Samsung Invests $70B in AI Chips, The Cubanator Joins, Apple: Behind in AI, Ahead in Revenue | Mark Cuban, John Kim, Eugen Alpeza, Ari Herbert-Voss, Alex Konrad, Carl Eschenbach & Pat Grady, Jim Cantrell, Tom Hulme

You're watching TVPN. Today is Thursday, March 19, 2026. We are live from the TVPN 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 easy to 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 to. That's a narrative violation. We're having some fun.

0:00

We're out of control.

0:26

We got a great show for you today, folks. Carl Aschenbach is back 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 let him introduce himself. Let's pull up the linear lineup. 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.

0:27

The Cuban agent.

0:52

What a fantastic return to form for us because the first time we had him on the show we discussed. And we can talk about Cuban in a second, but of course we have our Lambda Lightning round and Alex Conrad 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. And it'll be an interesting time to reevaluate what's actually happening. There's been a lot more points.

0:53

I don't know, John.

1:29

We just have more ads.

1:30

We said that ads would be fine and now the world is ending. Yes, now we had the.

1:30

It's not because of the ads though. It's not because of the ads. It is much more complicated than that. But here's a white pill. Samsung is investing $70 billion to advance their fab capacity. 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 ph. From the TVs. They, of course, are a major player in HBM high bandwidth memory. 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 billion USD a year in revenue. Maybe 250 billion this year in revenue. Really good. All that's USD. 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 to think 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 the iPhone and Apple and they're second in the semiconductor foundry business to TSMC. Semiconductors still make up 30 to 40% of their business and they supply HBM to Nvidia for the H100 and Blackwell system. So it's not like they're sitting out the AI bull market. They are doing great, they are definitely participating, they're incredibly important in the AI buildout. But if TSMC is bottlenecked and TSMC is sort of risk off and they're not going to be guiding to 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 going to put another 70 billion 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 H100 or the Blackwell chip. That's been more of like AMD's game. And AMD also fabs at 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.

1:38

They want their chips with the dip.

4:09

They want their chips with the dip. And that's what Samsung does too. That's all you know. And so the FSD system, if you have a Tesla, you might be familiar with like HW3 hardware 3 that has been deployed into millions of cars. And it was fabbed on Samsung's 14 nanometer process, which is a lagging node. We're not in the 3nm, the crazy frontier stuff, but it's working and it's on the road. And According to a US regulatory probe, there were 3.2 million 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 fabbed at 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. 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 a Tesla data center runs on these Dojo chips. 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 at TSMC on 7 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 done so much press around GTC and so many different launches, you know that Nvidia is just going to suck a lot of the air out of the semiconductor discussion this week.

4:10

Out of the clean room.

6:11

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. We were actually struggling to find it. There was one Wall Street Journal article about it, but it has not SEO'd. Well, maybe they need to do some more podcasts or something. But they did, in fact. I mean, Jensen's doing a whole fleet of shows and interviews and all sorts of things.

6:11

Podcaster says companies should podcast harder.

6:35

Yes, yes, yes, yes. The solution to everything is more podcasting, talking. My book here.

6:39

Yeah, but I think this is particularly important, especially this morning. I guess the CCP put something out in the last 24 hours, basically saying, hey, Taiwan is going to have an energy crisis due to the broader global energy crisis.

6:45

So we need to reunify peacefully.

7:00

There's an opportunity for peaceful reunification, but

7:01

peaceful reunification, even if it's completely peaceful, and all the Taiwanese people just say, hey, we want to be part of China, they all vote for it democratically. That's going to be rough for the American chip buying industry. If you're a buyer of chips that are fabbed there. And so having another chip on the board, metaphorically to make physical chips is probably a good thing. You know, I was writing yesterday, I'm very excited about Samsung, very excited about intel, very excited about all of the new fabs. The Gigafab. The Terafab is the one that Elon's talking about.

7:04

Launches in five days.

7:38

Oh, did he actually say that?

7:39

He said seven days.

7:42

Seven days ago. Wait, five days, like the plan. Launches.

7:43

He just said Terrafab launches in seven days. Okay, so I don't know what launches mean.

7:48

And Tyler, what's the lead time for an ASML lithography machine?

7:53

Yeah, I mean it's at least like, you know, it's five, three, five years. Yeah, it depends on which. Like tools.

7:57

So the terafab will be ready in five and the ASML machine boost asml.

8:02

It's alien technology. It's possible Elon's going up and back to space all the time. Maybe he got some of his own.

8:08

An extreme ultraviolet lithography machine on the moon. 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. Stocks 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. We've been discussing this constantly and it's going to be very constraining over the next few years. So every increase in capex in the supply chain is a step in the right direction. And so Samsung gets the first gong hit of the. Congratulations to everyone over at Samsung. Making. Making a big bet. Who else is making big bets? Cursor is making big bets. Before we talk about Cursor, let me tell you about Phantom cash. Fund your wallet without exchanges or middlemen and spend with the Phantom card. And let me also tell you about Label Box, RL environments, voice robotics, evals and expert human data. Label Box is the data factory behind the world's leading AI teams.

8:14

So Cursor is out with Composer2.

9:16

Composer2.

9:19

It is frontier level at coding, priced at 50 cents per million input tokens and 2 1/2 dollars per million output tokens. It's also they have a fast version. 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 run, providing a far stronger base to scale our rl. It performed quite well. On. What is it? Cursor bench.

9:20

Yes. Which is a funny bench, but which is.

9:49

Well, yeah, yeah. Actually, TVPN performs quite well on TVPN bench too.

9:53

Yes. It's a little silly to design the bench and then publish the bench. 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 axes. And like, we're in the top right corner, of course, because the axes are, like, good and cool. Like, we're the only one that's.

9:58

TVPN bench is like technology podcasts publish at least three hours of content every week.

10:25

Yes, naturally. Exactly.

10:31

Naturally.

10:33

We are right at the top.

10:33

Right at the top.

10:35

Right at the top.

10:36

And it's actually. There's no one else on there.

10:36

Yes. But, yeah, I mean, this seems fair. It is a little bit odd to read this because 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. 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 cursor bench. That feels surprising based on the General vibes around Opus 4.6 generally. But cursor has specific needs for specific customers. And I don't know, what else do you think is going on here?

10:38

Yeah, I mean, the cost is really big. Like, this is basically like 10x cheaper than opus.

11:42

Yeah.

11:47

So I think also, you know, cursor has kind of been like, not really a, like, dark horse. Like, everyone knows about it, but in the coding race, it's like, everyone's like, okay, there's Codex versus cloud code.

11:48

Yep.

11:57

But, like, you know, if you imagine that, you know, cloud code and codecs are kind of like these environments for getting a ton of, like, really good data for training coding models like, Curtsar's had that for way, way longer than OpenAI or Anthropic. So you should imagine that at least in the near term, they actually have really, really Good data that they can train these good models on. And obviously this is a very specific model. They've said it like you're not going to write poems with this model. It's this very specific kind of almost like point solution model where it's just

11:57

don't listen to them. Tyler, write a poem with the model. Poem. Bench.

12:28

Poem. Bench, Yeah. I would be interested to know like how many sacrifices were made because it's at a certain point, like 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.

12:32

Yeah.

13:02

Well, I think like if you look back at just like the general history of like machine learning AI, like the lesson is that like big general models always beat these small specific models.

13:03

Yes.

13:11

But if you kind of zoom in on the timescale like you can still train, you know, glm, some open source model on a very specific task like accounting or something and you can like hill climb and you can actually make it better than the frontier models right

13:11

now at that specific thing. But the question is like especially at cost. Especially at cost, yeah.

13:23

Yes, yeah, very much so. But like on the long term, if you zoom out what actually went here, it seems like it's basically always going to be these big general models.

13:28

And 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. If you were to think about a Python if statement, just flow control, that is truly deterministic. Yes. If you piped the same question of the if statement, is this number bigger than this number? You pipe that into 5.4, it's going to get it right all the time. It's going to 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 100%, well then there's this upper bound that even like the bigger, smarter model doesn't get you any benefit at all. So you're just purely in cost control mode, I would imagine.

13:36

Yeah, that's reasonable. But I think this is not a

14:37

great example because coding is more coding.

14:40

We're not at 100% saturation on just coding.

14:42

Yeah, I mean, look at the, look at the chart. Like the best performing models are sitting at 65%, 63, 64%. So there's clearly more room to saturate this particular bench. I'm actually super interested to know about what goes into Cursor Bench at this point because I feel like when I see every benchmark, it's like 100% now. But that's just from, you know, the old, the old models.

14:44

Legendary poster Senkalp says all sh 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's taking on anthropic and OpenAI with a new AI coding model.

15:10

Would that matter? Like at this point, if they have Composer two and it's a small model, but it's good at writing code and it performs well on Cursor Bench. And the Cursor users are satisfied with the Composer 2 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. And you know what, it's. Maybe there's taste that wouldn't pull you from the gpu.

15:27

Yeah, I would just say at this point right now, I don't think we have any visibility into how much of Cursor's revenue right now is tied to using OpenAI or anthropic models.

15:54

Well, I think 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. 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 I 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 under the fold. What else is going here?

16:05

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 who used to manage to spread out monthly credits over a month, see all of it used up in One to two days.

16:41

Oh, interesting.

16:55

Are furious and switched.

16:56

It does feel like there's a little bit of like an economic war here.

16:57

Yeah. And this is what came up, you know, earlier this month around the lab, sort of subsidizing.

17:01

Yeah.

17:07

You know who's they're not. They're not in an easy position, but they're such a talented team.

17:10

Well, you know who's great at 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. 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.

17:15

Nikita says we're rolling out summaries for articles now. Just tap the summarize button if you want to know if it's worth your time to read it. And yeah, it's basically Grok. Turn this into a regular tweet. I am excited about the listen button. I've had this on my commute. There's so many moments where I'm like, I wish I could just have somebody read this article.

17:41

I actually wound up doing this with a number of will Menitis long form essays. I would copy them, put them into 11 reader from 11 labs and have it read it to me in sort

18:01

of a silly voice.

18:13

A silly voice. It was a good time.

18:14

Well, I was actually trying to use Grok. I was trying to use Grok in the X app to just take an article, paste it into Grok and say, hey, can you read this to me? And it said cannot find the post. But it couldn't. Kind of.

18:15

It is sort of crazy reflecting on the fact that there is so much software out there that we talked about. Doordash. How can you completely reimagine the experience with agents on the platform? And there's so many different things that you can do to sort of like re architect 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 and everyone wants okay, if there's an image, I want you to have a text version so it's searchable. I've complained about if I see a Funny meme on X and then I want to go search for it later. Impossible. There's just no way you could ever do it because that is stored in Twitter's database or X's database as image number 762542. And someone's comment was just like, this changes everything. And I'm never going to 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 going to 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 struggling through these things right now as search becomes more important and as ranking becomes more important. Meta is 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, grok, 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 Grok, like at Grok, is this true? 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 the whole pitch was like, better content, more substack model, no ads. And. And he never really got it to a perfect product market fit. But it was an interesting idea.

18:31

Yeah. I think it's because people are deeply addicted to X. It is very valuable to them to be on there to participate. 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. Like if X was valuable to you and you didn't pay the $10 a month, yeah, it was going to 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.

21:05

Yep.

21:42

So it was a good trade.

21:42

Yeah. 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 were on X. Like, I mean you see Travis Kalanick on X replying to things. It's like he's raising money, he's growing a business. There's a lot of value in advertising to him because he's going to be picking a corporate card soon or he probably already has or might be in that market. He might be picking a payroll suite. There's all these things where if you could deliver that to that audience, it would be incredibly valuable and the CPM should be through the roof. But I think for privacy reasons and for a variety of other reasons and sort of like, 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. And the criticism that we saw from the Oscars is always like YouTube ads are generic. It's just like for a pillow or injury or something. That applies to every single person. But there's always this hyper targeted opportunity there.

21:43

Yeah. The other thing is the paid program with X has seemingly worked in that we know a lot of people that happily pay and have no plans to churn. But it would be a failure in the context of like meta scale.

22:48

Right.

23:04

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.

23:04

Oh, on X. Yeah.

23:14

So you're talking about somewhere in the range of 100 to 200 million of like ARR.

23:16

Yeah.

23:20

And if Mark, if Zuck had launched a product like that, he would just wind it down. Right. Reels went from 0 to 50 billion of run rate in like a handful of years. Right. That's what, that's what a home run looks like. And so I think it makes sense for X, but it certainly is not a home run from a consumer application standpoint. And they still need the overall business.

23:21

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 bestselling offer, shared. This is how ChatGPT ads.

23:42

He's like the SEO guy, I think.

24:03

Okay. He said the data is only from five businesses, but these businesses also run Google and Meta ads. Compared to Meta, ChatGPT's lead quality is 256% higher. On the flip side, lead quality is 49% lower than Google. I mean that seems like a miracle to be in between two hyperscalers on day one, basically. But on the bright side, due to add cost, it's substantially cheaper from a CPA perspective than Meta. And this was sort of what we were talking to the good folks over at Ridge about was that at least in the early days, like being early to a new ad platform that 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, ChatGPT 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. Google makes $460 per user per year in the United States, 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 makes sense. I would argue, or she would argue, that ChatGPT'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 152 billion in annual revenue. 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 billion. That's, that's actually a crazy difference because $200 a month subscription is like super high. Like, you know, you're talking 20 times like Netflix or something else that's, you know, premium and like really important.

24:05

Yeah, the $200 subscription at the time was crazy.

25:57

Yeah.

25:59

But even at that point, some of the people that were more kind of just like AI pill, generally we're like, oh, it's actually possible that someday you could spend $20,000 a month.

26:00

I was like, give me the $20,000 month plan. And it sort of came 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 ChatGPT ads are already outperforming Meta in effectiveness. This just gets better. Just gets better over time. So interesting. The question about Will Menitis 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. 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 Applovit? Profitable advertising made Easy with Axon AI. Get access to over 1 billion daily active users 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.

26:10

So Carl says it's time to return to the place where I know I can have the most impact. I'm beyond excited to be 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. 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. I have no interest in the view from the front of the room. I will leave that to our two great leaders, Pat and Alfred. I want to lead from behind, empowering each of you. Egoless impact, contagious energy, mentor and build great leaders. Always ready to serve. Carl's the man. We will have him on in just 30 minutes. So we can wait to cover more of that story.

27:16

But first we got to go to his Allen Co. Photo shoot. Dual wielding coffee, jump rope and a faded Sequoia T shirt, Andrew Reed says immediate, overwhelming response to the VC push up debacle. Welcome back to Sequoia, an all time great partner. That's a great photo. He's looking great there. Let me tell you about Plaid. Plaid Power is the apps you use to spend, say borrow and invest securely connecting bank accounts to move money, fight fraud and improve lending. Now with AI. This is an interesting story. This is an interesting story.

28:14

Apple is way behind in AI and still making a fortune from it. Let's see.

28:47

Begs the question are they actually behind AI?

28:52

Revenue is set to top 1 billion this year. Reassuring investors wary of rivals sky high spending.

28:56

And keep in mind they have a

29:01

chart here showing gross revenue from Genai apps as well as Apple's commission.

29:02

Look at this. The beginning of 2025 was really the boom of gen AI app growth. 400 million is this monthly app store revenue. Wow, they're really cooking and then sort of flatline.

29:09

Yeah, it's so interesting that it actually dropped.

29:25

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 where are the bounds? Obviously, Apple's had pretty strict App Store rules around adult content and what else you can do. Even just the app reconstituting itself, pushing changes because they want to review every line of code that goes in the App Store. If someone's pushing 10, 20, 30,000 lines of code a day, that's a lot of code for Apple to review. It's going to 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 the Wall Street Journal and dig into this.

29:30

Apple's on pace to surpass 1 billion 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. It's 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. That means they typically pay the App store tax roughly 30% of subscription fees in the first year and 15% a year thereafter. Though rates vary. Gen AI apps paid Apple nearly $900 million in App Store fees in 2025 with with almost a billion of revenue and very, very, very little capex. Three fourths of the revenue Apple rakes in from Genai apps in its App store come from ChatGPT. Next, at about 5% is Xai's Grok. There we go, Grok.

30:16

I mean there's so many different funnels. They did the essay competition, they did the video competition. And I mean 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. I'm not kidding.

31:13

Yeah, Grok in the iPhone App Store is at did 12 million last month.

31:34

Yeah. And I know like the true like AI heads will be like, Grok's behind on this benchmark model or whatever. Tyler, is that a correct characterization?

31:38

Yeah. Grok did more revenue. Grok did more revenue last month than Claude in the App Store.

31:47

But, but like, I've, I've started having conversations with. I'm. I mean, I'm using ChatGPT, but I wanted to just, I wanted to get up to speed on, on Taiwan and the, just the, like, what was 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 like with one search to Wikipedia or one search to any, it's probably baked into the weights of 3.5. But so like, if I'm just going to be like, chatting with someone who's like, reasonably smart, like, I would say grok is there. And so what do you think?

31:53

Yeah, but you could be talking to someone who's really, really smart.

32:37

No, not if you're asking like basic, basic knowledge retrieval questions that, like, they're like, any model's gonna one shot and just be.

32:41

Yeah, but you're just describing stuff that you could just like, actually Google.

32:49

Yes, but I can't Google via voice in my car on the drive. And for someone who's driving a Tesla and has a Groq integration right there, they're just like, sure, like, this is great.

32:51

Okay, yeah, that's fair.

33:02

It's like, not like the frontier use case is important. That's where the action's happening. That's what's driving the next order of magnitude of growth. But, but there are plenty of people who are like, Google's search overviews are amazing. And they're like, that's my level and that's good.

33:04

Yeah, but I don't think those people have actually tried GPT 5.4 Pro. So good.

33:21

It is good, but it's slow. And truthfully, you can fire off the exact Same query to 5.4 Pro and 5.5.4 Fast. Fast. And if the query is simple enough, the answer will be exactly the same. Because if I ask 5.4, 5.4 extended thinking, like, what is the capital of California? And it thinks for 10 minutes and it just tells me, Sacramento.

33:28

See, there you go. That's why you need to think. A lot of people, I told you,

33:59

I run my life on GPT2. I hallucinate a lot.

34:03

But people have said I have the mind of GPT2.

34:08

It's true, it's true. But. So I think for some use cases, a smaller model, something's a little faster, something that's not absolutely Frontier is fine. So I don't know. What do you think?

34:11

So imagine that.

34:26

Do you think there's something else going on?

34:27

5.4 Pro Spark. So it's on Cerebra's chips?

34:28

Yes, yes, yes.

34:32

Would you hit that every single time? When would you not use it?

34:33

I would not use it if I was doing, like, a deep research report, necessarily, because I just want extended reasoning for certain things.

34:36

No, but I'm saying, like, you could have that, like, oh, oh, 5.4 Codex Spark, which is, like, super fast, extensive reasoning, but it's still super fast. It's on service chips. Right. If you had that.

34:42

Yes. Money is no object. Absolutely. Like, you know, I'm happy to. To pour out the glass of water to get the best and the best intelligence possible.

34:54

I just think that even if you just care about speed, there's still better. I think, in my opinion, right now, there are better models than usual.

35:05

Okay, so walk me through it. Like, 5% of App Store revenue seems really high. What's driving that?

35:12

Yeah, not everyone is extremely tapped into. The current model that came out two days ago. You got to use it.

35:19

So you agree with me. I think you agree with me about. About the fact that good enough intelligence is still, like, a good business to the tune of 5% of App Store revenue from Gen AI apps.

35:25

But I'm saying that, like, you, because you know about this stuff, you should like, there's better things that you can do.

35:36

I told you.

35:41

I told you.

35:42

I'm talking to ChatGPT. Look, don't shame me. I'm not the one. But I'm just saying, I don't even think you should be shaming someone who's talking to a model.

35:42

I'm not shaming them. I think I'm saying you're model shaming could be better. You could have a much better experience.

35:51

Okay. Okay. So you want to evangelize the frontier. You want to evangelize the frontier. But I mean, I'm just wondering, like, if we did, we need a new Turing Test. So we need to have random people come in and they get to talk to 5.4 or, you know, 4.0 or something. And can they tell the difference? And which one do they prefer?

35:56

They might prefer 4.0.

36:18

They might prefer 4.0. 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 probably. Unless they're really, really grinding and they're trying to do something that requires a really long reasoning chain. It's totally possible that they're just like, yeah, it gave me the right answer. That's a narrative violation. Anyway, let's continue. Apple's revenue from generative AI apps rose from about 35 million in January to a high of 100 million in August.

36:19

Do nothing, win.

36:57

Do nothing, win. Create an app store over a decade ago and just keep reaping the rewards they sowed. And now they're reaping. Sales have fallen from their peak partly because ChatGPT downloads have declined, according to the data. As a proportion of Apple's total sales, $1 billion is small. Yet Gen apps are the 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. 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 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 iPhones 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. Apple investors want to see progress from Apple's own AI strategies such said Charles Reinhardt, 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, Claude Code Codex, any of those developers. They're probably not. Even if they, even if they are winding up using like a ChatGPT subscription in Codex, they're probably setting that new subscription up on desktop.

37:00

It's a toll road on the actual

38:54

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

38:56

those Apple and AI is exciting for Apple because they need, they need a new product that they can just randomly bill you like 299 yeah. Anytime they need like what are you talking about? Cash 299 like don't, don't you get just random Bills from Apple, like here and there, 2.99.

39:03

Like $2.99.

39:22

Yeah. Like, I feel like every time I check my email, it's like Apple has charged you like some random amount for some. Or something for some subscription.

39:24

No, I do get emails from Apple, but it's always like two days after I bought or rented a movie on Apple tv and it just says like, you rented this movie? And I'm like, yeah, I know. I click the button. It's fine, you don't need to email me.

39:32

In other news, Rolls Royce has scrap plans to go all electric by 2030 as quote, drivers prefer V12 engines. Would you look at that? I mean, and this is just a total shock. Total shock. Yeah, total shock. Drivers totally had to experience, you know, being forced EVs forced upon them for the last few years to know that they preferred combustion engines after all. Of course, I'm kidding. I think a lot of people were just sort of saying this over and over. Manufacturers were not listening.

39:44

Everyone said Elon has been saying the Roadster reveal will blow your mind if it has a V12.

40:21

We've been.

40:28

People are going to be going crazy if he drops a V12. That would be. That would completely break the Internet. It would be incredible. Anyway, let me tell you about public.com, investing for those who take it seriously. Stocks, options, bonds, crypto treasuries and more with great customer service. Let me also tell you about MongoDB. What's the only thing faster than the AI market your business on MongoDB? Don't just build AI, own the data platform that.

40:29

Let's talk about this Tesla that you were following yesterday.

40:54

Oh yes. Did you drop this in the chat already? I sent it to you. Oh no, we 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.

40:57

And it had a vanity plate that

41:18

was very sci fi.

41:19

Sci fi. So it was mixing like, I do want to go to Mars, but not with Elon.

41:20

Yep.

41:25

The license plate basically said beam me

41:27

up, beam me up.

41:29

So they want to go to Mars but not with Elon. They support.

41:30

They have an incredible amount of disposable

41:33

income based on law enforcement. They enjoy high trim levels, but they, they, they do not agree with Elon's actions.

41:34

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, like, they just feel like they're competing with X app.

41:41

California has now spent over $100 million on a new bridge to nowhere. It is a wildlife bridge, which I've driven by hundreds of times. I've been seeing it. I've been experiencing the traffic that it causes. I'm not against the concept of a wildlife bridge. In fact, I think it's fantastic.

41:52

It does feel like. But it is in a concrete jungle. This is beautiful.

42:17

Totally.

42:21

This has a lot of opportunity to actually improve the visual aesthetics of this particular part of the state.

42:21

Caleb Hammer says, bro, this state cannot be real.

42:27

Isn't. Isn't Caleb Hammer.

42:30

It's very real.

42:32

Isn't Caleb Hammer. He's like a finance.

42:33

Yeah, he's got like the number one.

42:36

He's like the one person you'd come to to be like, should I spend $100 million in a bridge? And he'd say, like.

42:37

And it's actually. It's actually quite a bit more than 100 at this point. And the funny thing is it's just kind of a bridge, but it's lacking the entrances to the bridge. I feel like if it looks like

42:41

even just a little bit of wood to smooth it out so that it looks like there's at least going to be start of a ramp to get on the bridge. The bridge looks solid. The actual center part looks solid. It doesn't feel that hard to finish this bridge. I'm optimistic that this gets done in the next hundred years, like, tops.

42:53

Apparently Colorado built a wildlife bridge for a low cost of $15 million. Oh, that's not bad. Functionally, something very, very similar. The interesting thing is apparently the bridge is in some part for cougars.

43:13

Cool.

43:29

And the wild thing is like, on one side of the bridge you have a bunch of residential homes, and on the other side you have a bunch of cougars. And so they're now going to. The cougars are able to go basically hang in all the backyards. So we'll see how this goes. But I'm excited for this to be finished up. It's been. As long as I have lived in Southern California, they've been working on this bridge. And it's about time.

43:29

Well, former partner of TVPN Fall, a generative AI model hosting service that you know and love, is in talks to raise a 300 million to $350 million at an $8 billion valuation. Annualized revenue has hit $400 million, up from 200 million in October.

43:57

That's the insane. No, they've executed really, really, really, we're good friends. Insane. So congratulations to them growth and look forward to having having them on after they move past the advanced talk phase.

44:18

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.

44:31

Yeah, I don't know about the last part. They seem very online.

44:50

Yeah. And I don't know too much about the issues but there's, there is like if they're truly competing in consumer like there 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 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. 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 anderal job posting, but it is in fact for a policy manager who will be hopefully stopping people from.

44:53

No, no, no. I think I read this as somebody whose job it is to decide how Claude is used to create chemical weapons and high yield explosives.

45:44

I think it's. I don't know, I think it's probably like this person decides like, where's the edge? So if you're asking like, okay, I have a firework and I want to make sure it doesn't go off. Like should I, you know, throw it 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 the C4? Or something like that. There's all these policy edges where if you're talking about Counter Strike and you say let's plant the bomb, it shouldn't flag that as okay, you're actually trying to plant a bomb. It's like you're asking about a video game. We know how to interpret that appropriately. But there needs to be a human in the loop to decide where that frontier is and where that particular trick is.

45:54

Anyway, Orf says what terrifies me is if AI were to cure cancer and save 50 million Americans. Imagine the backlash from hard working scientists who wanted to cure cancer themselves.

46:39

They will be involved for sure.

46:50

Well, it's interesting that that was, that was like at least one person's response to the Australia dog story where they were like yeah, this, we've been able to do this for a while but like don't do this. Which was, you know, an interesting response to somebody who, you know, went on and multi year journey to try to save their dog. Seemingly is having some good outcomes.

46:52

Very, very odd. Let me tell you about Railway. Railway is the all in one intelligent cloud provider. Use your favorite agent to deploy web apps, servers, databases and more while Railway automatically takes care of scaling, monitoring and security. And let me also tell you about Vanta Automate Compliance and Security. Vanta is the leading AI trust management platform.

47:16

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 timetable.

47:34

Anything made before 2028 is going to be valuable. That is such a vague. Someone was hanging out with Paul Graham and was like, let me vague post irl.

47:47

I require content.

47:57

I require content.

47:59

This is going to be very valuable. I'm not, I wouldn't.

48:00

We are working on something that will be incredibly valuable. 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.

48:05

This actually is. We were just messing around this morning with. With an existing product that we had had a breakthrough. We had a major breakthrough.

48:15

We. I had nothing to do with it.

48:22

We. And when I say that, I mean Ben had a breakthrough that I think will change one of America's pastimes forever.

48:25

I think so actually it'll be before and after.

48:33

I'm actually so confident in this that I'm willing to vague post about it.

48:36

My patent for sure.

48:40

Get this young man a patent.

48:42

I'm on a patent. I have a patent. It's great. Yeah, when you get a patent you can also like frame it, get a little tombstone. It's very nice. Regardless of what happens with the business, it's like a good moment in your business career to have a patent.

48:44

Do you have a tombstone for your patent?

48:53

I don't. I need to order one. It has been issued. Like my name's on it. I'm like the seventh name on the list or whatever. But I'm technically on it and so I should get my plaque or whatever. I'm sure you can just buy them. There's probably something out 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. I don't.

48:55

I mean, that's the whole plot of terminate.

49:22

Just say you're not AGI.

49:23

Just say you're not AGI Pilled. Like, just. Everyone's saying it's going to be like Terminator. It's going to be like Terminator. Well, what happens in Terminator? They invent time travel. And so you're going to be able to go back. You're going to be able to go back?

49:25

Yeah. I feel like after we get AGI and we can build incredible things, like those will be really valuable too, right?

49:35

Yes, yes. But yes.

49:40

I mean, by good time, he is

49:42

correct that, like, you know, images in ChatGPT and VO3 and Mid Journey, like, don't decrease the value of the Mona Lisa. That's just like, odds obvious. And everyone agrees on that except you. You're like, I would actually like to go to the Mid Journey Louvre.

49:44

Maybe that's why Banks. Maybe Banksy sort of intentionally kind of kind of reveals himself. I don't.

50:00

I didn't follow that story. Like, how did that happen? Because I feel like most people would just.

50:06

I think somebody just caught him with a. Hopefully Scott is watching and can fill in. But I think he. I think he was just kind of like caught in the act, really. But maybe he's confident enough. Hey, AGI is coming. AGI is here. My stuff's still going to be worth a lot. Even I don't want to be in the shadows anymore.

50:10

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 possible. Imagine being in the Terminator future and creating the time machine and just being, okay, I'm gonna go back in time and paint new paintings that then I can acquire over time and have new Mona Lisas. He's just like, no, we sent you back to save the human race, 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 interesting, and I agree, it is interesting. Interesting thing to noodle on. Similarly, CrowdStrike, interesting idea. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. Let me tell you about TurboPuffer as well. Serverless vector and full text search built from first principles and object storage. Fast 10x cheaper and extremely scalable.

50:30

Martin Shkreli.

51:30

What does he say?

51:31

He's coming on Monday for the great debate. Peptide debate says good music is the last mile of AI. And Lil Wayne has some thoughts. Should we listen on AI music? Let's play this clip.

51:32

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 business now? Challenge the challenge, bro. That's wild.

51:42

I love it. AI is a better thing. I love that AI is what it is because, man, I love to be able to stand right next to whoever AI is, he, she, they, whatever or whatever.

51:56

But AI is standing right next to right now.

52:06

I'm still better.

52:08

Keep telling what you do again. Yeah, going to run your list. I do this, I do that.

52:13

I love it. I love the challenge of it.

52:20

The first time I seen somebody was

52:22

my friends was a little worried. They was like, man, bro, they got this AI stuff or you can just ask it to do give you a

52:24

verse like Lil Wayne.

52:30

And so I did it. I said, let me have verse like little one. And she gave me her best shot.

52:31

Yeah.

52:36

On a couple devices that, you know,

52:38

not only a phone, a computer, even for a commercial.

52:40

I was shooting for the Alexa thing. I want to hear and I have

52:43

a thing called Proto at home.

52:46

They got his own little robot thing, asked her to give me one and they all, you suck. We're going to be okay.

52:48

I fuck with that Beanie Siegel. I think he had to start using it because he like was losing his voice a little bit.

52:57

Yeah. Another rapper to Mog, basically.

53:04

That's his take. That's so funny.

53:06

That's great.

53:08

Well, how does, how are designers feeling about AI these days? 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 this debate's playing out between Google and Figma. Hadley Harris says 12 years later, the VC who passed on Figma seed because Google could kill them is finally feeling seen. 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.

53:08

I was on Google, apparently this is engagement bait. Other people are testing similar prompts and getting much, much, much worse results.

53:53

Yeah, I don't know. I was on AI.google.com or just AI.google, not even AI.google.com, looking at all the different Gemini features and it feels like the next challenge is just, just integrating all these different things. They have so many great models. Nanobanana, VO3 NotebookLM, Gemini Flow, AI mode. There's so many. And actually piping a workflow from one to another is certainly going to be the next question. And does this all live in the Google search box? Is it in Google Apps or something? Either way, they're certainly investing in AI across the organization. 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 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?

54:03

Because they had two internal teams that they brought together.

55:17

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 necessarily shipping the org chart, but shipping some of the internal naming schemes that were like abbreviations.

55:20

Even like Nano Banana Pro. The image models used to just be like Gemini 3.1 image, whatever. They didn't get 3.1, but there we go.

55:39

There we go.

55:51

Like nanobanana was famously just like the internal name used, right?

55:51

Yeah. And sometimes these internal names 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. It doesn't sound like an AI product. Like when you have Siri and Alexa and then you have Rufus and Argus or something sparky 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 break out. But Gemini has been an interesting name. It's good. Like it balances both. It sounds like a product, but it sounds, it's just one word. It sounds like a. It doesn't anthropomorphize too much, but a little bit it is reference. There's a lot of deep knowledge there. Quickly, let me tell you about 11 labs. Build intelligent real time conversational agents. Reimagine human technology with 11 labs. And let me also tell you about Vibe Co, where DTC startups. Where am I going? Where DTC brands, B2B startups and AI companies advertise on streaming TV, pick channels, target audiences and measure sales, just like on Meta. So without further ado, we have our first guests of the show, Pat Grady and Carl Eschenbach from Sequoia Capital in the TV show.

55:54

Guys.

57:15

Carl, Pat, how are you guys doing?

57:15

We're doing great, man. We're doing great. It's great to be with you guys.

57:17

Yes, honored to be. 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's the thinking? What's the role? Sort of break it all down for

57:21

us from the moment Carl left Sequoia.

57:35

Yeah, come on back. Come on back.

57:39

Yeah, no, well, maybe I'll just start and then my partner, Pat here can jump in. And I say my partner because I've been his partner for 10 years. I joined almost 10 years ago at Sequoia, which was an incredible journey at that time to join. And then I decided to step away, back into an operating role. You know, after an eight year total journey at work day, 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, I'll be back. You'll have me back. Because I always had wished, I dreamed and envisioned 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, typical fashion. The news was out and it was within no exaggeration five minutes. I started getting texts from Pat Grady. Every single partner at Sequoia. Not only did I get them, but my wife started to get them. And they were like, when is Carl coming back? We want you back. And I will tell you it's a blessing to be back. And here we are today.

57:42

Okay, walk me through the bull case for becoming or, you know, going back into venture capital in 2026. There, you know, 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 going to eat everything. You know, Google is going to beat every company now OpenAI is going to beat every company Sequoia has investments in the labs. What's the opportunity that you see for new startup formation, new growth rounds? Where do you want to, to see opportunity either in AI or in software or outside of AI? What is your thesis for why it's going to be a rewarding experience to be a venture capitalist now?

59:11

Yeah, well, it's a great question, but let me step back and go back two months ago. First, when I sat down at workday, I did open the aperture up and look at everything and 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. And some of those private companies are the companies that our friends here, 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. And to be part of it across many companies as opposed to a company, is something that really excited 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 greatest partners in the world, people that are smart as hell, 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 just in my first two weeks. While I haven't been fully on board yet until today, I've met with so many companies for Sequoia and got to experience the vibrancy of what's happening in the AI world. 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, Pat Grady, and just be part of a generational shift, both as 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.

59:54

Love it.

1:02:12

It's amazing. So you talk about this massive technology shift, which, you know, we can all agree on, is part of your thesis of coming back and judging from the, 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, 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 helping both portfolio companies and the, you know, the entire team at Sequoia just level up?

1:02:13

Yeah, no, clearly, I think that's a big part of my personal mission going forward. 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, 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. 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 38 years and having been here for six and spent 32 years in operating roles, I felt like I was uniquely positioned to bring wisdom, to bring advice, 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 in, 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. And that's why I'm here. And I couldn't be more excited about it, guys.

1:02:56

Nowadays, it feels like. Feels like. And also in the data, companies are growing faster than ever. And you get what would have been maybe 10 years ago, like five years of company building compressed down into two years. When you're kind of mentoring CEOs or leadership teams in the portfolio, 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.

1:04:55

Yeah, so it's a great question. And I'd have Pat chime in because they're seeing this, obviously, every single day, raising around in one, two, three weeks later, they're raising another round, and then

1:05:36

they're trying to figure out what the

1:05:47

hell to do with that capital. 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, you're running plays faster me, it's hard to defend. 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. 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.

1:05:48

Yeah, 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. You know, our partner Konstantin 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 Asian is about the way information is distributed. Cloud, mobile, Internet, all of those are revolutions in communication is about the distribution of technology or about information. This is a revolution in computation. It's about the processing of information. 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. Right. And so you can be running like heck in a particular direction. If it turns out that that technology floor shifts Underfoot, all of a sudden you got to change direction. And so I think one of the big sort of things we have learned from the founders who are doing it best, the Daniel Nadlers and Winston Weinberg's 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, you go in the right direction.

1:06:58

Makes sense.

1:08:22

It feels like an amazing time to join Sequoia. The technology industry is bigger than ever. Venture capital is bigger than ever. 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 what was that? Like 2002, right?

1:08:23

Yeah. Wow. You're taking me way back. Yeah. I joined VMware in 2002 and when I joined, I think there was a couple hundred people with probably 95% of them being engineers. I think it was a deeply technical company by great founders out of Stanford and Diane, the founding CEO, great people. I remember joining this young little company, basically no revenue, and saying, hey, we're going to go change the world. Like every startup says, we're going to change the world. And I remember Diane Greene saying to me, we're going to virtualize these little x86 computers and the entire world's going to run on top of them. And I remember talking to Diane at the time, they said, diane, you mean like mainframe partitioning? LPARs, that's where we do. No, we're going to do it on these little pizza boxes. And I'm like, well, who the hell's going to do that, right? And then I went home and I thought about it and then I had to go, quite honestly to my wife and say, all right, I just left. Working for a Bay Area company living in Pennsylvania, computing. I committed I wouldn't do that again. I thought about this more and I said to myself, wow, if Diane, in this incredible technical team can do what they say they're going to do and turn that slideware into software that virtualizes these servers and allows you on multiple applications, operating systems simultaneously. 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.

1:08:47

Yeah.

1:10:23

And the journey began there. The first year or two, no one was buying it. It's like all Startups go through that phase, like, wow, you want me to take all of these 10, 20 servers, 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, 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 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. So we had to unplug cables to show things were actually working. And then it inflected and quite frankly, one of the greatest professional journeys of my life, being there 14 years, a couple hundred people to 20,000. And I was so blessed to be there because I got to do so many different roles in the company. I was never CEO. I was always, I guess, number two guy at the time across three great CEOs between Diane, Paul Marich and Pat Gelsinger and got to be a CFO for a while of 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 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.

1:10:24

What made you push through that one to two years where you felt kind of of silly even selling the product, just given that there wasn't. It didn't feel like you weren't feeling that pull from the market. Eventually you got the breakthrough with V Motion, but what was the signal that made you keep just running down opportunities?

1:12:12

Great question. Very simply, the engineering talent at the time, 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. And I kept saying, I remember at the time telling people, right, we move from forecasting numbers or revenue or bookings to forecasting. Literally our forecast calls would how many proof of concepts have we started? Because if someone tested worked, it literally worked. And we were having.

1:12:33

So the market was like, we don't believe you. And you just had to actually convince them to let you show them.

1:13:23

Yeah, well said. I had passion, I believe I had conviction. And I witnessed the technology working as advertised. A lot of times it doesn't in startups and it takes a while to get there. And I knew it was not if I knew it was when the market would tip and come our way. And then when it tipped and inflected it, it took off very quickly. And then we started to see all this competitive pressure come in with open source technologies like KVM, you know, 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. It was an incredible journey and I'm so grateful for that. 14, 15 years.

1:13:31

Amazing.

1:14:16

Yes. It's such a, such a wild ride. I mean, you've at various points been working at organizations with 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 venture capitalists 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.

1:14:17

Yeah, I think I, I can identify patterns and I have enough experience for the six years that I was here with Pat and the team, learning from them about what to look for in a founder and whether or not they can scale. One of the things I absolutely look for is self awareness in founders 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 think 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 the other people as part of the company to help me scale so I can focus on what I'm really good at. 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, 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.

1:15:01

I actually reminded the first time. I don't know if Carl remembers this. First time I Met Carl was 2010 and it was Doug Leone, Fred Luddy, who's the founder of ServiceNow. And I went to visit Carl to get some advice on scaling ServiceNow. And I was probably in my, I was in my late 20s, Carl's in

1:16:36

his early 40s, still in his late 20s.

1:16:53

Look how young this guy.

1:16:55

It bothers the hell out of me, guys, how good, how young, how smart, helping run one of the most iconic partnerships in the world. And here I sit, turning 60 this year. He pisses me off every time.

1:16:57

So I have pages of copious handwritten notes from this meeting which I'm sure exists somewhere around here. But the one liner that stuck in my brain, which is very consistent with what Carl was just saying, was attitude determines altitude and will determines skill. And I always think about that and we kind of morph that into the expression. Attitude is the ultimate input. 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. 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. And so 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 going to keep cranking.

1:17:10

Yeah, really well said on the introspection.

1:18:09

Yeah. Taking a side on the introspection gate,

1:18:12

I was going to try and tease something up, but you really delivered. 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. The saaspocalypse public companies. 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 when they're working in the technology industry.

1:18:18

Yeah, I'll let Pat start and then I'll give you my perspective because I've answered this question about 17 million times in the last three and a half years at work, and I have a different perception than probably most.

1:18:57

Yes.

1:19:09

So, you know, it's funny, the first thing that comes to mind is a line that I learned from a man named Carl Eschenbach who was a partner at Sequoia from 2016 to 2022. And the line is people do business with people. And I think there's a foundation model, maximalist point of view that the labs themselves are going to do everything and every nook and cranny of the economy. And I just have a hard time imagining that version of the future coming to fruition because people do business with people. And I think that between a job to be done and the raw capabilities 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 to get to the right answer with the least amount of paint. And there's probably a person in between who's going to do that work. And as a customer, you want to do business with that person. And so I think people do business with people is going to remain true. The shape that that takes in terms of what the businesses are is probably going to 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 salesforces and servicenows in 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 going to see with this, the wave of AI software is this third layer on top of those, which some people call system of intelligence.

1:19:12

I don't want to call it that.

1:20:44

It's the layer that does the work. You know, 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. I think that's what we're going to see. And as a result I think those system of record companies are relatively safe.

1:20:45

Safe.

1:21:01

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, 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 agency capability that's getting deployed. 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 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, come up with some sort of value function, basically wrap all the context around the capabilities of the foundation model to achieve the outcome that the business person wants. And so I think there's a very important job to be done for those that new layer of companies. And again, people want to do business with people like there's a lot of value and having somebody you trust take your hand and lead you into the AI future.

1:21:01

So first of all, it's the first time I heard someone else ask this question to someone else other than me

1:21:57

and then use you for the answer.

1:22:04

Actually it's so funny, I was sitting here thinking I am going to respond but you're going to hear something very similar from me. I'll start in kind of reverse order. I do think there is power to use Pat's exact analogy of a system of records, a system of action, a system of engagement and I will use system of intelligence 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 workthrow you're in a unique, unique position to have a great enterprise AI software company that stands the test of time. 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, 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. It 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. They're not going anywhere. Incumbency is incredibly powerful in the enterprise. 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 fortunate, 500 companies 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. And some of these big SaaS companies have that. 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 work day 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 day either on their own or on top of and through some of these SaaS companies. So I think it's an end 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. But I think the current narrative out there of these SaaS companies being overblown or being in trouble is completely overblown and obviously I'm biased. I think work they 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 iterate leveraging AI and just completely disrupt markets. Vegas markets that don't have all of the data, don't have the content and don't have the workflows.

1:22:06

What advice would you give to a Fortune 500 CEO that maybe is an incumbent that's thinking about buying versus building these AgentIQ products?

1:25:32

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 that comes with an AI background, Build as much as 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. It's both. You know, at workday in the last six months I was there, we bought four AI companies and they become part of the core fabric of the company that Anil and Garrett and his 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 to say think, you say it's, it's one or the other. You have to do both.

1:25:44

I think it's also one of the

1:26:32

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 Harvey for everything related to legal. Kind of a no brainer to go Sierra for everything, everything related to customer support. You know, you should probably try something like Expo to work on pen testing. Like, these are excellent companies with excellent people who spend all day obsessing over a particular problem. Why take your best engineers and ask them to go do that? Go do something that's going to be unique to you.

1:26:33

Okay, last question.

1:27:11

Pat, by the way, Pat makes a great point. Having spent a lot of time with CEOs of Fortune 500s around the world, there's this whole narrative, we're going to do it ourselves, we're going to 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 and let them go focus on financials or insurance or retail or whatever, cpg, you know, let them focus on what their core business is. Why build that technology if someone can do it much faster outside the company?

1:27:13

Last question for Carl. A few years ago you were spotted at the Allen Co. 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?

1:27:49

Well, the answer, I hate to use this term again, but both. I was bringing coffee. I was bringing a coffee back to the room. For my amazing wife of 35 years,

1:28:07

Anna,

1:28:17

I used to drink probably 8 to 10 to 12 cups of coffee a day. Wow.

1:28:24

That's all I have all day.

1:28:29

That's amazing.

1:28:31

And that's all I have all day until I get to dinner. When I eat dinner, it's my one meal a day.

1:28:32

That's fantastic.

1:28:36

Wow.

1:28:37

Incredible amount of energy. Well, it's clearly working. Thank you so much for taking the time to come chat with us.

1:28:38

It's so good to see you guys both back together.

1:28:42

Yes, no, thank you.

1:28:45

And I, I just want to say, listen, I, I just want to thank Pat.

1:28:47

Yeah.

1:28:50

I want to thank Alfred, I want to thank the entire partnership here at Sequoia for allowing me to join them and serve alongside them. Our, our, our partners, our customers. Yeah, 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 it.

1:28:50

Yeah, we're excited for you. Thank you so much.

1:29:19

Incredible stuff.

1:29:21

We will talk to you soon. You guys have a good rest of your day.

1:29:22

Cheers.

1:29:25

Goodbye. Let me tell you about 10 to

1:29:25

12 copies a day.

1:29:28

That's incredible. They're the makers of Devin, the AI software engineer. Crush Crush your backlog with your personal AI engineering team. And let me also tell you about fin, the number one AI agent for customer service. If you want AI to handle your customer support, go to Fin AI. And without further ado, we've been running along but we will bring in Jim Crantrell 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 want to talk about how you're thinking about the business and also just the orbital economy more broadly. Yeah.

1:29:29

So I've been in the automotive and aerospace industries for north of 35 years and had positions everywhere from the front space agency to early at 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'm on my 12th space or automotive startup and Phantom Space is the last one of them but several of them have gone public since then and Phantom Space was sort of the ultimate of all these startups that looking to solve the problem that really needs to be done.

1:30:09

Yeah, that story of going to Russia to try and buy the ICBM has been Told and written about in books. But what does the current narrative get wrong? What's your side of the story? What, what were expectations like going into that meeting? Was it seen as a long shot at the time, or did you think that it was likely to work?

1:30:46

Yeah, no, it was a complete long shot. When Elon called me, he had just left PayPal and had this idea of trying to inspire humanity to become multiplanetary, as he still talks about. And he wanted to do what amounted to a stunt to, you know, show that we could send creatures to Mars. 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 want to sell to us, they were just being Russians. And Elon announced to all of us, in a sort of shocked way, 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. Now we can see 25 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 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. What 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 and the whole nine yards. So here I am.

1:31:08

There you go. What's the modern version of 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 tractical problem right now in space? That people are maybe undercounting.

1:32:35

So I think there's three tracks that it's going down. One is the military use of space, which we see ongoing today. Wake up and read the news every morning. 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. And now AI is the killer app that enables this, much like the Internet came along was the killer app that enabled Starlink. 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 common narrative is going to portray it.

1:32:53

Okay, how will it be different? I mean, 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 startup that's planning to put data centers in space. There's a whole bunch of other people that are approaching this problem. But how do you think people are getting it wrong? And how do you think you fit in?

1:33:34

Yeah, so Nvidia to just address that has nailed the silicon.

1:33:59

Right.

1:34:04

So they're going to be the winners on that, I believe. I think so, among others. Right. But they're going to be one of the primary winners and thank you for doing that. Nvidia number two is there's going to be a camp that I think is mostly hype that says we're going to put these large language model hyperscalers into orbit. If I'm generous, that's maybe 20 years out. And it's like flying a big factory on a huge rocket that doesn't exist there. So everything that's going to happen in the future is going to be distributed data centers on a much smaller scale. Everything's more expensive. Right. So we're at least 10 times, maybe 100 times more expensive to do something in space today. So, so the really killer app I see is to put AI inference in orbit close to where the data tsunami is being generated. And it's today it's a tsunami and tomorrow it's going to be a mega tsunami. And what the problem is is, is being able to get that data back so that there's, there's this, this funnel that restricts how much of that can get back. So it's a natural way to reduce that data load and get it back to the Earth. Maybe later we'll solve the issues with, you know, with, with, with the earth power and heating. But you know, Phantom, you know, we've been at it for 10 years, one form or another, writing patents, writing about it, speaking about it. It's nothing new for us. And we're putting together microdata 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 in an ecosystem for others to implement their creativity on.

1:34:05

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 going to build a new rocket, but are you planning to do connectivity through Starlink? Like where will the partnerships happen and then where will your core value prop live within the supply chain?

1:35:44

Yeah, it's a great question because this is exactly where I think all 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 their version of XAI in orbit. You really have to have that. And you know, SpaceX is going to dominate a lot in that Phantom space. We have exactly the same playbook. So those who don't have that vertical integration are always going to be at the risk of what amounts to a very scarce launch site supply. Even today, you know, 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, you know, the freightliner. And so, so, you know, we find a real market for that. 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, takes five to 10 years. So, so that's going to always be scarce. The rest of it is really a matter of supply chain control. Yeah, so, so the, you know, the Silicon Nvidia, you know, all the rest of the satellite parts suppliers, but you 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 in the space app store on top of it so that, so that people can build their own code.

1:36:07

Yeah, 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 want to be launching, like I imagine taxis, they go everywhere, they launch from everywhere. Like how else play out the taxi analogy for me a little bit more.

1:37:38

Well, so launch is like the critical cost of getting any data system into orbit, period. And so, you know, 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, you're in 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. So mass production, like the car you drive probably cost $100 million and you may be paid $100,000 for it.

1:37:59

It.

1:38:31

And there's a huge cost reduction through this year number. So at Phantom, we're going to apply both 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. 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 site. 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 going to be in a position to control, you know, the railroads or the shipping lanes, as it were.

1:38:32

Interesting. So are you looking who's working?

1:39:15

Yeah, yeah. What's the process to create more capacity?

1:39:17

So it's very complicated, it's very bureaucratic and it's very political.

1:39:22

So.

1:39:26

So we have five different launch ranges in the United States.

1:39:26

Yeah, exactly.

1:39:30

Music's my ears.

1:39:31

Yeah. Right. 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 Canaveral. And so there are so many pads you can put on there. Most of what we're using today is legacy from what was built in the Cold War. We're grandfathered into the, the bureaucratic process that approved those pads. So any new ranges, you're going to run into huge opposition. There have been people who tried to build new ranges on the coasts of this country. And everybody not in my backyard comes out of their home to oppose it. Right. And even in California at Vandenberg, SpaceX recently got in a lawsuit. We had about half their capacity, which was governed ultimately by the Coastal Commission in California. And you know, SpaceX had to sue and they got a little bit more capacity. But that's what we're heading into. That's why you see these launch ranges around the world coming into play. And the problem for US companies is we're restricted from taking our launch vehicles to these foreign countries without government approval.

1:39:33

Yeah, yeah. It's so tricky because I can imagine living next to, you know, a launch pad and the first time the route rocket goes up, you're like, wow, that was amazing. And then if it's like we're going to be launching those every 20 minutes, my Windows are shaking a lot. I actually would like.

1:40:39

Exactly.

1:40:55

The novelty wears off pretty quickly. Yeah. And so yes, 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.

1:40:57

Give us, give us any predictions around the moon economy.

1:41:12

I was gonna say moon over the next decades.

1:41:16

Yeah.

1:41:20

I have to say I'm surprised by the, by the SpaceX pivot to the moon.

1:41:20

Okay.

1:41:23

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? Do we go to Mars?

1:41:24

So you thought it was logical to do moon first.

1:41:34

Right.

1:41:37

And so you're not surprised at how late the pivots happen.

1:41:39

Yeah, it doesn't really matter, honestly in terms of their technical capability. 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. It could be a business decision. There's certainly, I think, a more near term economy there. I think of Mars 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 500 years ago began forming and Mars someday will have its own manufacturing bases. And you know, 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 moon's 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 an, effectively a theological choice where it's really not, it's just a technical issue.

1:41:42

Economic opportunities on the Moon.

1:42:42

Yeah.

1:42:44

That you think are interesting.

1:42:45

We've heard about regolith and maybe like a mass driver, but there's so many opportunities obviously besides tourism.

1:42:47

The most obvious one is Helium three. So this is pushed out by the sun. There's something like 18 kg of it in the United States in the Strategic Resources Source. It's a byproduct of nuclear weapons manufacturing. Now what are you going to use it for? Well, you can use it for a couple of things. Clean fusion energy. It's 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. 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'm no geologist, 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 would be. As long as we can solve the transportation problem. It all comes back to the rocket, by the way.

1:42:54

Yeah, makes a lot of sense. Well, thank you so much for taking the time.

1:44:06

Yeah, great to meet you.

1:44:09

Congratulations and we'd love to talk to you soon. Yeah, come back, have a good rest of your day. Let me tell you about Cisco. Critical infrastructure for the AI era unlocks seamless real time experiences and new value. You 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. And without further ado, let's bring in Tom Hum hum from gv. Tom, how you doing?

1:44:10

What's going on?

1:44:40

Hey guys, can you, we could hear you for a second. Can you hear us?

1:44:40

You're back, you're back.

1:44:44

Where are you calling in from? Can you hear us now? Yes. No, check.

1:44:47

Okay, check.

1:44:52

Can you hear this? I'm going to tell you about Sentry. Sentry shows developers what's broken and it helps them fix it fast. That's why 150,000 organizations use it to keep their apps working. Could you hear that? Because I can also potentially tell you about the New York Stock Exchange. Because if you want to raise capital, Tom, you got to 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.

1:44:53

We'll get Tom back. We will have ready. There is some breaking news that we do got to talk about, which is

1:45:21

that Jeff Bezos more fired up than a personalized ad. Okay, breaking news.

1:45:28

Jeff Bezos in talks to raise 100 billion for AI manufacturing fund. The Amazon founders traveled to the Middle East, Singapore in fundraising effort linked to Project Prometheus.

1:45:32

That is incredible.

1:45:42

Very exciting.

1:45:44

We have the red lights.

1:45:44

Exciting.

1:45:45

Breaking news. Advanced talks. I don't care if it's just advanced talks. I'm in the. Congratulations to Jeff Bezos.

1:45:45

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. More recently, he went to Singapore to raise funding for the effort as well.

1:45:54

He.

1:46:07

It's being described as a manufacturing transformation vehicle.

1:46:08

I think you're going up against tk, Right?

1:46:12

I mean, TK Is not as directly focused on manufacturing. Like, this is something I asked. No, no. He's saying manufacturing, transportation like it's a vehicle. A fund for transforming manufacturing.

1:46:16

Oh, yeah, yeah, yeah, yeah. It's like an investing vehicle aiming to

1:46:28

buy companies in major industrial sectors such as chip making, defense, aerospace. Let's try again with Tom. Get out of here. Tyler. It's Tom time.

1:46:31

Here we go. Hey, Tom, can you hear us?

1:46:40

Oh, no, no. We don't have audio. We don't have audience. Okay.

1:46:44

Okay, guys, try it out. Nothing. Okay. We. We. You can hear us. We can't hear you, but we can tell you about this post that we enjoyed from Larican. Got my horse to water. Now for the easy part.

1:46:47

I'm going to continue. The fund is aiming to buy major industrial sectors such as chip making, defense, and aerospace. It would dwarf the size of some of the world's largest bio funds and rival SoftBank's $100 billion fund. I got to wonder, how much do you think Jeff is pitching in himself? I could see him anchoring. He's like, I'm good for 30 something in that range.

1:47:03

Yeah. Yeah, he's got some fun.

1:47:28

But this is such a white pill.

1:47:30

Yeah. Why?

1:47:32

I mean, the whole. This is like, you know, we need to manufacture. You know, basically, we need to re. Industrialize America. We're not going to do it by just copying everything from the past. There's some element of transformation that needs to happen as well as new efforts. And this is. This is tremendous news.

1:47:33

Yeah. And I mean, there has been, like, A venture capital boom in re industrialization. But most of the funds that we talk to that are in that category are 50 million, couple hundred million, certainly nothing at this scale. And this has got to be incredible news for the founders that we talk to that are part of the re industrialization effort because 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 blog which has some fantastic articles. Let me tell you about Okta. Okta helps you assign every AI agent a trusted identity. So you get the power of AI without the risk. Secure every agent, secure any agent. Will OpenAI increase the cost of ChatGPT? This is a Kelsey market out there. It's at a 46% chance if either ChatGPT Pro or Plus have a price increase after January 2, 2026 and before January 1, 2027.

1:47:54

So in the based on the current pricing of $20 a month and $200

1:49:03

a month, what do you think? I feel like this isn't financial advice, but I feel like they're not going to move the price points because they're focused on so many other things.

1:49:07

Yeah. The only thing is I could imagine an additional plan on top of it.

1:49:17

Yeah, totally.

1:49:22

But that would be an incremental plan.

1:49:23

Max is right there. We got pro, we got plus, we got pro. Sign me up for the Max plan. And I think they also have a light plan and I would imagine there's go, go, go. Yeah. So I would imagine that there's more tiers within there at the same time.

1:49:25

Give Tyler the goat.

1:49:39

Ripping the band aid off of price adjustments is extremely painful and probably the earlier you do it, the better. Like Netflix. Yeah, yeah. Like Netflix has been increasing prices and when they're at 9.99amonth or something, it's very normal. And then when you go up, it starts everyone's, oh, you raise the price. But if you just raise it every couple months anyway, we're good. Third time's the charm. How you doing?

1:49:40

I'm very good.

1:50:03

Can you hear me? Fantastic. Introduce yourself.

1:50:04

Who are you? Tom Hume. I'm one of GV or Google Ventures Managing partners. I'm based in London. I'm going to hope I'm going to bring as much energy as Carl.

1:50:09

I love it. I love it.

1:50:17

It's a tough act to follow, but it's a good start.

1:50:18

AI good or bad, what's your strategy? What are you investing in what are you seeing?

1:50:21

As you can imagine, 80 or 90% of what we're doing is I. In truth, it's hard to imagine a credible founder that isn't leading with it at the moment. And so we're viewing everything, I mean, in your email that you sent out today about Samsung, about some of the effects of what's going on in the Middle East. We're even looking at that through the lens of AI and how it should affect our investing strategy.

1:50:25

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 going to 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 going to help them, you know, if you join the board, you're going to help them go global. What are you thinking?

1:50:49

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. 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 master's programs are actually in Europe. 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 shows global. 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, Sneak's founder Guy Pijani, who has now done tesol. 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 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 seeing that Mastermind.

1:51:14

Got it. Yeah. Does Europe broadly give England enough credit for DeepMind because it got rolled into Google so quickly, But I feel like the UK punches way above its weight in terms of AI research with DeepMind and maybe that's underrated.

1:52:34

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, it was really hard for people to see the 2017 Transformer paper had not been written for five 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 Hassabis, 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. So there's great NEO labs being funded right now. You've got reinforcement learning companies like Recursive superintelligence like Tim Rotasho 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. They deserve huge credit for that, for every one.

1:52:54

So yeah, yeah, yeah. When you look at a NEO lab, it feels like there's a thesis where it's just okay, you have a brilliant technical mind, they're going to go explore. 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, at least from conversations, do you have an idea of how the NEO labs might plug into the broader AI ecosystem either through partnerships with big labs or are you talking to NEO labs that are saying we can leapfrog on certain vectors or maybe we can launch our own consumer product? That's happened before. How do you think about where the NEO Labs fit in post the research phase?

1:53:57

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. 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 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. Often they will actually service their unique intelligence through API.

1:54:43

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.

1:55:37

Yet.

1:55:57

I mean one that everyone's really excited about.

1:55:58

But it's partly.

1:56:01

We just exited the business to Apple is people keep asking me what Q is. So Q Israeli company, second biggest acquisition.

1:56:02

It was in stealth until the acquisition, right?

1:56:13

Correct. So I was on the board for the whole of that period. We led the seed and did the series A with our friends and Kleiner, Aleph and Spark. And that company is going to 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 150 words per minute. It's high input information because of intonation, etc. Versus typing which might be 90 words a minute. We invested in Neuralink, which is like the very invasive version of high throughput. And 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 a consumer perspective, nothing.

1:56:16

Any ideas or guesses? 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 Apple iPhone users will get to experience in 2027? Is it the longer term? Will they ever kind of like do you think there'll be a moment where they're like wow, this is a huge.

1:57:01

Yeah, I think it's going to be a wow moment and I think it'll be in 2028. And 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 for example, invested in nothing. They just sent me their new products which I'm going to unbox after this. But they incredible smartphones we Believe that actually the value accrues to the distribution. And so whoever owns those smartphones.

1:57:31

Yeah, Carl being in the position. Carl being in the position of 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 is a very cool position to be in. Yeah.

1:58:05

Yeah. It's a fun time. Well, thank you so much for taking.

1:58:21

You brought the energy. You brought the energy.

1:58:23

My apologies for that.

1:58:26

I also brought the technical issues. So apologies next time it happens. Well, thank you so much.

1:58:27

No, it's great to meet you, Tom. Come back on set to see you both.

1:58:32

Take care. Have a great day.

1:58:34

Thanks. Let me tell you about Figma. No matter where your idea starts, Figma may clog code, codecs 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.

1:58:35

Let's play soon. But let's play if we have time before the Cubinator joins.

1:58:50

We're working on some.

1:58:58

We're working on it. I don't think we have time. I'll try to.

1:58:59

Let's rotate that screen and I think we're almost ready. The one small news article here that we can talk about is that Meta has signed a 10 year lease for a 15,000 square foot townhouse on 697 Fifth Avenue to open Meta Lab New York, its first Manhattan flagship retail location. They painted it completely blue. Apparently the store will focus on hands on demos of Meta, AI glasses and VR head headsets. So they're getting into the retail space. Well, let's figure out.

1:59:03

Still working on it. I can tell you about Way Shirt Capital.

1:59:36

Okay, tell me.

1:59:40

They invested in SpaceX at apparently 200. Okay. It's fake news. Brutal.

1:59:40

That was quick.

1:59:52

Brutal. I was like this seems too good to be true. Your pitchbook is. But we can tell you about Rivian Robo Taxis.

1:59:52

Oh yes.

2:00:02

Uber and Rivian have announced a deal. Uber is going to invest 1.1 and a quarter billion in Rivian and deploy up to 50,000 R2 robo taxis. I'm so interested to see what Rivian can actually do on the robotaxi side. Friends that have owned Rivians have said that the autonomous driving is fantastic. 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.

2:00:03

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 TVPN Ultra one. Mark, can you hear us?

2:00:35

Yes, but you're too loud. Hold on one second.

2:00:48

Too loud.

2:00:51

Too loud.

2:00:51

Okay.

2:00:52

Yeah, no, because of my ear.

2:00:53

Great to have you, Mark. Thank you so much.

2:00:55

Hey guys.

2:00:57

Hey, how are you doing?

2:00:58

Hey guys. Okay, well, I'll deal with it.

2:00:59

Good to see you. How's your 2026 going? We haven't talked this year yet. What's life like?

2:01:01

I'm loving life. I got no complaints whatsoever.

2:01:07

Yeah, that's amazing.

2:01:09

Yeah, I'm loving life.

2:01:10

That's great. Are you? So you're not disappointed about the rollout of ads in LLMs thus far then?

2:01:11

Is that it hasn't ruined your year?

2:01:19

Because 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 want to check out the Journal. Seemed innocent enough to me. But how are you feeling?

2:01:21

I haven't seen it at all, so it hasn't ruined my life at all.

2:01:31

Okay.

2:01:33

What's your information diet? Because it's hard not to log on the Internet and not start black pilling these days.

2:01:34

Yeah, no shit. So my first stop, My first stop is a site called Mimio Random, which kind of 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 world. And then after that all the different newsletters and emails that I get, just that try to keep me up.

2:01:41

How are you processing the flood of cold emails that appears to be thoughtful, but is AI generated? Actually AI generated because you are notorious for your response rates and getting back to so many people that have reached out, but. But it feels like maybe an impossible task now.

2:02:03

No, I do what everybody else does. I bought a Mac Mini.

2:02:23

You did?

2:02:25

You know, yeah, for sure. And I'm still learning.

2:02:26

So you're just like, you hit me with AI, I'll hit you with AI back right away.

2:02:31

Right back.

2:02:34

Right.

2:02:34

It's not even like the cold emails because that's pretty obvious, you know, 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, so you just gotta train it to hit the unsubscribe button and I just review it and all that shit. So it's still a work in progress, but at least I have a path.

2:02:36

Well, the issue with us is that historically, if you had a podcast and somebody wrote you an email and said, hey, I really appreciated this moment where you're talking about this one thing.

2:02:56

Totally. You're like, oh, they actually tell like,

2:03:05

hey, at least they, they press play and at least they found a moment. But now I just does it instantly. So there's no way to clock whether, whether something's real or not.

2:03:07

Yeah. And that's okay, right? Because they're going to. The response rates most likely will be so low. We're in that trial and error phase where people are like, we're going to try it, see what happens. Maybe we'll get lucky and then they'll get bored and then it'll drop off.

2:03:17

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 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.

2:03:31

Yeah. Agents for everything.

2:03:49

Yeah.

2:03:50

It's just because once you figure out how to do agents, then you can do them a little better than most other people and then you can turn that into what would have been a SaaS business in the past is now we'll create your own marketing team and we'll 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.

2:03:51

That's it.

2:04:10

And I'm seeing dozens of those, typically one for every industry you can ever possibly imagine.

2:04:11

And are they growing revenue faster? Are they growing profit faster?

2:04:16

Neither.

2:04:21

They're just still trying to get some, just trying to get some traction at all, you know, because if you're growing revenue quickly, you're probably not coming to me yet.

2:04:21

Okay.

2:04:31

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, you know, or sign up or, you know, now there's a little bit of a battle to use USDC for payment as the payment rails to make it so that just give me your wallet and you know it's going to end up being a scam and a lot of people are going to get ripped off there. But I think the real thing right now is agents for verticals and trying to turn that into replace all your employees so you can start up or you can cut costs.

2:04:32

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.

2:05:08

Yes and no. Yes, they should be. No, people won't understand them and the other sharks wouldn't understand them.

2:05:17

Sure.

2:05:22

But yeah, I mean, effectively, anything you can do.

2:05:23

But you only need one shark to understand.

2:05:25

Yeah. Right. And I'm not on the show anymore.

2:05:28

It's time to go back.

2:05:31

It's time to go back.

2:05:32

Yeah. What was the anatomy of? I think we talk about what makes for a great company all day long. We'll talk about that throughout the show today. But what makes for a company that will put on a particularly captivating Shark Tank appearance?

2:05:35

You got to remember, it's for tv. You have to be entertaining. And if it's not entertaining in some shape or form, it's just not going to work. Regardless of the quality of the business. If you don't have charisma, you don't have a compelling pitch that's entertaining, it doesn't matter. You could be selling dollar bills for 50 cents and it would fail.

2:05:52

Interesting. How important is 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 the physical product presentation?

2:06:12

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 15 years, we only had one. Really just choke right where they couldn't spit it out, maybe two, which is amazing. It's a testament to Mindy and the producers there how hard they prepare them.

2:06:24

Yeah. How do you think Shark Tank and shows like it will change in the era of AI video generation? You know, endless content. Is it stronger than ever because it's a known brand or is there some weakness there? How do you see that playing out?

2:06:47

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. Sure. I think for Shark Tank, it's not going to have to change because of AI or technology, simply because you're really communicating to a family audience. And the message you're communicating isn't, hey, 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. And so that's really what makes Shark Tank successful, not the quality of the businesses.

2:07:08

Yeah. What about sports? I've seen some robots playing tennis. They're going to 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?

2:07:40

I mean, maybe for the referees, like you've seen in tennis, but that's it. I think in reality, more people will want to go to, in real life events than before. Because if, you know, if you're just managing agents, looking at output, looking for exceptions, you're going to want some human touch.

2:07:54

Right.

2:08:12

You're going to want to be able to engage. And I think that that's really, really important. And I think that's where sports will grow. I mean, you're starting to see that now with what happened with the Olympics. The World Baseball Classic became much more popular because people want that disengagement from all the stress that's happening right now.

2:08:12

Yeah. At the same time, it feels like there's almost an opportunity for, not to bring it back to targeted advertising. But AI can tell me, okay, my favorite team's in town, I should go to this particular game. I should, should remind me at the right time instead of just signing up.

2:08:35

Yeah, that's not AI. Yeah, that's not really AI. Yeah, that's just targeting. Right. And I'm going to tell you what, in terms of, I'm going to take it down a different path because I'm contrarian on this. And that's with robotics. I think everybody's making this push for humanoid robots. I think they might have a five year lifespan and then they'll fail miserably, maybe 10.

2:08:49

You mean the companies or the device or the individual physical robots or both.

2:09:12

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. 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. I think houses are going to 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 look more like spiders, that could, you know, but had, you know, the ability to carry and lift things, whatever, more like ants, I guess. Maybe. 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 going to be full form humanoids. They're going to be whatever the optimal shape is and they're kind of co designed. You design the house to fit the robot and you design the robot to fit the house. And I think you could go expensively on both.

2:09:18

You know, 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? Like if it's on wheels, like you just put it. Yeah.

2:10:46

Like you see, like the old house. Dumb way dumb waiters, right? 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 mechanized equivalent to that, 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 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 stairs are an issue at all.

2:11:04

Yeah. How do you think about just these types of ideas? AI products generally getting rolled out and then hitting it, bumping up against human, human guardrails. Like when I hear that, I think that sounds incredibly sci fi and potentially possible from an engineering perspective. But then you try and remodel your house and you're stuck in permitting for two years. And so that tends to slow the progress down a little bit. Is that technology okay?

2:11:41

Yeah, of course it is.

2:12:12

But that's all technology during the interim period, right?

2:12:13

Sure.

2:12:15

There's always a transitional period where you go from, 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 run all the ethernet cables and all that shit.

2:12:15

Right.

2:12:31

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. We'll find ways to adapt. I think, I think 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 going to do are going to be outside and are going to have to consume in the interim at least either satellite bandwidth or 5G bandwidth. And I don't think there's going to be enough bandwidth when you're working with video based AI models.

2:12:32

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? What are you thinking is going to happen there?

2:13:18

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. Oh my God. Because. Because like when you're going 25 miles an hour, it's no big deal.

2:13:32

Yeah.

2:13:43

You go on a highway and you're going 70 miles an hour and there's a median right there in the middle of the highway.

2:13:44

Yeah.

2:13:50

I was like shaking like, I was like, I don't, you know, Elon's cool for whatever, but you know, I ain't trusting them that much.

2:13:50

Right.

2:13:57

You know, and I'm like

2:13:59

Mad Max.

2:14:02

No, no, no, no, no, no, no. You know, but you can set a dilemma 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've got to go the speed limit. And it was scary as fuck trying to go 70 miles an hour. And I don't want to be there when somebody paints some adversarial. You know how there's graffiti in the weirdest places? Wait until there's adversarial graffiti.

2:14:03

Oh yeah, yeah.

2:14:28

Like somebody. If somebody paints, it's the roadrunner, a brick wall.

2:14:29

It's roadrunner.

2:14:32

Paint it to look like the road road running.

2:14:33

Wiley Coyote.

2:14:35

No, that's like ridiculous.

2:14:37

Right? Wiley Coyote's gonna paint the tunnel and then you slam into it.

2:14:38

There's somebody somewhere trying to figure out how to fuck up self driving mode. Right.

2:14:44

For sure.

2:14:50

Because it's just taking video input. And you know what? It could be some pattern. And all of a sudden you're seeing this, this pattern on medians or, you know, overlaid on stop signs or whatever.

2:14:51

Yeah.

2:15:04

You know, because, you know, somebody's got to do that because it's just too easy not to.

2:15:05

Yeah. Hyper realistic camo wrap gets confused, you know, eventually.

2:15:10

Yeah, whatever. Right.

2:15:15

You wrap your car in camo. And if the camouflage is effective, you're going to confuse the AIs. It's a risk.

2:15:16

And there could be a predator. Alien versus predator predator could show up. Right. And if Arnold isn't there to save us, it's possible.

2:15:23

I mean, speaking of Arnold, are you. It sounds like you're in a good mood, you're optimistic about things. Does the question of AI doom come into your mind? These runaway robotics, are you worried about that at all?

2:15:31

No, not even the least for the reason I just mentioned.

2:15:45

Right.

2:15:48

In order, like. Like right now LLMs are basically bimodal with some video.

2:15:48

Right.

2:15:55

Where it's almost all text and pictures. With some video. You can't model the world with that. 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.

2:15:55

Right?

2:16:20

Large language models don't understand. Every time, every time, every time, Right. And there's no ever. And it's hysterical, you know, unless your mom. Right, but you get the point, right? The large language models we have today can't do that. And so we have to evolve to model that can capture the world and physics and deal with the latency of capturing or not 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 is taking over. I just don't see how it's going to happen. Now you can have 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, Right? That's going to be application specific. So I'm not afraid of that at all. And I also think that we're talking about agentic applications. I think particularly for small, medium sized businesses and some large businesses, they're not going to have that skill set. It's not going to 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, like when 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 going to understand how to do any of that shit at all.

2:16:21

Yeah, that makes a ton of sense.

2:17:54

What. What advice are you giving to friends? Portfolio companies, et cetera, around navigating as a business leader during a time where we have major global conflict. I don't know what exactly you're working on in 2002, 2003, 2004, but there's so much. I mean, right now, everyone's hoping for a quick end to the conflict, but it's hard to lean on that.

2:17:56

You know, it's funny, in 2002, when we attacked Iraq, I created something called the Fallen Patriot Fund, which was just money available that I funded myself. Money available for the families of soldiers who didn't return or soldiers that were 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.

2:18:25

Right.

2:18:59

You could have an opinion whether it was right or wrong, but hey, there were WMDs, right? Weapons of mass 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 are out. Algorithms are like fingerprints. No two are alike. 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. 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.

2:19:00

Yeah, we're all trying to predict the future together. Well, based on wildly different kind of influences.

2:19:58

Exactly. 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, we just don't. And we spend more time trying to filter and determine what's real and what's not, so that it's almost impossible to really do anything but just hope and pray.

2:20:07

We have a couple questions from the chat. The first one is about cost plus drugs. Can you give us an update there? How's it going with this? Yeah, fantastic. But give us a sense of scale, give us a reminder of the strategy, reintroduce the company.

2:20:29

Sure.

2:20:53

So what you go to costplusdrugs.com 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. 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 underinsured, 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. And because of that our business is just skyrocketing. So that's part one of our business. Part two to our business. For my company, for 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 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 1500 or $2500 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. Think about that, right? And then you have the denials and then they underpay late play callback. 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. 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, 100 to 100% of Medicare unless it's really complicated. 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. And it's just blown up. I mean, it's just incredible. We 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. You don't need to be dependent on the insurance company to come up with the right deal because they won't. They'll steal from you.

2:20:53

Did you ever. I mean, it's such an interesting, such an interesting company for you, because I feel like 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 or have you burned out on that stuff?

2:23:37

Creatine powder, the Cubinator protein stack?

2:23:57

I'm in the. No, this is obviously much more important.

2:24:03

Yeah, I just thought you. Nobody looks at health care and says the economic side is great. We're doing it the right way in this country. It's the exact opposite. And so if you're going to try to disrupt, go big or go home. Right?

2:24:07

Another question from the chat. What's the most underrated business you've seen in your career? I think they're talking about something that is, the moment you saw it, collect and you were like, okay, this is a wildly mispriced asset or something that could really fly.

2:24:19

Streaming.

2:24:35

Streaming. Yeah.

2:24:35

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? And this is right when the Internet just started. Right. It was brand new to everybody. And I'm like, let me figure it out. And so we started a company called Audionet and got the rights to, you know, hundreds of schools, hundreds of radio stations, TV stations. Back then, the copyright laws were different. Created our own Internet jukebox and unlimited 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.

2:24:36

What was the domain name negotiation like? Jordi's a big fan of great domain names.

2:25:15

Great question. Great, great, great, great question. So when we started, it was Audionet and I just registered it. Nobody had it. But then.

2:25:22

Wait, audionet.com or audio.net?

2:25:30

no, audionet.com.

2:25:33

okay, I like it. Yeah.

2:25:34

Because we were just doing audio in 1995, and then by 97 we started to do video and Audionet wasn't Going to cut it. And So I found Broadcast.com because we wanted to broadcast everything and anything and found the guy and paid him $8,000. And he was thrilled to get the $8,000. Yeah. This is 1997.

2:25:36

Did he ping you after that? Did he ping you after.

2:25:55

Yes, he did.

2:25:58

Yes, he did.

2:25:59

But wait, it gets better. But wait, there's more. Right? And so I'm like, oh, shit, this is nothing. 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 dot com. So, literally, I own Final four dot com. I own baseball dot com. I own sandwich dot com. You name it, I bought it. I bought it for. I would buy, like, just packages of URLs, right?

2:26:00

And just.

2:26:34

And this is because people were just going to their browser and being like, sandwich.com, they would type it in.

2:26:35

Google didn't. Exactly, exactly, exactly. Everything was a portal, right? Everything was a front, front door. And so I was like, anything that generated traffic, and I've done it since like, I own Mr. President dot com. I own democracy dot com.

2:26:41

He privatized democracy Private.

2:27:00

I was worried.

2:27:04

That's the most American thing I've ever. I've ever heard. I love that. That's incredible. Okay, the last question for the chat, and we'll let you get back to your busy day. I want to flip it around. 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 technology or maybe an anonymized company, something like that.

2:27:05

Yeah.

2:27:35

God, I'd have to think about it, you know that what was not the motorized skateboards. They weren't called.

2:27:37

With the two hoverboards. Hoverboards. Hoverboards. So hoverboard future, everyone traveling on hoverboards.

2:27:42

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, et cetera. And so we started a company that did hoverboards, and there were so many more patents already in place than I ever imagined. We couldn't get past them. And that it failed miserably.

2:27:50

Yeah, yeah, yeah. That was a very interesting boom. The Hoverboard boom. It sort of came out of Shenzhen fully formed because there was a massive supply chain and they were all over, but there was no one brand. They were like 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 over and

2:28:10

they were making a killing.

2:28:29

Oh, yeah. They were killing. Oh, yeah, yeah.

2:28:30

What? Is it still possible to create a widget and make like, $100 million from it? Or does the cut or do the clones come? Because I know the guy who made like, the fidget spinner, like, his claim to fame.

2:28:32

Right, right. That's cool.

2:28:48

But he didn't.

2:28:49

It got knocked off like that.

2:28:50

Yeah. I mean, it was the kind of thing that, like, was a hit product.

2:28:51

It's all on Amazon. All on Amazon. Right. So I started talking to some Amazon resellers, like Mid 24, because I was just curious about some things. Things I 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, right. For your. But if you're Chinese, there's no limit 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.

2:28:55

Oh, so you're just screwed because you're screwed.

2:29:31

Yeah, 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.

2:29:35

Okay, I know, I know one. I know one widgets company that bought the next five most popular widget companies in the category that were knocking them off, and they just continue to operate them. But they have enough ranking on Amazon and they have scale.

2:30:21

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. Not the manufacturing, but just from an IP and from an Amazon cost perspective, 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 sense legislatively. You 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 90 days to check in. And all of a sudden the whole industry changes and American manufacturing skyrockets and because that, that cost of knockoff isn't just about the cost of losing sales. It's the administrative, the legal cost. There's just so many nuanced things that you have to spend money on.

2:30:38

We have knockoff issues and like we spend thousands of dollars to have our lawyer, like chase him down and send take down requests from our merch.

2:31:39

Like just T shirts and stuff.

2:31:48

Yes. Oh, yeah. Merch is crazy. And then IP too, right? All the DMCA takedown notices because they're just scraping and you know, reposting all that shit. Right. That's easy to fix if, you know someone has the guts to do it.

2:31:50

What is the anatomy of using your likeness once you've made an investment, what does 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 slap your face next to their product and clip 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. He said it looks nice.

2:32:04

Yeah. I mean, it depends on the company. Usually I don't even care. But two things. One, you know what Synthesia is? Synthesia IO?

2:32:31

Yeah, yeah, I think so.

2:32:38

Yeah, they've been on the show.

2:32:40

Yeah, yeah, yeah.

2:32:41

They have the avatars, they have Victor and all those guys. Yeah, well, I was their first investor, so I send them there.

2:32:42

Okay. Yeah.

2:32:46

Your dog, Your dog. That's a unicorn.

2:32:47

Come on, dude.

2:32:50

And I gave them like a lot of money. Yeah, I gave them a lot of money. And this was 10, 12 years ago. Way ahead of the curve.

2:32:55

Yeah, there we go. Okay, so Synthesia.

2:33:01

Yes, so Synthesia. So I'll push them to Them or like I'll just. Around like you saw with Sora, they had. 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. And they. Sora 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 video that use my likeness, you went the. It showed the logo for Cost Plus

2:33:12

Drugs

2:33:41

and it's been used like hundreds of thousands of times. And I know we've seen a bump as a result.

2:33:44

So Smart John did the less commercial thing. He said portray me as a bodybuilder.

2:33:48

But of course, the store is kind of falling behind now, so they kind of. I don't know if they'll know.

2:33:58

It's good. It's gonna, It'll just get added into chat GPT and then you got a billion people just, just pumping Cost plus drugs.

2:34:02

Yeah.

2:34:09

It's always, it's always crazy to me to see it. Like I tell it, you know, don't. You know, because it has terms of service, you can't show drug use. And so there's pictures of me like doing lines of coke and, and I

2:34:09

got, you know, so it's kind of crazy, but ridiculous. When is the right time for a company to apply to Shark Tank?

2:34:20

Anytime. You just don't know. I mean, they have open auditions all the time. So if you go to Shark Tank's website, it'll give you all the information there and you just got to go out there and have fun.

2:34:29

Go out there and have fun.

2:34:40

How are you processing the peptide Boom? Both FDA approved.

2:34:41

Non protection 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. Show me the trials and show me the research.

2:34:46

You mean the non FDA approved, just the stuff coming off the boat or

2:34:58

are you short Eli Lilly?

2:35:03

No, no, no, no, no. The insulin. Like the real. Because when people talk peptides, you're talking supplements on stuff.

2:35:05

Right, right.

2:35:11

But the Eli Lilly stuff.

2:35:12

Yeah.

2:35:14

Not.

2:35:14

Not Ozempic, that's running super bowl, very heavily regulated. Yeah, that makes sense.

2:35:15

No, because that stuff's going to come down in price. And now, you know, Lily and Novo are smart now with their GLP1s. They're working around the PBMs. They're doing direct to patient, direct to company. And that was brilliant. That was really smart.

2:35:20

Yeah. Yeah, that's very cool. Well, thank you so much for Taking the time, Jordy.

2:35:32

It's always fun.

2:35:36

This is always fun. Have a good one, Mark.

2:35:36

Fun, guys.

2:35:39

Enjoy the rest of your time.

2:35:39

Appreciate it, guys.

2:35:41

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.

2:35:42

Oh yeah. I came up with the name. I came up with. I'm not going to say it. I'm not going to say it, but the domain's available.

2:35:56

Okay, we're getting the domain.

2:36:02

We're getting the domain. You're going to Shark Tank. You're going in the Tank.

2:36:03

I'm so excited.

2:36:07

Going in the Tank, Ben.

2:36:07

I'm so excited for this.

2:36:09

Not you, Tyler.

2:36:10

Not you, Tyler.

2:36:10

Keep working on, keep working on our other, our other launch once. Yeah, all right, we got it. We got to hit the size gong.

2:36:11

Okay. What do we have to do?

2:36:18

Ro Khanna.

2:36:18

Ro khanna.

2:36:20

What did 609 million of trading volume while in Congress? He's fighting back against the elites by trading against them.

2:36:20

I was, I was, I was talking to Jordy about this this morning.

2:36:30

Morning.

2:36:32

And I was like, is 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

2:36:32

trade that much where the only volume is the buy.

2:36:42

The buy and then you just hold. But, but he's putting up big numbers. But maybe he's running like, maybe he has like 10k in a high frequency trading. Yeah.

2:36:45

Long, short strategy.

2:36:55

It's just, they're just eking out milliseconds.

2:36:56

Yeah, maybe he's running. Maybe he's got a stack of 40 open, open cloth.

2:36:59

Yeah, maybe he's been poaching from Jane street and so he's putting up a lot of volume.

2:37:04

This is just insane volume. From the anti elite champion.

2:37:07

He's crazy.

2:37:13

He said, you guys want to dance? I'm trade against you.

2:37:14

How do you even have time to consider 37,000 trades? Like he's, I mean, how many. I mean that's, that's how many minutes are in a year? In a year.

2:37:17

That is a lot of volume and a lot of trades.

2:37:30

525,000 minutes in a year. So you can spend 20 minutes on each trade if you're working 24, 7.

2:37:34

He's been in.

2:37:42

I'm sure there's something else going on.

2:37:44

He's been in office for nine years.

2:37:45

It's probably just like A like a investment manager? Yeah, he says it's his wife's money prior to the marriage.

2:37:47

Well, he's averaging 11 trades a day since he went into office nine years ago. Roughly.

2:37:54

Yeah. And the stock ban legislation, that's no

2:38:00

days off, that's weekends, holidays, I don't know.

2:38:02

Let everybody trade. Why not?

2:38:06

Yeah. Sounds like he's locked in.

2:38:09

He's traded at all times. What else is going on?

2:38:11

We are removing sanctions on Russian in and Iranian oil, which is craziness. Craziness.

2:38:15

Didn't think that would happen. Let's watch the public latest ad. Is that what we should pull up next?

2:38:25

Pull it up. Actually, let's pull up this video first of our president of Gary Tam. But this is Gary Tam when He sees a YC applicant using GStack to ship 500,000 lines of code daily. This is one of the best videos of all time.

2:38:32

Just pulling out a wad of cash. I'm ready to invest.

2:38:46

Quickly counting it.

2:38:49

It is so funny how lines of code became like not the new eyeballs. And now it's new.

2:38:50

They're the new eyeballs.

2:38:56

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 and whoever can do it fastest.

2:38:57

Okay, but how do you define a line of code? Like I can just write a for

2:39:13

loop that says 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?

2:39:17

Okay, but can I have the same line of code 10,000 times?

2:39:31

You've invented the for loop. Potentially. Print. Print this. That would be the most efficient way to do it. Potentially.

2:39:34

Let's pull up this ad.

2:39:41

It might even be faster to just clone a repo.

2:39:42

Right.

2:39:45

Clone a 10,000 line repo. Do you have to write it from scratch? We need to write the ground timing.

2:39:46

Pull up the ad.

2:39:51

Okay.

2:39:52

Sir.

2:39:52

Yeah. What are we watching here? Well, looking at your portfolio, you've got diverse equity exposure, broad market etf, some fixed income. How however, I am seeing a gap here. College basketball, baby.

2:39:53

I recommend a three leg parlay, maybe

2:40:06

sprinkle in a few place props just

2:40:09

to even things out.

2:40:11

I've got a strong read on an early upset.

2:40:12

If you're looking for a broker that's

2:40:16

not also your bookie, we invite you to try public.

2:40:18

It's a Good ad. Really, really solidifying public's position as.

2:40:22

Which has been very, very consistent.

2:40:26

Yeah, very, very smart these days, taking shots.

2:40:28

I wonder if they're gonna actually run that on TV for March Madness, would

2:40:31

that be the right place to run it? I feel like March Madness viewers kind of want a bookie. Like they want to bet.

2:40:36

Well, March Madness is just like kind of everyone.

2:40:41

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. Lambda is the super intelligence cloud building AI supercomputers for training and inference that scale from one GPU to hundreds of thousands. And we'll bring in our next guest, John Kim from Paraform. How are you doing? Thank you so much for taking your time to come chat with us. Please introduce yourself and the company.

2:40:43

Hey guys. One of the founders and CEO of Paraform. We are a Gentex hiring platform platform that makes hiring exceptional talent as easy as pressing a button.

2:41:13

I love it.

2:41:23

So our first product, we got. We got your button in the mail. We did, we got your button. We got a package from you guys.

2:41:23

It was very well recorded.

2:41:28

It was a great, great execution. The only issue is the chocolate completely exploded everywhere over the phone.

2:41:30

So it made it way more memorable, honestly. Yeah, yeah, yeah.

2:41:37

I will never forget.

2:41:40

Maybe there's alpha. There's deep alpha there, there.

2:41:41

Anyway, but it knows. Awesome.

2:41:43

And thank you for the kind. So who is the customer? Who's paying for this? Is it large corporations, small companies, startups, or do you have the applicant pay sometimes? How does the business model work?

2:41:44

Yeah, yeah. So it's the company's paying. We started out helping startups, you know, build their 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 public companies like Palantir are customers.

2:41:56

Yeah.

2:42:11

Wow.

2:42:11

And you raised some money. How did it come together?

2:42:12

Yeah, yeah, we raised a $40 million round led by Scale Venture Partners.

2:42:16

I need to wait for the congratulations. And help me understand how you're going to deploy capital to accelerate at this particular moment, 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. There's SDRs to hire. How are you thinking the shape of the business evolves over the next 12 to 18 months?

2:42:21

Yeah, no, definitely. I mean, might be just like a classic answer, but we obviously want to continue to do best in class growth. We grew a ton 10x to our revenue last year and we want to continue to grow at a fast pace. So in order to do that, you need to grow our team and all that stuff and also accelerate our product roadmap. Right. I think in particular I'm personally spending a lot of time this year really just narrowing down, focusing on our product roadmap.

2:42:51

So yeah, one more thing I will

2:43:19

mention is we sort of started in tech and helping tech companies hire. 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 deploying capital, going across industries as well.

2:43:22

Yeah, talk to me about the legal hiring market. 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, walk me through that.

2:43:44

Yeah.

2:44:00

I mean since we're a recruiter marketplace, 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 a lot of lateral attorney and partner hiring at law firms are driven by recruiting agencies. So these 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 doing that.

2:44:01

How are you thinking about just areas of growth in the US economy broadly? If you stack rank, there's a lot of energy around re industrialization right now. We were hearing that Electricians might be the LeBron James of the next era. But that feels like, I don't know, that Electricians are on the Internet the same way that software engineers are where they might have public GitHub profiles, house blogs, LinkedIn profiles. How are you thinking about solving those next verticals?

2:44:25

Yeah, no, I think like, definitely like defense and government seems to be a huge area of growth. Yeah, like you said, manufacturing, like anything that's sort of like atoms, not bits, I think is like sort of also going to grow a ton. I actually think like travel, entertainment, like those industries, media, you know, is going to do well as well. So yeah, we're looking at what sort of verticals to go after. Like to your point, based on what, you know, what we think are exciting. I also read the anthropic report where they published sort of like what jobs are going to be like sort of replaced by all that stuff and oh

2:44:56

yeah, you know that spider chart and then Andre Karpathy posted something similar.

2:45:30

Yeah, I mean I think actually like you know my point of view is that the economy is not like a zero sum game, like it's actually an abundant. So I actually not too worried about AI replacing people. I mean sure there's some adjustment on how we need to upskill ourselves and differentiate but I think every technological revolution humans figured out a way.

2:45:34

I mean that's the interesting thing about that chart is that what's missing from that chart of jobs that will go away is the new jobs that will be created like live stream error. Business technology news was not a thing when I was a kid. There's zero chance that I ever could have put that down as like my future career will be live streamer.

2:45:57

What?

2:46:15

That wasn't a thing.

2:46:16

What in conversations with investors for this round, what were like what kind of exits like were kind of reference in the, in the recruiting space I know there's like public recruiting firms like you know these, these companies scale to like mass. Massive, massive. You know they're, they're not. No, I'm talking about like non tech companies that are just like we do staffing and recruiting.

2:46:16

Oh yeah, yeah.

2:46:40

In different kind of verticals. But there's massive massive companies in the space. Are you comping to those and saying like hey we, there's, we can be a billion dollar business just based on serving a similar kind of sector?

2:46:41

Yeah, I think, 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 I think.

2:46:54

Well yeah, 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's not like a perfect comp where Figma's like well look, you have Adobe so we're just going to like some percentage of Adobe.

2:47:02

Yeah, I think the way I look at it is if you look at the total amount of like dollars spent spent on recruiting, broadly speaking like where does it go to? And actually the biggest spend category is external recruiting. So outsourcing recruiting, working with recruiting agencies, staffing agencies. So like that's sort of the biggest spend. But actually if you look at traditional like VC dollars over the last 10, 20 years, it all went to like HR software or recruiting software. And that category is actually not that big. It's like maybe 10 billion that I'm not sure exactly but it's not the biggest category yet. 90% BC dollars went in there. 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. So, yeah, we're going after the biggest market in recruiting. Yeah.

2:47:22

Amazing. Well, thank you so much for taking the time to come chat with us. Congratulations on the new round.

2:48:25

Great to get.

2:48:29

Good luck.

2:48:30

Thank you.

2:48:31

Soon.

2:48:32

Great to see you, John.

2:48:32

Have a good one.

2:48:33

Cheers.

2:48:34

And we will continue our Lambda Lightning round with Eugene from edra. He's the co founder and CEO. He has some exciting news for us today. Eugene, how are you doing? Good, how are you guys?

2:48:34

Thank you for having me.

2:48:47

Exiting stealth. I love when companies exit stealth because. Welcome to the public eye. Please introduce yourself and the company.

2:48:48

My name is Eugene Alpez. 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. And, and nobody has that. You can't go to any company and tell them, just tell me, I don't

2:48:56

know what to do. How am I supposed to tell you what to do?

2:49:15

Yeah, so what we do is we built an agentic learning system that just hooks up to their existing systems of record, 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.

2:49:18

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?

2:49:35

For sure.

2:49:53

So we have a couple of core systems that are really good for us. So we do ServiceNow, Jira, Outlook, of course, can't forget Outlook, Salesforce, Zendesk are some of the main ones, ones that are kind of the first ones that we are working on top of.

2:49:54

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.

2:50:08

Yeah.

2:50:16

So I mean our specialty is like the larger the company, the better it is, the messier the process, the more of a challenge they have. So if you look at some of our customers that we went public with yesterday includes ASOS, Cushman, Wakefield, HubSpot.

2:50:17

So pretty big.

2:50:31

Yeah.

2:50:32

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. So how did you get those deals done?

2:50:33

Yeah, well, we've been around the block for about 10 years doing a lot of these things, so we had enough of a network and I think it's just a very compelling pitch.

2:50:43

Right.

2:50:52

Like I'm not telling you. Let me come in and it's going to take three to six, six months and we're going to 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. 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.

2:50:52

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, 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?

2:51:14

Yeah, so we need the smartest possible model to help us figure out what people are doing and what the process actually is. 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 it tends to be fine.

2:51:32

That makes sense. And how much did you raise? I want to hit the gong.

2:51:49

We raised $30 million.

2:51:52

Thank you.

2:51:57

Congratulations.

2:51:58

Just Sequoia or did you let anyone else get a slice?

2:52:00

So Sequoia let our a. We had eight VC and Astar who they let our seed already so we have continued support from them too.

2:52:05

Murderer's Row. Fantastic. Great lineup. Well, congratulations on the progress. Congratulations on exiting stealth and thanks for taking the time to come chat with us today. Yeah, great to be talk to you soon.

2:52:13

Thank you.

2:52:23

Have a good one. Let me tell you about Restream 1 livestream, 30 plus destinations. If you want to multi stream go to restream.com and we will continue our Lambda Lightning round with Ari from Runcivil who's in the restream waiting room. Let's bring Ari in. How are you doing?

2:52:24

Howdy.

2:52:41

Good to meet you.

2:52:42

Hey, good to meet you. Please introduce yourself and the company.

2:52:42

Yeah, happy to. All right, so I am a man on a mission where we're trying to automate hacker intuition. I guess I can start with a brief introduction to myself. So I was technically the first security hire at OpenAI back in 2019. I was a grad student at Harvard doing my machine learning PhD and I saw GPT2 come out and I was like, wow, this would have been really useful back when I was a miscreant teenager doing insane operations on the Internet. 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 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 GPT3 and on the Codex model. I also built our first monitoring system for when we started offering the API, as is the thing that customers were then using to make sure the customers were following our terms of service. 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. Black pill 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 we focus on the monitoring? 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 going to be able to play whack a mole. You kind of have to get offensive with it. So I started this company. I have very blessed to work with my co founder, Vlad Ionescu, who built the red team at Meta. And then I have a team of really strong engineers that we've 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.

2:52:47

Are you seeing more danger and risk from large scale state actors or the script kiddies who are just trying to wreak havoc. Or is it both? Because I feel like some of the problems with the new AI security threats, 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.

2:54:37

Yeah, I'd say it's actually kind of a combination of the two. I'd say like you have two types of threats and oftentimes it also depends on the type of organization that you are too. So for our customers that are smaller startups, like they're not really seeing any of this kind of stuff. But for our larger enterprises, we've been asked by a lot of them if they basically want to replace us with their bug bounty. They want to replace their bug bounty with us.

2:55:04

Oh, they want you to win all of the bug bounties. That's great.

2:55:25

Just don't make mistakes.

2:55:29

That's your immediate TAM and I'm sure much further. But talk to me about model distillation. There's been a lot of news about it's not as serious of a threat. It feels more like a business threat. But I've always been shocked by the stories about different open source companies where it feels like they trained on American Lab and that seems like something that the lab should be able to detect. Is that hard? Is that something you can help with?

2:55:30

Yeah. So that's not what we do, but it is something that I've dealt with previously and it is something that everybody does and everybody kind of knows about as sort of a bit of a dirty secret. But I'll also say that when you do distillation, the model that you get out of it is going to be like net less good than the model that you're distilling off of. That's just Information Theory 101. So. So 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.

2:55:58

Yeah, just actually breaking into the system.

2:56:22

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 how you sell the product right now because I understand like the opportunity at a high level. You know, basically every. All these companies are distributing intelligence that's hard to understand how it's going to be used. A lot of people are going to use it for things that they shouldn't. You want to stop that? But what is the specific pitch in this moment? In time, yeah.

2:56:24

I'd say, for one thing, focusing on 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 of the way that we've built our product is that if you have more attack surface, it's just much more interesting for the type of thing, 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. They have a lot of old code bases that go back 40 years. There's a lot of cursed things in their environments. Trying to get like, additional coding tools in is kind of tricky. And actually I have kind of an interesting hot take for you if you'll take it, please.

2:56:52

Love it.

2:57:26

Okay.

2:57:26

So obviously there's a lot of movement in security in terms of, like, the markets, especially when Anthropic dropped some of their news about some of their vulnerability discovery stuff. So I think a lot of people are concerned about whether or not are the language model labs just going to solve security. What I think is interesting is if code gets so much better in terms of security, the main question is, does that mean that hacking gets harder? My answer is no, because I think that speed is what's going to kill us. The space of these large possible attack vectors requires a lot more data than simply the code. If you look at the code, I like to think about it as you're looking at the code of, of, or looking at the bones of a dinosaur. You're going to find a lot of interesting things about structure, but you're going to miss a ton about things like muscles and whether or not they have feathers and also like, behavior and broader things like that, which are also very important for understanding the ecosystem. And that's true of code as well. And it's true of computers. It's easier to find bugs with the code. 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. 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 off 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 10 years. And we get like pretty nice payouts from that, which is always fun.

2:57:27

That's really cool. Talk to me about your take on the forward deployed engineer pattern model, trend boom, whatever you want to call it. Are you in favor of that? Are you employing that at this time?

2:58:51

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 startups, what we've learned is that people just want to solve the problem. Like the CTO comes to us and is like, hey, I have this deal blocked by SOC2, I really need to get, get a pen test. And we're like on it. Got you fam. And we get them, they're on their merry way. But with these enterprise companies, it's a lot more of a political process. Security in general is kind of, it's partly the people and 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 jobs are going to 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. 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.

2:59:06

I'm 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. Because everyone is going to be vibe coding. Like we are a 10 person team. We have like three systems and we're sort of security second. Maybe we're working on it.

2:59:54

I have a black pill for you then.

3:00:22

So tell me.

3:00:23

Yeah, I don't think so because people don't like paying for security.

3:00:24

Okay. Isn't there another way that you can make it so cheap or bake it in or partner with a lab where I'm vibe coding something and I, you know, get runcible installed or it's modeled into the system.

3:00:29

Yeah, the SoC2 example is relevant because that's somebody that's like, I have to

3:00:42

do this because I'm selling the software,

3:00:46

it's hurting my revenue.

3:00:48

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.

3:00:49

Think about it. We bought hundreds of thousands of dollars versus like camera equipment before we bought cameras to secure, you know.

3:00:58

Oh yeah.

3:01:07

And even when we were doing that, we're like, like,

3:01:09

I 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 bucks, 200 bucks for like a month long subscription, how much are you going to pay for like additional security on top of that? That's something that you're going to have to sell direct to that company. And there's not a lot of companies that really offer code security related stuff. So I think for companies that are making the bet in that space, they're focused a bit more on the ecosystem, which is. We're focusing a bit more on the overall ecosystem within an enterprise that has a ton of ancient code that is going to require a lot more in order to fix. And they also have just these enormous attack surfaces that need some help.

3:01:13

Yeah, yeah. That makes no sense. Well, how much did you actually raise? Tell me about the funding round. We want to ring the goal.

3:01:46

Oh yeah. So we raised 40 million, which we love.

3:01:52

Who came in?

3:01:57

Congratulations.

3:01:58

So Coastal led the round. We had participation from S32 conviction. We also had a bunch of angels as well. So Nikesh Arora, who I know is on the show.

3:02:00

Yeah.

3:02:10

Jeff Dean. Goodfellow.

3:02:12

Wow.

3:02:14

Ian Goodfellow too.

3:02:15

It was pretty good.

3:02:16

That's incredible. Congratulations.

3:02:16

That's the lineup.

3:02:18

Thank you so much for taking the time time to come. Break it down for us.

3:02:19

I can, I can visualize the Coachella.

3:02:21

Thank you for securing the American software ecosystem. We appreciate that as well. Get every bug bounty that is out there. You deserve it. We'll talk.

3:02:23

Great to meet you. Very, very bold. Cheers.

3:02:31

Thank you.

3:02:33

Goodbye. And we have our last guest of the show. We will leave the land of lightning round and bring Alex Conrad in to the TVP and Ultra dump from upstarts Me. How are you doing, Alex? Good to see you again.

3:02:33

Back.

3:02:47

Hey, I'm back. It's great to be virtually in the Ultra dome.

3:02:49

Yes. I love that poster behind you.

3:02:52

That's a tv.

3:02:55

Oh, is that a tv?

3:02:56

We're high tech here, John.

3:02:58

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. I don't know how have you defined your beat? I think everyone knows your beat from before with the Midas list, of course. But what's changed? What's remained the same?

3:03:00

It's been almost exactly a year since we launched and you guys had me on the show, which is awesome. As you know, year one startup, everything is crazy, but a lot of fun. We've launched a podcast. We have started doing some feature stories. We had one on William Hockey from column that was a lot, lot of fun a couple weeks ago.

3:03:21

That's right.

3:03:38

And just. And having a lot of fun, experimenting. You know, we haven't been to the Ultradome in person, but that's a year two stretch goal. Yes.

3:03:38

What about lists? I remember we talked about this and I was like, I know you can't do the Midas list that's left behind, but I feel like there's a big gap in the tech media landscape around lists. Market maps do well. People are split on them. We had a lot of fun with, with a Metis list of AI researchers. 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 something there

3:03:45

and you're the guy, you know, I'm sorry to say we don't have that list for you yet, but maybe that'll be a thing this year. We are trying to do really service oriented coverage for founders. I think the reality is founders are super busy, right. And so are builders at startups. And so our podcast is one commute length. It's a, you know, if you're not listening to TVPN yet, you're driving to the office. You can tune in for upstarts each week, you know, 35 minutes. And then similarly, we tried with our article this week, a illustration where this woman, Natalie Fratto, 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.

3:04:13

That's very cool.

3:04:56

Very cool.

3:04:57

I read about this company Giga today that I don't even know if I should call it a startup. They haven't raised any money, but they're.

3:04:58

It's a business.

3:05:07

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 want to cross over into the Tech ecosystem. How do you think about the broader ecosystem and knock on effects of the AI boom?

3:05:07

Well, startup can mean anything these days, right? Like I remember when we all started our career, a startup was venture backed. It was maybe less than seven years old. It wasn't hiring people for a billion

3:05:29

dollars, you know, wasn't worth a trillion dollars pre ipo.

3:05:38

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. I think similarly with these companies, in my mind, if they're trying to be really high growth, they're trying to move fast, and if they're serving a tech savvy audience, that's good enough to be a startup.

3:05:43

Yeah, I love it. What do you think about 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. Is that something?

3:06:00

Scoop athletes.

3:06:14

Scoop athletes. Is it 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?

3:06:15

There is a huge endorphin rush. Like if we're chasing endorphins and avoiding cortisol, I think like, you know, when you do publish that scoop, it can feel really good, you know, for a while, our biggest story at Upstarts was the last summer we wrote about a startup that had left OpenAI and they had raised a ton of money to do an RL reinforcement learning company. And when you looked at the spike in subscribers we got, that felt really good in a way. But you don't want to play that game all the time. I think it does end up being chasing a rush that is not sustainable. And so I think I will let Katie roof and those self described scoop athletes chase it for the love of the game. For me, it's only really relevant 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

3:06:28

than those last guys in terms of the horse race. Obviously you ran the Midas list for many, many years. Are there any venture capitalists who are underrated right now or do you think that there's any misconception 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. 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. What other stories are interesting in the venture capital landscape broadly?

3:07:15

Well, first, I think this year we're going to have to start a upstart spotted on the street VC thing. Because I spotted Keith Raboy at a 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 who are with Keith were like, who is this dude? So 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.

3:07:57

TMZ paparazzi.

3:08:20

Yeah, that's right. That's the coverage we need, right? We need the gossip coverage. VC again. But on a serious note, I mean, I love the domain experts, like the really nerdy guys who are not posting a lot on X, who are just really well regarded when I ask around, like, hey, who's really smart on GPUs? And so my advice to VCs usually is like, have a thing you're known for. If all you're known for is posting on Twitter X, that's probably not a defensible strategy in the long run.

3:08:22

Yeah, yeah.

3:08:51

People, what is? What advice 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?

3:08:52

I mean, at the end of the day, venture is a results business. I mean, 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 to notice. 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. Often journalists like me or at the big shops, 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. If you're not one of those first two or three VCs that the founder mentions as a reference, that's not great. So I'd start there with, are you top of mind for your biggest Winners.

3:09:05

Yeah.

3:09:47

So it's a mix of results plus the mic drop moment in the last 12 months, plus kind of founder brand. Is that a good way to think about it?

3:09:48

Well, yeah, I mean, the Midas list is data only, so the founder brand doesn't matter as much. But I think if you're feeling like, hey, I want those flowers.

3:09:59

It's data. Yeah, well, it's data. It's data only. But it's not just like blended IRR across every investor.

3:10:07

Still a crazy, crazy internal politics at every VC firm of like, 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.

3:10:13

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 startup, Clay. And you know, she, she will have her deals that she sourced and she was involved in and will she be in the history in years? You know, we don't know. And I think, you know, still, 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, for Midas, that can be tough because like five people at Sequoia claim each, you know, big deal.

3:10:25

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, you brought it in and you're going to be on the board. You get 80%, but I work the deal with, with you, So I get 20% and we all sign and then

3:10:52

we know who got the system of record.

3:11:08

A system of record? Erp, basically. But I don't know if that's employed at every VC firm. Has there ever been in your memory 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 out and they're like, wait, they own 20% of this company? This is crazy.

3:11:10

Yeah, I mean, a firm that was historically under the radar was Sutter Hill.

3:11:45

Oh, yeah.

3:11:50

So Michael Spicer, when Snowflake went public, he got tons of credit, deservedly so. But they had been totally under the radar and so the. Those more incubation type ones, those are really interesting. And I think otherwise, the thing to know with the S1 is it's usually a big dog at the firm whose name is attached, but that doesn't mean they necessarily were the person who did the deal. What happened early 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 know any of this trivia. And so that was terrifying for me. Over time, 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 don't wish that data on anybody's head.

3:11:51

That's hilarious. Do you view venture capital and the startup ecosystem as like, a buyer's market or a seller's market? 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?

3:12:33

What an easy question, right? You're saving all the easy ones for last. I think we continue to be in that have and have not market where I think you see crazy valuations for companies that have traction. And then I hear from so many startups that are still like, how do we meet these guys? How do we get anyone to pay attention to us? And it's humbling for me that even though I'm saying, hey, we want to cover startups 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.

3:12:53

Yeah. Will you ever write a book?

3:13:30

About what?

3:13:33

About you guys?

3:13:34

No, about your experience. I mean, this is a common path. I feel like sometimes you find a company or team that and the scoop grows into a book. Sometimes there's a composite profile of an industry or career. I don't know. It sounds like. No, it sounds like you have no appetite for book at all. But is that.

3:13:35

Well, I think I just don't have the bandwidth. I mean, like, you guys, I think I'm in the arena every day putting points on the board. And I think books seem like a beautiful stretch goal if upstarts really scales. But I wanted to write books in the past, maybe, but I think you need to really have the idea. You can't just reverse engineer it. It's like saying, I want to be a founder and not knowing what company.

3:13:55

Yeah. You have to have a book in you at the time and then it just has to.

3:14:16

And you have to love the topic. Right. Like, how boring would it be to write the world's 10th book about Nvidia? Like, do we need that? I don't think so.

3:14:20

I don't know.

3:14:27

I don't know.

3:14:29

Jordy's like, you're going to do it.

3:14:30

Sounds good.

3:14:32

I mean, I would read an entire book just about the leather jacket potential

3:14:33

or the leather jacket leather jackets.

3:14:39

Or just an entire book just around the history of dlss. Just deep learning. Super sampling.

3:14:41

Well, you know what? I think you guys are speaking to that I do think about a lot. Like, information is so crazy right now. You guys have these amazing guests on every day. You're grinding and so many people are out there putting out good information. Is there room for that person who just kind of disappears, Disappears for a long time on a crazy project and comes back with, like, a big fish?

3:14:46

Yeah, yeah, yeah. No, 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 tv? It just would never be on tv. But it's turned into a TV show. Multiple episodes every week, Fantastically successful. They build a whole business. They have a studio and team, and 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. 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 300k. And they're like, but our business is making a million dollars now. And they'd say, okay, it doesn't work. And they'd come back and be like, you know what? We're ready. We got a million and a half dollars for. And they're like, but our business is doing 3 million. Like, we can't step away. And so this tug of war is always happening. 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. All the. All the other.

3:15:08

Yeah, I mean, I've just come back to this as, like, legacy media brands are the best place to go, you know, fishing. Because they will say, yes, you can. We're going to pay you a salary, and you're going to go work on the story.

3:16:09

Yeah.

3:16:22

And you might not be able to show any real results for a longer period of time. Doesn't work that well for a substack model where you got to show value.

3:16:22

Yeah, yeah, yeah, that's totally true.

3:16:31

I mean, every week I feel like I got to win, win the week. You know, I feel like I'm proving myself to my audience every single week and day. I will say we are doing these quarterly profiles now. Hockey was the first one with column. I think we have a really cool one cooking for the second quarter. And the dream is that maybe we put four of those in a little booklet.

3:16:33

That'd be cool.

3:16:53

That can be on a coffee table. And maybe we start to get into print and have fun that way. But it's baby steps.

3:16:53

Yeah, that makes a lot of sense. Do you have a media critique take on the future of investigative journalism where that might exist, what the funding model for that is? Because it feels harder than ever to have a journalist go and spend a year on something that may or may not work out. Yeah.

3:16:59

I think the short answer is that I agree with Jordi in a lot of ways that you do need the sort of big shops that can still weather the storm. For someone 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 signals and doubles and then you look for the home run. So I do think a team is important there. But one thing I would challenge people to think about is, is there a way to fund a project for a year, whether it's Patreon or Substack or something like that, where you do a year or even a multi year subscription where you say, we're going to give you money up front, do the best, craziest thing you can do in that time, and it can be as few as one thing, but then we'll be happy. Because I think the challenge, as you said with Substack, is substack sends you the numbers. You can see them going up and down. You never want to 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.

3:17:18

Yeah, same stuff. Well, thank you so much for taking.

3:18:18

Let's hit the gong for a year. Is it actually the year, the first year. Did you hit the anniversary yet or is it.

3:18:21

We're a week away.

3:18:27

Can we hit the gong. Anyway, we're going to hit it.

3:18:28

Thank you so much.

3:18:34

Great to catch up, Alex.

3:18:34

Great to catch up and we will talk soon.

3:18:35

Give our best to the team.

3:18:37

Goodbye.

3:18:38

Cheers.

3:18:38

All right, see you guys soon.

3:18:39

Here's some advice. Don't buy AirPods. You need the Sony WH1000XM5 WH CH720N WS1000XM5CH520 get those. Just pick those up. That's what Dylan.

3:18:40

I can't believe how mainstream this post is. Whoa.

3:18:59

I didn't realize 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 xm4s, which I think is the, like the last three digits, 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 XM4s, but rough with the naming schemes. Anyway, thank you for watching Leave us five stars on Apple Podcasts and Spotify. It's been an honor and we will see you tomorrow. Goodbye.

3:19:02

Boom.

3:19:38