It's so so interesting that that it actually dropped.
Speaker 3:Yeah. Well, we did read that article a few days ago about how Apple has been pushing back against some of the vibe coding apps. And there's this question about, you know, where are the bounds? Obviously, Apple's had pretty strict app store rules around adult content and, you know, what else you can do, even just the app reconstituting itself, pushing changes because they wanna review every line of code that goes in the App Store. If someone's pushing ten, twenty, 30,000 lines of code a day, that's a lot of code for Apple to review.
Speaker 3:It's It's gonna slow things down. So that could be a little bit of what what we're seeing. Maybe they've capped out on their ability to review all the vibe coded apps that are flooding the app store. But let's go to Wall Street Journal and dig into this
Speaker 2:Apple's on pace to surpass 1,000,000,000 in AI revenue this year, a tidy sum that demonstrates the company's AI advantage even as it struggles to deliver an AI strategy of its own. Its Siri chatbot is still weak by modern AI standards. What Apple does have that the other AI players don't is a dominant position making devices. However however fancy OpenAI, Google, Anthropic, and XAI make their chatbots, iPhones are still a primary way to deliver them to customers. Mhmm.
Speaker 2:That means they typically pay the App Store tax roughly 30% of subscription fees in the first year and 15% a year thereafter. The rates vary. Gen AI apps paid Apple nearly $900,000,000 in App Store fees in 2025 with all you know, almost 1,000,000,000 of revenue and very, very, very little CapEx. Three fourths of the revenue Apple rakes in from Gen a apps Gen ai apps and its apps were come from ChatGPT. Woah.
Speaker 2:Next at about 5% is XAI's Grok. We go, Grok. Fucking
Speaker 3:I mean, there's so many different, like, funnels. They did the essay competition. They did the the video competition. And, I mean, I've I've talked to people that are just still they're like, you know, like people that are in the Apple ecosystem, they're like in the Tesla ecosystem. And so they're like, yeah, I talked to Grok on my way to work.
Speaker 3:I I'm not kidding.
Speaker 2:Yeah. Grok in the iPhone app store is at did twelve million last month.
Speaker 3:Yeah. And I know I know, like, the the the true, like, AI heads will be like, Grock's behind on this benchmark or model or whatever. Tyler, is that a correct characterization?
Speaker 2:Yeah. Grock did more revenue Grock did more revenue last month than than Claude in the iPhone app store.
Speaker 3:But but, like, I've I've I've started having conversations with I I'm I mean, I'm using JGPT, but I I wanted to just I I wanted to get up to speed on on Taiwan and the the the just the like, what was the the reason for the original civil war and stuff. And so I was just having a conversation back and forth, and at no point was I like, oh, I really needs to be, like, you know, GPT 5.4 pro. It's like, these are things that exist just, with one search to Wikipedia or one search to any it's probably baked into the weights of 3.5. But so so, like, if I'm just going to be, like, chatting with someone who's, like, reasonably smart, like, I would say Grock is there. And so what do you think?
Speaker 5:Yeah. But you like, you could be talking to someone who's really, really
Speaker 3:No. Like, not if you're asking, like, basic basic knowledge retrieval questions that, like, that, like, any model's gonna have one one shot and just be
Speaker 5:Right. Yeah. But you're just describing stuff that you could just, like, actually Google.
Speaker 3:Yes. But but I can't Google via voice in my car on the drive. And for someone who's driving a Tesla and has a Grok integration right there, they're just like, sure. Like, this
Speaker 5:is great. Okay. Yeah.
Speaker 3:That's fair. It's like not and, like, the frontier use case is important. Like, that's where the action's happening. That's what's driving the next order of magnitude of growth. But, like, there are plenty of people who are like, Google's search overviews are amazing.
Speaker 3:You know? And they're like, that's like, that's my level. And like, that's good. And they're like Yeah.
Speaker 5:But like, I don't think those people have actually tried like GPT 5.4 pro.
Speaker 3:But I don't So good. It is it is good, but it's slow. And truthfully, like like, you can fire off the exact same query to 5.4 pro and five point pro and five point foe, 5.4 fast fast. And and if the query is simple enough, the answer will be exactly the same. Because if I ask if I ask 5.450.4 extended thinking, like, what is the capital of California?
Speaker 3:And it thinks for ten minutes, and it just tells me, say, like Sacramento. See? You Yeah. There you
Speaker 2:go. That's why you need to think. A lot of
Speaker 3:people I told you. Run my life on GPT two. I hallucinate a lot. But
Speaker 2:People have said I have the mind of GPT two.
Speaker 3:It's true. It's true. But but so so I think I think for I think for some use cases, you know, a smaller model, something's a little faster, something that's not, you know, absolutely frontier is is fine. So I don't know. What what what do think
Speaker 5:about that? Imagine that.
Speaker 3:Do you think there's something else going 5.4
Speaker 5:pro Spark. So it's on, you know, Subra's Chips.
Speaker 3:Yes. Yes.
Speaker 5:Yes. Would you hit that every single time? When would you not
Speaker 3:use it? I would not use it if I was doing, like, a deep research report necessarily. It it because I want I I just want extended reasoning for certain things.
Speaker 5:No. No. But I'm saying, like, you could have that. The like
Speaker 3:Oh. Oh. Oh. Oh. Use like five two Five three four
Speaker 5:is like Yeah. Fast extended reasoning, but it's still super fast. Good sign service chips. Right?
Speaker 3:So you could
Speaker 5:if you had that
Speaker 3:Yes. You'd find one Money is no object. Absolutely. Like, I you know, I'm I'm I'm happy to to pour out the glass of water for to to to get the best and and the best intelligence possible.
Speaker 5:Like, I I just think that even if you if you just care about speed, there's still better I think in my opinion, like, now, there are better models than than drone. Okay.
Speaker 3:Okay. So so so walk me through it. Like, percent of app store revenue seems really high. What's driving that?
Speaker 5:Yeah. Not everyone is, like, extremely tapped in to, like, the, you know, the current model that came
Speaker 3:out two days ago, you
Speaker 5:gotta use it, like
Speaker 3:So you agree with me? I think you agree with me. About About the fact that that, like, good enough intelligence is still, like, a good business to the tune of 5% of app store revenue from Gen AI apps.
Speaker 5:Yeah. It's good. But I'm saying that, like, you because you know about the stuff.
Speaker 3:Yeah. Yes. Like, there's nothing to do I it. Told you. I told you I'm talking to Chad GPT.
Speaker 3:Look, don't don't shame me. I'm not the one. But I'm just saying, like, I don't even think you should be shaming someone who's talking to a
Speaker 5:old not model. Shaming them. I think I'm saying
Speaker 3:Your model shaming.
Speaker 5:Could be better. Like, you could have a much better experience.
Speaker 3:Okay. Okay. So you wanna evangelize the the frontier. You wanna evangelize the frontier. Yes.
Speaker 3:But I mean, I I'm just I'm just wondering, if we did we need a new touring test. So we need to have random people come in and they get to talk to 54 or, you know, 40 or something. And can they tell the difference? And which one would do they prefer?
Speaker 5:They might just prefer four o.
Speaker 3:They might prefer four o. This is the new this is the new New York Times writing test. We should we should put one of these out and be can you actually tell the difference? This is interesting because I feel like a lot of people say they can, but they they they probably unless they're really, really grinding and they're trying to do something that requires like a really long reasoning chain, it's totally possible that they're just like, yeah. Like, it's it's it gave me the right answer.
Speaker 3:Like, it looks good. That's a narrative violation. Anyway, let's continue. Apple's revenue from generative AI apps rose from about 35,000,000 in January to a high of 100,000,000 in August. Do nothing win.
Speaker 3:Do nothing win. Create an app store over a decade ago and just keep reaping the rewards. They they sowed and now they're reaping. Sales have fallen from their peak partly because downloads have declined according to the data. As a proportion of Apple's total sales, $1,000,000,000 is small, yet Gen AI apps are a growth driver for Apple services business, which investors have focused on in recent years because it has grown faster than device sales and boasts higher profit margins.
Speaker 3:Apple's dominant share at the top of the smartphone market affords it another luxury, time to get its own AI strategy right. So they're making money while they figure everything else out. Apple's AI plans plan runs counter to strategies of competitors that are spending hundreds of billions of dollars on chips and data centers to build frontier language models. Apple is spending a fraction of that, aiming instead to use all of the personal information people store on their iPhone together with the chips that it designs itself to power an on device AI strategy. That strategy could prove a winner if, as some AI researchers have suggested, access to user data and strong privacy makes on device AI the dominant way consumers access the technology.
Speaker 3:Apple investors want to see progress from Apple's own AI strategies, such, said Charles Reinhart, chief investment officer of Johnson Asset Management, an Apple shareholder, quote, if they can act as a toll road for providers of AI, then they'll probably end up looking good long term for not having the big CapEx overhang. Now I have to imagine that Apple is not capturing any revenue from enterprises, developers, Clog Code, Codex, any of those developers. They're probably not even if they even if they are winding up using, a ChatGPT subscription in Codex, they're probably setting that new subscription up on desktop.
Speaker 2:Road on on the on the actual
Speaker 3:Yeah. Side. But it's a toll road on consumer, which is consumer sales. All the more reason to get into ads, honestly, because Apple does not tax those.
Speaker 2:And and AI is exciting for Apple because they need they need a new product that they can just randomly bill you, like, $2.99 Yeah. Anytime they need a cat, like, a
Speaker 3:What are talking about? Cash. $2.99?
Speaker 2:Like, don't don't you get just random bills from Apple, like, here
Speaker 3:and $2.99? Like, $2.99?
Speaker 2:Yeah. Like, I I feel like every time I check my email, it's like, Apple has charged you, like, some random amount for some
Speaker 3:or something.
Speaker 2:For some subscription.
Speaker 3:No. I do get emails from Apple, but it's always like two days after I bought I bought or rented a movie on Apple TV. And it just says like, you rented this movie. I'm like, yeah. I I know.
Speaker 3:I clicked the button. It's fine. You don't need to email me.
Speaker 2:In other news
Speaker 3:Okay.
Speaker 2:Rolls Royce has scrap plans to go all electric by 2030 as quote, drivers prefer v 12 engines. Would you look at that?
Speaker 3:Look at
Speaker 2:I mean, and this is just total shock. Shock.
Speaker 3:Yeah?
Speaker 2:Total shock. Yeah. Drivers totally had to experience, you know, being forced EVs forced upon them for the last few years to know that they they they preferred combustion engines after all. Of course, I'm kidding. You think people were just, you know, sort of saying this over Yeah.
Speaker 2:Over and over. Manufacturers were not listening.
Speaker 3:Everyone said Elon has been saying the Roadster Reveal will blow your mind. If it has a v 12, then We've created maybe. We've
Speaker 2:been People are going crazy.
Speaker 3:If he drops a v 12, that would be that would completely break the Internet. Yeah. It'd be it'd be incredible. Anyway, let me tell you about public.com. Investing for those who take it seriously.
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Speaker 3:Own the data platform that
Speaker 2:about this Tesla that you were following yesterday.
Speaker 3:Oh, yes. Did you drop this in the chat already? I sent it to you. Oh, no. Wait.
Speaker 3:We we shouldn't we shouldn't shouldn't share the actual picture. But I saw a Tesla that was a very funny mix of it had the anti Elon club on it, but also an 1199 license plate. And it was a plaid and it just like mixed every possible political ideology together.
Speaker 2:It had a vanity plate
Speaker 3:It was very
Speaker 2:sci sci fi. Fi. So was like, I do wanna go to Mars Yep. But not with Elon. Yep.
Speaker 2:They want cops. The license plate basically said, beam me up.
Speaker 3:Beam me up.
Speaker 2:So they wanna go to Mars, but not with Elon. They support
Speaker 3:They have an incredible amount of disposable income based
Speaker 2:on enforcement. They enjoy high trim levels, but they they they do not agree with Elon's actions.
Speaker 3:Well, maybe they work for a rival AI lab or something. And so they they're extremely sci fi pill, but they just don't like they they just they they just feel like they're competing with X.
Speaker 2:California has now spent over a $100,000,000 on a new bridge to nowhere. It is Wildlife Bridge which I've driven by hundreds of times. Okay. I've been seeing it. I've been experiencing the traffic Mhmm.
Speaker 2:That it causes. I I'm not against the concept of a wildlife bridge. In fact, I think it's fantastic.
Speaker 3:It does feel like But it is a very concrete jungle, this is beautiful. Totally. This has a lot of opportunity to actually improve the visual aesthetics of this particular part of the state.
Speaker 2:Caleb Hammer says, bro, this state cannot be real.
Speaker 3:Isn't isn't Caleb Hammer
Speaker 2:It's very real.
Speaker 3:Isn't Caleb Hammer he's like a finance Yeah.
Speaker 2:He's got like the the number one.
Speaker 3:He's like the one person you'd come to to be like, should I spend a $100,000,000 in a bridge? And he'd say like
Speaker 2:And it's actually it's actually quite a bit more than 100 at this point. And the funny thing is, like, it's just kind of a bridge, but it doesn't it's it's lacking the entrances Yeah. To the bridge. I feel like it's basically built like a
Speaker 3:Even just a little bit of wood to, like, like, smooth it out so that it looks like there's at least going to be start of a of a of a of a ramp to get on the bridge. Like, the bridge looks solid. The actual center part looks solid. It doesn't feel that hard to finish this bridge. I'm I'm optimistic that this gets done in the next hundred years, like tops.
Speaker 2:Apparently, Colorado built a built built a wildlife bridge for a low cost of $15,000,000. Oh, that's not bad. Like, functionally, something very, very similar. The the interesting thing is, apparently, the bridge as is in some part for cougars. Cool.
Speaker 2:And the wild thing is, like, on one side of the bridge, you have a bunch of, like, residential homes.
Speaker 3:Mhmm.
Speaker 2:And on the other side, you have a bunch of cougars. And so Yeah. They're now gonna the cougars are gonna be able to go hang basically hang It's exciting. In all the backyards. So we'll see how this goes.
Speaker 2:But I'm I'm excited for this to be finished up.
Speaker 3:Mhmm.
Speaker 2:It's been as long as I have lived in Southern California, they've been working on this bridge and it's about time.
Speaker 3:Well, former partner of TBPN, Fall, a generative AI model hosting service that you know and love, is in talks to raise 300,000,000 to $350,000,000 at an $8,000,000,000 valuation. Annualized revenue has hit $400,000,000 up from 200,000,000 in October. That's the No.
Speaker 2:They've executed in really
Speaker 3:We're good friends. Insane. So congratulations to them.
Speaker 2:Growth. And look forward to having having them on after they move past the advanced talks Yes.
Speaker 3:Yes. Yes. What is Miles Brundage saying? He says, I'm a bit worried that Anthropic is an org wide case of AI psychosis that makes them think Claude is good enough that they can ship random product features without breaking things, but they in fact do keep breaking things and they're not online enough to notice people complaining.
Speaker 7:Interesting. Yeah.
Speaker 2:Don't know about the last part. They seem very online.
Speaker 3:Yeah. And I I I don't know too much about the the issues. But there there is like, if they're truly competing in consumer, like, are, like, low hanging fruit, like text to speech on deep research reports is not a feature that exists yet. Feels very obvious. But it's it's so interesting being this dynamic where, you know, you can ship things so fast, and yet there's some obvious product improvements that are just sort of stuck in the queue because there's a lot to do, and it's an exciting time.
Speaker 3:What else is Anthropic doing? They're hiring for a policy manager who will be in charge of chemical weapons and high yield explosives. This reads like you're going to be building high yield explosives, which sounds like an annual job posting, but it is in fact for a policy manager who will be hopefully stopping people from
Speaker 2:No. No. No. Think I I I read this as somebody whose job it is to decide how Claude is used to create chemical weapons and high yield explosives.
Speaker 3:I think it's, I don't know. I I think it's probably like this person decides like where's the edge. So if you if you're asking like, okay, I have a firework and I wanna make sure it doesn't go off, like, should I, you know, throw in the trash or put in the recycling or take it to a special place? Like, Claude should answer that. But if you go to it and you ask it, like, how do I build this c four or something like that, like like, there's all these, like, policy edges where if you're talking about Counter Strike and you say like, let's plant the bomb, it shouldn't flag that as, okay, you're actually trying to plant a bomb.
Speaker 3:It's like, you know, you're asking about a video game. We we know how to interpret that appropriately. But there needs to be like a human in the loop to decide like where that frontier is and where that particular is. Anyway.
Speaker 2:Orf says, what terrifies me is if AI were to cure cancer and save fifty million Americans, imagine the backlash from hardworking scientists who wanted to cure cancer themselves.
Speaker 3:They will be involved for sure.
Speaker 2:Well, it's interesting that that was Yeah. That was like at least one person's response to the Australia Really? Dog story
Speaker 3:Oh, right.
Speaker 2:Where they were like, yeah, this we we've been able to do this for a while, but like, don't do this Mhmm. Which was, you know, an interesting response to somebody who, you know, went on a multi year journey to Yeah. Try to save their dog. Yeah. Seemingly is having some
Speaker 3:Success. Outcomes. Very, very odd. Let me tell you about Railway. Railway is the all in one intelligent cloud provider.
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Speaker 2:So. PG says anything made before 2028 is going to be valuable. And he's quoting an OpenAI employee who he says implicitly discloses their
Speaker 3:Timetable? Anything made before 2028 is going to be valuable. That is such a vague someone was hanging out with with Paul Graham and was like, let me vague post IRL. That guy is so vague.
Speaker 5:I require content.
Speaker 3:I yeah. I require content.
Speaker 2:This this is gonna be very valuable. I'm not would up.
Speaker 3:We are working on something that will be incredibly valuable. One one of our team members had a major breakthrough and it could be the blockbuster product of the year. I'm very excited for this.
Speaker 2:This actually is we were just messing around this morning with with an existing product that we had.
Speaker 3:Had a breakthrough.
Speaker 2:We had a major breakthrough.
Speaker 3:We I had nothing to do with it.
Speaker 2:We and when I say that, I mean Ben, had a breakthrough that I think will change one of America's past times forever.
Speaker 3:I think so. Actually. That it'll be I mean, I before and after
Speaker 2:confident in this Yes. That I'm willing to vague post about
Speaker 3:him a patent. For sure.
Speaker 2:Get this get this young man a patent.
Speaker 3:I'm on a patent. I have a patent. It's great. Yeah. When you get a patent, can also like frame it, get a little tombstone.
Speaker 3:It's very nice. Regardless of what happens with the business, it's like a good moment in your business career to like have a patent.
Speaker 5:Do you have a tombstone for your
Speaker 7:patent?
Speaker 3:I don't. I need to order one. It has been issued, like my name's on it. I'm like the, you know, seventh name on the list or whatever, but I'm technically on it. And so I should I should get my, you know, plaque or whatever.
Speaker 3:I'm sure you can just buy them. There's probably something on there. What did PG give? He gave some more context. He said this was after I mentioned the idea of buying rare old things as a hedge since the one thing AI won't be able to do is go back in time that we know of.
Speaker 3:I don't
Speaker 1:I mean, that's a whole plot of Terminator.
Speaker 2:You're not
Speaker 3:Just say you're not AGI pilled. Like, just everyone's saying it's gonna be like Terminator. It's gonna be like Terminator. Well, what happens in Terminator? They invent time travel.
Speaker 3:And so you're gonna be able to go back. You're gonna be able to go back.
Speaker 5:Yeah. I feel like after we get AGI and we can, like, build incredible things, like, will be really valuable too. Right?
Speaker 3:Yes. Yes. But yes.
Speaker 2:I mean By a good time
Speaker 3:to travel. They're like they're like like, you know, images in chat GBT and and and v o three and mid journey, like, don't decrease the value of the Mona Lisa. Like, that's just, like, obvious, and everyone agrees on that except you. You're like, I would actually like to go to the mid journey Louvre.
Speaker 2:Maybe that's why banks maybe Banksy sort of intentionally Oh. Kind of revealed himself. I
Speaker 3:don't I wouldn't follow that story. Like, how did that happen? Because I feel like most people would
Speaker 2:just caught him with a Scott is Yeah. Watching Yeah. And can fill in. But I think he I think he was just kind of like caught in the act. Really?
Speaker 2:That's maybe he's confident enough, hey, AGI is coming.
Speaker 3:Okay.
Speaker 2:AGI is here. Yeah. My stuff's still gonna be worth a lot. Yeah. Even I don't wanna be in the shadows anymore.
Speaker 3:Yeah. That's very interesting. So anyway, Paul Graham clearly does not believe in the Terminator thesis of the AI future where time travel is op, is is is possible. Imagine being in the Terminator future and creating the time machine and just being, okay, I'm gonna go back in time and and paint new paintings that then I can acquire over time and have new Mona Lisa's. He just He was just like, no, we sent you back to save the human race.
Speaker 3:It's like, but I gotta hang out with Leonardo da Vinci. I gotta build my art collection. He said, I don't put too much weight on the specific year, but the shape of the idea is is interesting. And I agree. It is an interesting thing to to noodle on.
Speaker 3:Similarly, CrowdStrike, interesting idea. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. Let me tell you about Turbo Puffer as well.
Speaker 3:Serverless vector and full text search built from first principles in object storage. Fast, 10x cheaper, and extremely scalable.
Speaker 2:Martin Screlly.
Speaker 3:What does he say?
Speaker 2:He's coming on Monday Okay. With a great debate. The great peptide debate says good music is the last mile of AI.
Speaker 3:Mhmm.
Speaker 2:And Lil Wayne some thoughts Let's on AI play this clip.
Speaker 3:Let's play this two minute clip from Lil Wayne on a podcast. Let's see. Here we go. How do you handle AI in this in this business now? Challenge.
Speaker 3:The challenge. Bro, that's wild. I love it. AI is a better thing. I love that AI is what it is.
Speaker 3:Yeah. Because, man, I love to be able to stand right next to whoever AI is, he, she, they, whatever or whatever AI is, stand right next to it, and I'm still better. Hey, man. Up? Go keep telling me what you do again?
Speaker 3:Yeah. Go go run your list. I do this, I do that. I love it. I love the challenge of it.
Speaker 3:First time I seen it, somebody was my my friends was a little worried. They was like, man, Brody got this AI stuff where you couldn't just ask it to do give you a verse like Lil Wayne. And so I did it. I said, let me have a verse like Lil Wayne. He gave me her best shot.
Speaker 3:Yeah. I put it on a couple of devices that, you know, not not only a phone, a computer even for a commercial, I was shooting for the Alexa thing. I wanna hear I have a thing called Proto at home. They got his own little robot thing. Ask her to give me one and they all, oh, you suck.
Speaker 3:I'm gonna be okay. I fuck with that. Yeah. Yeah. Another Beanie Siegel.
Speaker 3:I think he had using it because he like was losing voice a little bit.
Speaker 2:Yeah. Another rapper to Mogg.
Speaker 3:Basically. That's his take. It's so funny. That's great. Well, how does how are designers feeling about AI these days?
Speaker 3:Samir says, bro, it's so over for designers. Google Stitch is insane. Google launched a new generative AI design tool where you can sketch something out on a piece of paper, turns it right into an image. And there was a lot of back and forth over, you know, how how this debate is playing out between Google and Figma. Hadley Harris is twelve years later, the VC who passed on Figma's seed because Google could kill them is finally feeling seen.
Speaker 3:Lots of amazing work done, of course, in the interim. Very, very silly. Will be interesting to see how Google pipes this into the other tools. I was on Google's
Speaker 2:Apparently apparently, this is an engagement bait. Yes. Other people are testing similar prompts and getting much, much, much worse results.
Speaker 3:Yeah. I don't know. I I was on a i.google.com or just a i.google, not even a i.google.com, looking at all the different Gemini features. And it feels like the next the next challenge is is just integrating all these different things. They have, like, so many great models, Nano Banana, VO three, Notebook LM, Gemini, Flow, AI mode.
Speaker 3:There's a there's so many. And, actually, piping of a workflow from one to another is is is certainly going to be, like, the next the next question. And does this all live in the Google search box? Is it in Google apps or something? Either way, they're they're certainly investing in AI across the organization.
Speaker 3:And Ryan Peterson says whoever named Gemini at Google really named it. In the mythology, the immortal twin gives up his immortality to save the life of his mortal twin. It's just like Google giving up a 100% of its free cash flow to make sure DeepMind survives. That is not actually the reason for the name Gemini. But do you know the name for why they picked Gemini?
Speaker 2:Because they had two internal teams that they brought together.
Speaker 3:Brought together. Yeah. The twins. It's a good name. And it's really they were suffering from a bit of a naming crisis for a while with Bard and Palm and they were definitely shipping a little bit of like not not necessarily shipping the org chart, but shipping the some of the internal naming schemes that were, like, abbreviations.
Speaker 5:Even like a Nano Banana Pro, the image models used to just be, like, Gemini 3.1 image.
Speaker 3:Yeah. Or whatever.
Speaker 5:It it they didn't get 3.1, but
Speaker 3:There we go. There we go.
Speaker 5:Like, Nano Banana was famously just like the internal name Name.
Speaker 2:Used. Right?
Speaker 3:Yeah. And sometimes these internal names can can really fly in consumer context. Mostly, I don't know what it is, but something about like Nano Banana, like, really sticks out. It's so funny. There's it it doesn't sound like an AI product.
Speaker 3:Like, when you have Siri and Alexa, and then you have Rufus and Argus or something, Sparky, both from Walmart. Like, doing another human name can actually be a disadvantage because you just get lost in the clutter. But if no one's really using the Nano Banana name I know Strawberry was used by OpenAI before, but no one had really, like, used that as a public name. It certainly, like, helped them helped them break out. But Gemini has been an interesting name.
Speaker 3:It's good it's good. It, like, it balances both. It sounds like a product, but it it it sounds but it's just one word. It sounds like a it it doesn't it doesn't anthropomorphize too much, but a little bit. It is reference.
Speaker 3:There's a lot of deep knowledge there. Quickly, let me tell you about Eleven Labs. Build intelligent real time conversational agents, reimagine human technology with Eleven Labs. And let me also tell you about vibe.co, where DTC startups I didn't like the argument with this. We're DTC brands, b to b startups, AI companies advertise on streaming TV, pick channels, target audiences, and measure sales just like on Meta.
Speaker 3:So without further ado, we have our first guests of the show, Pat Grady and Carl Eschenbach from Sequoia Capital in the What are going on, guys? Carl, Pat, how are you guys doing?
Speaker 6:We're doing great, man. We're doing great. It's great to be with you guys.
Speaker 3:Thank you so much for, hopping on the show on this day. Walk us through the decision. How long have you guys been talking about potentially reunifying? What what's the thinking? What's the role?
Speaker 3:Sort of break it all down for us.
Speaker 8:From the moment Carl left Sequoia.
Speaker 3:Yeah. Come on back. Come on back.
Speaker 6:Yeah. No. Well, maybe I'll just start, and then my my partner, Pat, here can jump in. And I say my partner because I've been his partner for ten years. Like, I joined almost ten years ago, you know, at Sequoia, which was an incredible journey at that time to join.
Speaker 6:And then I decided to step away back into an operating role, you know, after an eight year total journey at Workday, five years on the board and then back into the operating role. And I remember, quite honestly, when I left Sequoia three years, three months ago, I said to Pat and the team, you know, I'll be back.
Speaker 2:I'll be back.
Speaker 6:You'll have me back because I always had wished, I dreamed and envisioned of coming back here, and I thought it would be a great place to end my career and provide the impact to the partnership, my partners and companies that we work with. And, you know, when I stepped down at Workday, now two months ago, we started talking without exaggeration that day. Yeah. Typical fashion, the news was out, and it was within, no exaggeration, five minutes. I started getting texts from Pat Grady Yep.
Speaker 6:Every single partner at Sequoia. Not only did I get them, but my wife started to
Speaker 3:get him.
Speaker 1:Full time.
Speaker 6:And they were like, when is Carl coming back? We want you back. And and I will tell you, it's a it's a blessing to be back, here we are today.
Speaker 3:Okay. Walk me through the bull case for becoming or going back into venture capital in 2026. There it's maybe a little bit crazy narrative, but there's a narrative around like AI is eating everything, AGI is here, the big labs are dominating. They're gonna eat everything. You know, Google is gonna beat every company now.
Speaker 3:OpenAI is gonna beat every company. Sequoia has investments in the labs. What's the opportunity that you see for new start up formation, new growth rounds? Where do you wanna to see opportunity either in AI or in software or outside of AI? Like what is your thesis for why it's going to be a rewarding experience to be a venture capitalist now?
Speaker 6:Yeah. Well, it's a great question, but let me step back and go back two months ago first. When I stepped down at Workday, I did open the aperture up
Speaker 3:Sure.
Speaker 6:And look at everything. Yeah. I looked at everything from going back into an operational role at very large companies, big public companies. I looked at operational roles in private companies. Mhmm.
Speaker 6:And some of those private companies are the AI companies that our friends here at Sequoia at the time had invested in and being part of it. And then I also started to think about, well, what would it be like to go back into Venture, go back to Sequoia at a time of what I would describe as the most massive technology disruption we've ever seen in the history of mankind.
Speaker 3:Mhmm.
Speaker 6:And to be part of it across many companies as opposed to a company is something that really me. Joining someplace like Sequoia, and I'm biased when I say this guy, the greatest venture capital firm on planet Earth ever, Mission Living, the great the greatest partners in the world, people that are smart as hell Yeah. That even I, at this age, get to learn from every day, and to be part of something so iconic in the midst of this massive tectonic shift and get to explore across so many different companies as opposed to a company is something that really excited me. Mhmm. Just in my first two weeks, while I haven't been fully, you know, on board yet until today, I've met with so many companies for Sequoia, right, and got to experience the vibrancy of what's happening in the AI world.
Speaker 6:And I just felt like Sequoia is a place that gives me the opportunity to stay engaged, partner with incredible people like my young man here next to me, Grady and his team, and just be part of a generational shift both at Sequoia inside the building and outside the building when it comes to building tectonic technology companies that will stand the test of time. And I get to be part of that across all different dimensions of this crazy environment we're living in.
Speaker 2:I love it. It's amazing. Sure. So you talk about this massive technology shift, which we can all agree on. Is part of your thesis of coming back and judging from the letter that you sent to the team, it felt like to me like some element of your approach is like, hey, a lot of stuff is changing in terms of technology and markets.
Speaker 2:But a lot of what you're trying to bring is kind of wisdom around maybe what isn't changing which is human nature and leadership and how to work with people and how to get the most out of your teammates. Is that like part of your mindset at all in just coming in and and helping both portfolio companies and the, you know, the entire team at Sequoia just level up?
Speaker 6:Yeah. No. Clearly, I think that's that's a big part of my personal mission going forward. If if you read the letter that I sat down and wrote one evening to Pat and Alfred in the partnership. And by the way, I wrote that letter after looking at a lot of operating roles and talking to a lot of other venture capitalists and firms.
Speaker 6:And I kept coming back to myself and saying, why not Sequoia? Why not Sequoia? That was always my grounding point when I was thinking about what to do next. Fast forward, I wrote that letter because I have a mission in life. A mission in life to give more than I get.
Speaker 6:A mission in life to not focus on success, but focus on significance and impact to others, including my partners, the partnership, and founders. And now being in the industry for thirty eight years and having been here for six and spent thirty two years in operating roles, I felt like I was uniquely positioned to bring wisdom, to bring advice, to bring coaching, to bring mentorship to younger founders, right, to help them achieve their personal and professional goals. And the Sequoia platform and my incredible partners like Pat and Alfred and Andrew and the rest of the team here give me that opportunity to bring what I'm most interested, and that is serving others, to the table at a time that while, yes, technology is moving at a pace and rate that we've never experienced, there's also a need to help people understand how to build, scale, grow, lead, inspire, motivate others. And that's something I'm super passionate about. And my incredible partners here at Sequoia said, hey, this is a place for you to do all of that, both inside and outside the building.
Speaker 6:And and that's why I'm here, and I couldn't be more excited about it, guys.
Speaker 2:Nowadays, feels like it feels like and also in the data companies are growing faster than ever and you get, you know, what would have been maybe ten years ago, like five years of company building compressed down into two years when you're kind of mentoring CEOs or leadership teams, you know, in the portfolio, how like, what what advice are you giving them around that new dynamic, which is that, hey, you might raise three rounds in a year. You might be adding headcount at a much higher rate than you had to. And meanwhile, again, the technology is shifting at this insane exponential rate as well.
Speaker 6:Yeah. So it's a great question. And I'd have Pat chime in because they're seeing this, you know, obviously, every single day. Companies are raising a round. And one, two, three weeks later, they're raising another round, and then they're trying to figure out what the hell to do with that capital.
Speaker 6:But let me go back and just share with you one of the principles that I've always focused on when it comes to business strategies. And I always have talked about speed as being one of the best business strategies ever. This is long before the current environment we're in. And I say that because I use, if you will, a sports analogy. If Pat is faster than me, is operating or executing faster than me, running plays faster than me, it's hard to defend.
Speaker 6:Speed is a business strategy. And right now, we're in the midst of everything happening very, very quickly, so speed becomes more important. But you can't be sloppy. You can't do things in a wasteful way. You can't just spend unlimited capital because at some point, that capital will have to be replenished and now have to come to people like us and others.
Speaker 6:So I think there's a dimension of how to leverage speed as a winning business strategy, but also be smart about how to do it and where you're spending those dollars. And I'll let Pat chime in and what they're seeing. I saw it today on some of the calls that Pat was leading across the partnership.
Speaker 8:Yeah. I I think that's well put. Speed is, you know, one dimension of a vector. The other is direction. I think the other thing that's interesting right now, it's not just how quickly things are happening, it's how dynamic the entire market is.
Speaker 8:You know, our partner Constantine has this framework that there are some revolutions in computation and some revolutions in communication. A revolution in computation is about the way information is processed. A revolution in is about the way information is distributed. Cloud, mobile, Internet, all of those are revolutions in communication. It's about the distribution of technology or of information.
Speaker 8:This is a revolution in computation. It's about the processing of of information.
Speaker 3:Like
Speaker 8:that. The result of that is that the raw ingredients that you have available to build your product change every day or at least every week, possibly every month. But they're changing fast. Yeah. Right?
Speaker 8:And so you could be running like heck in a particular direction. If it turns out that that technology floor shifts underfoot, all of sudden, you gotta change direction. And so I think one of the big sorta things we have learned from the founders who are doing it best, the Daniel Nadlers and Winston Weinbergs of the world, is that talent density matters so so so much. If you it's not about being bigger, it's about being better. It's about having the densest possible talent pool so that when the world shifts, you're not caught flat footed.
Speaker 8:You go in the right direction.
Speaker 3:Mhmm. Makes sense. It feels like an amazing time to join Sequoia. The technology industry is bigger than ever. Venture capital is bigger than ever.
Speaker 3:We're in an AI boom. But I'm wondering if you could turn back the clock for me and tell me what the vibe was like when you joined VMware because it feels like a very different time. And and what was that like, you know 02/02? Yeah. 2002.
Speaker 3:Right?
Speaker 6:Yeah. Wow. You're taking me way back. Yeah. I joined VMware in 2002.
Speaker 3:Yeah.
Speaker 6:And when I joined, I think there was a couple 100 people with probably 95% of them being engineers. I think it was a deeply technical company by great great founders out of Stanford and Diane, you know, the founding CEO. Great people. And I remember joining, you know, this young little company, basically no revenue, and saying, hey. We're gonna go change the world.
Speaker 6:Like, startup says, we're gonna change the world. And I remember Diane Green saying to me, we're gonna virtualize these little x 86 computers, and the entire world's gonna run on top of them. And I remember talking to Diane at the time, he said, Diane, you mean, like, mainframe partitioning, LPARTs? That's where we do. But then he said, no.
Speaker 6:We're gonna do it on these little pizza boxes. And I'm like, who's gonna hell who the hell is gonna do that? Right? And then I went home and I thought about it. Yeah.
Speaker 6:And then I had to go, quite honestly, to my wife and say, alright. I just left working for a Bay Area company, living in Pennsylvania computing. I committed I wouldn't do that again. And I thought about this more, I said to myself, wow. If Diane and this incredible technical team can do what they say they're gonna do and turn that slideware into software that virtualizes these servers and allows you run multiple applications operating with systems simultaneously.
Speaker 6:I said to myself, if they can do that, the next thing I said is, I can figure out a distribution strategy and I can sell that shit, silly.
Speaker 3:Yeah.
Speaker 6:And the journey began there. The first year or two, no one was buying it. It's like all startups could go through that phase. Like, wow. You want me to take all of these ten twenty servers
Speaker 3:Yeah.
Speaker 6:Physical servers, separated by physical computers and put them on one. And if that server goes down, then everything goes down. And I'm like, yeah. That's what you should do. Yeah.
Speaker 6:You didn't go real well at the beginning. But then we hit an inflection. And then once we hit an inflection with this technology at the time that they brought to market, it was called vMotion, which would actually allow you to take a live running virtual machine and move it across physical servers without the application ever going down. So now you had some redundancy and backup. And when we started to show people that, first, they're like, wait, this isn't really working.
Speaker 6:So we had to unplug cables to show things were actually working. And then it inflected and, quite frankly, one of the greatest, you know, professional journeys of my life, being there fourteen years, a couple 100 people to 20,000. Yeah. And and I was so blessed to be there because I got to do so many different roles in the company. I was never CEO.
Speaker 6:Mhmm. I was always, I guess, number two guy at the time across three great CEOs between Diane, Paul Maritz and Pat Gelsinger. And I got to be a CFO for a while at a public company, got to help run product when our CTOs left. It was just an incredible journey. It gave me a view into a startup.
Speaker 6:Mhmm. And it gave me a view of how to scale companies. And it really helped me get a deep understanding of how to build global operations and build them at scale at the enterprise level. Yeah. Why did you what
Speaker 2:what made you push through that one to two years where you felt kinda silly even selling the product just given that that, there wasn't it didn't feel like you weren't feeling that pull from the market. Eventually, you got the breakthrough with vMotion. But what was the signal that made you keep just running down opportunities?
Speaker 6:Great question. Very simply, the engineering talent at the time and if you look at now, the industry is proliferated with incredible talent from VMware. It's everywhere. From CEOs to head of sales to head of engineering, it's everywhere. What gave me the conviction and belief to keep pushing through is whatever that engineering team said the product would do, it would do.
Speaker 6:And I kept saying, I remember at the time telling people, right, we moved from forecasting numbers or revenue or bookings to forecasting. Literally, our forecast calls was how many proof of concepts have we started because if someone tested it, it worked. It literally worked. And we were having
Speaker 2:So the market was like, we don't believe you, and you just had to you just had to actually convince them to let you show them.
Speaker 6:Yeah. Well said. I had passion, I believe, I had conviction, and I witnessed the technology working as advertised. A lot of times, it does it in start ups, and it takes a while to get there. And I knew it was not if.
Speaker 6:I knew it was when the market would tip and come our way. And then when it tipped and inflected, it took off very quickly. And then we started to see all this competitive pressure come in with open source technologies like KBM, OpenStack, Hyper V by Microsoft. But we just stayed focused. We stayed convicted about the technology, and we proved it time and time again to anyone who tested.
Speaker 6:It was an incredible journey, and I'm so grateful for that fourteen, fifteen years.
Speaker 2:Amazing.
Speaker 3:Yes. It's such a such a wild ride. I mean, you've, at various points, been working in organizations of a 100 people up to 20,000. Do you feel like you have a good calibration on when you're talking to a founder or an executive, just asking yourself the question, can you see this person thriving in an organization that's three orders of magnitude bigger? I don't even know if that's a relevant question anymore for a venture capitalist to be asking, but I'm curious if you feel like there is a set of patterns that you've discovered or a set of skills that are on display from younger, more up and coming executives and founders that sets them up for success at massive scale.
Speaker 6:Yeah. I think I can identify patterns and I have enough experience for the six years that I was here with Pat and the team and learning from them about what to look for in a founder and whether or not they can scale. Yeah. One of the things I absolutely look for is self awareness in founders.
Speaker 3:Mhmm.
Speaker 6:And are they honest about what they're good at? Because a lot of these founders, quite frankly, are just incredibly intelligent human beings. And sometimes they they they can do everything when in fact they can do everything but not great. And they have something they're really good at. And do they have self awareness to say, but I need to go get to other people as part of the company to help me scale so I can focus on what I'm really good at.
Speaker 6:Do they have the ability to know when to turn things over to others is critically important, and I've seen that happen time and time again. And then the other things, quite frankly, that I personally look for, I'm sure Pat I heard Pat talk about this this morning, there are attributes and characteristics of people that I look for that are way beyond the intelligence side of the equation. You can't teach grit. You can't treat strive. You can't teach a great attitude.
Speaker 6:You can't teach determination. Right? All of those are things that are innate and part of people, and you want to see that in these founders. And when you find someone who has that passion, drive, desire, relentless ability to fight through challenges, issues, and opportunities, and then they have the intellectual horsepower on the other side, when that comes together, that's a beautiful thing.
Speaker 8:I actually reminded the first time I I don't know if Carl remember this. First time I met Carl was twenty ten. Mhmm. And it was Doug Leone, Fred Luddy, who's the founder of ServiceNow, and I went to visit Karl to get some advice on scaling ServiceNow. And I was probably in my I was in my late twenties.
Speaker 8:Karl's in
Speaker 6:his early forties. Still in his late twenties. Yeah. Look how young this guy is. And It bothers the hell out of me, guys.
Speaker 6:How young, how smart, helping brought one of the most iconic, you know, partnerships in the world. And here I sit turning 60 this year. He pisses me off every time.
Speaker 8:But so I I have, like, pages of copious handwritten notes from this meeting, which I'm sure exists somewhere around here. But the the one liner that stuck in my brain, is very consistent with what Carl was just saying, was attitude determines altitude and will determines skill. And I always think about that and and we kind of morphed that into the expression attitude is the ultimate input. Mhmm. And I think when you see these founders I'd also kind of use the Ray Dalio line, you know, pain plus reflection equals progress.
Speaker 8:Mhmm. When you see these founders who are willing to take a risk and experience the associated pain and then reflect very honestly on what happened and what they can do better next time, progress is inevitable. Mhmm. And so I'd I'd almost say there's this, and like, you have to have the right attitude to put yourself in that position. But if you're willing to take risk and experience a little bit of pain, and then if you're willing to be intellectually honest with yourself and self aware and sort of clinically diagnose what you can do better next time, like, those founders are just gonna keep cranking.
Speaker 8:Yeah. Really well said.
Speaker 2:Long introspection. Yeah. Taking aside taking aside on the introspection gate.
Speaker 3:Was gonna try and tear something up, but you really delivered. Talk to talk to us about both of your agreements or disagreements maybe. I'm sure you've been debating the future of enterprise software, the future of what's going on in the SaaS pocalypse public companies, like just the nature of business changing. What remains true now that hasn't changed and won't change for decades versus what maybe has changed in the last few years and needs an update in terms of how people think about how businesses grow, how businesses flourish in when they're working in the technology industry.
Speaker 6:Yeah. I'll let Pat start, and then I'll I'll give you my perspective because I've answered this question about 17,000,000 times in the last three and a half years at Workday. And I have a different perspective than probably most.
Speaker 3:Yes.
Speaker 8:So, you know, it's funny. The first thing that comes to mind is a line that I learned from a man named Karl Eschenbach
Speaker 1:Oh, yes.
Speaker 8:Who who is a partner at Sequoia from 2016 to 2022. Mhmm. And, the line is people do business with people. Mhmm. And I think there's a there's an there's a foundation model maximalist point of view that the labs themselves are gonna do every everything and every nook and cranny of the economy.
Speaker 3:Yeah.
Speaker 8:And I just have a hard time imagining that version of the future coming to fruition because people do business with people. Yeah. And I think that between a job to be done and the raw capabilities
Speaker 3:Mhmm.
Speaker 8:Of a model, there's a lot that needs to happen. But, like, shape it into the path of least resistance for you to travel down as a user
Speaker 3:Yeah.
Speaker 8:To get to the right answer with the least amount of pain. And there's probably a person in between who's gonna do that work. As a customer, you wanna do business with that person. And so I I think people do business with people is gonna remain true. Mhmm.
Speaker 8:The shape that that takes in terms of what the businesses are is probably gonna change. I think in the world of software, you know, the first wave on the on prem to cloud transition was this transitioning of systems of record, you know, the workdays and Salesforce's and ServiceNow's of the world. The second layer on top of that was the systems of engagement. You know, those systems of record might own the core database, but then there are a bunch of different workflow applications that reside on top. I think what we're gonna see with this the wave of AI software is this third layer on top of those, which some people call system of intelligence.
Speaker 8:I don't wanna call it that. It's the layer that does the work. You know? It's the it's the agents getting deployed that may or may not need those workflows beneath them, but certainly need access to everything that's sitting in that system of record. Mhmm.
Speaker 8:I think that's what we're gonna see. And and as a result, I think those system of record companies are relatively safe. Mhmm. They may not catch a lot of net new workloads because a lot of the net new workloads might go to the AI native companies. Mhmm.
Speaker 8:But I think they're overall pretty safe. I think some of those workflow based companies in the middle are in trouble because they're neither the system of record nor the Eugenic capability that's getting deployed.
Speaker 3:Yep.
Speaker 8:And so they'll have to figure out how to become, like, that agent harness, so to speak, for whatever job needs to be done. And then I think those AI native companies on top, the the basic thing they need to achieve is figure out the context of this organization, figure out the guardrails, come up with some sort of an eval framework, some come up with some sort of a value function. Basically, wrap all the context around the capabilities of the of the foundation model to achieve the outcome that the business person wants. And so I I think there's a very important job to be done for those that new layer of companies. And and, again, people wanna do business with people.
Speaker 8:Like, there's a lot of value in, you know, having somebody you trust take your hand and lead you into the AI future. Yeah.
Speaker 6:Yeah. I love it. So so first of all, it's the first time I heard someone else ask this question to someone else other than me. And
Speaker 2:And then use you for the answer.
Speaker 6:Actually, it's so funny. I was sitting here thinking, I am gonna respond, but you're gonna hear something very similar from me.
Speaker 3:Sure.
Speaker 6:I'll start in kind of reverse order. I do think there is power, to use Pat's exact analogy, of a system of record, a system of action, a system of engagement, and I will use system of intelligence. Mhmm. Because I think if you have the bottom three and you can layer on an agentic or agent strategy and you back that up with the data, the context of the data, and you own the business process workflow, you're in a unique unique position to have a great enterprise AI software company that stands at test time.
Speaker 3:Yeah.
Speaker 6:I don't think we're in a world where does AI win or do the incumbent SaaS companies win. I think we're in a world of and. Mhmm. And I think some people are the beneficiaries of AI like a Workday, like a Salesforce. And then others maybe have more headwind because they can be disintermediated because there's AI and you don't need access to all that data.
Speaker 6:I personally believe all of the challenges with software companies at scale and what's happening in the stock market are completely overblown. I've been saying that repeatedly. Mhmm. They're not going anywhere. Mhmm.
Speaker 6:Incumbency is incredibly powerful in the enterprise. Yep. Incumbency is even more powerful for in a company like Workday, who I was blessed to be there for over three years, has a 98% gross retention rate of 11,000 customers, 65 plus percent of them being Fortune 500 companies.
Speaker 3:Yeah.
Speaker 6:Not going anywhere. And the other thing we can't forget is why I say and is because what matters in the enterprise is scale, security, and compliance. Mhmm. And some of these big SaaS companies have that. Mhmm.
Speaker 6:That all being said, the pace and rate of change that can happen outside of the big incumbent and big SaaS companies who are innovating like crazy, we're innovating at Workday like I've never seen, have an opportunity to start completely fresh and start from scratch, get to leverage all the technologies and all the models that are out there, and build agents and agentic solutions faster than anyone else. And they're going to be able to go in the enterprise and provide value day one, either on their own or on top of and through some of these SaaS companies. So I think it's an and opportunity that's going to happen in the enterprise, in the market as a whole. There's going to be some winners. There's going to be some losers.
Speaker 6:But I think the current narrative out there of these SaaS companies being overblown or being in trouble is completely overblown.
Speaker 3:Mhmm.
Speaker 6:And, obviously, I'm biased. I think Workday stands in a very unique position to completely, you know, continue to crush the ERP market, both on the HR and finance side. And I couldn't be more bullish on the opportunity ahead. But at the same time, I'm super excited watching these young, talented people now that we get to invest in and how quick they can iterate leveraging AI and just completely disrupt markets
Speaker 3:Yeah.
Speaker 6:Legacy markets that don't have all of the data, don't have the context, and don't have the work flows.
Speaker 2:What advice would you give to a Fortune 500 CEO that maybe is an incumbent that's thinking about buying versus building these agentic products?
Speaker 6:I tell them to do both. I think if you have all the data and you have the context of the data and you can build a great engineering team, right, that comes with an AI background, build as much as you of it you can. At the same time, go do acqui hires. Go buy technology companies that are completely AI native from the beginning and bring them into your organization. I wouldn't say do one or the other.
Speaker 6:It's both. Mhmm. You know, at Workday, in the last six months I was there, we bought four AI companies, and they've become part of the core fabric of the company that Aneel and Garrett and the leadership team there get to take advantage of. At the same time, they bring in their talent on their own as they build out their organization. So I don't say think you say it's it's one or the other.
Speaker 6:You have to do both.
Speaker 1:I think
Speaker 8:it's also one the classic questions of what do you want your best people focused on. You know, do you want your best people building the same sort of stuff you can get out of the box from somebody else who spends all day long thinking about that thing? Or do you want your best people creating competitive advantage for your company? Like, I think if you're a Fortune 500 company right now, kind of a no brainer to go with Hardeep for everything related to legal, kind of a no brainer to go with Sierra for everything related to customer support. You know, you should probably try something like Expo to work on pen testing.
Speaker 8:Like, these are excellent companies with excellent excellent people who spend all day obsessing over a particular problem. Why take your best engineers and ask them to go do that? Go go do something that's gonna be unique to you.
Speaker 3:K. Last question.
Speaker 6:Pat, by the way, Pat makes a great point. Having spent a lot of time with CEOs of Fortune five hundreds around the world, there's this whole narrative. We're gonna do it ourselves. We're gonna build our own agents, and they will do some of that. But why if you can go to a Harvey, right, get what they've already built and leverage it and very quickly get a return on that investment so there's a time cost to value equation here for the enterprise, go with that solution.
Speaker 6:And let them go focus on financials or insurance or retail or whatever is CPG. You know, let them focus on what their core business is. Why build that technology if someone could do it much faster outside the company?
Speaker 3:K. Last question for Carl. A few years ago, you were spotted at the Allen and Company conference sporting two coffee cups. You have an incredible amount of energy. Are you a two coffee in the morning guy, or were you bringing an extra coffee for a friend?
Speaker 6:Well, it the answer, I hate to use this term again, but both.
Speaker 3:Okay.
Speaker 6:I was bringing coffee. I was bringing a coffee back to the room for my amazing wife of thirty five years, Anna. And and
Speaker 3:and Hey, Ben.
Speaker 6:Yeah. And and and I used to drink probably eight to 10 to 12 cups of coffee a day.
Speaker 2:There we go.
Speaker 3:Wow. That's amazing.
Speaker 6:And that's all I have all day until I get to dinner when I eat dinner. It's my one meal a day.
Speaker 3:Fantastic. Wow. Incredible amount of Well, it's clearly working. Thank you so much for taking the time come chat with us.
Speaker 2:It's so good to see you guys both
Speaker 5:back together.
Speaker 3:Yes. No. Thank you.
Speaker 6:And I I just wanna say, listen, I I just wanna thank Pat. Yeah. I wanna thank Alfred. I wanna thank the entire partnership here at Sequoia for allowing me to join them and serve alongside them.
Speaker 3:Yeah.
Speaker 6:Our partners, our customers, our companies we're investing in, our founders. It's a true honor to be back. I'm super excited about the journey ahead. And I think, you know, Sequoia is uniquely positioned to continue to be one of the most iconic, mission oriented venture firms of all time, and I'm proud to be back part of
Speaker 7:it.
Speaker 3:Yeah. We're we're excited for you. Thank you so much.
Speaker 2:Incredible stuff.
Speaker 3:We will talk to you soon.
Speaker 2:Great see you guys.
Speaker 3:Have a good rest of your day.
Speaker 2:Cheers.
Speaker 3:Goodbye. Let me tell you about
Speaker 2:Ten to
Speaker 3:twelve mission.
Speaker 2:Coffees a day.
Speaker 3:That's incredible. They're the makers of Devon, the AI software engineer. Crush your backlog with your personal AI engineering team. Let me also tell you about Finn, the number one AI agent for customer service. If you want AI to handle your customer support, go to fin.ai.
Speaker 3:And without further ado, we've been running along, but we will bring in Jim Cantrell from the Phantom Space Corporation. Sorry to keep you waiting, Jim. Thank you so much for taking the time to join the show. How are you Please, you have a fascinating background. Give us a little bit of your background leading up to this company, and then I wanna talk about how you're thinking about the business and also just the orbital economy more broadly.
Speaker 4:Yeah. So I've been in the automotive and aerospace industries for north of thirty five years and had positions everywhere from the front space agency to early SpaceX. I was the guy that took Elon to Russia to buy Russian missiles and when that didn't work, we started SpaceX. And after that, I am on my twelfth space or automotive startup, and Phantom Space is the last one of them. But several of them have gone public Yeah.
Speaker 4:Since then. And, you know, Phantom Space was sort of the ultimate Yeah. Of all these startups that that looking to solve the problem, I think, really needs to be done.
Speaker 3:Yeah. That that story of going to Russia to try and buy the ICBM has been has been told and written about in books. But what what does the current narrative get wrong? What's your side of the story? What were expectations like going into that meeting?
Speaker 3:Did you was it seen as a long shot at the time, or did you think that it was likely to work?
Speaker 4:Yeah. No. It was a complete long shot. You know, when he when Elon called me, he had just left PayPal Yeah. And had this idea of, you know, trying to inspire humanity to become multiplanetary, as he still talks about.
Speaker 4:Yeah. And he wanted to do what amounted to a stunt to to, you know, show that we could send creatures to Mars.
Speaker 3:Right.
Speaker 4:That turned into something that we put together, which was a growth chamber to land on Mars on a lander, and we needed Russian rockets to buy it. So by the time we got done dealing with the Russians, they didn't wanna sell to us. They were just being Russians. And Elon announced to all of us in sort of shocked way, we we we heard that he wanted to start the company SpaceX and build the rocket ourselves. So I will tell you that very few people gave us a snowball's chance in hell to make that happen.
Speaker 4:Now we we can see twenty five years later where that ended up. But, you know, everybody betted against Elon and the rest of us. And, you know, what the story's gotten wrong and what it gets right. What it gets right was, you know, this determination of this guy who knew nothing about rockets, who decided to learn everything he could. And he he got a bunch of space cowboys around him, and most of us were sort of revolutionaries in thought at least and wanted to stick it to the system and do something that everybody said we couldn't do.
Speaker 4:But story got wrong. Sometimes people write and say I was never part of it. I don't know why that got written in, but I was definitely employee and had founder stock in the whole nine yards. So here I am.
Speaker 3:There you go. Amazing. What's the modern version of the the long shot in space? We've heard about colonies on the moon, colonies on Mars, space data centers. What do you think is the most practical problem right now in space that people are maybe undercounting?
Speaker 4:So I think there's three tracks that it's going down. One is is, you know, military use of space, which we see ongoing today. Right? Wake up and read the news every morning.
Speaker 3:Yep.
Speaker 4:The second one is planetary settlement, which is what SpaceX is trying to accomplish. And everything that Elon does, I believe, is aimed at that planetary settlement goal. And then the third is kind of more recent, even though I've been thinking about it for almost a decade, is putting compute in space. So now AI is the killer app Yeah. That enables us much like the Internet came along as killer app that enabled Starlink.
Speaker 4:So I think what we'll see is the next generation of AI in space, these so called space data centers, but not in the way that the the the common narrative is going to portray it.
Speaker 3:Okay. How will it be different? I mean Jensen Huang at GTC earlier this week was standing on stage saying that he will be providing chips. Elon has given some outlines around what that might look like. We've talked to Star Cloud, a start up that's planning to put data centers in space.
Speaker 3:There's a whole bunch of other people that are approaching this problem, but how do you think people are getting it wrong and and and how do you think you fit in?
Speaker 4:Yeah. So, you know, NVIDIA Yeah. To just address that is is nailed to silicon. Right? Yeah.
Speaker 4:So so they're they're gonna be the winners on that,
Speaker 3:I believe. I think so.
Speaker 4:Among others. Right? But they're gonna be one of the primary winners and Yeah. And thank you for doing that, Nvidia. Mhmm.
Speaker 4:Number two is there's gonna be a camp that I think is mostly hype that says we're gonna put, you know, these these larger language model hyperscalers into orbit. Mhmm. If I'm generous, that's maybe twenty years out. Right? Yeah.
Speaker 4:And and it's like flying a big factory on a on a huge rocket that doesn't exist there. So everything that's gonna happen in the future is going to be distributed data centers on a much smaller scale. Mhmm. Everything's more expensive. Right?
Speaker 4:So we're at least 10 times, maybe a 100 times more expensive to do something in space today. So so the the the the really killer app I see is to put AI inference in orbit Mhmm. Close to where the data tsunami is being generated. And it's today, it's a tsunami, and tomorrow, it's gonna be a mega tsunami. Mhmm.
Speaker 4:And what the problem is is is being able to get that data back. So there's there's this this funnel that restricts how much of that can get back. So AI is a natural way to reduce that data load and get it back to the Earth. Maybe later we'll solve the the the issues with, you know, with with with the earth power and and heating. But, you know, Phantom, you know, we've been at it for ten years, one form or another, writing patents, writing about it, speaking about it.
Speaker 3:Mhmm.
Speaker 4:It's nothing new for us. And we're putting together micro data centers to address exactly this along with data backhaul from the satellites to really exploit what we think is the next killer app there and create a Space App Store environment for others to implement their their creativity on.
Speaker 3:So where do you think in the supply chain or the rest of the orbital economy, there is enough maturity that you will never really need to, build? I imagine you're not gonna build a new rocket, but are you planning to do connectivity through Starlink? Like, where will the partnerships happen? And then where will your, you know, your core value prop live within the supply chain?
Speaker 4:Yeah. It's it's a great question because this is exactly where I think all the the differences between the approaches become evident. So it's my belief that, in order to be successful in this, you really have to vertically integrate much the way we did in the early days of SpaceX. We saw that building the rocket and building your satellites and then implementing, in their case, Starlink and now, you know, their version of x AI in orbit. Yeah.
Speaker 4:You really have to have that. And, you know, SpaceX is is gonna dominate a lot in that phantom space. We have exactly the same playbook. Mhmm. So those who don't have that vertical integration are always gonna be at the risk of what amounts to a very scarce launch supply.
Speaker 4:Even today, you know, there there is a perception that there's more launch than we need, and it's not true at all. It's very scarce. You know, Phantom, we're building something we call the Daytona, which is quite a bit smaller than anything SpaceX builds. So we're more the taxi, they're more the freightliner. And so so, you know, we find a real market for that.
Speaker 4:People are buying our things and there aren't that many people that can actually build launch vehicles at work. It's a really tough business and it takes five to ten years. So so that's gonna always be scarce. The rest of it is really a matter of supply chain control.
Speaker 3:Yeah.
Speaker 4:So so the, you know, the silicon, NVIDIA, you know, all the rest of the satellite parts, suppliers, but, know, you have to have somebody put it all together, operate it, and manage it. So we think of ourselves as building the railroad to space, And then ultimately, the Space App Store on top of it so that people can build their own code.
Speaker 3:Yes. Talk about some of the trade offs of the launch vehicle decisions. Are you thinking about reusability? Is that less of a factor at this scale? How frequently do you wanna be launching?
Speaker 3:Like, I imagine taxis, they go everywhere. They launch from everywhere. Like, how else, play out the taxi analogy for me a little Well, bit
Speaker 4:so so launch is like the critical cost of getting any data system into orbit, period. And so, you know, it's it's incumbent on companies to control that cost. And if you can build it internally, if you can gather the capital and the talent to do it Mhmm.
Speaker 2:You're in
Speaker 4:better shape. So there's there's a trade on getting that cost down between building them super large like Starship and reusability and then mass production.
Speaker 3:Mhmm.
Speaker 4:So mass production like the car you drive probably cost a $100,000,000, you may be paid a $100,000 for it. Yeah. And there's a huge cost reduction through this year number. So at Phantom, we're gonna apply both the reusability and the mass manufacturing because we're smaller, we can do that. Whereas Starship, as an example, won't necessarily be mass manufactured but probably mass used.
Speaker 4:So reusability is a core thing more for the logistics of these things. And then the other side of it, here's the other choke point in the business is launch sites. We are really out of range capacity, launch range capacity in The United States. And we will be, I think, at that limit within five years. And so companies that control that range capacity are gonna be in a position to control, you know, the railroads or the shipping lanes as it were.
Speaker 3:Are you looking yeah.
Speaker 2:What's the process to create more capacity?
Speaker 4:So it's very complicated, it's very bureaucratic and it's very political. We have five different launch ranges in The United States. Exactly.
Speaker 2:Music to my
Speaker 1:ears. Yeah, right.
Speaker 4:So most of them are all federal ranges that we built during the Cold War. And there's one in California, one in Florida, we know at least about the one in Florida very, very nicely, Cape Canaveral. And so there are so many pads you can put on there. Most of what we're using today is legacy from what what was built in the Cold War. We're we're grandfathered into the, you know, the the pull the the the the bureaucratic process that approved those pads.
Speaker 4:So any new ranges, you're gonna run into huge opposition. There have been people who tried to build new ranges on the coasts of of this country, and everybody not in my backyard comes out of their home to to oppose it. Right? Mhmm. And even in California, Vandenberg.
Speaker 4:Yeah. You know, SpaceX recently got in a lawsuit. We had about half their capacity, which was governed ultimately by the coastal commission in California. Yeah. And, you know, SpaceX had to sue and they got a little bit more capacity, but that that's what we're heading into.
Speaker 4:That's why you see these launch ranges around the world coming into play. Yeah. And the the problem for US companies is we're restricted from taking our launch vehicles to these foreign countries without government approval.
Speaker 3:Yeah. Yeah. It's so tricky because I I can imagine living next to, you know, a a launch pad. And and the first time the rocket goes up, you're like, wow. That was amazing.
Speaker 3:And then if it's like, we're gonna be launching those every twenty minutes. Like, my windows are shaking a lot. I actually would like. Exactly. The novelty wears off pretty quickly.
Speaker 4:Cool. Just gonna see. Yeah.
Speaker 3:Yeah. And and so and so, yes, we're obviously as a country, we need to figure out where these go that are not disruptive and are scalable and are tied to the supply chain. Maybe actually near a railroad. Who knows? A physical railroad.
Speaker 2:Give us give us any predictions around the moon economy I
Speaker 3:was gonna say moon.
Speaker 2:Over the next Yes. Decade.
Speaker 6:Yeah. I have
Speaker 4:to say I'm surprised by the by the SpaceX pivot to the moon. Okay. It's been something, you know, since I was first in this business that a lot of us saw as a logical pivot. And there was it was almost like a religion between do we go to the moon first or we go to Mars?
Speaker 2:Right. So you thought it was logical like To do twenty
Speaker 3:years ago. Right?
Speaker 2:And so you're surprised you're surprised for how late the pivots happened.
Speaker 3:Yeah.
Speaker 4:It it doesn't really matter, honestly, in terms of their technical capability.
Speaker 3:Sure.
Speaker 4:It's it's it's more incremental in terms of the development of the technology, which is probably why they did it. I really don't know why they did it. Yeah. It could be a business decision. There's certainly, I think, a more near term economy there.
Speaker 4:I think of Mars, you know, as as being so far away, eventually that economy will have to form on its own, kind of like this new world where we all sit formed as an independent economy from Europe five hundred years ago, it began forming. And Mars someday will have its own manufacturing bases and, you know, you you might have products labeled made on Mars, right? But that's a longer term thing and, that's really where Elon's mind always was, you know, from the early days that I was with him, that it was all about Mars. And to me, the movie is just a stepping stone on on that way, and I think there's a lot of people who see that as a, you know, sort of a effectively a theological choice. Where it's really not.
Speaker 4:It's it's just a technical issue.
Speaker 2:Mhmm. Economic opportunities on the moon Yeah. That you think are interesting?
Speaker 3:We've heard about regolith and and and maybe like a mass driver, but there's so many opportunities, obviously, besides tourism.
Speaker 4:The most obvious one is helium three. So this is pushed out by the sun. There's something like 18 kilograms of it in The United States and this is strategic resource. It's a byproduct in nuclear weapons manufacturing. Now, what are you gonna use it for?
Speaker 4:Well, you can use it for a couple of things. Clean fusion energy is one of the few fuels that doesn't create radioactivity as a byproduct. So that's obviously desirable. Right? The second part is for quantum computing, which a lot of these have to be near zero.
Speaker 4:So this is one of the few substances that you can cool to near zero temperature, and the other is an absolute zero in temperature. So there's a huge demand on that now, once you start mining it, does that, you know, that price collapse? Probably to some degree. The second one that I see is this this mineral, this rare earth mineral kinds of deposits, and we honestly don't know enough about what's up there. We have a pretty good idea from the Apollo missions, but there's probably a lot of rare earth deposits, my guess, and I don't know geologists, but I would guess there's probably some rare earth minerals that, you know, mining from the moon, which would be more palatable than tearing up our beautiful earth Mhmm.
Speaker 4:Would be as long as we can solve the transportation problem. And all comes back to the rocket, by the way.
Speaker 3:Yeah. Makes a lot of sense. Well, thank you so much for taking the time.
Speaker 9:Yeah. Great to
Speaker 3:meet Douglas. Congratulations. And we'll we'd love to talk to you soon.
Speaker 2:Yeah. Come back. Alright.
Speaker 3:Bye bye. Have a good rest
Speaker 2:of your day, Let
Speaker 3:me tell you about Cisco. Critical infrastructure for the AI era. Unlock seamless real time experiences and new value with Cisco. And let me also tell you about Console. Console builds AI agents that automate 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets.
Speaker 3:And without further ado, let's bring in Tom from GV. Tom, how are you doing?
Speaker 2:What's going on?
Speaker 10:Hi, guys. Can We
Speaker 3:could hear you for a second. Can you hear us?
Speaker 2:You're back.
Speaker 3:You're back. Where are you calling in from? Can you hear us? No? Yes?
Speaker 3:No? Check. It's okay.
Speaker 2:Check.
Speaker 3:Can you hear this? I'm gonna tell you about Sentry. Sentry shows developers what's broken and it helps them fix it fast. That's why a 150,000 organizations use it to keep their apps working. Could you hear that?
Speaker 3:Because I could also I can also potentially tell you about the New York Stock Exchange. Because if you wanna raise the cap if you wanna raise capital, Tom, you gotta do it at the New York Stock Exchange. I'm sure a lot of your companies are aiming for IPO. Let's get them live on
Speaker 2:the Well, New York Stock get Tom back.
Speaker 3:Will we will have team troubles.
Speaker 2:Is some breaking news that we do gotta talk about, which is that Jeff Bezos
Speaker 3:more fired up than a personalized ad. Okay. Breaking news.
Speaker 2:Jeff Bezos in talks to raise a 100,000,000,000 for AI manufacturing fund. The Amazon founder has traveled to The Middle East Singapore in fundraising effort linked to project Prometheus.
Speaker 3:That is incredible.
Speaker 2:Very exciting.
Speaker 3:We have the red lights going.
Speaker 11:Exciting.
Speaker 3:Breaking news. Advanced talks. I don't care if it's just advanced talks. I'm hitting the Congratulations to Jeff Bezos.
Speaker 2:He's meeting with some of the world's largest asset managers to raise funds for the project. A few months ago, he traveled to The Middle East to discuss the new fund with sovereign wealth representatives. Mhmm. More recently, he went to Singapore to raise funding for the effort as well. Mhmm.
Speaker 2:He's it's being described as a manufacturing transformation vehicle.
Speaker 5:Mhmm. I Wait. Against TK. Right?
Speaker 2:I mean, TK is not as directly focused on manufacturing. Like, this is vehicle. Right? No. No.
Speaker 2:He's saying manufacturing transport like, it's a vehicle, a fund for transforming manufacturing.
Speaker 3:Oh. Yeah. Yeah. Yeah. Yeah.
Speaker 3:Yeah. It's like an investing vehicle.
Speaker 2:It's aiming to buy companies in major industrial sectors such as chip making defense vehicle industry. Aerospace. Let's try again with Tom. Get out of here, Tyler. It's on time, Tom.
Speaker 3:Here we go. Hey, Tom. Can you hear us?
Speaker 2:Oh, no. Okay. No. We don't have audio. We don't have okay,
Speaker 3:guys. Try it out. Nothing? Okay. We you can hear us.
Speaker 3:We can't hear you. But we can tell you about this post that we enjoyed from Lilarieken. Got my horse to water. Now for the easy part.
Speaker 2:I'm gonna continue. The fund is aiming to buy major industrial sectors
Speaker 3:was laughing about that.
Speaker 2:Such as chip making defense in air space. It would dwarf the size of some of the world's largest bio funds and rival SoftBank's a $100,000,000,000 fund. I gotta wonder how much how much do you think how much do you think Jeff is pitching in himself? I could see him Mhmm. You know, anchoring.
Speaker 2:He's like, I'm good I'm good for 30. Yeah. You know, something in that range.
Speaker 3:Yeah. Yeah. Yeah. He's he's got some fun.
Speaker 2:But this is such a white pill.
Speaker 3:Yeah? Why?
Speaker 2:I mean, the whole this is like, you know, we we need to we need to manufacture, you know, basically, we need to re industrialize
Speaker 3:Yeah.
Speaker 2:America. Yeah. We're not gonna do it by just copying Yeah. Everything from the past. There's some element of transformation that needs to happen as well as new efforts.
Speaker 3:Yeah.
Speaker 2:And this is this is tremendous news.
Speaker 3:Yeah. And I mean, there there has been like a venture capital boom in re industrialization, but most of the funds that we talked to that are in that category are 50,000,000, couple 100,000,000, certainly nothing at this scale. And this has got to be incredible news for the the founders that we talked to that are part of the reindustrialization effort because they they they have a new potential investor. Did you see that OpenAI has acquired Astral who will be joining the Codex team? So finally, OpenAI has Astral Codex, which of course is a great play on Astral Codex 10, the the blog, which has some fantastic articles.
Speaker 3:Let me tell you about Okta. Okta helps you assign every AI agent a trust identity so you get the power of AI without the risk. Secure every agent. Secure any agent. Will OpenAI increase cost of ChatGPT?
Speaker 3:This is a Kalshi market out there. It's at a 46% chance if either ChatGPT Pro or Plus have a price increase after 01/02/2026 or and before 01/01/2027. So in the in
Speaker 2:the Based on the current pricing of $20 a month and $200 a month.
Speaker 3:What do you think? I I feel like I this isn't financial advice, but I feel like they're not gonna move the price points because they're focused on so many other things.
Speaker 2:Yeah. The only the only thing is I could imagine an an additional plan on top of it. Yeah. Totally. An incremental plan
Speaker 6:versus change.
Speaker 3:Max is right there. We got pro. We got plus. We got pro. Sign me up for the max plan.
Speaker 3:Yeah. And I think they also have a light plan, and and I I would imagine
Speaker 4:go. Go.
Speaker 3:Go. Yeah. So I would imagine that there's more tiers within there. At the same time
Speaker 2:Give Tyler the goat.
Speaker 3:Ripping the Band Aid off of price adjustments is extremely painful, and they're probably the earlier you do it, the better. Like Netflix. Yeah. Yeah. Like Netflix has been increasing prices.
Speaker 3:And when they're at $9.99 a month or something, it's very normal. And then when you go up, it like, oh, you're raising the price. But you can just raise it every couple of months. Anyway No. We're good.
Speaker 3:Third time. Third time's the charm. How are doing?
Speaker 10:I'm very good. Can you hear me, guys? Hey.
Speaker 3:Yes. Hey. Fantastic. Introduce yourself.
Speaker 10:Who are I'm Tom Hulme. I'm one of GV or Google Ventures' managing partners. I'm based in London. Fantastic. Hope I'm gonna bring as much energy as Carl.
Speaker 3:I love it. I love it.
Speaker 2:It's a tough act to follow, but it's a good start.
Speaker 3:AI, good or bad. What's your strategy? What are you investing in? What are you seeing?
Speaker 10:As you can imagine, 80 or 90% of what we're doing is AI. In truth, it's hard to imagine a credible founder that isn't leading with it at the moment. Mhmm. And so we're viewing everything. I mean, in your email that you sent out today about Samsung, about some of the effects of the, what's going on in The Middle East.
Speaker 10:We're even looking at that through the lens of AI and how it should affect our investing strategy.
Speaker 3:Sure. And then in terms of the portfolio founders that you're talking to, how interesting is the sovereign AI efforts? How interesting is just finding amazing entrepreneurs that are gonna run through walls all over the globe, and they just happen to be there, so you're the first point of contact. You meet them early versus maybe going to an American entrepreneur that has some traction. You're gonna help them, you know, if you join the board, you're gonna help them, go global.
Speaker 3:What are you thinking?
Speaker 10:Yeah. Absolutely. So one of the things we're really proud of is that we actually are sort of a global firm, primarily The US and Europe. And so we offer founders soft landings in Europe if they're American companies and vice versa. So that's something that works well.
Speaker 10:But in truth, we're finding we're meeting more and more technical founders, and Europe has an edge on that. To give you an idea, I think 35 of the world's AI researchers or masters programs are actually in Europe.
Speaker 3:Yeah.
Speaker 10:We've got four of the top technical universities globally in Oxford, Cambridge, Imperial, ETH, Zurich. And so there is this incredible sort of talent building up. So historically, I think Europe's bottleneck was probably human capital and financial capital. The financial capital is now global. Your guys' show is global.
Speaker 10:Now the human capital is really growing, and we're seeing a real multiplier effect in two ways. So the first is the very best founders are starting companies over and over again. So we have investments in, for example, Sneeq's founder, Guy Pajani
Speaker 3:Mhmm.
Speaker 10:Who has now done Tessel. Most of our European founders are actually repeat founders. And the second thing is we have an equivalent of the sort of PayPal mafia happening. So Do
Speaker 12:you mind?
Speaker 10:We were early investors in GoCardless. We've now seen other companies coming through as a result of that, like Monzo. And I think we're just fintechs. Seeing that nonspire effects.
Speaker 3:Got it. Yeah. Does does Europe broadly give give England enough credit for DeepMind? Because it got rolled into Google so quickly, But I feel like like The UK punches way above its weight in terms of AI research with DeepMind, and maybe that's under discussed.
Speaker 10:Oh, I think it's under discussed. And I think it's easy. People will often post rationalize it and say how great it would have been if it had stayed independent. But we've got to remember, when DeepMind was really going in 2012 Yeah. It was really hard for people to see.
Speaker 10:The 2017 transformer paper had not been written for five, you know, years. It's early days, and so it's easy to look back and say it was obvious. It wasn't at the time. But I think the person that single handedly has done as much for tech in The UK as anyone else is Demis Ocevitz, the founder. He insisted on keeping a base here because he knew the technical talent was here, and now we're seeing that kind of multiplier effect.
Speaker 10:So there's great neo labs being funded right now. You've got reinforcement learning companies like Recursive Superintelligence.
Speaker 3:Yeah.
Speaker 10:Like Tim Roctacio is based here. Richard, Sasha, and Timo from the West Coast. You've got ineffable, Dave Silver's new company. You've got world model companies, and these are all coming out of GDM. So you're getting this multiplier effect.
Speaker 10:They deserve huge credit for that, for every one sorry. After you
Speaker 2:Yeah.
Speaker 3:Yeah. Yeah. When when when you look at a NeoLab, it feels like there's a thesis where it's just, okay. You have a brilliant technical mind. They're gonna go explore.
Speaker 3:Yeah. The price might be high, but you're underwriting it as, you know, a venture style bet. There's a chance that something great comes. But do you have or at least from conversations, do you have an idea of how the NeoLabs might plug into the broader AI ecosystem either through partnerships with big labs? Or are you talking to Neolabs that are saying we can leapfrog on certain vectors or maybe we can launch in our own consumer product that's happened before.
Speaker 3:What what how do you think about where the NeoLabs fit in post the research phase?
Speaker 10:Yeah. One of the questions we've been asking ourselves is the current s curve of technology that we're on, perhaps the third phase of large language models and diffusion models, like the existing companies are doing very well, and they're often chasing benchmarks. You become what you measure, and so they're really driving fantastically into that. The question is, what are the other s curves of technology that could be explored? And the two that I think are really interesting are world model companies at the moment.
Speaker 10:So Ami Labs just got funded. Our portfolio company, Odyssey, is going in that direction from diffusion. And then reinforcement learning, we think there's huge work can to be be done. So if novel breakthroughs can be made on either of those, we think that they actually can be complementing to the existing companies, and they could work in addition. So very rarely, they may go full stack and create their own product.
Speaker 10:Often, they will actually service their unique intelligence through API.
Speaker 2:Yeah. That makes sense. Predictions around the next breakout prosumer products from Europe. We've seen the lovables, the granolas, anything that is, like, very on the radar in London, everybody's talking about but hasn't necessarily broken containment and gone super global yet.
Speaker 10:I mean, one that everyone's really excited about, but it's partly we just exited the business to Apple is people keep asking me what Q is. So Q is a Israeli company, second biggest acquisition
Speaker 3:in my Apple.
Speaker 2:It it the the the it was in stealth until the acquisition. Right?
Speaker 10:Correct. So I was on the board for the whole of that period. Did the we led the seed and did the series a with our friends at Kleiner, Alpeza, and Spark, and that company is gonna do something very special. A few years ago, we had a thesis that actually voice is really interesting because you can communicate in voice about a 150 words per minute. It's high input information because of intonation, etcetera, versus typing, which might be 90 words a minute.
Speaker 10:We invested in Neuralink, which is like the very invasive version of high throughput,
Speaker 2:and
Speaker 10:then we started exploring what are private ways to communicate by voice, and Q is that company. So I'm asked about that a lot at the moment. The other one I'm excited about from
Speaker 2:a consumer any any ideas or guesses? It's it's probably not your information to share, but like time you know, Apple is making, you know, huge push and effort right now. They need to show the world that they still got it on the on the software side. Is Q something that, you know, Apple, you know, iPhone users will get to experience in 2027? Is it the longer term?
Speaker 2:Will they ever kind of like well, do you think there'll be, like, a moment where they're like, wow. This is, you know, a huge
Speaker 6:I yeah.
Speaker 5:I think it's gonna be
Speaker 10:a wow moment, and I think it'll be in 2028.
Speaker 2:Okay. And
Speaker 10:and, you know, our belief is actually that if you believe the software, the models actually kind of overshoot requirements, then a lot of the value will actually accrue to the physical devices because it'll be the distribution point. So we we, for example, invested in nothing. They just sent me their new products, which I'm gonna unbox after this. But they incredible smartphones. We believe that actually the value accrues to the distribution, and so whoever owns those smartphones.
Speaker 2:Yeah. Carl being in Carl the being in the position of the you know, they've proven they can make beautiful products, but then also being able to be really flexible and quick around implementing AI all the way down to the hardware level. It's very cool position to be in. Yeah.
Speaker 3:Yeah. It's a fun time. Well, thank you so much for taking
Speaker 2:You brought the energy. You brought the energy.
Speaker 10:Bet my apologies, but I also brought the technical issues. So apologies. Next time.
Speaker 3:It happens. Well, thank you so much.
Speaker 2:No. It's great to meet you, Tom. Come back on soon.
Speaker 10:See you both. Take care. Have a great day.
Speaker 3:Thanks. Let me tell you about Figma. No matter where your idea starts, Figma make quad code codex or a sketch, the Figma canvas is where ideas connect and products take shape, build in the right direction with Figma. And without further ado, we do actually have
Speaker 2:Let's play
Speaker 3:soon, but Let's
Speaker 2:play if we have time before the Cubanator joins. We're we're working on some We're working on it. I don't think we have time. I'll try to
Speaker 3:Let's rotate that screen and I think we're almost ready. The the the the one small news article here that we can talk about is that Meta has signed a ten year lease for a 15,000 square foot townhouse on 69697 5th Avenue to open MetaLab New York, its first Manhattan flagship retail location. They painted it completely blue, apparently. The store will focus on hands on demos and Meta AI glasses and VR headsets. So they're getting into the retail space.
Speaker 3:Well, let's figure out
Speaker 2:Still working on it. I can tell you about Weighshirt Capital.
Speaker 3:Okay. Tell me
Speaker 2:invested in SpaceX at apparently 200 and oh, okay. It's fake news. Brutal.
Speaker 3:That was quick.
Speaker 2:Brutal. I was like, this seems too good to be true. PitchBook is but we can tell you about Rivian Robo Taxis.
Speaker 3:Oh, yes.
Speaker 2:Uber and Rivian have announced a deal. Uber is going to invest 1 point 1 and a quarter billion in Rivian and deploy up to 50,000 r two robotaxis. I'm so interested to see what Rivian can actually do on the robotaxi side. Yeah. I I have friends that have owned Rivians have said that
Speaker 3:I love them.
Speaker 2:The Experience autonomous is driving is fantastic. Yep. It just feels like this. I I I will be very interested to see if more than, you know, a couple companies can really crack it quickly.
Speaker 3:But it's a young company, very agile, and lots of opportunity. Well, I believe we have Mark Cuban in the restream waiting room. Let's bring him in to the TBPN Ultra. Mark, can you hear us?
Speaker 1:Yes. But you're too loud. Hold on one second.
Speaker 3:Oh, too loud.
Speaker 2:Too loud. Okay.
Speaker 1:Yeah. Because I had to great to
Speaker 3:have you, Mark. It's great. Thank you so much.
Speaker 1:Hey, guys.
Speaker 3:Hey. How are doing?
Speaker 1:Hey, guys.
Speaker 7:Oh, well.
Speaker 1:I'll deal
Speaker 2:with it.
Speaker 3:Good to see you. How's your 2026 going? We haven't talked this year yet. What's life like?
Speaker 1:I'm loving life. I got no complaints whatsoever. Yeah. That's amazing. Yeah.
Speaker 1:I'm loving life.
Speaker 3:That's great. Are you so you're not disappointed about the rollout of ads in LLMs thus far then? Does that save
Speaker 2:us ruin your
Speaker 3:year? Because when I saw the first ad, it was for the Wall Street Journal, and it was just a little little bubble at the top. Hey. You might wanna check out the journal. Seemed innocent enough to me.
Speaker 3:But how are you feeling? I haven't
Speaker 1:I haven't seen it at all, so it hasn't ruined my life at all.
Speaker 2:Okay. What's your information diet? Because it's hard not to log on the Internet and not start black pilling these days.
Speaker 1:Yeah. No shit. So my first stop my first stop is a site called Memeo Random Okay. Which kinda gives me an update on all the what's happening in the world. My second stop is Drudge Report because that gives me the hyperbole on everything that's happening in the And then after that, all the different newsletters and emails that I get Mhmm.
Speaker 1:Just that try to keep me up.
Speaker 2:Mhmm. How are you processing the flood of cold emails that appears to be thoughtful but
Speaker 3:Is AI generated?
Speaker 2:Actually AI generated because you are notorious for Yes. Your response rates and getting back to so many people that have reached out, but it but it feels like maybe an impossible task now.
Speaker 1:No. I do what everybody else does. I bought a Mac Mini.
Speaker 3:You did? You know? Yeah.
Speaker 1:Yeah. For sure. That's amazing. I'm still learning.
Speaker 2:So you're just like, you hit me with AI, I'll hit you with AI back right away.
Speaker 1:Right back. Right. Because it's it's not even like the cold emails, because that's pretty obvious. Yeah. You know?
Speaker 1:It's pretty easy to see. It's people subscribing me to shit, and, you know, the good news is Gmail has an unsubscribe button. Yep. So you just gotta train it to hit the unsubscribe button. Okay.
Speaker 1:Then I just review it and all that shit. So it's still a work in progress, but at
Speaker 2:least I have
Speaker 1:a path.
Speaker 2:Well, the the the issue with that with us is that historically, if you had a podcast and somebody wrote you an email and said, hey, I really appreciate this moment where you're talking about this one thing.
Speaker 3:Totally. You're like, oh, they actually listen to the
Speaker 2:tell like, hey, at least they they press play and at least they But found a now Yep. AI just does it instantly. Yep. So there's no way to clock whether whether something
Speaker 1:Whether it's real or not. Yeah. And that's okay. Right? Because they're gonna the response rates most likely will be so low.
Speaker 1:We're in that trial and error phase Mhmm. Where people are like, we're gonna try it, see what happens. Mhmm. You know, maybe we'll get lucky and then they'll get bored Mhmm. And then it'll drop off.
Speaker 3:Yeah. Is owning a Mac mini a green flag for entrepreneurs these days? Talk to me about what you're seeing in early stage startups in this AI era. Like, where where where are the interesting builders? What patterns are you seeing that are like, oh, I didn't think that this person would be going down the Founder Road, but they are now.
Speaker 1:Yeah. Agents for everything. Yeah. You know? It's just because once you figure out how to do agents Mhmm.
Speaker 1:Then you can do them a little better than most other people.
Speaker 3:Mhmm.
Speaker 1:And then you can turn that into what would have been a SaaS business in the past is now, you know, we'll create your own marketing team, and we'll, you know, do all these different things for you that you no longer have to do, and we'll charge you x number of dollars a month. Mhmm. That's it. And I'm seeing dozens of those, you know, typically one for every industry you can ever possibly imagine.
Speaker 3:And are they growing revenue faster? Are they growing profit faster?
Speaker 1:Neither. They're just still trying to to get some just trying to get some traction at all.
Speaker 3:Yeah.
Speaker 1:You know? Because if you're growing revenue quickly, you're probably not coming to me yet. Okay. You know? Because, you know, the marginal cost to start is so low, and it's so fast, and you're using the agent, so if they can get anybody to give them a credit card
Speaker 3:Yeah.
Speaker 1:You know, or sign up, or, you know, now there's a little bit of a battle to use USDC for payment, the payment rails Yeah. You know, to make it so that, you know, just give me your wallet, and that's, know, it's gonna end up being a scam, and a lot of people are gonna get ripped off there.
Speaker 3:Yeah. Hell yeah.
Speaker 1:But but I think the real thing right now is agents for vertical verticals and trying to turn that into replace all your employees so you can start up or you can cut costs.
Speaker 3:Do you think any of those agent focused sort of like niche, at least niche to start businesses, would be a fit for Shark Tank?
Speaker 1:Yes and no. Yes, they should be. No, people won't understand them, and and the other sharks wouldn't understand them. Sure. But, yeah, I mean, effectively, anything you can do But
Speaker 2:you only need one shark to understand.
Speaker 1:Yeah. Yeah. Right? And I'm not on the show anymore. So fuck.
Speaker 2:It's time to it's time to go back. It's time to go back. Gotta be chance. You gotta be.
Speaker 3:Yeah. What what what was the anatomy of I I I think we talk about what makes for a great company all day long. We'll talk about that throughout the the show today. But what makes for a company that will put on a particularly captivating Shark Tank appearance?
Speaker 1:You gotta remember, it's for TV. You have to be entertaining. Yeah. And if it's not entertaining in some shape or form Mhmm. It's just not gonna work regardless of the quality of the business.
Speaker 3:Mhmm.
Speaker 1:If you don't have a, you know, charisma, you don't have a compelling pitch that's entertaining Yeah. It doesn't matter. You could be selling dollar bills for 50¢, and it would fail.
Speaker 3:Interesting. How important is, like, the visual component? There's a lot of physical products, but at a certain point, it gets too big for the studio. How important is it, like, a physical product presentation?
Speaker 1:Well, the good news is the producers will work with you on that, and they make them practice over and over and over. And of the hundreds, if not thousands of pitches I saw in fifteen years
Speaker 3:Yeah.
Speaker 1:We only had one really just just choke.
Speaker 3:Mhmm.
Speaker 1:Right? Where they couldn't spit it out. Maybe two, which is amazing. It's a testament to to Mindy and the producers there, and how hard they prepare them.
Speaker 3:Yeah. How do you think how do you think Shark Tank and and shows like it will change in in the era of AI video generation, you know, endless content? Is it is it is it stronger than ever because it's a known brand, or is there some weakness there? Like, how do you see that playing out?
Speaker 1:It all depends on platform. It's like you guys. Right? You know? It really just depends on reach of the platform and quality of the product.
Speaker 3:Sure.
Speaker 1:I think I think for Shark Tank, it's not gonna have to change because of AI or technology simply because you're you're really communicating to a family audience.
Speaker 6:Mhmm.
Speaker 1:And the message you're communicating isn't, hey. Here's a here's a bunch of businesses that are great. The message you're communicating is that could be you on the carpet. The American dream is alive and well. Sure.
Speaker 1:And so that's really what makes Shark Tank successful, not the quality of the businesses.
Speaker 3:Yeah. What about sports? I've seen some some robots playing tennis. They're gonna be playing basketball soon. I don't think I'll be watching robot basketball, but how do you think live events, sports, basketball will change over the next decade?
Speaker 1:I mean, maybe for the referees like you've seen in tennis, but that's it. Yeah. I think in reality, more people will wanna go to in real life events
Speaker 6:Mhmm.
Speaker 1:Than before because if, you know, if you're just managing agents, looking at output, looking for exceptions, you're gonna want some human touch. Right? You're gonna want to be able to engage. And I think that's that's really, really important. And I think that's where sports will grow.
Speaker 1:I mean, you're starting to see that now with, you know, what happened with the Olympics. The World Baseball Classic, you know, became much more popular because people want that disengagement from all the the the stress that that's happening right now.
Speaker 3:Yeah. At the same time, it feels like there's almost an opportunity for not to bring it back to targeted advertising, but but AI can tell me, okay. My favorite team's in town. I should go to this particular game. I should remind me at the right time instead of just signing up
Speaker 1:for the newsletter. That's not really AI. Yeah. This is targeting. Right?
Speaker 1:And I'm gonna tell you what. In terms of I'm gonna take it down a different path because I'm contrarian on this. Yeah. And that's with robotics. Mhmm.
Speaker 1:I think everybody's making this push for humanoid robots. Mhmm. I think they might have a five year lifespan, and then they'll fail miserably. Maybe ten. Yeah.
Speaker 1:You mean the divide
Speaker 2:you mean the companies or the divide or the individual robots Or both?
Speaker 1:Both. Both. Right? Because I think everybody defaults to, well, we live in a human world, and humanoids will take the place of humans for various functions, particularly in the home. Mhmm.
Speaker 1:And I think there's just no chance. I think if you look at warehouses and what Amazon does, they're not humanoid robots carrying boxes. They're robots that are designed to fit the environment. And I think, you know, I've heard people say, well, a house is a house. You need a humanoid.
Speaker 1:I think houses are gonna be redesigned completely so that whatever the optimal robot is that allows it to simplify the house, that's where houses will go. So, I'll give you an example. If we had robots that looked more like spiders that could, you know, but had hand, you know, the ability to carry and lift things, where more like ants, I guess, maybe.
Speaker 3:Yeah.
Speaker 1:Right? But and you could create a house where the pantry and the refrigerator and the washing machines were hidden behind the garage, if you even have a garage. And that way, you could redesign it so all the living space was for people. Because you know that the robots aren't gonna be full formed humanoids. They're gonna be whatever the optimal shape is, and they're kind of co designed.
Speaker 1:You design the house to fit the robot and you design the robot to fit the house. And I think you could go a on both.
Speaker 2:You know, the the humanoid founders will tell you, you know, how do you solve stairs. Right? Like, it doesn't work for wheels. But if the robots are really great, people you could put, like, a mini robot elevator. Right?
Speaker 2:Like, if if it's on wheels, then you just put it yeah.
Speaker 1:Like, you you see, like, the old house dumb way dumbwaiters. Right? Mhmm. Where there's just the thing where you pull it, you put it in there, and you pull it up, and it goes up to the next floor, and somebody opens it up. You're gonna see, you know, a a a mechanized equivalent to that.
Speaker 1:Right? Where the it's it recognizes the little, you know, ant robot that's coming up, and it opens up a little door that's, you know, that leads to the size of whatever it is it needs to carry or whatever, and then it goes up the dumbwaiter, does this thing on the next floor, the next floor, the next floor, and does what it needs to do. I don't think, you know, stairs are an issue at all.
Speaker 3:Yeah. How do you think about just these types of ideas, AI products generally getting rolled out and then hitting it bumping up against, like, human guardrails? Like, when I hear that, I think, like, that sounds incredibly sci fi and potentially possible from an engineering perspective. But then, you know, you try and, you know, remodel your house and then you're stuck in permitting for two years. And so that tends to slow the progress down little bit.
Speaker 3:Is that is
Speaker 1:all technology? Okay. Yeah. Of course it is, but that's all technology during the interim period. Right?
Speaker 1:Sure. There's always a transitional period where you go from the old to the new. Like, back in the day, you know, there wasn't enough electrical outlets for your PC. There wasn't enough, you know, you had to go into the walls to to run all the ethernet cables, and all that shit, right? Mhmm.
Speaker 1:You know, and so the houses and offices weren't designed for that because it wasn't considered when they were built, but they adapted. You found ways to adapt, and it'll be the same thing with homes. It'll be same thing with offices. Yeah. We'll find ways to adapt.
Speaker 1:I think, you know, the biggest challenge going forward is going to be as we go from an LLM world to a worldview world of AI, where we're taking in video and learning from the video and extracting rules from the video, a lot of the things that we're gonna do are gonna be outside, and are gonna have to consume in the interim at least, either satellite bandwidth or five g bandwidth. Mhmm. And I don't think there's gonna be enough bandwidth when you're working with video based AI models.
Speaker 3:Interesting. Interesting. You mentioned maybe a garage not existing in the future. Is that a way to say that you're excited about self driving cars? Like, what are you what are you thinking is gonna happen there?
Speaker 1:You know, I I played around. I have a Tesla, and I upgraded for a couple months, and it terrified the shit out of me. Not that I didn't trust it. Yeah. Oh my god.
Speaker 1:Because, like, when you're going 25 miles an hour, it's no big deal.
Speaker 3:Yeah.
Speaker 1:You go on a highway, you're going 70 miles an hour, and and there's a median right there in the middle of the highway.
Speaker 3:Yeah.
Speaker 1:I was like shaking. Like, I was like, I don't you know, Elon's cooler for whatever, but, you know, I ain't trusting him that much. Right? You know?
Speaker 3:And I'm not You're
Speaker 2:doing mad
Speaker 1:for this
Speaker 3:mode? Yeah.
Speaker 2:You know about mad max.
Speaker 3:No. No. No.
Speaker 1:No. You No. Know, but you can set a delimiter where it's like, how much above the speed limit are you willing to go? And if the speed limit is 65 or 70, you know, you gotta go the speed limit, and it was scary as fuck trying to go 70 miles an hour. And I don't wanna be there when somebody paints some adversarial you know how there's graffiti in the weirdest places?
Speaker 1:Wait until there's adversarial graffiti.
Speaker 3:Oh, yeah.
Speaker 2:Yeah. Like, somebody if somebody paint
Speaker 3:if they put brick wall It's Roadrunner.
Speaker 2:Paint it to look like the road Roadrunner.
Speaker 1:Wiley Coyote is No. Gonna That's, like, ridiculous shit.
Speaker 3:Right? Like, there's Wiley Coyote is gonna paint the the the tunnel, and then you're slam into it.
Speaker 1:There's somebody somewhere trying to figure out how to fuck up self driving mode, right?
Speaker 3:For sure.
Speaker 1:For sure. Just because it's just taking video input. Yeah. And you know, what it could be some pattern, all of a sudden, you're seeing this pattern on medians or, you know, overlaid on stop signs or whatever.
Speaker 3:Yeah.
Speaker 1:You know, because, you know, somebody's got to do that because it's just too easy not to.
Speaker 3:Yeah. Hyper realistic camo wrap gets confused, you know, eventually.
Speaker 1:Yeah. Whatever. Right?
Speaker 3:You wrap your car in camo, and if the camouflage is effective, you're gonna confuse the AIs. It it's a mess.
Speaker 1:You just might and there could be a predator. Right? Alien versus predator. Yeah. Predator could show up.
Speaker 3:Right? It's possible.
Speaker 1:Arnold isn't there to save us.
Speaker 3:It's possible. I mean, it's speaking of Arnold, are you it it sounds like you're in a good mood. You're optimistic about things. Are does the question of AI doom come into your mind, these runaway robotics? Are you worried about that at all?
Speaker 1:Not even the least. For the reason I just mentioned, In order like, right now, it's LLMs are basically bimodal with some video. Right? Where it's almost all text and pictures with some video. You can't you can't model the world with that.
Speaker 1:You just can't. AI right now doesn't understand the consequences of its recommendations. It has no idea what happens next. A two year old kid with a high chair and a sippy cup knows if it pushes the sippy cup over the off the high chair, mom's coming running, and the kid's gonna start laughing at mom. Right?
Speaker 1:Large language models Every time.
Speaker 2:Every
Speaker 1:time. Time. Right? And there's no hard language models ever. Right?
Speaker 1:Ever.
Speaker 3:That's true.
Speaker 1:And it's hysterical, you know, unless you're mom. Right? But but you get the point. Right? You the the large language models we have today can't do that.
Speaker 1:Mhmm. And so we have to evolve to models that can capture the world and physics, and deal with the latency of capturing or not being having access to video that you can't see, and so you have to try to model that. And not only does that take up a lot of processing power, but it takes up a lot of bandwidth, as I mentioned before. And so the Terminator's taking over, I just don't see how it's gonna happen. Now, you can have, you know, localized brains for military applications, and power get better, and manual dexterity will get better, all that, but that's not going to allow you to take over the world.
Speaker 1:Right? That's going to be application specific. So I'm not afraid of that at all, and I also think that, you know, we're talking about AgenTic applications. I I think particularly for small medium sized businesses and some large businesses, they're not gonna have that skill set. It's not gonna be natural for them to do that, And I think kids coming out of school today that have taken some Python, don't have to be comp sci majors, but have done AgenTic AI.
Speaker 1:Like, I go talk to schools, that's what I tell them. You know, get into Claude, you know, teach yourself all the AgenTic stuff, and then go to small businesses because they're not gonna understand how to do any of that shit at all.
Speaker 3:Yeah. That makes a ton of sense.
Speaker 2:What what advice are you giving to friends, portfolio companies, etcetera, around navigating as a business leader during a time where we have, you know, major global conflict. I don't know what exactly you're working on in 2002 Yeah. 2003, 2004, but there's so much I mean, now, everyone's hoping for a quick end to the conflict, but it's hard to lean on that.
Speaker 1:You know, it's funny. In 2002, when we attacked Iraq, I created something called the fallen patriot fund, which you know, was just money available that I funded myself. Money available for the families of soldiers who didn't return, or soldiers that were you know horrifically injured or disfigured or whatever it may be, and we paid out millions of dollars. But the bigger point was the way the media world was back then, we kind of just trusted what was presented to us by the gatekeepers. Right?
Speaker 1:You could have an opinion whether it was right or wrong, but hey, there were WMDs, right? Weapons of mass discussion, destruction, and we kind of trusted. Now there's so many information sources and social media, and we really only consume what the algorithms show us, you know, and each one of us has a different algorithm. Like the three of us, our algorithms are like fingerprints. No two are alike.
Speaker 1:And because of that, everybody's got a different perspective on what's going on in Iran and what's happening around the world. And to me, that's scary. Right? It's hard to know what's real and who to trust, and now with AI, video, you know, what's been created, and we really are in our cross our fingers, and hope things work out for the best, because I don't know that there's a way for anybody to really participate in a decision or make a good decision.
Speaker 2:Yeah, we're all trying to predict the future together Within perfect based on different well, based on wildly different kind of influences.
Speaker 1:Exactly. You know, we don't have access to the information we truly would need in order to make a cogent decision or even have a decent opinion. I mean, just don't, and we spend more time trying to filter and determine what's real and what's not so that it's it's almost impossible to really do anything but just hope and pray.
Speaker 3:Mhmm. We have a couple questions from the chat. The first one is about cost plus drugs. Can you give us an update there? Yeah.
Speaker 3:How's it going with the thesis?
Speaker 1:Yeah. Rushiness.
Speaker 3:The rushiness. Sound good. Yeah. Fantastic. Like, give us a sense of scale.
Speaker 3:Us a a reminder of the strategy. Reintroduce the company.
Speaker 1:Sure. So what you go to cost+drugs.com Mhmm. And you put in the name of the medication. If it's one of the thousands we carry, then we actually show you our actual cost. Then we show you that our markup is only 15%, and we charge you $5 for shipping and handling, and then the credit card fee.
Speaker 1:And in doing so with only a 15% margin, we're unless it's like a $4 Walmart drug, we're almost always the cheapest option for anybody. So if you're under insured, if you don't have insurance, you know, even to compare it against your co pay or co insurance, we may be cheaper than your co pay. Wow. And because of that, our business is just skyrocketing. So that's part one of our business.
Speaker 6:Mhmm.
Speaker 1:Part two to our business, for my company, for my my employees and their families, I went around and talked to the CEOs and CFOs of a lot of hospitals and found out where they were getting ripped off by the insurance companies. You know, if you think about this, and and I don't think many people do, if whatever your deductible is, if something happens to you and you can't afford it, even if you have great insurance, you might have a 1,500 or $2,500 deductible, which is big company, good insurance, but if you don't have that money and 40% of people don't have $400 for an emergency, when you go to the hospital as an example, they literally end up loaning you the money. And that, as a result, we've turned hospitals and providers into subprime lenders.
Speaker 3:Yeah.
Speaker 1:Think about that.
Speaker 3:Yeah.
Speaker 1:Right? And then you have the denials, and then they underpay, late play, call that. So anyways, so I went to local hospital, Baylor Scott and White, who's a really forward thinking hospital system, and I said, look, I understand where you're getting ripped off by the insurance carriers. I'll pay you on time. I'll pay you what we committed.
Speaker 1:I won't claw back. I won't lay pay. In exchange, I want two things. I want a better price. I want it as a reference price of Medicare, about 100100% of Medicare, unless it's really complicated.
Speaker 1:And more importantly, we created a site called costpluswellness.com, and we are going to post this contract on costpluswellness.com so that any business, you guys, TBPN, anybody any size that wants to direct contract can reach out to Baylor Scott White and get the same pricing that we get. Mhmm. And it's just blown up. Mean, it's just incredible. Have more than 9,000 providers, and what we're trying to do is teach companies who self insure in particular that they can take control of their expenses.
Speaker 1:You don't need to be dependent on the insurance company to to to come up with the right deal because they won't. They'll steal from you.
Speaker 3:Did you ever I mean, you're yeah. It's such an interesting, it's such an interesting company, for you because, I feel like when when when you have as big of a presence as you do, it could be a book or a course or a protein powder. Did you look at anything else? Yeah. Or have you burned out all that stuff?
Speaker 2:Protein powder. The Cubanator the Cubanator protein stack. I'm
Speaker 3:in the no. This is obviously much more much more important. Yeah. I
Speaker 1:just thought, you know, nobody looks at health care
Speaker 3:Yeah.
Speaker 1:And says, you know, the economic side is great. Yeah. We're we're doing it the right way in this country. It's the exact opposite. And so if you're gonna try to disrupt, go big or go home.
Speaker 1:Right?
Speaker 3:Another question from the chat. What's the most underrated business you've seen in your career? I I think they're talking about something that, like, you it is the moment you saw it, it clicked, and you were like, okay. This is, like, a wildly mispriced asset or something that could really fly. Streaming.
Speaker 3:Streaming? Yeah.
Speaker 1:We called it Internet broadcasting. I sat down with a buddy of mine in 1995 at a California pizza kitchen, and he was like, how can we listen to Indiana basketball in Dallas, Texas? Texas? Yeah. And this is right when the Internet had just started.
Speaker 1:Right? It was brand new to everybody, and I'm like, let me figure it out. And so we started a company called AudioNet
Speaker 12:Yeah.
Speaker 1:And got the rights to, you know, hundreds of schools, hundreds of radio stations, TV stations. You know, back then, the copyright laws were different. Created our own Internet jukebox and unlived the number of Internet radio stations and started streaming until we sold it to Yahoo. That was the most obvious thing I'd ever seen in my career.
Speaker 3:What was the domain name negotiation like? Jordy's a big fan of of great domain names.
Speaker 1:Great question. Great, great, great, great question. So when we started, it was AudioNet and I just registered it. Nobody had
Speaker 3:it. Yeah.
Speaker 2:Then Wait. Audionet.com or audio.net?
Speaker 1:No. Audionet.com.
Speaker 3:Okay. I like it.
Speaker 1:Yeah. Because we were just doing audio in '19 Yeah. '90 And then by '97, we we started to do video and AudioNet wasn't gonna cut it.
Speaker 3:No.
Speaker 1:And so I found broadcast.com because we wanted to broadcast everything and anything. Yep. And found the guy and paid him $8,000, and he was thrilled to get the 8,000 Wow. Yeah. This is 1997.
Speaker 1:Did he did he ping
Speaker 2:you after he ping you after
Speaker 1:Yes, y'all did. But wait, gets better. But wait, And there's more. So I'm like, oh, shit. This is nothing.
Speaker 1:Right? It's an automatic traffic generator. And so I started going out there and just glomming up and just grabbing all kinds of URLs so that we could put content on them, and then drive it back to broadcast.com. So literally, I owned final4.com. I owned baseball.com.
Speaker 1:I owned sandwich.com. You name it. I bought it. I bought it for I would buy, like, just packages of URLs. Right?
Speaker 2:And just this is because people were just going to their browser and being like This is before I see it. Sandwich.com.
Speaker 3:Before searching.
Speaker 2:And they would type it in.
Speaker 1:Google didn't people just Exactly. Com. Exactly. Everything was a a portal. Right?
Speaker 1:Everything was a front door. And so I was like, anything that generated traffic. Yeah. And I've done it since. Like, I own misterpresident.com.
Speaker 3:Okay.
Speaker 1:I own democracy.com. I I you know, I I mean,
Speaker 2:all kinds of democracy.
Speaker 3:Check democracy private.
Speaker 1:I was worried. I was worried.
Speaker 3:American thing I've ever I've ever heard. I love that. It's incredible. Okay. The last question from the chat, and we'll let you get back to your busy day.
Speaker 3:I I wanna flip it around. What's a what's a business that you've seen in your career that you wanted to work so well, but for whatever reason, the business just didn't achieve what you had in mind and why. Yeah. And you don't need to be specific about this particular company. I mean, like, a a technology or maybe an anonymized company, something like that.
Speaker 1:Yeah. God. I'd have to think about it. You know that what was not the the motorized skateboards. They weren't called with the Hoverboards.
Speaker 1:Hoverboards. Hoverboards. Yes. Yes. Hoverboards.
Speaker 1:So I I buddy
Speaker 3:I love hoverboard future. Everyone traveling on
Speaker 1:hoverboards different. Yes. So a buddy of mine, his son was an engineer, and I was like, okay, this kid could try to come up with some new ways to do hoverboards, make them safer, etcetera. And so we started a company that did hoverboards, and there were so many more patents already in place than I ever imagined.
Speaker 3:Mhmm.
Speaker 1:We couldn't get past them, and that it failed miserably.
Speaker 3:Yeah. Yeah. Yeah. That that was a very interesting boom, the hoverboard boom. It sort of came out of Shenzhen fully formed there was a because massive supply chain and they were all over, but there was no one brand.
Speaker 3:There were, like None. A ton of different brands because really what was going on was there was one amazing supplier in China that had, like, 20 different companies that were reselling it all
Speaker 1:And they
Speaker 3:were making a killing. Oh, yeah. They were killing Oh, yeah.
Speaker 1:Yeah. What is
Speaker 2:it still possible to create a widget and make like a $100,000,000 from it? Or does the or do the clones come? Because I I I I know the guy who made like the the the fidget spinner, like his claim to fame.
Speaker 1:Right. Right. That's cool.
Speaker 2:And But but he didn't
Speaker 1:It got knocked off like that.
Speaker 2:Yeah. I mean, it was it was the kind of thing that like was a hit product.
Speaker 1:That's all on Amazon. Okay. All on Amazon.
Speaker 2:Oh, so
Speaker 1:it's Right. So so I started talking to some Amazon resellers like mid twenty four because I was just curious about some things. I'd see some things on on X. And as it turns out, if you're an American seller, it may have changed, so correct me if I'm wrong. If you're an American seller, you can have one company that sells on Amazon.
Speaker 1:Right? For for your but if you're Chinese, there's no limit. Yeah. And you don't even have to have a nexus. So if you're that American company and you're making sales and making money, then you have to pay taxes and define your nexus and, you know,
Speaker 2:Oh, so you're just all screwed because you're your
Speaker 1:You're cost screwed.
Speaker 3:Yeah. Yeah.
Speaker 1:Because so these Chinese companies to this day, as far as I know, these Chinese companies don't have to have a nexus, don't pay the taxes even though they're supposed to. Right? You can literally have a Chinese bank account, and Amazon will send the money right to that Chinese bank account. And I was proposing to these guys and talking to some legislators at the time that Chinese companies should have to post a bond before they can sell the product and post it on a website that whatever whatever .gov so that, you know, the fidget spin guy spinner guy could come in and say, you know, we have an agent now that continually continuously checks to see if there's a knockoff of their product, and then can challenge it. And then at least there's that 10,000 or $25,000 bond that offsets the risk for that fidget spinner.
Speaker 2:Okay. One I widgets company that bought the next five most popular widget Oh, wow. Companies in the category that Yep. Were knocking them off and they just continue to operate them Yep. But they have enough ranking on Amazon
Speaker 1:But it's just wrong. It's just wrong that yeah. Because any whether it's China or Vietnam, any country, if you're outside The United States, you immediately have a cost advantage. Mhmm. Not the manufacturing, but just from an IP, from a and from an Amazon cost perspective.
Speaker 1:Why in the world is it cheaper for a Chinese or Vietnamese company to sell on Amazon and to easily knock off than it is for an American company to sell the original product? That makes no So dumb. Legislatively, could fix it in a heartbeat. You got to post a bond. $25,000 bond, depending on the size of the market, maybe more, and then give everybody ninety days to check it, and all of a sudden the whole industry changes, and American manufacturing skyrockets, and the because that that cost of knockoff isn't just about the cost of losing sales, it's the administrative, the legal cost, that there's just so many nuanced things that you have to spend money on.
Speaker 2:We have a we have a knock we have knock off issues, and like we we spend thousands of dollars to have our lawyer like chase them down and send take down From our
Speaker 3:merch, like just t shirts and stuff.
Speaker 1:Yes. Oh, yeah. Merch is crazy, and then IP too, right? Yeah. All the DMCA takedown notices because they're just scraping and Yeah.
Speaker 1:You know, reposting, all that shit. Yeah. Right? That's easy to fix if, you know, someone has the the guts to do it.
Speaker 3:What is the anatomy of using your likeness once you've made an investment? What what does the the best relationship look like? I imagine it's very open and transparent, but I imagine that anyone who's been associated with you at all is trying to, like, slap your face next to their product and, like, flip it all over. And maybe you haven't invested yet, and you just said, oh, it looks nice. And then they're like, clip it.
Speaker 3:He said it looks nice. You know?
Speaker 1:Yeah. I mean, it depends on the company. Okay. You know, usually, I I I don't even care. But two things.
Speaker 1:You know what Synthesia is? Synthesia.io?
Speaker 3:Yeah. Yeah. I think so.
Speaker 1:Oh, yeah.
Speaker 2:They've been on the show.
Speaker 1:Yeah. Yeah. They have the avatars. Yeah. Victor and all those guys.
Speaker 3:Yeah. Yeah.
Speaker 1:Well, I was their first investor, so I send them there.
Speaker 3:Okay. Yeah. Yeah.
Speaker 2:Dog. Dog. That's a unicorn. Come on. And
Speaker 1:I gave them, like, a lot of money. Yeah. I gave them a lot of money. This was ten, twelve years ago, way ahead of the curve. Yeah.
Speaker 3:There we go. Okay. So Synthesia.
Speaker 1:Yes. And so, Synthesia, so I'll push them to them, or like I'll just fuck around like you saw with Sora. They had Oh, yeah. So I just I I put one picture of me out there, but I was playing with it because I want to learn all this stuff.
Speaker 3:Yeah.
Speaker 1:And they sort of had this thing where you can put conditions on how when it can be used. Yeah. So I made a condition. I made a condition so that at the end of every video that used my likeness, you had that it showed the logo for cost plus drugs.
Speaker 2:So
Speaker 5:smart. Cost plus drugs
Speaker 2:that much.
Speaker 3:Yeah. And
Speaker 1:it's been used, like, hundreds of thousands of times, and I know we've seen a bump as a result.
Speaker 2:That's so John did the less commercial thing. He said, portray me as a body builder. It's funny.
Speaker 1:A lot less commercial. But, of course, the sore is kind of falling behind now, so they kinda I don't know if the No.
Speaker 2:It's good. It's gonna it'll just get added into ChatGPT, and then you got a billion people just just pumping cos plus drugs.
Speaker 3:Yeah. And it's always
Speaker 1:it's always crazy to me to see it. Like, tell it, you know, don't you know, because it has terms of service.
Speaker 3:Yeah.
Speaker 1:Can't show drug use and dah dah
Speaker 3:dah Sure.
Speaker 1:And so there's pictures of me, like, doing lines of coke and shit, and I got, you know, so it's kind of crazy, but
Speaker 3:Ridiculous. What when is the right time to for a company to apply to Shark Tank?
Speaker 1:Anytime. You just don't know. Mean, have open auditions all the time, so if you go to Shark Tank's website Yeah. It'll give you all the information there. Yeah.
Speaker 1:And you just gotta go out there and have fun.
Speaker 3:Go out there and have fun.
Speaker 2:How are you processing the peptide boom? Both FDA Non
Speaker 1:participant. Non participant. I'm not a believer in that shit at all. Like, every single LLM that I put it into and asked for, you know, show me the trials and show me the research.
Speaker 2:You mean the non FDA approved, just just the the stuff coming off the boat? Right.
Speaker 3:Or or are you short Eli Lilly?
Speaker 1:No. No. No. No. No.
Speaker 1:The insulin like, the real because when people talk peptides, you're talking supplement type stuff. Right? Yeah. Right. But, yeah, the Eli Lilly stuff?
Speaker 3:Yeah. No. Not Ozempic that's running Super Bowl ads. No. No.
Speaker 3:No. Very heavily regulated. Yeah. That makes sense.
Speaker 1:No. Because that stuff's gonna come down in price. And For now, you know, Lilly and Novo are smart now with their GLP-1s.
Speaker 3:Yeah.
Speaker 1:They're working around the PBMs and doing direct to patient, direct to company. Sure. And that was brilliant. That was really smart.
Speaker 3:Yeah. Yeah. That's very cool. Well, thank you so much for taking the time, Jordy.
Speaker 1:Yeah. It's always fun.
Speaker 3:This is Super fun.
Speaker 10:Fun.
Speaker 3:Have a good one.
Speaker 2:See you.
Speaker 1:Mark's fun, guys.
Speaker 3:Enjoy the
Speaker 1:rest time. Appreciate it.
Speaker 3:You soon. Goodbye. Let me tell you about Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents. I think we got a future shark tank.
Speaker 2:Oh, yeah. I I came up with the name. I came up
Speaker 3:with I'm not gonna say Yeah.
Speaker 2:Yeah. I'm not gonna say it, but the domain's available.
Speaker 3:Okay. We're getting the domain.
Speaker 2:We're getting the domain. Okay. You're going to shark tank You're going
Speaker 3:to shark
Speaker 2:You're going the tank. I'm
Speaker 3:so excited for this.
Speaker 2:Not you, Tyler.
Speaker 3:Not you, Tyler.
Speaker 2:Keep working on keep working on our other our other launch.
Speaker 3:Once yeah. What
Speaker 2:Alright. We gotta we gotta hit the size gong.
Speaker 3:Okay. What do we have to do?
Speaker 2:Ro Khanna.
Speaker 3:Ro Khanna.
Speaker 2:What did he 609,000,000 of trading volume while in Congress. He's fighting back against the elites, trading against them.
Speaker 3:I was I was I was talking to Jordy about this this morning and I was like, is is like volume is hard because you can be very a very high volume trader, but I was reflecting on, like, there are years when I just don't really trade that much.
Speaker 2:Or the only volume is the buy.
Speaker 3:The buy and then you just hold
Speaker 2:or something.
Speaker 3:Yeah. But But He's putting up big numbers. But maybe he's running like maybe he has like 10 k in like a high frequency trading
Speaker 2:Yeah. Long short strategy.
Speaker 3:It's just they're they're just eking out milliseconds of a tick.
Speaker 2:Yeah. Maybe he's running maybe he's got a stack of 40 open Yeah. Open claw. Yeah. Maybe he's been
Speaker 3:poaching from Jane Street, and so he's putting up a
Speaker 2:lot of volume. This is just insane volume from the anti elite champion.
Speaker 3:He's crazy.
Speaker 2:He said, you guys wanna dance
Speaker 3:thousand trades.
Speaker 2:Trade against you.
Speaker 3:How do you even have time to consider 37,000 trades? Like, he's I mean, how many
Speaker 2:I mean, that's
Speaker 3:How many minutes are in a year in a year?
Speaker 2:That is a lot of volume and a lot of trades.
Speaker 3:500,000 525,000 minutes in a year. So you can spend, you know, twenty minutes on each trade if you're working twenty four seven.
Speaker 2:That is He's been in in I'm
Speaker 3:sure there's something else going on.
Speaker 2:So he's been in office for nine years.
Speaker 3:It's probably just like a like a investment manager. Yeah. He says it's his wife's money prior to the marriage.
Speaker 2:Well, he's averaging 11 trades a day since he went into office nine years ago, roughly.
Speaker 3:Yeah. And the and the stock ban legislation
Speaker 2:That's no days off. That's that's weekends I Holidays.
Speaker 3:I don't know. Let everybody trade. Let why why not? What?
Speaker 2:Yeah. Sounds sounds like he's locked in.
Speaker 3:Trade at all times. Oh, what else is going on?
Speaker 2:We are removing sanctions on Russian and Iranian oil Mhmm. Which is Craziness. Craziness.
Speaker 3:Didn't think that would happen. Let's watch the public latest ad. Is that is that what we should pull up next?
Speaker 2:Pull Are there Actually, let's let's pull up this this video first of our president. Of Gary Tam. But this is Gary Tam when he sees a YC applicant using G Stack to ship 500,000 lines of code daily. This is one of the best videos of all time.
Speaker 3:Just pulling out a lot of cash. I'm ready to invest.
Speaker 2:Quickly counting it.
Speaker 3:It is so funny how lines of code became like not
Speaker 2:the important. Eyeballs.
Speaker 3:And now it's new
Speaker 2:They're the new eyeballs.
Speaker 3:Oh, the lines of code are the new eyeballs? I hope not. I was thinking that we should do a challenge here in the studio where every member of the team has to race to generate 10,000 lines of code. And whoever can do it fastest
Speaker 5:Okay. But how do you define a line of code? Like, can just run a for loop that says
Speaker 3:I will run a for loop after the lines of code are generated, and I will pass every line of code individually through GPT 5.4 Pro, and I will ask it one question, does this count as a line of code?
Speaker 5:Okay. But can I have the same line of code 10,000 times?
Speaker 3:You've invented the four loop. Potentially. Print print this. Let's pull That would be the most efficient way to do it, potentially.
Speaker 2:Let's pull up this ad.
Speaker 3:It might even be faster to just clone a repo. Right? Clone a 10,000 line repo. Do you have to write it from scratch? We need to write the the ground
Speaker 5:Download timing.
Speaker 2:Pull up the ad. Okay.
Speaker 3:Sir. Wait. Yeah. What are we watching here?
Speaker 6:Well, looking at your portfolio, you've got diverse equity exposure, broad market ETFs, some fixed income. However, I am seeing a gap here.
Speaker 1:College basketball, baby. Recommend a three leg party. Maybe sprinkle in a few flake
Speaker 6:props just to even things out. I've got a strong read on an early upset.
Speaker 1:If you're looking for a broker that's not also your bookie, we invite you to try Public.
Speaker 3:It's a good ad. Really under we're really solidifying Public's position
Speaker 10:as Yeah.
Speaker 2:Know, Which has been very very
Speaker 3:yeah. Very very smart these days. Taking shots at another
Speaker 2:I wonder if they're gonna actually run that on TV for March Madness.
Speaker 3:Would that be the right place to run it? I feel like March Madness users kind of want a bookie.
Speaker 2:Like they want to Well, March Madness is just like kind of everyone.
Speaker 3:Yes. Yeah. Makes sense. Anyway, we have our start to the Lambda lightning round. Let's take a look at the beautiful cloud and let's tell you about Lambda.
Speaker 3:Lambda is the superintelligence cloud, building AI supercomputers for training and friends that scale from one GPU to hundreds of thousands. And we'll bring in our next guest, John Kim from Paraform.
Speaker 2:How are doing? Going on.
Speaker 3:Thank you so much for taking the time to come chat with us. Please introduce yourself and the company.
Speaker 7:Hey, guys. One of the founders and CEO of Paraform. We are a agentic hiring platform that makes hiring exceptional talent as easy as pressing a button.
Speaker 3:I love it.
Speaker 7:So our first product
Speaker 2:We got we got your button in the mail. We did. We got your button. We got a package from you guys.
Speaker 3:It was very well recorded.
Speaker 2:It was a great, great execution. The only issue is the chocolate completely exploded everywhere over the
Speaker 1:phone. So
Speaker 3:It made it way more memorable, honestly.
Speaker 2:Maybe Yeah. Yeah. I will never forget that. Maybe there's alpha.
Speaker 3:There's deep alpha there there. Anyway
Speaker 2:But but no. It was awesome. Tell
Speaker 3:me. Thanks for the color. So who is the customer? Who's paying for this? Is it is it large corporations, small companies, startups, or do you have the applicant pay sometimes?
Speaker 3:How does the business model work?
Speaker 7:Yeah. Yeah. So it's the company's paying.
Speaker 1:Okay.
Speaker 7:We started out helping startups Yeah. You know, build founding teams. Now, we have sort of SMB mid market enterprise. So, you know, everyone from, like, a fast growing startup all the way to, like, public companies like Palantir are our customers. Yeah.
Speaker 3:Wow. And and you raised some money. How did it come together?
Speaker 7:Yeah. Yeah. We raised a $40,000,000 round led by Scale Venture Partners. I need to wait for the Congratulations.
Speaker 3:And Yeah. Yeah. And and and help me understand how you're going to deploy capital to accelerate at this particular moment in time. Because I imagine that actually building the platform has gotten easier, but engineers are still expensive. You still have to do top of funnel work.
Speaker 3:There's SDRs to hire. How are you thinking the shape of the business evolves over the next twelve to eighteen months?
Speaker 7:Yeah. No, definitely. I mean, it might be just like a classic answer, but, you know, we Sure. You know, obviously want to continue to, you know, do best in class growth. We grew a ton, 10x store revenue last year, and we wanna continue to grow,
Speaker 3:you know, at a
Speaker 12:at a fast
Speaker 7:pace. So in order to do that, you know, we need to grow our team and, you know, all that stuff. Yeah. But and and also accelerate our product road map, right? I think in particular, I'm personally spending a lot of time this year, you know, really just narrowing down, focusing on our product road map.
Speaker 7:So, yeah. Oh, one more thing I will mention is we sort of started in tech and helping tech companies hire, you know, EPD talent, sales, design, you name it. Actually, we launched a new vertical, so we're helping law firms hire as well. You know, our goal is to be a universal hiring platform, not just for tech companies. So obviously, capital going across industries as well.
Speaker 6:Yeah. Talk to me about
Speaker 3:the legal hiring market. Like like, are you sourcing those people in a different place? Like, what's different about that that requires investment and changing the and generalizing the platform? Yeah. Yeah.
Speaker 3:Walk me through that.
Speaker 7:Yeah. I mean, since we're a recruiter marketplace Yeah. You know, in order to scale to another industry, we basically need a sort of a new set of supply, like legal recruiters. You know, actually, lot of lateral attorney and partner hiring at law firms are driven by recruiting agencies. Sure.
Speaker 7:So the, like, boutique, you know, sort of heavy hitters, like, who do all the recruiting. So, yeah, I guess, to expand, we need a new set of supply. So we're we're doing
Speaker 6:that. Yeah.
Speaker 3:How are you thinking about just areas of growth in The US economy broadly if you stack rank, like, there's a lot of energy around reindustrialization right now. We were hearing that electricians might be the LeBron James of the next era. Yeah. But that feels like I don't I don't know that electricians are on the Internet the same way that software engineers are where they might have public GitHub profiles, blogs, LinkedIn profiles. How are you thinking about solving those next verticals?
Speaker 7:Yeah. No. I think, like, definitely, like, defense and government seems to be a huge area of growth. Mhmm. So yeah.
Speaker 7:Like you said, manufacturing, like, anything that's sort of, like, atoms, not bits, I think is, like, critical. So we're gonna grow a ton. I actually think, like, travel, entertainment, like, those industries, media, you know, is gonna do well as well. So, yeah, we're looking at what sort of verticals to go after, like, to your point, based on what what, you know, what we think are exciting. I also read the Anthropic report where they published sort of, like, what jobs are gonna be, like, sort of replaced by AI, all that stuff.
Speaker 3:Oh, know, that spider chart and then under Kirkpatty posted something similar.
Speaker 7:Yeah. I mean, I I think actually, like, you know, my my point of view is that the economy is not, a zero sum game. Like, it's actually, like, an abundance game. So I actually you know, I'm not too worried about, like, AI replacing people. I mean, like, sure, there's some, like, adjustment on, like, what how we need to upskill upskill ourselves and differentiate, but I think every technological revolution, like, humans figured out a way.
Speaker 7:Right?
Speaker 3:Well, I mean, the the that's the interesting thing about that chart is that what's missing from that chart of things jobs that will go away is, like, the new jobs that will be created. Exactly. Like Yeah. Live streamer, business technology news was not a thing when I was a kid. I there's Yeah.
Speaker 3:Zero chance that I ever could have put that down as like, my future career will be live streamer. What? That wasn't a thing.
Speaker 2:What in in conversations with investors for this round, what were you like, what kind of exits, like, were kind of referenced in the in the recruiting space? I know there's, like, public Oh, yeah. Recruiting firms, like, you know, these these companies scale to, like, massive massive
Speaker 3:talk kind of company.
Speaker 2:You know, they're they're not no. I'm talking about, like, non tech companies that are just, we do staffing and
Speaker 3:Oh. Yeah. Yeah.
Speaker 2:Kind of verticals. But there's massive massive companies in this space. Are you comping to those and saying, like, hey, we there's we can be a billion dollar business
Speaker 3:Yeah.
Speaker 2:Just based on serving a a similar kind of sector? Yeah.
Speaker 7:I think I'm not I'm I'm not too sure if that was, like, the focal point of all the conversations, but I think it's a great question nonetheless. Like, think
Speaker 9:Well, yeah.
Speaker 2:And I just I just say that because there hasn't been, like like every company has to hire a bunch of people, but there's not like the the The Facebook The face recruiting. There's nothing that like there there's not like a perfect comp where
Speaker 6:Yeah.
Speaker 2:Figma is like, well, look, have Adobe, so we're just gonna like eat some percentage of Adobe.
Speaker 7:Yeah. I think the way I look at it is if you look at the total amount of like dollars spent on recruiting, broadly speaking, like where does it go to? Mhmm. And actually, the biggest spend category is external recruiting. So outsourcing, recruiting, working with recruiting agencies, staffing agencies.
Speaker 7:So, like, that's sort of the biggest spend. But, actually, if you look at traditional, like, VC dollars over the last ten, twenty years, it all went to, like, HR software or recruiting software, and that category is actually not that big. It's, like, maybe 10,000,000,000. I I'm not sure exactly, but it it's not the biggest category. Yet 90% VC dollars went in there.
Speaker 7:So I think there's a little bit of a, you know, I think mismatch there, but obviously the market we're going after is, you know, like, you know, labor market itself. Right? I think I've heard somewhere also, like, we're shifting from paying for, like, software to paying for work. And instead of sort of building paying for tools, we're paying for outcomes. And I think Paraform is, like, very much aligned with that trend.
Speaker 7:So, yeah, we're going after the biggest market in recruiting.
Speaker 3:Yeah. Amazing. Well, thank you so much for taking the time to come chat with us. Congratulations on the new round.
Speaker 2:Great to get them together.
Speaker 3:Good luck.
Speaker 6:Thank you.
Speaker 3:You soon.
Speaker 2:Great to see you, John.
Speaker 3:Have a good one.
Speaker 2:Alright.
Speaker 3:Cheers. And we will continue our Lambda Lightning round with Eugen from Edra. He's the cofounder and CEO. You have some exciting news for us today. Eugene, how are
Speaker 2:you doing?
Speaker 9:Good. How are you guys? Thank you
Speaker 3:for having stealth. I love when companies exit stealth.
Speaker 2:Because Welcome to the public eye.
Speaker 3:Welcome to the public eye. Please introduce yourself and the company.
Speaker 9:My name is Eugen Alpeza. I'm the CEO and co founder of Edra. With Edra, really what we saw is that models are smart enough to do basically any work inside an enterprise, but the only problem is you have to tell them exactly what to do. Mhmm. And nobody has that.
Speaker 9:Right? Like, can't go to any company and tell them, just tell me
Speaker 2:what to do. How am I supposed to tell you what to do?
Speaker 3:Yeah. Yeah.
Speaker 9:So what we do is we built an agentic learning system that just hooks up to their existing systems of record Mhmm. Figures out what their people are already doing, writes it out for them so they can see it, and then we use that to actually automate and do the work.
Speaker 3:Makes sense. So talk about what it means to, like, just hook up to their internal systems Because I feel like there's 20 tools in every category, and every company has 30 tools, and you multiply that together. That's a lot of integrations. Writing new integrations is easy, but is there a platform that you can sit on top of?
Speaker 9:For sure. So we have a couple of core systems that are really good for us. So we do ServiceNow, Jira, Outlook, of course, and we get Outlook.
Speaker 11:Sure.
Speaker 9:Salesforce, Zendesk are some of the main ones Sure. That are kind of the first ones that we are working on top of.
Speaker 3:Yeah. And then I'm sure if there's a client that's big enough that could maybe prioritize an integration or something. But how big are the companies that you're working with at this point?
Speaker 9:Yeah. So, I mean, our our specialty is, like, the larger the company, the better it is. The the process, the more of a challenge they have. So if you look at some of our customers that we went public with yesterday Yeah. Includes Asos, Cushman Wakefield
Speaker 3:Wow.
Speaker 9:HubSpot. Right? So pretty pretty big.
Speaker 3:Yeah. What was the process like for closing those deals? Do you meet at conferences? I imagine that it's not some sort of direct response ad. You were in stealth.
Speaker 3:So how'd you get those deals done?
Speaker 9:Yeah. Well, we've been around the block for about ten years doing a lot of these things. So we had enough of a network. And I think it's a just a very compelling pitch. Right?
Speaker 9:Like, I'm not telling you, let me come in and it's gonna take three to six months, and we're gonna figure out what we're doing. I'm literally saying, hey, just give me one static cut of your data, and in a week, I will show you new things about your own company's operations you didn't know about. Right? And if I can come back with that one week with something new, don't hire me. But so far, it's been going pretty well.
Speaker 3:Are you throwing frontier models just at every problem because you're in a high growth phase? You want to have the best possible product? Or are you already offloading certain jobs to lagging models, open source models, cheaper models? Just how much of the Pareto frontier are you using these days?
Speaker 9:Yeah. So we need the smartest possible model to help us figure out what people are doing and what the process actually is. Yeah. But then if you do that well enough, you don't need a super sophisticated model for it. So we just need something that's good at instruction following and it tends to be fine.
Speaker 3:That makes sense. And how much did you raise? I wanna hit the gong.
Speaker 9:So we raised $30,000,000. Thank
Speaker 2:you. Congratulations. Just Sequoia, or did you, let anyone else get a get a slice?
Speaker 9:So so Sequoia led our a we had a t c and a star who, they led our seed already. So we we have continued support from them too.
Speaker 3:Some murderers, bro. Fantastic. Well, congratulations on the progress. Congratulations on exiting Stealth, and thanks for taking the time to come chat with us today.
Speaker 2:Yeah. Great to Talk
Speaker 3:to you soon.
Speaker 9:Thank you.
Speaker 3:Have a good one. Let me tell you about Restream. One livestream, 30 plus destinations. If you want a multistream, go to restream.com. And we will continue our Lambda Lightning round with Ari from Run Civil, who's in the Restream waiting room.
Speaker 3:That's bringing Ari in. How are you doing?
Speaker 6:Abbey. Good to meet you.
Speaker 3:Hey. Good to meet you.
Speaker 2:What's happening?
Speaker 3:Please introduce yourself and the company.
Speaker 12:Yeah. Happy to. Alright. So I am a man on a mission where we're trying to automate hacker intuition. I guess I can start with a brief intro to myself.
Speaker 12:So I was technically the first security hire at OpenAI Oh. Back in 2019. I was a grad student at Harvard doing my machine learning PhD.
Speaker 3:Yeah.
Speaker 12:And I saw a GP two come out, and I was like, wow. This would have been really useful back when I was a miscreant doing insane operations on the Internet.
Speaker 3:Yeah.
Speaker 12:So I ended up bundling up a couple of demos of things that I would have made as a miscreant, and I sent them to Sam Altman, and I sent them to Jack Clark, who was Yeah. The head of comms at the time. And then kind of the rest is history. They liked it enough that they invited me to come join, and so I was there for three years. I was a core researcher on g p three and on the codex model.
Speaker 12:I also built our first monitoring system for when we started offering the API as the thing that customers were then using Yeah. To make sure the customers are following our terms of service. Sure. And then I left the company in part because we just didn't have a good answer for when the bad guys have access to everything. Yeah.
Speaker 12:Blackpill moment for me was when we were doing this anonymized review of model outputs. I saw somebody trying to lock a file system, and that could be totally benign, you know, educational, like, how does encryption work? Or it could be somebody, you know, futzing around with malware and ransomware specifically. And there's really no way of telling that particular intentionality. And at the time, like, our thought was, well, what if what if we focus on the monitoring?
Speaker 12:We just block people that are doing bad stuff. But, realistically, when you have something that says explosive as language models have become, you're not gonna be able to, like, play whack a mole. You kinda have to get offensive with it. So Yeah. I started this company.
Speaker 12:I have very blessed to work with my cofounder, who built the red team at Meta. Mhmm. And then I have a team of really strong engineers that we pulled from some of the top security engineering teams in the industry, and we're focused on building something that will make the Internet just broadly more safe, and it's just really rewarding to see a payoff.
Speaker 3:Are you seeing more more danger and risk from, like, large scale state actors or, like, the script kiddies who are just trying to, like, wreak havoc, or is it both? Because I feel like some of the some of the it's like like some of the the problems with, like, the new AI security threats, like, there's new capabilities, but there's also, like, a lot more cost than just, like, running some PHP script that, like, guesses WordPress passwords, like, back in the old days?
Speaker 12:Yeah. I'd say it's actually kind of a combination of the two. I'd say, like, you have two types of of threats, and a lot of oftentimes, it also depends on the type of, organization that you are to. Mhmm. So for our customers that are smaller startups, like, they're not really seeing any of this kind of But for our large enterprises, we've been asked by a lot of them if they they basically wanna replace us with their bug bounty.
Speaker 12:Okay. They wanna replace their bug bounty with us.
Speaker 3:Oh, yeah. They want you to win all of the bug bounties. That's great.
Speaker 2:Because don't make mistakes.
Speaker 3:That's your that's your immediate TAM, and I'm sure I'm sure much further. But Yeah. Talk to me about model distillation. There's been a lot of news about it's it's not as as serious of a threat. It feels more like a business threat, but I've always been I've always been shocked by, you know, the stories about different open source companies where it feels like they trained on an American lab, and that seems like something that the lab should be able to detect.
Speaker 3:Is that hard? Is that something you can help with? Yes.
Speaker 12:Yes. So that's not what we do, but it is something that I've dealt
Speaker 5:with previously.
Speaker 12:And it is something that everybody does and everybody kind of knows about. It's sort of a bit of a dirty secret. Mhmm. But I'll also say that when you do distillation, the model that you get out of it is gonna be, like, net less good than the model that you're distilling off of. Yeah.
Speaker 12:That's just information theory one zero one. So it it's something that is somewhat of a business threat, but it's not as big of a business threat as, say, like, stealing the actual model itself.
Speaker 3:Yeah. Just actually breaking into the system.
Speaker 2:Can you give us your pitch to, like, a startup or a scale up on the customer side and then all the way up to a lab, like Yeah. How how you how you sell the product right now? Because I understand, like, the opportunity at a high level. Yeah. You know, basically, every all these companies are distributing intelligence.
Speaker 2:It's hard to understand how it's gonna be used. A lot of people are gonna use it for things that they shouldn't. You wanna stop that. But, like, what is the specific pitch in this moment in time?
Speaker 12:Yeah. I'd say, like, for one thing, focusing on like, security means a bunch of different things to different people. And right now, what we're saying is that smaller teams need different things from larger teams. And the benefit in of the way that we built our product is that if you have more attack surface, it's just much more interesting for the type of things that we can find for you. So we've been moving up into enterprises, and we have a lot of strong response from enterprise teams that are large.
Speaker 12:They have a lot of old code bases that go back forty years. There's a lot of cursed things in their environments. Trying to get, like, additional coding tools in is is kind of tricky.
Speaker 3:Mhmm.
Speaker 12:And I actually have kind of an interesting hot take for you, if you'll take it.
Speaker 3:Please.
Speaker 2:Love it.
Speaker 12:Okay. So, obviously, there's a lot of movement in security in terms of, like, the markets, especially when Onthropic dropped some of their news about some of their vulnerability discovery stuff. Yeah. So I think a lot of people are concerned about whether or not like, are are the language model map labs just gonna solve security?
Speaker 3:Mhmm.
Speaker 12:And what I think is interesting is if code gets so much better in terms of security, the main question is, like, does that mean that hacking gets harder? Yeah. And my answer is no because I think that speed is what's gonna kill us. Okay. So the space of these large, possible attack vectors requires a lot more data than simply the code.
Speaker 12:Yeah. So if you look at the code, I like to kinda think about it as you're looking at the code of the, or looking at the bones of a dinosaur. Yeah. It's you're gonna find a lot of interesting things about structure, but you're gonna miss a ton about things like muscles and whether or they have feathers and also, like, behavior and, like, broader things like that, which are also very important for understanding the ecosystem. Yeah.
Speaker 12:And that's true of code as well, and it's true of computers.
Speaker 3:Got
Speaker 12:it. It's easier to find bugs with the code. You know? Having the bones is very helpful for us even knowing that these dinosaurs exist, but you miss so much other stuff, and that is where the real delta lies here. Yeah.
Speaker 12:Authentication, for example, is famously difficult to suss out. Like, there are not very many I don't think there are any good authentication scanners out there. But the way in which we build our product, it's very good at finding auth bugs. And in fact, one of our strengths that we've heard continuously is that, like, we're very good at finding these weird esoteric things that have existed in bug bounties for, like, the last ten years, And we we get, like, pretty nice payouts from that, which is always fun.
Speaker 3:That's really cool. Talk to me about your take on the forward deployed engineer pattern model trend, boom, whatever you wanna call it. Are you in favor of that? Are you employing that at this time?
Speaker 12:That's a good question. I think that forward deploy is important if you're working with enterprise because a lot of them there's a lot of a human factor. Like, at least in in startups, what we've learned is that people just wanna solve the problem. Like, the CTO comes to us and is like, hey. I have this deal blocked by SOC two.
Speaker 12:I really need to get a pen test, and we're like, on it. Got you, fam. And we we get them. They're on their merry way. But with these enterprise companies, it's a lot more of a political process.
Speaker 3:Yeah.
Speaker 12:Security in general is kind of it's it's partly the people, and it it's also, of course, the software too. And what you can do with a forward deploy engineer is you can provide more of that layer of trust. You can communicate a lot more with the proper stakeholders so they don't feel like their job is gonna be taken away. There's a lot more, of the human factor that you're able to introduce when you have that. And I think that's why it's so popular.
Speaker 12:We do something somewhat similar there, and we find it to be particularly helpful with bringing people on board and being able to serve them faster faster.
Speaker 3:Looking at some of the customers here, Cursor, Turbo Puffer, Notion, Base 10, Thinking Machines. Congratulations. The business sounds great and makes a ton of sense, and obviously, you're raising money. But I'm curious if there's a almost like direct to consumer play at some point because everyone is gonna be vibe coding. Like, we are a 10 person team.
Speaker 3:We have, like, three systems, and, you know, we're sort of, you know, security second maybe. Maybe we're working Right? On have a black
Speaker 12:pill for you
Speaker 3:then. So tell me.
Speaker 12:Yeah. I don't think so.
Speaker 6:You don't think so?
Speaker 12:So because people don't like paying for security.
Speaker 3:Okay.
Speaker 6:But but but is is
Speaker 3:there another way that you can make it so cheap or bake it in or partner with a lab where, you know, I'm vibe coding something and I and I, you know, get Runcible installed or it it it it's it's modeled into the system.
Speaker 2:Yeah. SOC two example's relevant because that's somebody that's like, I have to do this.
Speaker 3:Because I'm selling software.
Speaker 2:It's hurting my revenue.
Speaker 3:But we've heard so many things about somebody's using OpenClaw. They're vibe coding something. They're running their business on it. And increasingly, it's turning into a system. And at some point, they need to think about security.
Speaker 2:What's the Think about it. We we Yeah. We we bought hundreds of thousands of dollars verse of, like, camera equipment Yeah. Before we bought cameras to secure, you know
Speaker 3:Oh, yeah. Office. Right. That's true.
Speaker 2:And even when we were doing that, we're like, like Yeah.
Speaker 12:Think there's there's some truth to that. But let's also think about, like, the economics of who buys these tools too. So if you're paying, like, $20, $200 for, like, a month long subscription Yeah. How much are gonna pay for, like, additional security on top of that? That's something that you're gonna have to sell direct to that company, and there's not a lot of companies that really offer code security related stuff.
Speaker 12:Sure. So I think for companies that are making the bet in that space, they're focused a bit more on, like, the ecosystem, which is we're we're focusing a bit more on, the the overall ecosystem within an enterprise that has a ton of ancient code that is gonna require a lot more in order to fix. And they also have just these enormous attack services that need some help.
Speaker 3:Yeah. Yeah. That makes a ton of sense. Well, how much did you actually raise? Tell me about the funding round.
Speaker 3:We wanna ring the gold.
Speaker 8:Oh,
Speaker 12:yeah. So we raised 40,000,000, which we love.
Speaker 7:Who came in? Congrats. So Coastal led the round.
Speaker 12:We had participation from s thirty two, conviction, lot Gil.
Speaker 2:We also
Speaker 12:had a bunch of angels as well. So Nikesh Arora, who I know is on the show.
Speaker 3:Yeah. Friday. That makes sense.
Speaker 12:Jeff Dean, Ian Goodfella.
Speaker 3:Wow. Ian Goodfella too?
Speaker 12:It was pretty good.
Speaker 3:That's incredible. Congratulations.
Speaker 2:That's the lineup.
Speaker 3:Thank you so much for taking the time to come break it down for us.
Speaker 2:I can I can visualize the Coachella software
Speaker 3:ecosystem? We appreciate that as well. Get every bug bounty that is out there. You deserve it. We'll talk to
Speaker 2:Great to meet you. Very, very, much. Cheers.
Speaker 3:Thank you. Goodbye. And we have our last guest of the show. We will leave the Lambda Lightning round and bring Alex Konrad in to the TV in UltraDump from Upstarts Media. How are you doing, Alex?
Speaker 3:Good to see
Speaker 2:you again. Back.
Speaker 11:Hey. I'm back. It's it's great to be virtually in the Ultradome.
Speaker 3:Yes. I love that poster behind you.
Speaker 2:It's very That's a TV.
Speaker 3:Oh, is that a TV?
Speaker 2:We're high-tech here, TV.
Speaker 3:Okay. That makes sense. Anyway, what's new since we last talked? Tell me about the shape of upstarts, how it's going, what type of beat you've I don't know. How have you defined your beat?
Speaker 3:Think everyone knows your beat from before with the Midas list, of course. But, what's changed? What's remained the same?
Speaker 11:You know, it's been almost exactly a year since we launched, and you guys had me on the show, which is awesome. And as you know, year one startup, everything is crazy, but a lot of fun. You know, we've we've launched a podcast. We have started doing some feature stories. We had one on William Hockey from Column that was a lot of fun a couple weeks ago.
Speaker 3:That's right.
Speaker 11:And just and having a lot of fun experimenting. You know? We we haven't been to the Ultra Dome in person, but that's a year or two stretch goal. Yes.
Speaker 3:What about, what about LIS? I remember we talked about this, and I was like, I know you can't do the Midas LIS. That's left behind. But I feel like there's a big gap in the tech media landscape around lists. Market maps do well.
Speaker 3:People are split on them. We had a lot of fun with a with a Metas list of AI researchers. Have you are listicles just cringe, or are they just actually not that interesting to you, or are they bad business? Because I feel like there's a there's something there, you're the guy.
Speaker 11:You know, I I'm sorry to say we don't have that list for you yet, but maybe that'll be a thing this year. Okay. We are trying to do really service oriented coverage for founders. Yeah. I think, you know, the reality is founders are super busy.
Speaker 11:Right? Yeah. And and so are builders at startups. And so our podcast is one commute length. It's it's a you know, if you're not listening to TBPN yet Yeah.
Speaker 11:Yeah. Driving to the office, you can you can tune in for upstarts each week, you know, to thirty five minutes. And then similarly, we tried with our article this week a illustration where, this woman, Natalie Frado, actually drew how data centers connect to this new GPU startup so that people could visualize it. And the hope is that it just helps people understand the info super fast.
Speaker 3:That's very cool.
Speaker 2:That's very cool.
Speaker 3:Or I I I I read about this company, Giga, today that I don't even know if I should call it a start up. They haven't raised any money, but they're It's
Speaker 2:a business.
Speaker 3:AI boom. It's just a business. Are you seeing, like, these knock on effects of the AI boom show up? And are you getting pitches from those folks, or do they see themselves as, like, outsiders and they're happy to remain outsiders, or do they wanna cross over into the tech ecosystem? Like, how do you think about the broader the broader ecosystem and knock on effects of the AI boom?
Speaker 11:Well, startup can mean anything these days. Right? Yeah. Like, I remember when we all started our career, a startup was venture backed. It was maybe less than seven years old.
Speaker 11:Yep. It wasn't hiring people for a billion dollars. You know? Wasn't worth
Speaker 3:a trillion dollars pre IPO. Yeah.
Speaker 11:That's right. And now startup, I think, is more of an aspirational goal. You know? Some days, Upstarts feels like a startup. Some days, it feels like a small business.
Speaker 11:Yeah. And I think similarly with these companies, my in my mind, if they're trying to be really high growth
Speaker 3:Yeah.
Speaker 11:They're trying to move fast. And if they're serving a tech savvy audience, that's good enough to be a startup.
Speaker 3:Yeah. I love it. What what what do you think about the the scoop economy, the big labs? There's so much drama, so many personalities. There are some journalists who've gone out and carved out, like, you know, they're just the scoop masters.
Speaker 3:Is that something
Speaker 2:Scoop athletes.
Speaker 3:Scoop athletes.
Speaker 2:Is it Trying to go to I I to the scoop policy.
Speaker 3:Someone who's, I don't think, ever had a scoop. I don't know if I just haven't felt a rush. Is it addictive? Like, what are the pros and cons of getting into that side of the business?
Speaker 11:There is a huge endorphin rush. Right? If if we're chasing endorphins and avoiding cortisol,
Speaker 3:I think, like, you know,
Speaker 11:when you do publish that scoop, it can feel really good. You know? For a while, our biggest story at Upstarts was last summer, we wrote about a startup that had left OpenAI.
Speaker 3:Oh, yeah.
Speaker 11:And they had raised a ton of money to do an RL, you know, reinforcement learning company. And when you looked at the spike in subscribers we got, like, that felt really good in a way. Yeah. But you don't wanna play that game all the time. I think it it does end up being, like, chasing a rush that is not sustainable.
Speaker 11:And so I think, you know, I will let Katie Roof and those self described Scoop athletes chase it for the love of the game.
Speaker 3:Yeah.
Speaker 11:For me, it's only really relevant if if there's something concrete like a lesson or an insight for that wider ecosystem versus just the horse racing of, hey. These guys from OpenAI raised even more money than those last guys.
Speaker 3:Mhmm. In terms of the horse race, obviously, you ran the Midas list for many, many years. There are there any venture capitalists who underrated right now? Or do you think that there's any misconceptions in the venture capital community? Because I feel like the strategies have shifted so much, and we're seeing bifurcation between the small funds and the mega funds.
Speaker 3:And there's folks who are venture capitalists, but they're trading in public markets all day long or running private equity shops now or buying hospital networks. Like, the strategies have evolved so much. Like, what's, what what other stories are interesting in the venture capital landscape broadly?
Speaker 11:Well, first, I think this year, we're gonna have to start a Upstart spotted on the street Yes. DC thing because I I saw I spotted Keith for a boy restaurant earlier this week in New York, and I gave him the eye, you know, and I said, come over. And we shook hands and, you know, the poor founders are with Keith. We're like, who is this dude? So I I do think we should do a segment of just where I spot VCs around New York City and San Francisco and awkwardly wave to them.
Speaker 3:TMZ. Paparazzi. Yeah. Yeah. Right.
Speaker 3:TMZ mode.
Speaker 11:That's the coverage we need. Right? We need the gossip coverage of VC again. For sure. But on a serious note, I I mean, I love the domain experts, like, really nerdy guys who are not posting a lot on x, who are just really well regarded.
Speaker 11:When I ask around, I'm like, hey, who's really smart on GPUs? And and so my advice to VCs usually is, like, have a thing you're known for.
Speaker 3:Yeah.
Speaker 11:If all you're known for is posting on Twitter Twitter slash x, that's probably not a defense you know, defensible strategy in the long run.
Speaker 3:Yeah. Yeah. People
Speaker 2:What is what what advice do you give to VCs that might be due for their first Midas list appearance now that you have a bit of space and you're not involved in the process? Interesting.
Speaker 11:I mean, at the end of the day, venture is a results business. I mean, you you guys have had guests on recently who talked about what is real and what is not. And I think the numbers generally do speak for themselves. You know, you get a big exit that is kind of the mic drop that I think Midas is a lagging indicator Mhmm. To notice.
Speaker 11:I think for VCs who feel like they have that portfolio that's not recognized yet, the first thing I would say is be top of mind for your founders. Mhmm. You know, often journalists like me or or at the big shops, like, we'll talk to a founder and we'll be like, who are the couple VCs who backed you who we should call to get to know your business better? Mhmm. If you're not one of those first two or three VCs that the founder mentions as a reference
Speaker 3:Mhmm.
Speaker 11:That's that's not great. So I'd start there with, like, are you top of mind for your biggest winners?
Speaker 2:Yeah. So it's a mix mix of results plus the mic drop moment in the last twelve months plus kind of founder brand. Is that a good way to think about it?
Speaker 11:Well, the yeah. I mean, the Midas List is data only, so the the founder brand doesn't matter as much. But I think if you're feeling like, hey. I I I want those
Speaker 2:flowers It's data. Yeah. Well, it's data it's data only, but it's not just, like, blended IRR across every investment.
Speaker 3:Crazy internal politics at every VC firm of, oh, yeah. That associate who was here for two years and, was the one who actually got that deal but then left, like, that's my deal now.
Speaker 11:Hey. I mean, you guys know venture is a tough game like that. You know? My wife just left VC to go into operating back at a start up, Clay. And, you know, she she will have her deals that she sourced and she was involved in.
Speaker 11:And will she be in the history in years? You know, we don't know. And I think, you know, similarly, if you source the deals and you moved on to another firm or you went back into operating, like, history will, I think, give you the credit in the long run. But Yeah. Yeah, for Midas, that can be tough because, like, five people at Sequoia claim each, you know, big deal.
Speaker 3:Yeah. Yeah. I heard that there's one firm. I don't know if it's benchmark, but they have, like, a ledger that when the deal closes, they all agree on the allocation. Okay.
Speaker 3:You brought it in and you're gonna be on the board. You get 80%, but I worked the deal with you, so I get 20%. And we all sign and then we know who got the
Speaker 2:System of record.
Speaker 3:A system of record, ERP, basically. But I don't know if that's at every every VC firm. Has there ever been in in your memory a a situation where sort of like a VC stake was discovered in sort of an IPO prospectus or like an S1? Because I imagine usually the VCs are taking plenty of victory laps throughout the process once things get close. But I'm wondering if there's ever been like the quiet VC, not on Twitter, not posting, and then all of a sudden the IPO comes on there like, wait.
Speaker 3:They own 20% of this company? This is crazy.
Speaker 11:Yeah. I mean, a firm that was historically under the radar was Sutter Hill.
Speaker 3:Oh, yeah.
Speaker 11:So Michael Spicer, when Snowflake went public, he got tons of credit, deservedly so. Yeah. But they had been totally under the radar. And so those more incubation type ones
Speaker 3:Yeah.
Speaker 11:Those are really interesting.
Speaker 3:Yeah.
Speaker 11:And I think I think, otherwise, the thing to know with the s one is it's usually, like, a big dog at the firm whose name is attached, but that doesn't mean they necessarily
Speaker 3:Yeah.
Speaker 11:Were the the person who did the deal. Yeah. What happened earlier in my career is people would be like, did you know I sourced that deal? And then I left that firm, and I hadn't been in the game long enough to, like, know any of this trivia, and so that was terrifying for me.
Speaker 3:Yeah.
Speaker 11:Over time, I I started to know all the trivia. Like, Airbnb was sourced by this person, and then this person was on the board, and then this person was on the board. And I I don't wish that data on anybody's head.
Speaker 3:That's hilarious. Do you view venture capital and the startup ecosystem as like a buyer's market or a seller's market? Like like, is it a good time to be in a startup versus it's a good time to be a VC? And where are we in the cycle?
Speaker 11:What an easy question. Right? You're you're saving all the the easy ones for less. I think, you know, we're we continue to be in that have and have not market where I think you see crazy valuations for companies that have traction. Yeah.
Speaker 11:And then I hear from so many startups that are still like, how do we meet these guys? Like, how do we get anyone to pay attention to us? And it's it's humbling for me that, you know, even though I'm saying, hey. We wanna cover start ups that aren't getting that coverage, even then, there are most that I just can't help or get to. And so I think, like, I would encourage people to get away from the buzzwords, you know, especially get away from Silicon Valley, and there's still plenty of companies that are not getting funding.
Speaker 3:Yeah. Will you ever write a book?
Speaker 11:About what? About you guys?
Speaker 3:No. About your experience. I mean, this is a common path, I feel like.
Speaker 2:Sometimes a company or team that
Speaker 3:And and and the scoop grows into a book. Sometimes there's, you know, a composite profile of an industry or career. I don't know. It sounds like no. It sounds like you've no appetite for a book at all.
Speaker 3:But is that Well,
Speaker 11:I think I just don't have the the bandwidth. I mean, I like you guys. I think I'm in the arena every day now Yeah. Putting points on the board. And I think, you know, books seem like a beautiful stretch goal if upstarts really scales.
Speaker 3:But, you
Speaker 11:know, I I wanted to write books in the past maybe, but I think you need to really have the idea. Yeah. You can't just reverse engineer it. It's like saying I wanna be a founder and not knowing what company
Speaker 3:Yeah. You have to have a book
Speaker 2:in you at
Speaker 3:the time, and and then it just has to sort of You
Speaker 11:have to love the topic. Right? Like Yeah. How boring would it be to write the world's tenth book about Nvidia? Like, do we need that?
Speaker 11:I don't think so. I
Speaker 2:don't know.
Speaker 6:I don't
Speaker 11:know. I Jordy's Jordy's like, you're
Speaker 2:gonna do I
Speaker 3:would I I mean, I would I would read an entire book just about the The leather jacket. Or
Speaker 2:or or
Speaker 3:the leather jacket. Leather jacket. Or just an entire book just around the history of DLSS. Just just deep learning super sampling.
Speaker 11:Well, you know
Speaker 3:what I
Speaker 11:think you guys are speaking to that I do think about a lot? Yeah. Yeah. Like, information is so crazy right now. Know?
Speaker 11:You guys have these amazing guests on every day.
Speaker 3:Yeah.
Speaker 11:You're grinding.
Speaker 6:Yeah.
Speaker 11:And, you know, so many people are out there putting out good information. Is there room for that person who just kinda disappears for a long time on a crazy project and comes back with, like, a big fish?
Speaker 3:Yeah. Yeah. Yeah. Know we talked about this, a while back with, there's this YouTube channel that I love called the Corridor Crew, and they, talk about visual effects, specifically very niche. How would that ever be on t it just would never be on TV, but it's turned into a TV show, multiple episodes every week, fantastically successful.
Speaker 3:They build a whole business. They have a studio and team. And and their their dream was always, okay, we're good at visual effects. We want to do a movie or be the VFX crew on a movie. We're capable.
Speaker 3:But they kept building up their YouTube business. And every time Hollywood would come to them, they would say, yeah, we'll give you, you know, we'll give you 300 k. And they're like, but our business is making a million dollars now. And they say, okay, it doesn't work. And they'd come back and be like, you know what?
Speaker 3:We're ready. We got a million and a half dollars for you. And they're like, but our business is doing 3,000,000. Like, we can't step away. And so this this tug of war is always happening.
Speaker 3:And I feel like the book is the same thing where, you know, can you really turn off the podcast? Or can you turn off the reporting? Or can you turn off the the the the all the all the Yeah. I mean,
Speaker 2:I I've just come back to this as like legacy media brands Yeah. Best place to go, you know, fishing Sure. Because they're they will say, yes, you can we're gonna pay you a salary and you're gonna go work on the story. Yeah. And you might not be able to show any real results for a longer period of time.
Speaker 2:Doesn't work that well for a sub stack model where you gotta show Sure. Value.
Speaker 3:Yeah. Yeah. Value every week.
Speaker 11:Yeah. That's totally true. I mean, every week, I feel like I gotta win win the week, you know. I feel like I'm proving myself to my audience every single week and day.
Speaker 3:No. We feel so I
Speaker 11:will say, we are doing these quarterly profiles now. Hockey was the first one with column.
Speaker 3:It's great.
Speaker 11:I think we have a really cool one cooking for the second quarter. And the dream is that maybe, like, we put four of those in a little booklet
Speaker 3:That'd cool.
Speaker 11:That, you know, can be on coffee table. And maybe we start to get into print and have fun that way, but it's it's baby steps, you know?
Speaker 3:Yeah. Yeah. Yeah. That makes a lot of sense. Do do you have sort of a media critique take on, like, the future of investigative journalism, where that might exist, what the funding model for that is?
Speaker 3:Because it feels harder than ever to have a journalist go and spend a year on something that may or may not work out.
Speaker 11:Yeah. I think the short answer is that I agree with Jordy in a lot of ways that you do need the sort of big shops that can still weather the storm for someone. You know, at Forbes, I would be hunting that big cover story and do it and then recharge my battery while other people were kind of putting up the singles and the doubles. And now it's like, you need the singles and doubles, then you look for the home run. I I do think a team is important there.
Speaker 11:But one one thing I would challenge people to think about is, is there a way to fund a project for a year? Like, you know, like, whether it's Patreon or Substack or something like that where you do a year or even a multiyear subscription where you say, we're gonna give you money upfront. Do the best craziest thing you can do in that time, and, know, it it can it can be as few as one thing. Yeah. But then we'll be happy because I think the challenge, as you said, with Substack is Substack sends you the numbers.
Speaker 11:You can see them going up and down. You never wanna see them going down. And so could we create that headspace via some sort of crowdfunded model? I mean, I would love to see the innovation.
Speaker 3:Yeah. Same stuff. Well, thank you so much for taking
Speaker 2:Let's hit the gong for a year. Is it actually the year of the the first year? Did you hit the anniversary yet? Or is
Speaker 3:it We're
Speaker 2:a week away. Can we wait We're gonna hit next.
Speaker 3:Thank you so much. Alex. Time. Great to catch up, and we will talk
Speaker 2:soon to the team. Goodbye. Cheers.
Speaker 3:Alright. See you guys soon. Here's some advice. Don't buy AirPods. You need the Sony w h 1,000 x m five WHCH720NWF1000XM5CH5Twenties.
Speaker 3:Get those. Just pick those up. That's what Dylan
Speaker 2:I can't believe how mainstream this post is.
Speaker 3:I didn't realize a 150,000 likes. What is Sony doing? They need to rename their products. Just call it like the Sony, I don't know, head pods or something, headphones. They should I mean, people say x m fours, which I think is the, like, the last three digits.
Speaker 3:That's what they refer to them or the last three characters. That's what they refer to the headphones as. And so we will just call them x m fours, but rough with the naming schemes. Anyway, thank you for watching. Leave us five stars in Apple Podcast and Spotify.
Speaker 2:Been an honor. Newsletter. I'd be with
Speaker 6:you today.
Speaker 3:We will see you tomorrow.
Speaker 5:Going flash bang.
Speaker 3:Goodbye. Boom.