David Tisch, Mike Vernal, Edward Mehr, Will Brown, Stocks Mogged as Trade War Escalates, R.I.P. Pope Francis, How Prior Beliefs Distort Perceptions, Why Robots Still Can't Make Nikes, Robots Join Chinese Half-Marathon

You're watching TVPN. Today is Monday, April 21, 2025. We are live from the temple of technology, the fortress of finance, the capital of capital, the Institute of Iron, the hall of hypertrophy. We wanted to kick it off with a post from my good friend Sahil Bloom. He's been on the show before as we highlighted his book. But this one hit hard, especially today. He says, here's the truth. If you're half in, you're. You're actually all out. Even 90% in gets you nowhere. There's something magical in the last little bit simply because so few are willing to do it. That's where you unlock new levels to the game. And it does not take talent, just courage.

Well, you're certainly being courageous today, John.

Thank you.

Congratulations.

Yeah. Big news. I'm all in on tbpn. I am entirely in. I'm completely in TVPN full time. The announcement went out today. Fantastic experience as an entrepreneur in residence at Founders Fund. It was a great two year, two year run. Incredible run. Fantastic team over there. They're really going to be suffering. They're just kicking off a new $4 billion fund. It's going to be rough, but you know, I think they'll be. I think they'll be okay.

Management fees on a $4 billion fund should maybe be able to find a replacement.

EIR for sure, for sure. But honestly, I mean, fantastic team over there.

Founder mode.

Founder mode. Super close with everyone. And of course we have Delian as a regular on the show already. Trey is coming back. He's going to be one of our first in person guests soon. We're getting Scott Nolan talking about general matter soon. So obviously the teal bucks will still be flowing. We're not getting paid directly by Founders Fund anymore, but we are getting paid by Ramp, our sponsor and one of a major founder fund position. That's right. So it's all one hand washes the other. Over here in tech media, remember we are 100% corporate backed. I'll never ask you for a dime. And yeah. So if you're a company, you want to sponsor us, hit us up because. That's right, we love our sponsors. Anyway, speaking of sponsors, the market's in turmoil. If you're trying to get on the action, head over to public.com investing. For those who take it seriously, they have multi asset investing industry leading yields and they're trusted by millions. The big news today, stock market is mogged. Absolutely mogged. As the trade war escalates, global markets tumbled amid renewed US China trade tensions and an unprecedented clash between President Trump and the Federal Reserve. Now, there's a rumor that President Trump threatened further tariffs on China and even raised the possibility of firing Fed Chair Jerome Powell. Alarming markets.

I'm sure you have to have a very long moment of silence for, for Jerome if that were to happen.

Apparently the rumor going around in the media is that the administration reportedly explored options to fire Powell after Trump lambasted the Fed, spurring fears about Fed independence. And so, yeah, the Fed is supposed to be independent.

We don't comment on politics. But it really is funny to come out with this tariff strategy and then be like, looking for somebody to fire who's important and like, fire the guy who's like, what did I do?

Yep. And so the Fed has the ability to lower interest rates when they're doing, I think, new auctions, but they aren't always doing new auctions. We talked about this with a buddy of ours who said that the Fed actually has not that much control over the long end of the yield curve because they try and do different things to, yeah, the 10 years, like the really important signal.

That's the one that you can try to finesse it.

You can try and finesse it.

It's going to do its thing.

It's going to kind of do its. And that's the, that's the economic indicator that a lot of people have been tracking. In fact, some Trump appointees had said that lowering the 10 year was a goal for this administration. And the opposite happened. The 10 year rose and that means, you know, potentially higher, higher, higher mortgage rates, less affordability. Maybe house prices come down because interest rates go up. Sometimes that happens, but in general it can be, it can lead to a lot of turmoil economically. And it's not where it wasn't the stated position of the, of the, of the administration. And so now they're maybe looking for someone new to step in to take over and potentially work towards lowering that interest rate. But there's only so much you can do. It is a free market.

S&P 500 and the Dow fell sharply with US stocks down over 10% year to date. Moment of silence.

Moment of silence.

This moment of silence is brought to you by ramp. Go to ramp.com tech shares led those losses after companies like Nvidia warning export restrictions to China would, quote, unquote, chisel billions off their sales. We talked about this last week.

The Nasdaq today alone is down 3.5%. It's a big, I mean, it's not 5% like it was a couple weeks ago, but it's not great. They're calling it the Sell America trade that picked back up on Monday. We've been saying this bull market for.

Short selling, bull market for coining, but I would prefer people don't create a coinage around Sell America.

No, no, no.

I don't live here and I like it, but it was the trade. Over the last few weeks, there's been a flight to safety. Gold has been on a record run which is accelerate, accelerated amid the uncertainty. People are just looking to avoid volatility. Bitcoin has also.

This is the interesting thing you want.

To talk about decoupling?

Yeah. I mean it's been like a back and forth narrative because Tyler Winklevoss posted hey, for the first time, bitcoin's not trading in lockstep with the market. So the market sold off and bitcoin didn't sell off as much. Normally they're highly, highly correlated, which is something that was theorized not to be the case if, if bitcoin really does become this, this asset of last reserve, this store value, this, this digital gold. But now after looking at the market from. And of course he posted that and immediately bitcoin moved in lockstep with the the. Which is kind of just like it feels like if you post something like very conviction led like that, you're just gonna get destroyed by whatever market does, I think.

Who's the Barshield sports guy? Dave Portnoy. Portnoy was posting about bitcoin. A lot of people decoupling. A lot of people said, oh, could be, you know, sort of bad signal that Dave Portnoy is bullish. But Bitcoin's down 7% year to date, but today it is up almost 2%.

Interesting.

Which is pretty meaningful.

You wouldn't expect that given how much the NASD is sold off. Typically they move in lockstep. So it'll be interesting to keep to follow that story. We're going to do a whole crypto day on tvpn, bring on a bunch of founders and investors and just general crypto folks and try and get to the bottom of like, what is cryptocurrency? That's the question I want to answer. Like, I know it has something to do with like numbers and money, but.

You'Ve never seen it.

I've never seen it. So I want to bring on some experts. We're going to bring on some people that run public companies, some people that are billionaires, multibillionaires, and we'll ask them, like, what is this whole crypto thing about? And that should be very informative.

Yeah. On a more serious note, interested to see where crypto goes from here.

Right.

There's been a cool down in the meme coin market.

Yep. The pump fund chaos seems to have subsided.

Yeah, we've seen that twice now. We saw this with OpenSea, you know, was doing, I forget, you know, hundreds of millions of net income a year. I think at its peak, Pump Fun was doing the same thing. Opensea's volume, you know, fell off a cliff, unfortunately. We'll see what happens.

They were in my YC batch. We should get on the show. I'd love to know. Kind of like, they have a lot of money, they have a lot of talent, they're. They're clearly planning their next act. I wonder what that would be. I think that, you know, a lot of people have written them off, but that might be wrong. Maybe they'll come back and do something else. There's, there's, there's clearly opportunity in crypto. If you have a lot of money and a lot of, you know, hardcore developers to build something, you build something.

But there's a possibility that they need to completely reinvent themselves. I agree, but that can also be a trap sometimes. The second that, you know, company reinvents themselves, the thing that they were originally working on rips again. So who knows what happens with NFTs.

Yeah, I mean, NFT specifically were always one of those things where I was willing to buy the narrative of, like, this is a digital art house, this could be the next Sotheby's. But their valuation was like 10 times what Sotheby's was or something like that very quickly. And so the idea of just being like a museum, like, I think at the height like NFTs were, the volume was higher than the fine art market. Well, hundreds of years of experience.

So two reasons for that. One, same thing happens in the art world where if you discover an artist and you buy up their works before they get into Sotheby's and these big auctions and galleries, et cetera, you can buy incredible pieces of art for thousands, you know, single digit thousands. And then the second, the reason for the volume is that it's very hard to have a, you know, $200,000 piece of art change hands six times in a day. But that was happening with Cryptopunks. That was happening with, you know, Bored apes and many, many, many, many other projects. So.

Oh, well, well, let's move on to the legacy of Pope Francis, he passed away, I believe this morning. In fact, it was so sudden that the Wall Street Journal, the print edition, does not mention his passing away. It mentions that Yesterday, thousands in St. Peter's Square on Sunday were treated to a surprise popemobile trip, drawing cheers and applause as Pope Francis continues his recovery from double pneumonia. He also met with President Vice President J.D. vance. And this was getting like, it's, it's pretty. I mean, I don't know that this is the case, but it feels like, like they did this because he knew that he was maybe not going to make it very much longer. And so it was like his last opportunity to go and see everyone. And it's just, it's just brave. I don't know, it's. It's beautiful. Anyway, the Wall Street Journal hasn't has an obituary, of course, and I think we should read through a little bit of it and give some background on who this man was. So he was elected the 2266th in 2013, and it marked a series of firsts. He was the first Jesuit pope and as an Argentine, the first from outside Europe. His legacy as Pope Francis, who died on Easter Monday at age 88, was disappointing. Even on the priorities he set for his papacy. Pope Francis was known for urging concern for the poor. In the best Christian tradition, he called for a clergy of shepherds who have the smell of their sheep. Interesting metaphor, I.e. priests and nuns who shared the suffering of their neighbors. He made support for the weakest among us, the rhetorical centerpiece of his papacy. He brought a public informality and openness to the Vatican. Alas, Pope Francis believed ideologies that kept that keep the poor in poverty. One of those earthly dogmas is radical environmentalism, which isn't about keeping the earth clean for human beings, but keeping the earth itself and treating man as the enemy. Interesting. So the Wall Street Journal is kind of coming for him a little bit on this, saying he shouldn't have been as much of an environmentalist as he was, which is interesting how much the vibe has shifted and we'll see where this goes the next with the next pope. In one of his writings as pope, he cited air conditioning as an example of harmful habits of consumption that will lead to mankind's self destruction. He didn't seem to realize that escaping poverty requires greater energy consumption, which is something we've, we've touched on with a lot of the founders on the show. Obviously Augustus Dirico is, is religious, but then also says that, you know, it is, it is our job as stewards to terraform and make the make, make the planet healthier.

There's a lot of evidence that if you enable humans to live in cooler climates, even just indoors, that can, you know, be quite positive, increase prosperity and also health. Yeah, yeah.

His papacy was marked by anti Americanism and not merely against Donald Trump. He seemed to believe that Latin America is poor because the United States is rich. That's a recipe for stagnation and despair, because the real reasons so many in Latin America languish in poverty are at home. Lack of rule of law, business, government, collusion, protectionism, and other barriers to human flourishing. Some attribute his hostility of free markets to his Latin American background. Born in Buenos Aires, Pope Francis at a young age was made the provincial, the provincial superior for the Jesuit order in Argentina during the time of the military junta. This was a hard line to walk, and some of some of his order accused him of unfairly being too friendly with the regime. Argentina for much of his life was dominated by Peronism, a brand of left wing populism named for Argentine President Juan Peron. When he looked around, he saw corruption and the rich doing very well as their fellow countrymen languished in poverty. Perhaps it was undeniable that he confused Argentinian Argentina's corporatism with capitalism, which is a common mistake. It makes. It makes a lot of sense. Less forgivable was his deal with Beijing as the Pope that gave the Communist Party influence in the choice of bishops. Conditions for Catholics in China have worsened. Though the Vatican has renewed the kowtow several times, the Vatican has stayed silent on the plight of publisher Jimmy Lai, who is China's best known imprisoned Catholic. Unlike his two immediate predecessors, John Paul II and Benedict, Pope Francis was from the progressive wing of his church. He punished traditionalist bishops who disagreed with his direction, and he has populated the cardinal ranks with fellow progressives. The irony is that progressivism is most popular in places like Europe, where the. The Sunday pews are empty. The church is thriving in Africa, among younger, younger Orthodox Catholics in the west and among younger Orthodox Catholics in the west looking for meaning in life beyond material consumption. The cardinal who will choose the Pope's successor will determine which future they want for the church and the world's 1.3 billion Catholics. Fascinating. Yeah. Interesting to see the Wall Street Journal kind of wrestle with his legacy in, in a tasteful but critical way.

One thing that he did is he got the popemobile he did to go electric.

Wait, really? That's a electric G wagon.

Electric G wagon. So it's no way the car that he was in yesterday for, I had no idea.

Because there is a new. There is a new G wagon that's electric, but they, they electrocute.

They're using the G580 base.

Really?

Which makes a lot of sense if you're in crowds. Yeah, let's not, you know, emit.

Let's flex on everyone with our G Wagons. Is that what you're saying?

That wasn't what I was saying, but.

Yeah, being elected, like a lot of sense.

But anyways, there were a lot of memes because JD Yeah. Saw him right before, had a visit yesterday.

Again, it makes sense. If the Pope is sick, you want to go visit him before he's sick. Anyone saying anything else is, is being a little silly, in my opinion.

Put on the tinfoil hat.

Put on the tinfoil hat. Anyway, there was an interesting article, an op ed by Roland Fryer in the Wall Street Journal that I want to go through. The economics of polarization. Are you familiar with Roland Fryer? Fascinating. So he's an economics professor at Harvard. Very outspoken, very. He's been a little controversial. There's like a, there's a back and forth. He was kind of attacked, but he came up with a bunch of behavioral economics for kind of foundational research. One of the most controversial things was that you should pay kids to do their homework. So basically, like create an economy for children. Yeah, but, but he, but he studied it and found that it was like one of the greatest motivators was just paying kids to, to, to do work.

Makes so much sense. Why would you not want to drill into a child's head that if you work hard, you will be rewarded?

Yeah, totally.

Because that's sort of the lesson of life.

Yeah.

Yeah. No, 100%.

100%. This started, you know, mowing lawns, picking weeds around.

Yeah. I was listening to Palmer Lucky on, on Tetragrammaton with Rick Rubin yesterday, and he was saying that he, he had, he, he built like the largest collection of VR headsets. And then he also built a massive gaming rig with six monitors and top tier computer hardware. And then that's what inspired him to go into VR and start Oculus. And I was just. And he was like, yeah, and I paid for all this, like doing like little OD jobs and like side hustles as like a kid. And I was like, yeah, but I'm running the math. And I'm like, if you're spending, if you're spending like $40,000, like you're pretty good at those side hustles. Palmer, like, like you were working hard. Like, it's very different.

Like white hat hacking.

Totally like that. I don't even know if it's that. I think I just had, like, true grind size for, like, not just mowing lawns, but, like, mowing a lot of lawns. Because most kids, you know, if they have like a side job, it's like 200 bucks a month or something. It's not. It's not enough to get you to like, a $20,000 investment in like, a gaming PC very quickly. Like, for me, it was mostly like, make some money and then go buy, like, a single video game for 50 bucks.

Some candy.

Some candy, exactly. This is the usual stuff, but seemed like Palmer really got the economic flywheel going early. But it makes sense because, like, he's very entrepreneurial. It makes sense that he'd be making a lot of money anyway. Roland Fryer just published some research on the economics of polarization that I think is fascinating. There's this big question about, you know, America seems more polarized than ever. What is driving that? And the subhead here is people tend to interpret ambiguous information as confirming whatever they believed to begin with. And so we'll read some of this article and go through it. But it's interesting to see, like, where else will this take place and where else can this potentially be exploited or mitigated, depending on your goals? I suppose. So nothing throws America's divisions into stark relief quite like having Donald Trump in the White House. But Mr. Trump is an effective. But Mr. Trump is an effect of polarization as much as a cause. We've been growing apart politically for decades. And so he gives some data to kind of back up this claim that the political division in America is not driven necessarily by Trump. Trump is like a product of it, so he says, and a catalyst in.

Many ways, because he's totally extreme.

Yes. Yes, totally. And so nowadays, 85% of Democrats, but only 30% of Republicans think the government should ensure that everyone has health care. So health care used to be a little bit more bipartisan, that the gap has grown 24 points during the last two decades. Then there's some other stats here. The government has too much power. When they poll people on that, 73% of Republicans say, yes, the government has too much power. Only 31% of Democrats say the government has too much power. And it's a 51 point shift. In fact, during the George W. Bush administration, Democrats were more likely to say that the government has too much power. And then the split on whether abortion should be all teams as wide. 30 points.

Yep. The other team has too much power.

Yep. Yep.

Which I agree with.

Yeah, yeah. 100% of people agree that they don't have enough power, I think. And then on global warming, the split is 33 points. On abortion, it's 30 points. And so lawmakers have also become more polarized over the last 50 years, and there's even polarization over why this happened. Some data suggests Republican politicians pulled to the right, but conservative notes that the. But conservatives note that the government has moved sharply to the left. And so 52% of Americans said that Democrats have moved too far left, while 35% said the Republicans had moved too far right. And so everyone is saying, oh, the Overton window is shifting. I haven't changed. Everyone else has changed. It's a very common refrain. Even seemingly nonpartisan measures such as the Consumer Sentiment Index reveal polarization. Republicans had more positive views than Democrats about their economic situation during the first Trump term. And then this flipped in 2021. So they're like, oh, yeah, like, I'm doing pretty well economically. Like, I got a job. Inflation's not too bad. And then in 2021, they're like. They're like, oh, like, it's terrible. Of course, like, Covid's in there. There was really inflation, there was stimulus. All sorts of stuff happened. But of course, people are more likely to report that, like, you know, I'm doing better if my guys in the big. In the big house, in the White House. How can two people observe the same information and come away with starkly different conclusions? And why do views on factual questions such as the cause of global warming or the strength of the economy break down social so neatly on ideological lines? And so Roland Fryer tells this anecdote about his wife and how this, like, inspired him to run this test, essentially. So he says his wife is a great driver, but she blows the horn way too much for his taste, which is hilarious. So any slight perceived or real, and you get a loud honk if she's behind the wheel. One morning when we were commuting, a car pulled past her on the highway and veered just slightly our way so that its tires drifted into our lane. She honked. I tried to reason with her. His driving was within the usual margin of error. What an economist thing to say. This is. This is totally within one standard deviation of driving abilities. Like, you shouldn't. You shouldn't be honking. Yeah.

Can be a lot.

Yeah.

Certain circumstances.

So her response, she says, I've kept myself from many, many accidents by being a proactive honker. And so they observed. He says, we observe the same incident, but we drew opposite conclusions and each became more convinced we'd been right all along. Is this consistent with rational thought? And could it explain why Americans have become so polarized? As soon as she dropped me off on campus, I ran to my office to tell a fellow economist this anomaly I had observed. Was my wife irrational? Was I? Or did we need to think about inference and decision making a bit differently? I first confided in Matthew Jackson, who specializes in social networks. He seemed as perplexed as I was because he knows my wife. He offered up several interpretations that would make her seem more rational. Finally, he relented, and it became one of the guiding examples for us to think differently about how humans process information when there is uncertainty. In the simplest version of the model they deployed, imagine that the truth is either A or B. Climate change either is or is not caused by human activity. There's no gray area in between. The death penalty either deters crime or it doesn't. No one really knows the truth. But we start with a prior belief about how plausible A or B seem. Each person observes a series of signals, information that suggests the truth might be A or B. Some signals are ambiguous and come off as AB rather than A or B. If you were fully rational, able to set aside prior beliefs, you'd store the information in sequence. A, B, ab, A, A, B, A, A, B, B. Like that. So, so when there's a confusing signal, you just think it's both. But. And if you add that up, that sequence that he describes, it's three points for A, three points for B, and three ambiguous signals. Like the signal doesn't, doesn't lean one way or the other. But if you tend to align unclear evidence with your previous expectation, you would come away thinking your original instincts were right because you'd, you'd count all the AB signals as A. If you're on, like team A originally, and so now you think the evidence falls on your side by a two to one margin, so you would count up six A's, you would ignore the three B's in the abs, and you would have three B's. So you'd say, hey, six to three. I'm seeing a pattern here. Further observations of the world entrench this view rather than correcting it, because future ambiguous, ambiguous signals will have the same skew. Our, our main mathematical result demonstrates that if a large enough share of experiences are open to interpretation, maybe the guy who drifts into your lane until you honk is an example of the horn saving lives. Or maybe you're an average. Average. He's an average driver who never posed a threat. Then two agents who have differing prior beliefs, who see the exact same sequence of events can often end up polarized, with one person being absolutely sure of A and the other of B. And so they. They ran an experiment online with 600 subjects modeled on a 1979 paper by Charles G. Lord. First present precipitate precipitants were presented with questions about their beliefs on climate change and the death penalty. They read a series of summaries of research about each topic. After each summary, we asked participants if they thought the summary provided evidence for or against the topic on a 16 point scale. After all the summaries were presented, we repeated the initial questions about their belief on the topic. There was a very significant correlation between a subject's prior belief and his interpretation of the evidence. More than half of our sample exited our experiment with more extreme beliefs than at the start, even though the evidence presented to them was neutral.

That is wild.

The discouraging implication is that in a world where information is plentiful, people will become more divided, not less. That is true even if they all see the same information, which they don't, because they can choose between Fox News or msnbc. And it's true, even if our widening divisions prove deeply unhealthy for our country. And that's why you got to turn off Fox News, you got to turn off msnbc, and you got to only watch tvpn. That's the only option. But there's so much to talk about here.

And we promise to validate your preexisting beliefs with data.

Absolutely. Absolutely. I thought this was interesting because this goes back to the debate around Facebook. So when there was increasing political polarization, it was kind of blamed on Facebook for funneling people into extreme echo chamber. Right. They called them. What were they called? I forget. I forget the name. There was like some buzzword for this. For this. Like you go down like a rabbit hole on YouTube and you start with like.

This was pre algo feeds even in the way they are today.

Yeah.

Of course there were algorithms that would decide what content serve you, but it wasn't. It was still heavily based on the social graph.

Is the term filter bubble. Filter bubble, yeah. And so you would search for, like, you would start a search like, you know, what to do after college, how do I get a job? And then you would land on, you know, a Jordan Peterson video. That was just, you know, about how to live your life, make your bed. Right. But then Jordan Peterson also had conservative views, and so you would go from the general life advice into his conservative views, but. And then he's not really that extreme. But then there'd be someone else who is recommended, who is like, just political. Less life advice and a little bit more extreme, and then a little bit more extreme.

Your bed with an American flag.

And so people would go down these filter bubbles, and then pretty soon everything they would be seeing was there. Zuck made the argument that we haven't seen political polarization in other countries where Facebook is very active. And so he was saying maybe this is more of a reflection on America than Facebook as a product because the usage data is really high. I think his example was Malaysia or Indonesia or something, and. And their society wasn't as polarized as America. But I think it's interesting that, that, that. That it's merely. It's potentially merely the. The explosion of information that creates division and. And if you. If you're just exposed to. If you're literally living in a cave, you're less partisan. Like, it's kind of. It's kind of interesting. Yeah. So, yeah, I mean, I don't really know where. Where all this goes. Like, does it exonerate Facebook and the social media platforms entirely? Clearly, there are some platforms that are, like, extremely skewed and biased. Like, that's kind of like by design almost, but it's, It's. It's interesting to dig into at the very least. Like, you as an individual, need to understand if you're interpreting those AB signals, those neutral. Those neutral evidence points adding to your side.

I think it also applies to the last few weeks with the tariffs.

Right.

People are like, oh, Treasuries are selling off. Oh, gold is. Gold is ripping. Bitcoin is ripping. And everybody's seeing sort of the same set of information, but applying different beliefs to it. Somebody might say, gold is ripping. People are basically shorting the dollar. They short the dollar. They're short America. So they're buying gold. Yet every financial crisis, for the most part, people tend to buy gold because it's seen as, you know, more stable and predictable and a true store of value.

Yeah.

Same thing with. With treasury selling off. It's like, okay, if you're in a trade war and there's this complex geopolitical, you know, dynamic and T bill yields are ripping because foreign governments are selling them. Well, there. There could be a lot of other reasons other than purely just sell America, America's over. The dollar's done that kind of thing. And so, yeah, it's, it's hard to.

Yeah, it's hard to balance all the different signals. But if you're looking to get in on the action with some gold, why don't you buy a gold watch on Bezel, go get dcom, download the app, pick up a Rolex day date.

A lot of people think, oh, I should buy gold. Yeah, I'm going to go get some gold bars.

Yeah, why not Gold.

Something you can.

Patek Philippe.

That's right.

Or gold. Yeah, buy a gold watch, go to Bezel. Your Bezel concierge is available. And now to source any watch on the planet. Seriously, any watch.

Not financial advice.

Not financial advice. But speaking of things that are somewhat related to fashion, robots are having trouble making Nike sneakers. This is an interesting story in the context of like reindustrialization. Trey Stevens had a piece on pirate wires, all about the importance of robotics and automation in the reindustrialization story that we should go through or talk to him about. But I thought this was an interesting discussion of like, okay, if the tariffs are here to stay and we are trying to boost US Manufacturing, what, what can we learn from Nike's move to Asia historically? And so Trump is betting that the terror, the threat of tariffs on low cost countries in Asia will pressure American companies to bring back manufacturing and jobs to the United states. But high U.S. labor costs mean companies would have to find a way to replace human workers with machines. For some industries, that's proved surprisingly difficult. Indeed, a years long effort by Nike to shift part of its manufacturing from China, Indonesia and Vietnam to North America illustrates how tough it is for US Brands to wean themselves off of the flexible, low cost contract manufacturers that use armies of laborers to churn out an array of products for consumers. Yeah, I mean, one of the interesting things about the push in Foxconn, where they bring in a million migrant workers, is that you can't really do that with robots like the Capex. There's no, there's no fungible flow of robotics yet that you could say, hey.

You just imagine a world in the future where you bring in 100,000 on demand robots for a, you know, a sprint, a seasonal sprint. But that world also feels pretty far 15 years away. It's hard to imagine it happening. Yeah, three years or on the timeline that the tariffs are on. Yeah, the most pressing issue.

Yeah, yeah, yeah. It's, it's not something that a company can think like, okay, we're like these Tariffs are going to affect our Q3 results. Like how do we, how do we automate everything? So this, this actually started a decade ago and it feels like we're still a few decades out from the robotics automation of footwear manufacturing. But back in 2015, Nike poured millions of dollars into an ambitious effort to partly automate what has always been a highly labor intensive industry that's making shoes. At the time, rising labor costs in China and advances in manufacturing techniques such as 3D printing opened the possibility of finding a new way to make shoes that would rely on fewer workers. Have you, have you ever seen Zellerfeld? It's a 3D printed shoe company. We should have. The CEO, and I've met him at a, at a party once, seemed like a good. And I think the company is doing very well. But they, but they've been obviously like small because they're startup. But it'll be interesting to see about where, where he thinks that will go.

Yeah, but this is interesting because even as far back as 2015, Nike One was trying to think about bringing production back to North America, localizing it, and it hasn't exactly panned out.

Yeah, yeah.

Which puts them in a tough position. Right. Because they're like, hey, we're getting tariff. And we've also been made a good faith effort to do this and it didn't pan out. Now here we are stuck between a rock and a hard place.

Yeah. So the, the shoe. Nike partnered with this company called Flex, an American manufacturer that helped Apple set up a complex factory in Texas to make Mac Pros. That's the one that. There was that picture of Donald Trump cutting the ribbon. The goal was to make tens of millions of Nike sneakers at a new high tech manufacturing site in Guadalajara, Mexico. By 2023, the plant would still include thousands of workers, but far fewer than are needed in Asia to make the same number of sneakers. If successful, the project could be a model for production in the United States, according to some involved in the effort. Nike's competitors also sensed an opportunity to rethink manufacturing. Built around massive Asian factories where armies of cheap, skilled laborers stitch fabrics and glue soles to shoes on hand. It feels less modern, more like a Ford Model T production line combined with a Middle Ages cobbler's bench, said Kevin Haley, the executive vice president of innovation at clothing maker Under Armour. In 2015, he pledged to use automation to make shoes in Baltimore in a project he called Project Glory. Love it. Good name, but you know, it's rough. Adidas also got in the action. They launched Speed factories in Atlanta and Germany with high tech manufacturing that quickly spit out shoes, heralding a new era in fashion footwear creation. They want to move out of China and Vietnam. They have the technology to do that differently, said Mike Dennison, Flex's then president. In 2016, Nike's effort was the boldest. The company aimed for large scale automated production in under a decade, which it said would save on labor costs and allow it to deliver new models of shoes to Americans faster. Tom Fletcher, who oversaw the project for Flex, came into the effort feeling confident. Having just built a highly complex Mac Pro factory for Apple in Austin, Texas, you would think that making shoes would be easier than making Mac Pros. And yet they ran into some trouble. At the time, Apple had been looking to bring some manufacturing home. Flex pushed to rejigger production lines and use automation, trying to find as many ways as possible to minimize human interaction. That experience came in handy. Jordy?

No, it's just interesting. Flex has not exactly performed despite, despite the boost in interest in localized manufacturing.

Are you looking at the stock?

Yeah, they're, they're, they're.

How big is the company?

Very large company already that $30 billion. I'm guessing one of 30 billion of revenue. I'm guessing one of the reasons for this is I bet their supply chain. Yep, they're, they're, they've still got, despite, you know, making efforts to help onshore. They have quite a bit of exposure to Asia.

Everyone does these days. If you dig deep enough, you're going to find some, some tariff goods in your supply chain, no matter who you are. So the machines were supposed to build the upper part of the shoe, knit fabric and add logos and glue the sole. I talked to somebody who was doing some outsourcing of the upper in China, went over there while the tariffs were there. Very chaotic and yeah, just like a very, a very rough go, big culture clash moment. And so these efforts ran into trouble. The robots struggled to handle the soft, squishy and stretchy parts that are integral to shoe making. Shoe fabrics also expand and contract depending on the temperature. While in shoemaking, no two soles are exactly alike. So yeah, I mean, if you consider like the benefit of automation on a car production line is that like some of these parts are too heavy for people to lift. So you have to use a machine and then it's the same, it's the same stamped, you know, metal every single time and it's dangerous and it's also just the exact same way. And then there's also welding going on and Shoes are much smaller and more fine grained and then obviously more malleable.

Yeah. Everything about making electronics is about perfect precision. Right. It's making sure that, you know, a component has a specific spot within a device and you need to make sure that it goes there.

That you kind of don't want a human on that.

Yeah. You can imagine that, that being harder for a human to do very consistently. Consistently. But if it means like, hey, we need to put this string in this hole and then that hole and over here feels very difficult for a robot to do entirely reliably.

Yeah.

All these things always sound trivial. Hey, we're going to make a robot that makes shoes.

It sounds so easy, honestly.

Yeah. It doesn't sound as hard as it is in practice. Right. That you have Nike doing.

I think it's, I would imagine that Crocs are fairly automated because it's kind of just like poor 3D print. Yeah. Pour the polymer in a mold and you're good. Just kind of like, you know, melt it together. But for something as complex as a Nike shoe that has a sole logo sewn on, there's, I mean even, even just lacing a shoe like that is incredibly difficult task for robot. Right. And they come laced like the, you have to poke those through. It's hard for me sometimes.

Shoes don't lace themselves.

No. You're trying to do something very precise and then it gets a little colder or warmer and the mature and the material changes on you. We did not anticipate that. As a result, factory production never became as automated as envisioned. As shoe production increased, the factory personnel swelled to 5,000, about twice as many as originally planned and costing more than a similar workforce in Vietnam. Task after task proved challenging to automate, like the delicate work of gluing soles to the upper part of the shoe. If you didn't lay it the right way, there would be a noticeable twist of the shoe. A misalignment that aesthetically means it would fail quality tests. A central product was also the huge variety of shoes Nike produces. For decades, American consumer companies have given designers nearly unlimited freedom to dream up the coolest products and relied on Asian manufacturers to deliver them. Unlike cars or iPhones, shoe models are changing all the time. Yeah, I mean if you think about some of the, like the how it's made episodes that clearly are heavily automated, it's very much stuff like, you know, even like food manufacturing. It's like every Cheeto is going to be the same. They're just going to go in like slightly different Size bags. And you can just imagine, you know, all that going down a conveyor belt. Little bit trickier when you're assembling a shoe where you know they're all different sizes.

Yeah.

I mean, we talked about sizing things crazy.

It's a plastic bag and then something needs to go in it.

Yep.

Fill it up and it moves down. It's like far more easy than a shoe which has. I mean, I bet the average Nike shoe has.

I mean, they sell a lot of them. Components, but they sell a lot of them. But when you think about the SKU complexity, I mean, what are there, like 20 different sizes of men's shoes just for a vanilla run? If you just want to be able to reach everyone from like a size 4 to a size 14 or something, like you're, you're in a very.

Nike says there's typically 23 parts to a shoe.

23 parts. Each one of those needs to be.

Different for the color lining and the color eyelet. Quarter, quarter over material. Damp outsoles, tip laces, swoosh.

Wow. It's like a miracle that these even exist, honestly.

Yeah.

And then the sizing thing you were talking about, it's like, great. You get it working for one size. This is going to work when you need to do the next triple XL.

Yeah. Size 15. It's no big deal. So automating manufacturing means designing simple products that machines can undertake over and over. Electronics manufacturing uses hard, standardized materials, as you mentioned, allowing machines to replicate the same step millions of times. You'll have to make sacrifices from how to design to the complexity of the materials and models you work with, says the former Nike executive who oversaw the project. That goes against what the consumer wants. They want an incredible diversity of product. And I mean, we see this in cars like the Tesla Model 3 Model S. Like, they look very similar. Even the Y and the X look very similar. They often come in the same colors. There aren't that many. You don't really see that many with like, oh, this one has fender flares, this one has wings on it. Like, all that stuff would be completely aftermarket. It doesn't come from the factory that way. Versus a more mature company like Mercedes sells like, like a wagon version of the, of the E450. Right. The E63. They also sell convertibles, the C series, they sell long wheelbase versions. They sell SUV versions, electric versions, for example.

The, the Q8 is the same as the Cayenne, is the same as the urus.

Yeah, yeah, yeah. Same powertrain.

All Volkswagen. So it's like basically the same car with like a different exterior and a different exhaust and like, and consumers want that.

Consumers want that. And so, so I mean Elon's found a way. And we'll go into the Tesla story later, but Elon's found a way to convince people in mass, at least during the height of the Tesla boom to you know, say, hey, yeah, it's going to look like every other Tesla 3 and you're going to get lost in the parking lot probably. But it has a summon feature. It has the best self driving, it's electric, it's super cheap.

Found a new way to defend.

Differentiate. Exactly. So it's like this appliance car. It's like it's moving it to the iPhone. Nike, if they really wanted to go all in on automation, they should have found a way to make a product that is as ubiquitous as the iPhone with as little standard or as much standardization.

Tesla is just getting hammered. Hammered down 10. Another no. 7%. But they're suffering from the trade, trade war tariffs. But then also the lack of a naturally also just a broader tech sell. Sell off. Yeah, yeah.

And yeah, I mean still no news about a gated manual, right?

That's right.

And so that's got to hurt the.

Kind of waiting on.

We're waiting on that. That, that's Ferrari's coming back by the way, with a, with a, a manual. They're doing a manual V8. They.

Did they name it yet?

I don't know. But no, they, they, all they said was that we are committing to a manual ice. Like no hybrid car.

They heard the Vibe Shift.

Well, they saw what happened with Porsche because Porsche launched the st, which was really great and then the R, I believe was manual as well. And so they said like there are certain collectors that just want manual, like more analog cars and they're willing to pay for them. And it makes sense for Ferrari.

They'll make a ton. Yeah, I was trying to think about it. I was trying to think what is the desire a highly desirable car that is a hybrid or electric LaFerrari. LaFerrari. I don't think LaFerrari is a hybrid.

I'm almost positive it is.

Is it? Yeah, you're right. You're right. Mogged.

Mogged. 918 Spider. Hybrid.

Yeah, the spider too.

296, but hybrid.

I guess I could have made it more precise and said in the last few years.

Right, in the last few years. I mean There's a new 911 that has a hybrid. I Think it'll sell pretty well. What else? Who else is the latest W1 from McLaren?

Yeah, I'm sure that is.

It's got to be hybrid, right? Everything's hybrid now. Anyway, let's get back to Nike. At one point, it took the Flex team eight months to figure out how to automate a way to put the Nike swoosh on a shoe. Only for Nike to move on to a new shoe line for which the method Nike developed no longer worked. And so there's just this cadence of, like, new shoes, they have to have new, new, new styles. They said it would have been easier to mass produce uncomplicated shoes such as ones with a machine knit upper part and matched with simple molded bottoms. But Nike was unwilling to put limits on its design and expected manufacturers to produce whatever new shoes their teams dreamed up. Manufacturing, in a lot of ways, did not have an equal seat at the table. And that's interesting because obviously the manufacturing of the iPhone is deeply integrated into the company. And they drive the manufacturing optimization that happens at Foxconn. This is the whole debate about are they transferring too much ip. But you know that the iPhone team is thinking about what is available on the camera side, how does that fit in? And then how can they build software on top of that? And that vertical integration has really led Apple to have the integrated approach that creates a fantastic product. Feels like Nike was very much still in the mindset of, like, design the.

Phone so that it would be insane to not get a case. Oh, what if we made it so the camera, like one of the primary use cases of the device, protrudes across the back so it doesn't sit flat? That is brilliant.

So by 2017, Flex's investors were balking at rising costs at the company, with some questioning why an outfit that makes electronics was involved in shoe production. Flex and Nike wound up the project.

Actually think is smart. It's like, hey, who's done really advanced scale consumer product manufacturing? Okay, they've done it in electronics. Probably a better. Generally a safe bet.

Yep.

But wasn't safe enough.

And so Flex and Nike wound up the project by early 2019. By then, under Armour had stopped mentioning to its investors project glory to make shoes in the United States. That year, Adidas, which had also faced challenges producing complex shoes with robots, said it would close down production in Atlanta and Germany. It shipped its speed factory technology to suppliers in Asia. The three shoemakers stuck with their original offshore locations. Vietnam, China and Indonesia. Even after pandemic era factory shutdown showed the risk of having Such a concentrated note of production. Adidas, Under Armour and Nike, they are not talking to the Journal about this. But now China, Vietnam and Indonesia are in Trump's sights. They got huge tariffs on them and there will be an army. Howard Lutnick said that the administration wants labor intensive industries to return to the US he actually said that there will be an army of millions and millions of millions and millions of people screwing in little, little screws to make iPhones. Says we're gonna make them here.

That's a word for word quote, word.

For word quote in a recent interview with cbs.

All right. I threw my how to make iPhones book in the trash. Nope, try to get it out. I need to go find a dump that they took it to. Yeah, got to get it back.

The threat of new tariffs is pushing some to ask whether Nike or others will ultimately have to reconsider efforts to automate manufacturing and bring shoe production back to the U.S. people think it's could still be done, although it won't be easy. You need some deep pockets and some patience because it's not going to happen fast. But yeah, we'll see.

You know what aren't patient?

Who?

Tariffs.

They're hitting, they're hitting right now.

Right now.

But if you want to track the tariffs, head over to Polymarket. I'm sure there's a bunch of great markets on what's happening in the tariff world. And if you're looking to cut costs because of tariffs, head over to ramp. Time is money. Save both. They got easy use corporate cards, bill payments, accounting and a whole lot more all in one place. Let's move over to the next story. Man versus machine as China shows off humanoid robots in half marathon. It's pretty crazy. Somebody came up to us in the gym this morning, was like, you guys are talking about this, right? And we were like, oh, I actually hadn't heard this, but it is in the journal China. The Beijing half marathon featured a road race between humans and 21 different robot models. And it showed how far robots are from mimicking people. Good example of why it's difficult to make shoes. It's also difficult for robots to run in shoes.

Yeah, they're both having been saying would like to see a humanoid robot drink 12 beers and play 18 and call it work.

Exactly. It's not happening this year. Not happening this year.

Not this year.

The Tian Can Kong Ultra, a humanoid robot runs across the finish line of a half marathon in Beijing. So let's run through this. Metal asphalt. Metal met asphalt in a ho and A half marathon that featured thousands of human runners and 21 Chinese humanoid robot models. Saturday's road race involving human runners and a score of robots in Beijing has been billed as a showcase of China's cutting edge technology. I gotta say, this is extremely cool for the robotics industry and we should be doing this here. I mean, you saw this. No, I posted.

You remember, I posted we need a. We need a Humanoid X Games. Right.

I want to see humanoids doing surfing.

I want them to see.

Do the 360, do the 1080.

Any athlete that Red Bull sponsors.

Yes.

Humanoid robot company should be saying, hey, we're going to get our humanoid to go cliff jumping, to go bungee jumping, to, you know, do it. You know, I want to see like.

You know, we really got to have the One X, the One X founders on Neo and a bunch of the other humanoid robotic founders on to talk about, you know, all our crazy ideas and, and force them to do it.

Big wave surfing.

Big wave surfing. That seems like the Turing test for humanoid robotics because if you can get.

If you can be waterproof, embodied AGI.

Also, I mean, I imagine these robots are pretty heavy. You gotta sink.

Yeah. That's the real test is a triathlon.

You swim? Yeah.

Can you swim?

Can you swim? Humanoid robot that swims. That's crazy.

How's your battery gonna hold up in good luck? An hour in salt water.

Yeah. Yeah. Is a honey stinger gonna take you across the finish line? I don't think so. You're gonna have to be recharging for an hour.

Robot.

So it's the 13 mile race, first of its kind.

The interesting is the size difference. Everybody just assumes humanoids will be, you know, six foot.

Yep.

They had four foot humanoids.

Four foot humanoids. Okay.

Little guys running around.

So China has said it wants the country to be a world leader in humanoid robots by 2027. They are well on their way. Based on what I've seen, Chinese authorities have lavish support such as subsidies, talent bonuses and tax breaks on robotics companies. In reality, the race telling me that.

For the first time.

They know how to do some central planning over there.

Yep.

You know, say what you will about.

Capitalism back to back.

If you look at the subsidized industries, there's another model that seems to be working pretty well. In reality, the race showed how. How both. How quickly and smoothly some robots are able to run, but also how far away humanoids are from still from being able to mimic human activity. Running is a very basic ability of human beings, says the chief technology Officer of the Beijing Humanoid Robot Innovation center, which developed one of the robots. China is making a major push to produce more and more sophisticated robots, in part to raise the automation level of its factories. Oh, they actually put the, they actually put the robot in sketchers.

That's really interesting too. So these weren't autonomous. Right. There's people following behind the robots, actually operating. Basically driving them with a joystick.

Joystick.

Like it's an RC car.

Yep.

But still very incredible feat.

Okay, so the first one, the first robot off the mark was the Tian Kung Ultra. Five foot nine. Hey, let's.

There we go.

Got to put you on the truth zone. They're not 4ft tall.

No.

5, 6ft. Yeah. 5, 9. 115 pounds. Humanoid, ideal build, featuring a pitch black head and sporting an orange tank top. Three people accompanied it to help control the robot. The race is the culmination of months of training. They had to navigate the course's flat and hilly roads and maneuver around six left turns and eight right turns. According to the organizers. Developers had to train the robots to keep their stability and balance to avoid falling over. The organizers initially planned to cut off the race at around three and a half hours, meaning that the minimum average speed was 3.7 miles per hour. Developers said the humanoid robotics can typically operate for no more than two hours on a single charge of their batteries. The faster they run, the shorter the distance they can cover. Components and parts could easily break while running, so developers replaced plastic parts with metal and used extra strong but costly materials. One company trained their humanoids by connecting the robot to a fitness machine like metal stand to prevent it from following. Tian Kung Ultra was developed by the Beijing Humanoid Robotic Innovation Center, a research institute also called X Humanoid, Informed by robotics firm ubtech, electronics and electric vehicle maker Xiaomi and the local Beijing government. It could run an average of six miles an hour and could handle hills, stairs, grass and sand. Said a profile on robot.

Impressive. Yeah, this is, this makes you think there we have a number of American Humanoids, Boston Dynamics, 1x figure, Tesla Optimus. There's a bunch, right? But we actually should have way, way more. If this is going to be very important technology, we should have 20 plus, you know, venture backed companies sort of vying for this, Right. They don't all need to raise hundreds of millions or billions of dollars, but it's an area that we should be probably investing more in.

And so as they're running the race, Tian Kung Ultra falls down. Because the battery failed, the robots were allowed to swap batteries and they changed the battery three times on this particular robot. Wound up finishing the race in the human male champion completed the race in 1 hour, 2 minutes and 36 seconds. That's pretty fast. Followed by thousands of exhilarated human runners. Some were exhausted, resting nearby to catch their breath. After 2 hours, 40 minutes and 42 seconds, Tian Kong Ultra was the first robot to reach the finish line. A large crowd of spectators, including government officials was were eagerly awaiting the robots. In the end, only Tian Kung Ultra and Little Rascal N2 were able to meet the original cutoff time. The organizers extended it to 4 hours and 10 minutes so that more robots could finish the race. So the humans still got it. But I mean you look at the. You look at the trend line here, I think in a couple years they're going to be crushing this. I see no reason why. It feels like a lot of it's probably battery technology. Like maybe they keep swapping the battery and that's fine. But if they can really find some sort of battery breakthrough that's gonna enable more power and like running in a straight line and some slight curves here and there that doesn't seem like as even as much of a challenge as like assembling a Nike shoe. Right. It seems pretty simple and so they should be able to win this bell.

Helicopter carrying a bunch of batteries with an extension cord.

Oh, extension core.

That humanoid is sprinting.

Unstoppable for sure.

50 miles an hour.

Unstoppable for sure. Anyway, very impressive. Should we move on to some big funding news?

Yeah.

Grunds lands valuation around 500 million as supplement startups. Boom. You're familiar with this company? I was less familiar. I saw Austin.

Not super familiar. Yeah. Follow them a little bit. Just because I had been aware that they had. I had heard about their first year numbers and it was kind of unbelievable. Like it was. A lot of companies have got to their gross revenue I think in their first year is what best in class is the run rate that companies will. Best in class companies can sometimes get to at the end of their first year. But they actually like did it.

Yeah.

In that year wasn't.

Yeah. So clearly the founder is an absolute dog. Yeah.

Was it Austin who was talking about.

Yes, I have the tweeter. He says Grunds was the most obvious billion dollar idea hiding in plain sight. AG1 is a 600 million dollar revenue business. The founder of Grunds was like what If I took AG1 and put it in a form factor that is easier to consume and doesn't taste like shit. Easiest billion dollars anyone will ever make. And I don't know that I don't know enough about the company to.

I mean I can tell you probably exactly why it's working so little. Nominative determinism. The founder's name is Chad. Okay so that probably has had something to do with the success but yes.

The idea of taking the points guy or something. People are saying he was like a points guy. I don't know. He says he's founder of Grunds Daily. Previous Stanford gsb he was a Summer's partner, Summer Summit Partners and he's on the board of Ruggable, Dr. Squatch, Brooklinen Solo stove and seven more. So like really, really great scaled up consumer products companies. I've seen the. I had a friend who was applying to work at Ruggable and the economics of that business were fantastic. Are you familiar with ruggable?

Ruggable is one and then Dr. Squatch is also very under the radar. I think that's going to be a massive outcome.

Yeah I mean we're seeing this with the Ridge wallet guys. Like there's, there's increasingly a divide between like, like good idea gets market traction but the real killers come in and optimize the business and just actually get the full value out of the company or out of the market. So throwing Chad a follow. But let's read through some of the the information article on this. So investors are on a health kick looking for new ways to tap into into the fast growing brands and the nutrition sector. This includes pouring money into selling into startups selling supplements particularly those that offer new ways for people to load up on vitamins, protein and other ingredients. Latest example is a two year old gummy supplement startup Grunds which raised fresh cash at an up to $500 million valuation in recent weeks. According to people briefed on the deal their monthly sales were roughly 10 million earlier this year. They recently added kids products as well as a sugar free version of its adult gummies. And a fresh influx of cash nearing nearly 10 million according to securities filings.

Wow.

Really low dilution. If that's 10 million on 500 post, not bad.

They're making, they're making plenty of money themselves. One thing the American consumer has always been undefeated. Undefeated but is especially undefeated in the context of gummy.

Oh everyone loves a gummy anything.

So many different. Yeah. With Create I was initially I talked to Dan right when he was starting Create and I was a little bit skeptical around kind of the market that he was going for. I'd taken creatine forever. But he was the first company that I'm aware of to put creatine in gummy format. And I talked to him like two months later. It was so obvious that the business was just working phenomenally well. And he's been knocked off a bunch of times since then. But fortunately, there's an interesting thing in the gummy space where there's always been issues with quality in the supplement space Dan was talking about specifically in gummies.

I watched a YouTube video about this separately and then Dan posted about it how some, you know, mass monster bodybuilding Guy tested like 20 of the top Amazon creatine gummies. And they were.

A lot of them had zero creatine.

Like, yeah, like 0.0001% of the label claim is wild.

Yeah.

Anyway, I mean, Chad, if you're a real Chad and you're serious about growing this business, get on numeral. Go to Numeral hq. Sales tax on autopilot. You know, you're gonna have to be paying sales tax on this stuff all over America. You can spend less than five minutes per month on sales tax compliance.

That's right.

Anyway, I want to keep digging into a little bit and then we'll move on to the next story. So they have other hot brands include Create Wellness. That's our boy. A line of creatine gummies which tapped into the muscle building supplements growing popularity on social Media to raise 5 million in Series A funding last fall. The brand has launched in retailers and is on pace for around 25 million in annual revenue when it raised fresh cash. Let's hear it for Create Gummies, Dan. Good job. The rise in popularity of weight loss drugs is also providing market Unilever too. Unilever's in the game. Oh, was in that deal.

Yeah.

Oh, that's awesome. With brands claiming they enhance weight loss or help with side effects of the drugs. Grunds, for instance, has run digital ads.

I had to just look that up. I thought I was leaking. Yeah, he did announce it last year.

Oh, yeah.

I was like, wow, I just broke your fundraise, Dan.

Sorry about that. No, no, it's in the information already. And so Grunds has run digital ads targeting people taking drugs like Ozempic who want to keep getting appropriate nutrients as their appetite fades. That makes sense. Whenever you're on a cut and you're in a caloric deficit, whether it's caused by Ozempic or just, you know, keeping yourself hungry because you're trying to get diced for summer, you. You want to maintain enough protein and Enough creatine and enough hypertrophy training and hard training so that you don't lose muscle mass during that cut.

Micronutrients too.

Micronutrients too.

What Groons is doing. Yeah.

And so they sell a monthly supply of gummy vitamins for $79 or $59 for monthly subscribers. They say the products pack more than 60 vitamins, minerals and other ingredients into one serving. And it markets as gummies, as cheaper, more convenient version of popular greens powders which are made of powdered vegetables and fruits mixed together into water smoothies.

Did you ever hear about this company Goli? Yeah, Goalie.

Wasn't that for Gut Health?

The apple cider vinegar gummies?

Yeah.

Aren't they really big?

They have. They are large. They do hundreds of millions of annual revenue.

Wild.

I think they've been somewhat unsuccessful in terms of like capturing kind of enterprise value around it. That said, just to give you a sense of the scale, they have 364,000 reviews on Amazon. So they sell 300,000 reviews?

Yeah.

Wow.

So run the numbers on what percentage of their customers you think have left an Amazon review and then you can get a sense of their scale. But it's in the hundreds of millions of annual revenue. So again, Americans are buying billions and billions and billions of dollars of vitamins.

You know what else has great reviews? Eight sleep. I got an 81 last night. I'm getting up on the routine quality and time slept was a little bit lower. But go and get a pod 4 ultra 5 year warranty, 30 night risk free trial free returns, free shipping.

Go to 8sleep.comtbpn last night autopilot made adjustments to boost my deep sleep by 42%.

Fantastic.

Thank you, Autopilot. I actually went to bed later than I would have liked because I was.

Watching Last of Us. Oh, you watched the Nathan for you?

It's not Nathan for your but it's the rehearsal.

Yeah, I love it. Was it good?

It honestly was giving. I almost was texting the team because he basically recreated the entire. An entire airport.

Yep.

In the episode just to. For.

That's the bar.

That's the bar. Our new studio, which hopefully we're signing the lease on today. We've been in diligence for a while, but we're going to have to just like recreate LAX if we, you know, if we want, you know, to reach Nathan Fielder levels.

He. He's been on a fantastic run. I've enjoyed everything he's put out. The old Nathan for you episodes are iconic. Very rare to have business and comedy.

Work so well together about aircraft safety.

Amazing.

So can't wait.

I'm enjoying Last of Us. Although it is terrifying, it's essentially a horror film and it's not ideal for the deep sleep, I think. So I might try and push that maybe Saturday afternoon.

It's so funny because White Lotus ended.

Yep. HBO likes to keep the dread high.

My wife was like, I'm very. I'm happy that we're not going to, like, be having these crazy cliffhangers and, and like, scary scenes right before bed. And then Nathan Fielder is, like, sitting there, like, walking through, like, the history of, like, every terrible, you know, aircraft, you know, accident. And it's just like, extremely stressful. Yeah, go check it out.

Go check it out. I mean, in, in the world of Hollywood, the name of the game is getting an Emmy or, or an Academy Award. It's Emmy season coming up. And breaking news. We're going to be going for a Daytime Emmy and we're going to get a billboard. We're going to get a billboard on ad quick for your consideration. Billboard. If you've been, if you've ever been driving around Los Angeles around Emmy season, all the shows have, you know, all their accolades up on the billboard. We're going to go to adquick.com out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising. Anyway, let's go to some timeline. We got our guests joining in 24 minutes. We got a great lineup. We're going to start showing you the lineup during the show. We're working on some new graphics packages, but we got David Tisch from Box Group, Mike Vernal from Conviction, Ed from Machina Labs, and then Will is coming on from Morgan Stanley. We'll be talking about what's going on in the venture market, what's going on at the early stage, mid stage, what's going on in AI investing, both at the foundation model layer and the application layer. I'm excited for the set of conversations, but. But let's run through some timeline posts in the meantime.

We got a post from Josh, actually, Lulu first.

Oh, you want to do Lulu first?

This is going to be a nice little surprise for you.

Please.

Michael and Ben and Scott, if you can pull it up.

Let's see.

Is it in the banger chat? No, it's just in the main chat.

In the meantime, why don't I tell you about Wander? They just launched Wander Malibu Vista. It looks fantastic. You can see the ocean from that thing. Find your Happy place. Book a wander with inspiring views, hotel grade amenities, dreamy bed, top tier cleaning and 247 concierge service. It's a vacation home, but better.

If you stay in that wander, let me know and go outside in the backyard and start yelling, I will be able to hear you.

Wait, really? Is that close?

Yeah.

That's amazing.

You'd have to yell pretty loud. But I think.

I don't think our listeners will have a problem with that. Yeah, with all the creatine and all the tea working out that's going on in our. In our community, I think they'll be fine. They'll be able to belt it out. But man, what a beautiful little. What is that? Driveway. But it's circular. Looks really beautiful.

I don't know.

I'm excited.

Here we go. Lulu says if Coogan does the eyebrow while describing your business model, congratulations, you're gonna have a Decacorn. She identified a specific. I guess so founders, this is something you can read into now. If you are, if you are. If Coogan is talking about your business, just pay attention.

I think are underrated when you're trying to express yourself.

He's subtly signaling something. And in this case it's very positive.

It's very fun. Yeah. What a journey. Five years ago, bored during COVID Saw a bunch of people. A lot of people already had podcasts, A lot of people had substacks. I was like, I want to do something different, but I think it's good to get just be noisy on the Internet because you're not really going to happy hours anymore. During COVID there's nothing going on. Why don't I start yapping on YouTube? And the first year was really, really slow. I think it took almost a full year to get more than like 100 views on a video. Like 50 episodes in a row. And it was just like, it was cool. I mean, for me, I didn't understand any of the stats. I didn't have any benchmarks because I was like kind of the only person in tech. Eventually Gary Tan was doing stuff, but he was so big, I wasn't really like comping to him. And so I'd just be like, oh, man. Like, I broke 100 views on this video. Like, it's a banger. Like, this is great.

So many people would have.

And I was just like fired up about that. But I enjoyed the process. And I was like, I did a lot of motion graphics, spent a lot of time in After Effects. I remember I did a video on breaking down Varda and I built a 3D model of a satellite that was, like, wildly inaccurate based on, like, what they actually do, but they hadn't announced what they were actually going to do yet. So I was just like, it looks like this. And it was just wildly inaccurate, but it looked really cool. And that's what matters. It illustrated the idea of them launching a satellite and then bringing it back down. And yeah, the first time I met Delian was in Miami at Hereticon. He was like, oh, yeah, you made, like, that video about Varda. We actually sent that to our real production team and said, like, make it like this, but, like, for us.

Yeah.

I was like, oh, that's great. I'm helping out. What a fun.

And then took you five years to realize you've just wanted to do a news to Newsmax.

Newsmax.

Always be newsmaxing. All right, we got a post here from Josh Pacini, who I have did a call with weeks ago, early TVPN.

Listener quote, tweeting Annie, she says, name a better dopamine hit than running. I'll wait. And he says, getting a post read on tvpn. Well, congratulations, Josh. Today's your day. You got your post read on tvp.

Josh also has a very cool AI startup focused on automating drug development.

That's cool.

If you want to work in that space. Go hit him up.

You know, it's funny, on one of the previous shows, we were talking about startup names and we were saying that, you know, there's this new boom in the American Manufacturing Company of America, or Advanced Manufacturing Company of America. Allen Control Systems, the San Francisco Compute Company, the New York Compute Company, the New York Browser Company or whatever. And we said, all of those are done. There's no more alpha there. We got to go back to the dot Lys. And Roy delivered on a Sunday afternoon. He drops his launch video at 2pm on a Sunday. What a funny time to launch on Easter Sunday. Clulee is out. It's the old school, Lynch. We're getting back in the Ly game. I love it. Clulee is out, cheat on everything, and has a very, like, very formally produced, like, really refined cinematic launch video. Some great motion graphics in there. We're gonna have Roy join the show tomorrow to break it all down, but massive launch, 4.3 million views. 16,000 likes as of the time of the show. And Chad Byers got in the deal, snuck a check in, and he breaks it down. The Cluley Manifesto. We want to cheat on everything. And interesting that he's using. We I guess he's already deeply involved with this company. Normally think about it as an investor, but this is clearly something he's really excited about.

Not sure the round he said was announced yet.

No, no, it is. Yeah. Yeah. 5 million. Delian said that he. That they raised. Maybe Delian leaked it, but then that's not on me. But Chad says we want to cheat on everything. Yes, you heard that right. Interviews, exams, sales, calls, meetings. There's. If there's a faster way to win, we'll take it. We built Cluli so you never have to think alone again. It sees your screen, hears your audio, feeds you, answers in real time, while others guess you're already right. And yes, the world will call it cheating, but so was the calculator. So was Spellcheck. So was Google. Every time technology makes us smarter, the world panics. Then it adapts, then it forgets, and suddenly it's normal. Active H. This is golden retriever mode. You don't need to know anything. You just sit there and the clulee answers every question for you. He says. But this is different. AI Isn't just another tool. It will redefine how our world works. Why memorize facts, write code, research anything when the model can do it in seconds? Founder mode. The best communicator, the best analyst, the best problem solver is now the one who knows how to ask the right question. The future won't reward effort. It will reward leverage and being a golden retriever. So start cheating. Because when everyone does it, no one is interesting.

Amazing. I'm pumped to have Roy on. And very fun little fun fact. Ben made all of our sound effects with his own voice. That is so.

That is true. If you like this, if you like, shout out to Ben.

Our producer could have been a voice actor.

Speaking of the other Ben, let's go to Ben Stiller.

That's right.

Sinners. He's posting about Variety. Sinners has a mass putting Variety in the truth zone. Okay, we'd like to see that. A founder. He's going founder mode because he's, you know, he's. He's a producer. He's the founder of many movies. Sinners has amassed $61 million in his global debut. It's a great result for an original R rated horror film. Yet the Warner Brothers release has got a $90 million price tag before global marketing expenses. So profitability remains a way a ways away. And he says, in what Universe does a $60 million opening for an original studio movie warrant this headline? It's a good question. I don't know. It's not that crazy because, I mean, when, when big studios put hundreds of millions of dollars before. Behind a, behind a film, like, they're typically hoping that they recoup all of that, like on day one. Right? So, I mean, it doesn't seem like variety is being like crazily negative here. And they did kind of couch that in, like, you know, they got a ways to go to get profitable, which is like, maybe factually accurate if the price tag really is 90 million. But it seems. Seems cool. I haven't seen the movie, but I don't know if I'll have a chance to go see an R rated horror film that seems hard to rally the troops around. But have you watched the trailer or seen anything about sinners?

I don't watch horror films.

No. Too scary. Might throw off your sleep. Score. And we're in a knockout. Knockout.

I can honestly say I've never watched a full one. I just don't. I don't get.

What about the classics? What about Scream or Cabin in the Woods?

I'm also not a movie person. I've seen three movies.

Three movies. Wolf of Wall Street, Wall Street, Wall Street 2. Those are the three movies, the only ones that matter. Scarface, Goodfellas, Godfather. No, you haven't even seen those, have you?

Yeah.

Have you seen Wall street too?

No.

Have you seen Wolf of Wall Street?

Yes.

Okay. And you've seen Wall Street. Have you not seen Wall Street?

No, I haven't.

Oh, my God. American Psycho.

I have seen that.

Okay, good.

But I read the book first.

Okay. Yeah, that's weird. The book is weird. The book is weird. Anyway, should we go to Jim Simons on the only, only rule he focused on in trading Goat? He says, we'll pull up the video, but he says something like, never doubt the computer. It's pretty great. Can we pull this video up?

Was probably never trusted trading decision that was made before ripping a heater.

Oh, yeah, he's a big smoker. Yeah. Jim Simon, in case you're not familiar, he's the worth $31 billion. 55th richest person in the world. He's the founder of Renaissance Technologies, a quant shop. No longer with us. Famously, there was a market crash. Everyone asked them what was going on at Renaissance. What was your team doing while the market was crashing? And they said, we were at a movie. Amazing.

Crazy.

Yeah.

They're just like, what are we gonna do? The machine will handle it. Anyway, we're ready to play the clip. The only rule is we never override the computer. No one ever comes in any day and says the computer wants to do this.

That's crazy.

We shouldn't do do it. You don't do it because you can't simulate that.

You can't study the past and wonder.

Whether the boss was going to come in and change his mind about something. So you just stick with it and it's worked. I love it. I mean this is the story of like this is Lisa doll, move 37. If the AlphaGo team had said, hey, we think this is an error, we're going to override what the computer is doing, they would have thought that they were more likely to be at least at all because it was a novel move that had not been considered by humans before. And in fact move 37 was very important in that game.

It's interesting too to think of it in the context of if you interject and insert human decision making, you're actually taking away from the program's potential success in the future, which could more than make up for a one time mistake. Right?

Yeah.

Like there could be if, you know, the Renaissance team, if the computer does something that loses money effectively, but then the next time it does that thing, it makes it back 10x. Right. Like, was it actually an error gambler.

Mindset in the computer? You're only one computer aided trade away from. I mean it literally worked.

He made $33 million, 99% of computer. Right. Quit.

Right.

Right before they hit a page, hit 100x.

Just imagine it has like a side internal thought and you're just like expand the reasoning on this one. It's just like, I'm feeling hot. I'm so do.

I got a hot hand.

I'm so do. Yeah, it's great. I mean, I wonder where else that philosophy has a potential impact. Like we saw this with the debate over social networking where there was a question about the algorithmic Social feeds feed people confirmation bias. They feed them content that they enjoy, they feed them brain rot. Sometimes maybe the steward of the network, Zuckerberg, who has essentially complete control over Meta, should step in and say, you know what, I'm going to dial back the brain rot or I'm going to dial up the, you know, turn down the news, turn up the entertainment, turn down the, you know, the, turn up the educational content. There's a bunch of things that in theory could, you know, feel right, but maybe the end state is just step back and maximize for ltv. Who knows? I don't know. I have a hot take on this, which is like The LTV is just like, if you actually think about the true LTV of a user of Facebook, it can actually drive a much stronger and more valuable outcome as opposed to optimizing for arpu, which is a one year metric. So if you're optimizing for a one year metric, you're going to try and sell someone, you know, like gambling, mobile games, anything that just pulls money out of their pocket and potentially gets them distracted from creating value in the, in the society. But if instead you focus on what is the true lifetime value of this potential Facebook user for five decades, for their entire life, well then it might actually be valuable to, instead of trying to get some kid to play Candy Crush and spend all their parents money on Candy Crush tokens, instead send them a bunch of educational content, get them really pilled on capitalism, they go build something really valuable, they make a bunch of money and then you can run advertisements on them for Rolls Royce and Lamborghini and you're going to make more.

Money dollars on, on meta ads.

Maybe, maybe, maybe. And so, and so there's an interesting theory where, like what, what are we saying when we, when we, when we say the kids are suffering from brain rot? What we're really saying is like they will not contribute to society, they will not become economically valuable.

But maybe they go and become slop farmers, maybe.

And if they pull themselves out of the slop by their own bootstraps, it's possible. Of course it's possible. It's possible. But I do think that there's something interesting where if you think about it from an ultra long time horizon, it can actually be economically efficient.

Our quarterly, you know, no system will allow for that type of.

But that's the beauty of Zuck. He doesn't need to think in quarters, right? He doesn't need to. And so I'm, I'm optimistic that, that, that someone like Zuck could take a really, really long view also. I mean, I think he has kids, I think he has a very good, strong moral framework. So I think he might just kind of like, you know, optimize for that naturally. But I do think that there's an economic model to optimizing for long, long lifetime value, lifetime value education and like human flourishing, economic flourishing even in the face of declining ARPU in the short term.

I would love to think that Zuck is thinking of themselves as, you know, of meta, as operating digital railroads and is like, you know what, we're gonna, you know, we're just gonna invest in delivering educational content to our children. For the next five to 10 years, we're going to get them really excited about learning and science because we will.

Make more money in the future. That's the key thing. It can't just be purely altruistic. It has to be. No, this is the right move for the shareholders, but it's gutsy and it would never fly if you're optimizing the next quarter's return.

Anyway, I had a post on Saturday relevant to Facebook. I said, someday you're going to look down and realize that the good old days are over. X will be like Facebook. Your group chats won't be popping and your phone will just feel different. Don't let this time slip away. You need to increase your screen time now before it's too late. And funny enough, that thought came to me on a Saturday when my screen time is the lowest, but it did. I've had the sense over time that Twitter and X are just sort of lindy and will kind of always be here. But it's very possible that X goes away Facebook at some point and then we're just, we're just the boomers on Facebook, just all, you know, yelling at each other and arguing will become like.

A TikTok reaction stream.

Yeah.

Or whatever's next.

You always, always got to move.

We're going to we me. We're going to We Me. It's on the come up. We talked about We Me. It's the future.

Yeah. The FTC says that we me is Facebook's, you know, biggest competitor.

Biggest competitor or one of the top two. One of the snap and then we me.

So we'll see you on We Me folks.

We really got to chase that down. We got it. We got to get that ce.

I'm going to let you do this next one.

Okay? So War doll says you need to be dad maxing. You need to be waking up at 5:45 on a Saturday to hit the gym and then coming back to wake up your wife and kids by blasting Creed while making breakfast. You need to be dethatching your lawn. I don't need even know what that means. You need to clean your car and then stare at it in the driveway for half an hour. You need to be telling your kids that Jerusalem belongs to those who worship Christ. You need to be treating Easter Sunday like Super Bowl Sunday. You need to be absolutely mogging, childless heathens with peak dad power moves as God intended. Very funny Easter post. Obviously there was a lot of like he is risen posts that went viral over the Easter Sunday, but I thought this one was. Was very funny. It is something that happens naturally. You start waking up earlier and earlier in 5:40.5. That's five minutes later than I wake up, actually. If I look at my alarm. 5:40 on the Ashton Hall Grind. Anyway, Sam D', Amico, friend of the show he's been on, he runs impulse stoves. He had a good take about aliens that I wanted to share. He says, I remain convinced that the best evidence that the US Government has not recovered crashed alien spacecraft is that one, that would be the coolest thing ever. And two, someone would have to share it in a group chat with the boys. And he is, of course, sharing a screenshot of Secretary of Defense Pete Hegseth is said to have shared attack details in a second signal chat. The Defense secretary sent sensitive information about strikes in Yemen to an encrypted chat that included his wife and brother. People familiar with the matter said, so.

Send that headline to your wife and just say, us. Us. I was trying to do that earlier, but kept getting paywalled by the New York Times. The failing New York Times wouldn't let me screenshot the headline of an article.

You guys just take the screenshot from this. It's great. We got a nice clean screenshot here from Sam. Yeah, very funny. I actually think this is a great take, but we should have Jesse Michaels on the show to give us the latest and greatest in the world of UAPs, UFOs, and alien aircraft, because. And spacecraft, because he has gone way deeper. And regardless of what you think about aliens, I think that Jesse's done a great job of finding interesting stories, interesting historical anecdotes, interesting anomalies. And even if you remain unconvinced after spending time with him, you will be entertained and you will feel like you are talking to an intellectual, not just a crazy conspiracy theorist. And so huge shout out to Jesse Michaels. One of the best to ever do it. We grew up on YouTube around the same time. Anyway, let's move on to Atlas Creatine Cycle. He says they should have a 420 for creatine monohydrate.

So true.

I love it. Willowbrand says 10. Six. Because 10 grams a day, and six looks like a G. Oh, okay, 10 G. I get it. So true, King. People are into creatine right now. A lot of debate over whether creatine.

I have 15.

You have 15 grams. Yeah, you're max.

Those are big scoops.

Yeah, yeah, yeah. Big scoops. Yeah, it's a little sandy, but you got to get it down the creatine. It seems like, you know, maybe it's.

A fast bargain, but it's the best hair loss.

It's the best hair loss supplement in the world.

Yeah, a lot of people talk about hair loss supplements thinking that they're supplements that, you know, I mean hair growth.

But you know, Joe Rogan's bald. Yeah, he looks strong. Maybe it's the creatine, who knows? Maybe it's genetics, maybe it's a million other things. But yeah, you never know. You never know.

It's worth it, worth the risk.

Anyway, we got four minutes. Let's do a couple more posts. This one by David Haber over at Andreessen was interesting. He says, in any fast growing organization, one of the best feelings as manager or CEO is having someone who works for you that I call Safe Hands. It's this implicit sense that you can delegate a task, project or line of business and trust that the person is going to execute with quality. We've talked about this before with like the levels to employ to different employee skill sets. The pyramid that Sean Pury outlined, Safe Hands isn't just about competence. It's about proactively communicating when issues arrive, acting as an owner when problem solving and operating independently without the need for micromanagement. Importantly, Safe Hands isn't tied to seniority. It's just remarkable how inconsistent it is across an organization when whenever I find someone who is Safe Hands at my prior company, especially junior folks, I pour responsibility on them. Many of these individuals stretched far beyond their original roles and became leaders at the company with several now successful entrepreneurs. It's one of the most common conversations I have with founders I work with, especially in the series B plus stage as they're beginning to bring on executive leadership for the first time. Do you know, do you feel like you have safe hands across every functional unit of your business? How much leverage do you feel you're getting from your team in those areas? Every CEO instinctively knows the answer to these questions and finding your Safe hands is a key step towards scaling yourself and the company. And Matt Grim says, I call this folks you can turn your back on and they're insanely valuable. In fairness, I didn't come up with that phrase. One of those types who reports to me told me and I'm shamelessly stealing it.

Got it.

Jordy, what's your take?

No, I think oftentimes, you know, in this case David and Matt are founders. Oftentimes founders end up getting credit for the things that these sort of Safe Hands roles end up doing.

Oh totally.

And so Matt is.

But that's the goal. You have to hire these people and then also train them and then take advantage of them.

Right. You know, back them when they go out to do their own thing.

Absolutely.

Well, before we have David, we got to talk about Eric. Eric Tornberg.

Oh, yeah, speaking of Andreessen, Eric Tornberg has joined. Andreessen Horowitz is a general partner. Fantastic news. He'll be on the show tomorrow to break it down for us. Very excited to talk to him. Been a good friend for years. Talked about media. He's been in the podcasting space for, for like multiple years now. Built turpentine, done tons of interviews and one of the greatest networkers in human history. I think probably he knows everyone and he will.

Child of the Internet.

He will just throw you in a group chat with the world's most important people randomly and I'll be like, why am I in this? But thank you. This is interesting.

Yeah, yeah.

Great guy.

Anyways, very excited for him for sure. And, and the firm and very excited to talk with him tomorrow.

Anyway, let's bring in our first guest, David Tisch from Box Group. How you doing, David?

Hi, guys. How are you? Great. On having a new job today.

I do, yes, thank you. Yeah, I'm taking it from part time 50 hours a week to full time 100 hours a week, but it's only up from here.

Are you hiring?

We are, we are hiring.

How do I pursue this?

Yeah, the VC to full time news anchor pipeline. You know, once you've done it all in venture. Yeah. Like you have the natural step when.

You, when you start in this industry. I feel like that's the ambition, a daily show that you can pontificate across the whole industry.

Yes.

Well, we're hoping, we're hoping to recruit you to be, you know, a week drop in. We will be your podcast.

Yes. This is, this is actually like jokes aside, like the way that you like work for us is that when news breaks, you bring it to us. When, when, when something happens that you have an opinion on, you come on the show and you talk to us.

You are elevating the venture capitalist way to we don't have news. We don't have things that happen. I feel like you are really claiming.

What about like the most complex and naughty geopolitical conflicts. I feel like you guys as a class are like the best in of.

Terms business overqualified to talk about it.

Oh, okay. So you. Do you want to stay away from politics?

So let's start with. Let's start with tariffs.

Yeah, let's start with tariffs. Iran, Russia, let's just go down the list.

Good day in the market. Everything's great.

Everything's great. Everything's great.

Have you heard about the accordion effect to early stage? Because that's our famous early stage line of like whatever happens in the latest stage market. It's like an accordion all the way to early stage. So reverberates over the course of, you know, three to five years. So we will not ever be impacted because the accordion basically never reaches early stage because something else will happen in the macro before then, which is a really nice. Don't ask us.

There's no liquidity so you can't panic sell even. Even if you wanted to. You can.

15 years. That's a, that's a, that's a third accordion ripple.

Yeah, I mean, I mean there's no better example of that than we have. SVB crisis, interest rates go up. It's the debt of venture we're hearing about. Oh, GPs are going to be giving back LP capital. But then, well, well, well, would you hear about this AI trend and all of a sudden it's time to rip checks.

Saved us all.

Saved us all.

Who would have thoughts?

Yeah, Wait. Yeah. What wasn't there? This was sort of before my time but there was a whole chatbot era, right? Wasn't there like chatbot. Yeah, it was supposed to be the thing. It was sort of right. It was just didn't have the underlying tech trend. Is that right?

I feel like the tech wasn't there but also the branding of chatbot to chatgpt isn't that different but magically different from a outcome and sort of adoption curve. If you look like the automated chatbots I think is what they were called for that moment in time they all fell on their face because they weren't interesting enough good enough. They were like pre programmed answers and then OpenAI releases in essence just an advanced version of that in many ways from a consumer positioning and here we are. And so you are like the idea of chatbot was right in how you're interacting with the tech. The tech to your point just wasn't good enough.

Yeah, 90% of chatbot founders quit right before they strike it back.

Right before they sell the OpenAI.

I don't know if I've actually we should find some chatbot founder who stuck it out.

So hugging face.

Hugging face is the one.

Yeah, that's right.

Hugging face is the winner. They were in a boot camp for chatbots.

No way.

And pivoted From a chatbot into hugging face. So that's your answer.

That's amazing. Yeah, we got to have. It's Clement on the show. Yes. Right, yeah, we got to have him on. That'd be great. So yeah, I mean to get a little bit more serious like, like how are you processing this year? What are you actually excited about? What is fatiguing you in venture these days?

We have our annual meeting tomorrow, so I'm in the middle of practicing our script on the market. So I can just try it, please.

I love AGMs. Yeah.

The pre liberation day, post liberation day market speech is different in some way. But you really, I don't know, you're investing at the earliest stage of a journey and trying to attach two people starting a company with big long term, 10, 15 year ambition to some moment in time macro or what today feels like an incredibly volatile macro where you actually can't even understand what stability looks like or new framework. It's impossible. And so the day to day job here is we meet people, we get really excited about what they're working on, we give them money and we wait 5, 10, 15 years to see how that all plays out. So the investment moment of investing in an early stage company feels totally decoupled from the macro of what's going on. The macro does impact the companies you invested in years ago as they come to market for more money as they figure out their revenue retention. But the day to day volatility I don't think has an impact on our day to day job of funding great people starting big ambitious visions.

Do you think that there are going to be stories from this tariff cycle that are like what happened in Covid where everyone was like Airbnb was particularly hurting as a startup. I mean they were public at the time, but they were. I still think of them as like a YC company. Right. And it found, it seemed like that the story of Airbnb was like Covid was a transformational moment for them and they emerged like a stronger company than ever. Do you expect that to happen to any startups maybe in your portfolio or just out there in the market that are getting beat up but might emerge stronger than ever.

So.

So like if you isolate tariffs that has a sure impact on a subset of companies very side of software in many ways I think there's software companies that involve logistics and shipping that definitely are impacted, but I don't know that the like come out of the tariff is a predictable framework. Like what does that actually mean? Do we get to free trade in Reality, do we get to some equilibrium? Is this China only that we're talking about? And I think within there lies a very hard to foresee again point of stability. Whereas at least in Covid if you said we return to a normal world that was a more predictable endpoint. If you assume early in Covid it was wait two weeks and then the world will start again and then it was some longer period. But I think there was an appreciation for what coming out of it could look like. Whereas I think right now you're in the creation period. Harder to guess. The easy guess is American manufacturing windfall. But that feels like a big stretch. Like no one's building a factory overnight. I feel like that happens in other parts of the world, not here.

It does feel like it could be a catalyst for the American dynamism companies, the re industrialized companies that have been placing that bet and kind of hoping for just a little bit of a boost that you can see a lot of like oh, that series A company went to series B like a little bit earlier because of this narrative and then that was enough to get them over an awkward hump, build some real infrastructure out and kind of like realize the vision. I think I've been like cautiously optimistic.

One of, one of the. From this, if you're a super early stage investor which, which Box group is.

Yeah.

And then you're trying to time markets by being like oh there's tariffs, let me make a bunch of supply chain related or manufacturing investments but then the company's not going to mature for five to potentially 10 years. So it could be a totally different environment. And one example that, but that was relevant. We had the CEO of Astranus on last week which I imagine you invested in like over at least over five years ago.

13 years ago.

13 years ago.

Overnight success.

And so overnight success. Oh, and that's like a good example of like you couldn't have. You thought that space was going to be important at the time and you liked it.

Actually we're early stage VCs. We knew we didn't crystal ball obviously. No, I mean like if you think about AI, we're, we're the earliest investor in a company called Clay and Clay created a vision, had a product and it was in need of AI for it to work. And, and it wasn't created yet. And so if you watch this seven year overnight success it clicked when the underlying technology caught up with what the go to market product was. And I think you see that a lot of the times that the founders who are early in a space and can see it through and wait for the world to come to them while they're sort of pushing the world to get there. That's where a lot of that magic is. And I think Astranis or zipline again, 14 years ago we funded Zipline. Wow is another example.

We are huge Zipline shills. Now that we talked to the founder, I mean, what an incredible story.

We left that conversation. We were basically, basically like would invest.

Buy at any price? Yeah, because I mean it's not just that he's been grinding it out for so long, but I feel like if you watch the launch video, like he paints the. It's the opposite of the black mirror vision. It's a very positive vision of the future and it's something that, yeah, job's not finished. He's going to be doing that for 20, 30 years easily. Like there's so much to do and now it's just a matter of manufacturing scale, economics, all the basic stuff. But like, like he's got the drive.

We went to his office on a recent trip to San Francisco and I probably hadn't been in his office in a decade. And we walked in and it was just like this jaw dropping American built hardware software combo that you like, you walked out of there and said this is the beginning of another 15 year vision.

Totally, totally was there. You know, looking back at these companies like Zipline, Astranis, was there ever a trend over the last, whatever, 15 years that you set that you were tempted to go all in on? Because I imagine there was a lot of investors of that era that said, oh, space is so cool, I'm going all in on it. Climate tech is so cool, I'm going.

To buy this crypto instant delivery, just NFTs, just.

Yeah, yeah, that was the one. Yeah.

No, I mean we're generalists. We are founder driven. We find people who have their own vision. I think us as a firm, we should never be in charge of coming up with ideas. That's not our job. Our job is to give people who have dreams, capital and support to help them. John, your company, I think is the single most heavily debated internal decision we'd ever made at Box Groove. From a moral standpoint, we had to like decide if it was good or bad. And so that was interesting. So we almost pivoted into drugs. That was an opportunity for us. But no, I like the world pivoted to AI. Right. So I think two years ago we were saying like 30 to 40% of the companies we see talk about AI or are oriented around AI. Last year was like 90 and this year it's 170%. You don't meet non AI companies right now. And if they're not AI first we're attacking an industry by bringing AI to it which is slower and stale. And I think that is a forced all in versus a sort of opted all in.

Does does to the different business models that seem to be emerging, does that change the way you're underwriting these investments? I'm thinking about highly capex intensive businesses where you're just expecting a ton of dilution. Or we've seen some companies that are kind of just doing like private equity style roll ups but they're raising from venture capital. And I imagine if you're not careful with pro rata or how you're sizing your bets like, like it could turn out to be like oh, we really didn't get the full bite at the apple. But is that something that even matters to you or is it just like back the founder? We'll figure it out.

Private equity roll ups in venture always ends well. Definitely.

Yeah, yeah. I mean we like to say private equity is not a mature business and so there's lots of opportunity for tech people to come in and disrupt. They don't take it seriously. Famously not. Not famously not cutthroat. Famously not cutthroat.

They're happy to leave all that money on the table.

Yeah, exactly. Just. Just dollars on the floor for VCs to come pick up. Right? Jordy?

No, no, no. I was more. How was. Has there ever, you know, it feels like over the last two years, call it, there's been more of these sort of roll ups than ever before. Was there, was there another. Did. Was there another kind of like general like market wide crack or was it just sort of like individual areas and opportunities?

I struggle to think that the way to build companies is to replicate another company that's succeeding. In these moments what you tend to have is one winner and a bunch of followers that don't win. And so can there be a single version of a rollup? If you look at Anduril, they're great at acquisitions. That's a different phrasing of the word roll up. Roll up is either we're going to buy a bunch of things that are the same size or we're going to buy like one big thing and then tuck in some other smaller things around it. So I think unpacking the nuance in these words is more important than assuming a general like success across A wide variety of companies. I think the like, moment in time where you probably saw fast followers or fast movers win was in the on demand business. Right. When Uber trained the world that you could touch something on your phone and something in the real world would happen, it unlocked like a behavior across the world that was very different. Right. And that was this phone to real world connection that I think opened up a ton of other businesses. I don't think they all worked, but I do think that that was a horizontal opening versus a business model innovation that has been used in other industries or financial industries and then applied in venture.

Yeah, the idea that the classic sort of like accounting firm roll up. When I look at that, it's like when it's been two weeks in my, like CPA is not like on it or like, is not, you know, like clearly like, you know, is busy with other clients. I'm like, it's not like I want to switch immediately, but I'm pretty quickly. And so the idea that you're just going to buy like 20 accounting firms and then slap AI on it and not have like 90% churn is just interesting.

But have you tried? I. I mean, it's pretty good.

Yeah, yeah, yeah, it's pretty, you know, it's only going to get it wrong 5% of the time and that's going to cost you millions.

But yeah, this is a topic that Jordi and I have been debated and it's kind of related to Uber opening the mindset of like this delivery, boom chat, GPT wrappers. It's been derided as a term. We've now seen the VS code for wars, but it looks like there's a chance that OpenAI buys windsurf for 3 billion. And I've been going back and forth to Jordi about this, like, is this game on for M and A in the rapper market? Because if OpenAI, who has, you know, great team, lots of money, can't like build it and they want to buy it, then do we see anthropic, do we see XAI buying stuff? Do we see Amazon, all of the Mag 7 buy stuff? And then maybe even, you know, you get into some of the just Fortune 500 companies that want to buy startups. And so I'm in this weird scenario where I've been somewhat accepting of the idea that a rapper might not be a power law outcome, but everyone involved in Windsurf, if this deal goes through, will do very well. And so what is your take on that market and does this narrative shift?

My take Was broadly that like this is highly strategic for OpenAI but that doesn't mean every rapper, even if they have a lot of traction, revenue is like suddenly strategic to a wide range of buyers, right?

Sure.

I think in my 15 years doing this, the thing I've underestimated or I overrated was the amount of M and A that would happen. I think if you go back in the early growth of like this era, if you look at, you know, anything from you know, Facebook and before that, Google, Yahoo, Twitter, on their way up, they bought tens if not hundred plus companies and a lot of that was for stock and it was stock that appreciated post acquisition incredibly valuable for both the company and the founders who sold. And I think if you look at the next wave of startups, a dramatic decrease in M and A because instead of buy you built and the acqui hire didn't prove out to be the best use of equity. A lot of the decision of buy versus build became easier as you thought about where to innovate. I think in sort of getting at your question, I hope we're entering a period of M and A. I think the easy way to rationalize it is the valuations of some of these companies that you mentioned are so big that they can afford to buy companies for substantial amounts that might actually align with the founder of the acquired's expectations. And I think that's where one of the other mismatch was happening, is that the company that wanted to buy another company was just not able to hit the price and so they didn't happen. And so I think one way to rationalize it is whether it's the big seven or the scaled AI companies have big enough valuations to go out and buy things for numbers that will hit a founder's expectation, which I think would unlock a lot of positive things in this ecosystem. One is liquidity. But two is like there isn't really an answer to how do things end right now for a ton of companies. And M and A is the piece that's been missing to me the most. It gets less discussed and I think Fortune 500 companies need to modernize. Right? And we saw that pressure 10 years ago when you heard like all the non tech companies are going to become tech companies, then the public markets punish you on a quarter by quarter basis and it's like forget that, we're not going to do any of that. But I think today AI might be such a dramatic forcing function that smart big companies need to move quickly to get ahead of the curve.

So optimism is that buy versus you mentioned these super acquisitive companies maybe 15 years ago and then that changed. Do you think that was a factor? I mean you guys basically Plaid was built out of your guys office. There's a lot of, there's been so much infrastructure built during the Plaid era. Do you think that that was part of the calculus for some of these bigger, you know, companies that would have been acquirers. But they said hey, like we could buy this tech and then maybe try to integrate it or we could get this team and do it or hey, this infrastructure exists and we can just.

Build it ourselves or so many factors. Like the biggest one to me is that the government didn't want big tech to buy more companies. And so if they were going to buy companies, they had to be like the biggest ones, not like they were going to fight the regulatory fights on big companies, not on small ones. And that dried a lot of it up. And then I think the valuation expectations was the other friction. When a startup decided they were worth a half a billion dollars and the potential acquirers wanted to buy them for $100 million, that was no longer interesting. And so it just, it decoupled rationality from playing out in the M and A world, right? You have to have like a buyer and seller meet on price in order for the deal to even get going. And I think that's where the biggest gap was. Plaid sold, right? Plaid sold and the government stopped it. And I think that that was.

To.

Me a interesting moment in the government getting involved in something that was debatable. And I think it also tells big companies, don't waste your time trying to get these things through. And that slows down a whole wave of potential M and A.

Interesting. I don't know if the M and A market relates to what you're seeing on the LP side, but we've heard that there might be some fatigue from LPs on what's going on in venture. But at the same time it feels like that David Goggins meme where venture just keeps on chugging no matter what. You're going into the agm, what are you seeing broadly in terms of LP appetite for ever bigger venture funds?

We're a small, adorable seed fund based in New York City, so we are not responsible to answer that question. I think your job if you take LP capital is to give them back a lot of money one day and I think if you haven't, you owe that to them. And so at some point the patience should run out. And I appreciate that. I think the challenges, the time for liquidity in early stage venture has gotten pushed significantly from where it was more predictable. A decade or two decades ago you could say seven to 10 years on an early stage fund and mean it. Today I think you say seven to 10 years and you're like, by that I mean like 12 to 15 and that, that's a substantial difference. And I think you need to align with your investors on what that timeline is because it's in a rational timeline. Like the people we fund, if you go back 15 years, they were like pre elementary school for the most part, right? Like if you look at the young founder that you're investing in today, a 15 year timeline is 2/3 of a life. Like it's an irrational number. And so these like the go in motion of making an investment to the return the fund to LP's timeline is so decoupled from I think a psychological standpoint that your stakeholders are just dramatically unrelatable.

On that topic of young founders, how has the early stage market evolved? It feels like there's a lot more products, like YC is bigger than ever. But then there's also Z Fellows, there's different fellowships, there's people that are just giving away money to people to go try a startup and then maybe I'll invest later. And obviously the Thiel Fellowship is kind of like a scaled version of that, but there's a lot of other initiatives. How has that changed your strategy? Has it changed your strategy at all? And kind of like what does the early stage market look like for you today?

I think there's always been these splashes of noise and very, very little. Like if you go back again, I'm old and so I've been doing this through these micro waves of change in the early stage market, very few products stay where they are. They move in different directions. They either get later. So if you think about new entrances as funds into the early stage market, most of the ambition is to become a bigger fund. And in doing so you become later by nature of scaling your business. And I think on a product side you're only as good as the product you're offering. And so what has been amazing to me about YC is they've just continued to compound quality of the satisfaction to their customer. They are, they are not free. Right? You're giving YC equity and yet if you look at like the happiness factor, the MPS or whatever cheesy acronym you call reviews, but like people go to IC because other people who went to YC loved it and they think it was entirely worth it. And so I think the products that get invented need to live up to the cost. And if the cost is free, like, nothing is really free. And so what comes with that freedom is that attaching to a brand, and if you attach your company to a brand, is that a good thing to have done or is there some negative externality that comes with that? And so I think, and it's probably not the end point for the products that are offering free capital to be free forever. I would assume that's a hard thing to scale. And so I think you have to just like, as a company, aligning yourself with the brand. The trusted brands have proven to be trusted for a reason, and the new ones need to earn that. And I think there are some that have been around long enough where you find good examples of quality coming from them. And those are the ones that I would tend to trust more.

You've been in the game for a long time. Can you tell me the story of your first investment ever?

Yeah. Our Box Group is named after our first investment.

Really?

So it's like a combination. So the first investment's a company called Boxy. It was a Roku competitor. We were in their seed round as an adorable check. I didn't want to write my name as an angel investor, so I created an LLC called Box Group to invest in Boxy, which made me feel bigger. The Box was like a cool nightclub in the city at the time. Felt like a cool word. I've looked with Aaron Levy. He registered box.net, like two months before I did Box Group, which I'm bitter about. So point he'll sue me. And over.

He's been on the shows too, so he can come on and debate.

Yeah, well, let's collab. We're all collaborative in this anyway. No, no competitors. So, you know, Boxy gets funded. Follow on by Fred Wilson. I'm like, oh, my God, I'm amazing at this. I got to read that guy's blog.

This is so cool.

And then General Catalyst came in, and then Avner, the founder, went in front of Congress to, like, fight the cable companies. So it was like an amazing first investment to, like, see the narrative of a startup. They sold to Samsung and they were built into, like, the Samsung smart TV technology. But the idea was right and the timing was challenging. They had to fight every single battle on behalf of the people that came after them. And I think that that was a really good lesson is.

Is do you see you have a ton of portfolio companies. Too many too Many, I'm sure to manage. Do you see? And Case Text is one of them, which is an interesting example because that was a company that no.

1 year overnight success.

Yeah, exactly, exactly. I'll hit the overnight success.

Overnight success.

But are you seeing that across?

Can we get a soundboard for our like, meet companies meetings like you definitely should.

Yeah, you should.

Handshake deal.

Yeah.

Raise your forecasts.

Yeah, yeah.

There's an internal bingo that we run that every time they say buzzwords, we.

We're preempting.

But how do, how do you think of AI in the context of the portfolio broadly? Are there. Are there a bunch of examples where it's kind of creating new momentum in the business or like tons of new opportunity or. And you know, I look at this like, you know, I have 50 odd personal investments.

All them will work.

All of them will work. I'm sure they've all been marked up. So. So I'm sure that's what the website.

Told me, which I was like, yeah, yeah, I can be 98% success successful.

Is it 98% hit rate? But, but, you know, how often are you seeing it sort of create momentum versus momentum just being something that once you lose it, it's really hard to kind of get it back if you're not getting, you know, sort of lucky.

I mean, Case Text is like the most amazing story. What a grinder into just being early in the right way. And I think to Jake's credit, he was always like the smartest person in the room and figured out how AI could come into what they were building in a differentiated way and like split a team off, built a product, got to market first in an industry that was ready for it. And so I think it's this. And he landed like, he landed an outcome that he changed his life and changed the team's life. And I think like a unique story. We're now like three years past that you're early to the game and so if you haven't figured out how to take your stale product or your product that's maxed out and begin to re energize it, it feels like you're a little late. There are those stories and I think Clay is the other side of it. Where AI happened and Clay benefited from sort of the speed of it and now is running. But I think within the portfolio there are companies that benefit from pieces of it. And whether that's on the cost saving side or the growth side, I think you can find examples of everything. But it's within the Verticals that I find the most interesting momentum just being recreated. Right. It's companies that are servicing customers and in some way, if they can be the deliverer of AI to an industry that can't get it themselves, that's a really big opportunity. And I think Casetext sort of represents that.

Yeah, that makes sense.

It's awesome. Thank you so much. This was a fantastic.

I came on here to promote something.

Oh yeah, let's go.

Give us something like that.

The Howard Stern of tech. And so when you go on Howard, you have to promote or like the late night shows, you have to promote. We have a conference that we're putting on with Union Square and First Round in Lux in New York called Founders nyc and it's Founders NYC Co. It's free, which is different than most conferences. It's for people who want to start a company. We got the founders of Datadog and Mongo talking to each other on stage. Sort of, to me, a collection of all the big great early companies that were built and scaled in New York coming on stage to just like sort of create the community effect of building here. And so if you.

Yeah. Do you want to take a victory lap on nyc just generally? No, no, no. I'm just saying when you, when you started box group, a lot of people, maybe, maybe no one had heard of.

We're like the, the, you know, pioneers of New York City.

No one had heard of New York City before that.

There was that era about tech.

Right.

The amount of, the amount of the capital concentration in New York City right now is incredible.

So many great.

Never been more.

We're like the pioneers that discovered Miami and the COVID era.

Yeah.

No, no, no, no, no.

Look, I think New York's a home for people that want to win. And I think whatever you do in New York, it's, it's like an incredibly harsh environment. And in order to stand out and win in New York, you have to fight friction. No one cares. Right. And that's what's actually fascinating to me about tech in New York is like if you went on a subway or to the restaurant nearby, nobody cares what you're doing. Like, no one cares about your business. No one cares about tech. And I think that friction creates people to have to fight a bigger fight here because there's not momentum, like, there's not somebody pulling you up and saying, like, we're all in this together. And so I, I think the community here is, is just like people put their head down and grind and it's produced some real success. And we're excited to put it all on stage.

That's amazing.

Well, thank you guys very much for having me. I'll see you tomorrow.

We'll see you back. See you back here soon.

Bye.

Cheers. That's a humble giant.

Yeah. Overnight success himself.

Yeah.

Well, next up, we got Mike Vernal coming in from Conviction. Very excited to talk to him. We'll bring him in from the waiting room now. Mike, are you there? Can you hear me? How are you doing?

I'm good, thanks. How are you two?

We're fantastic.

Great to have you.

Thanks for having me.

It's a wonderful Monday. I hope your Easter was well, if you celebrate. I hope your weekend was great and I hope you're off to a great start of the week.

Thanks. It was great.

Yeah.

Fantastic. Yeah. I mean, I'd love to kick it off with just a little bit of background on your career and then what you're excited about today, and then we can kind of go forward from there. Does that sound good?

Yeah, that sounds great. So let's see, my career. I've been. I've been an investor for the past decade. Kind of an accidental investor. I never aspired to this, but I sort of. I spent 15 years operating. I was at Facebook for many years and decided to give it a try, and it's been great. So I've been an investor for the past decade. I am, like, I'm very motivated just by individual founders and folks that I find compelling. And so a pretty broad set of companies. So a mix of consumer and SaaS and hardware and infrastructure and some others. Some of the larger companies are companies like Rippling and Notion and Verkada and Clay and a couple others.

We just heard about Clay. We just heard about Clay. David Tisch from Box.

Oh, yes, of course.

He was saying about how Clay was this overnight success that took seven years. But as they usually do. I'd love to know the story of the first investment that really made you catch the bug. Obviously, you were at Facebook for a long time, but then at some point you were like, I got a knack for this and I'm going to take it more seriously.

I made a handful of angel investments before I formally became an investor, but they were. And I think in retrospect, they're actually like. They're. They're pretty reasonable. Like, I only made a handful. I probably made like seven or eight. One of them was Notion, which is probably the best of the bunch. But like Wealthfront, it was like Notion and Wealthfront and this company called Human Interest, which is like a 401k provider, and a couple others.

Say again, I'm, like, randomly friends with Jeff Schneebly, who runs the company now. It's a fascinating story because it was a YC company. And then he came in as like a founder Mode CEO, but he had like. Like his background. I mean, I love him, but it's like, not super. He's. He didn't start the company. He has a MBA, and I believe he has a PhD, and he's almost like a manager Mode type of guy. But he's been fantastically successful with the company, and I'm just the biggest fan anyway. Sorry.

Yeah, exactly. Exactly. But I think none of them really motivated me to do it. It was more I. So I was lucky enough to join Facebook when it was relatively early, like a few hundred people, and I was there for eight or nine years, and I led a mix of sort of product and engineering at the company. And my wife and I had our first kid, and it was the first time that I took, like, six weeks off for paternity leave. And it was a little bit of a. It was like the first chance to catch my breath in eight or nine years. And I was trying to figure out, like, what I wanted to do next. And the obvious thing would have been to stay at Facebook. And Facebook is. Was, and I think still is just one of the most amazing companies out there. But I'd gotten to know a guy named Brian Schreier at Sequoia, and Brian was. Brian had actually backed two of my close friends at the series, a guy named Matt McGinnis, who's now the COO at rippling.

That's right.

And Steve Garrity at a company called Hearsay. And Brian had kind of said, if at some point you decide to pop your head up and do something else, you should come, come talk to us. And so one thing led to another, and I ended up at Sequoia. And it was a little bit of an experiment to just see if investing was. Would be fun and interesting. As it turns out, it is both fun and interesting.

So how did you, you know, people talk about, quote, unquote, operate? You know, investors love to say if they've spent, you know, two years at a company, they love to say they've had operating experience. You had some very real operating experience at Facebook. How did you feel? How did you feel? How durable were the learnings from the true operating experience versus finding sort of common truths about the way to do business and the way to build products and Teams that, you know, because, because, because I've found like, for example, like the influencer marketing that I maybe did in 2016 like no longer works. Right. But yet there were things that I learned in that era that you know, I still use today. Right. So how do you kind of delineate like, you know, like a higher level of abstraction? Yeah, higher level, sort of these sort of lindy ways of doing things that are durable and valuable to communicate to entrepreneurs that you back?

Yeah, it's a great question. I will say one thing that I think I learned that still applies and one thing I had no clue about, which I didn't learn until like the investing side of things. I think one thing, one thing that's underrated. Maybe it's not underrated about Mark at Facebook is he's incredibly patient. I mean, I guess you kind of see it. I think he's like spent $80 billion so, so far on like Reality Labs. Yeah, but I think, you know, he is, he is at the same time both like patient and impatient. I mean everyone talks about like the move fast, break things and I think there is like, I think like a very strong bias towards action and just like getting, getting stuff done. But he also like from a first principles perspective, kind of if something should work, like if something logically makes sense, he will just keep playing it out to try to, to until there's like new data that suggests that it, that it is wrong. Which I think explains a lot of the Reality Labs investment. And I think like, I think one thing that's underappreciated about like a lot of great companies, maybe it's appreciated, I don't know. But like they take a long time. Like, I mean some companies are really fast and off to the races. But like, you know, figma was like four or five years before it started to work. Notion was like four or five years before it started to work. Clay was four or five years before it started to work. I think Airtable, like was founded in 2010 and didn't really sort of break out until maybe 2017, 2018. I mean all this sort of the PLG companies, you know, everyone's, everyone says they like want to be a PLG company, which to me is like, yes, I want to be a high growth company that is a. I don't want.

To have to do sales. I want to grow quickly without doing sales too.

Yeah, exactly, exactly. It's like I also want to be born rich and handsome, but you know, what are you going to do? The.

It's.

It Takes, I mean these companies just take a lot of big time. And I think, I think if you've operated for a while and you've seen how like if you viscerally understand patience and like if you're, if you're doing random stuff or if you're like literally there's no hope, then you should probably throw in the towel. But in a lot of cases, if you're doing the right thing and it just hasn't hit yet, you just kind of sort of, you got to play out, play out some more cards. And I do think I've observed a lot of financial investors having a, like if it's not up into the right three months in, it's like, oh man, we made a mistake and like what the hell are you doing? Or I was talking to a founder recently who has like a financial investor on the board now and they were like, your competitor is you know, at 5 million in ARR. Why aren't you at 5 million in ARR yet? Which is like I get it on one level, but on another level like you just gotta, I think, I think you gotta make sure you're doing the right thing and sort of doing it in the right way. So I think that was one lesson that definitely carried over for operating, which I think you kind of don't have until I think is correlated with people who have done it and sort of understand the messiness of building something. I will say conversely at both, I mean I was at Microsoft before Facebook and in both cases you're pretty insulated from like the market you're operating in. Like I think once you get to a certain scale the you're kind of just thinking about how to build new things for your existing customers as opposed to how to really like start in brand new markets. And so I had no real intuition for how to like evaluate a business and whether it was a good business or a bad business. And if it was how to think about the like I do obviously sales and marketing teams at both Microsoft and Facebook. But you don't really build an intuition for how to like attack a new business category. I think unless you've worked at a startup. So that that was all new to me.

I have a question. I've heard founders bring up the example of Figma as a company that took a long time to get a product out into the market and get traction. It was what was like four or five years until the first million of ARR. And I've heard founders use that as a reference point and be like, we're doing the Figma thing, it's going to take a while. And I'm like, no, you're not. They were doing something that was like, fundamentally, you know, very technically difficult, leveraging a new technology when there was no not of. They were operating in a space that maybe wasn't hot for different reasons, like, you know, sort of cloud design collaboration. You know, you had. I'm sure there was other players, but they had sort of four years to be. Multiplayer wasn't a trend, Multiplayer wasn't a thing. They sort of created that. So what would you say to founders that. That tell you, you know, oh yeah, we're doing this, but then you look at the market and you say, well, you have four or five other companies that have sort of more advanced feature sets maybe and are highly, you know, it's highly competitive. And I feel like that having the opportunity to do the Figma thing is like a luxury of being like very early.

You got to earn that. You got to be Dylan to earn that.

Yeah, I mean, I don't think, yeah, if anyone came in and said it was going to take like four or five years to build Figma, I don't want. I don't think anyone would build Figma 2. I don't think anyone would fund Figma. I, I think there's an element of like, you, you have to. I think you have to be moving quickly in the short term. Like anyone, you know, sometimes founders will come in and say, I mean, what is it? It's April. And they will be like, oh yeah, we will be ready to launch at the end of the year. And unless you're like taping out Silicon or something, that. That scares the crap out of me because I don't know, there's a lot of time between now and the end of the year. And so I think you want someone that is just like iterating at an insane clock speed and learning at every iteration. And I think those iterations have to be pretty fast, but like, sometimes you just don't know when it's going to start to catch. And so I know the Figma story less well than some of these others, but it's. You're just talking to David and you guys.

Notion's a good example too, right?

Yeah, I was going to say that.

They were toiling away, doing something in relative obscurity until they found the thing that really was magical.

Yeah. One of my favorite set of videos you can find it online is there's a Notion product demo from I think late 2013 and it's this low code, no code environment, there's all these blocks, there's a stripe block so you can drop payments in. It's a pretty, it's a pretty wild demo because you see the through line from today to what it was back then and it's clear like all the ideas are basically the same. It's like this canvas and it's got blocks and you can drop all this stuff in. But of course the first iteration was wildly complex and no one really used it other than a handful of die hard folks that, that, that, that figured it out. And so of course like the rethinking of it was okay. Make this like an insanely great note taking app and then go from there. Note taking wiki and the like. And notion's an interesting example because I think there's like incredible stubbornness on the vision and I think like what Ivan has been trying to build has like not changed in 12 or 13 years, but there was like a lot of flexibility on tactics and it was like, okay, this thing didn't work, let's try it again, let's try it again until something caught. And I think that's kind of the, like the, the art of it is like have a really clear vision of where you're like what you're trying to build over a 5 to 10 year window and then, but just move insanely quickly and be willing to like constantly change tactics.

I've been super excited about the idea of a email client built ground up around AI. Yeah, it seems like an obvious startup idea. We saw like the, the Mailbox era where Dropbox bought Mailbox and there was a new email client startup every few years. Now we're in this dangerous territory where you have a company like notion where founder, mode, CEO at the helm, plenty of resources, clearly not asleep at the wheel, understands what AI is capable of. But as a product manager or just a user of email, how do you think about AI in the context of email? What are you hoping for? I have an idea in my head of what I want, but I think I might be wrong just because that's the nature of these things. So how would you break down that problem? How do you think about AI Email?

Yeah, I think actually this is one I've thought a decent amount about actually in the beginning. So if I go back two years ago, two and a half years ago, my theory of the world of what would be interesting to invest in was there's kind of like three levels of the stack, there's kind of the foundation models at the problem there's all, is at the bottom, there's like dev tools and infrastructure in the middle and then there's like applications at the top. And I was generally pretty pessimistic on the dev tools and infrastructure space because I think it's just moving really quickly at the app. The application layer seemed like the obvious place to invest and you can kind of subdivide the application layer into like, I would say like head, torso and tail or like horizontal and vertical however you want to split it. And I was actually pretty skeptical at the time. Like it was clear to me like I should not be writing my own emails in 2025. Or to like a very small degree. Like there is a massive amount of corporates. I've had like a gmail account for 21 years at this point. Like it should just be able to write every single email for me. But it's 2025 and I'm still writing my own emails. Like it maybe gives me like two word completions. And I think I have two conclusions from this. One is like the large tech companies are just, I think way too risk averse to build anything good here. Like I like this, Google must be able to build this. Like it's just, it seems like a very trivial problem. I assume like the risk of me accidentally saying something really offensive in email is just too high for them to launch anything here. And so I like, and I think that's kind of true writ large. Like there is also like there is not a great assistant experience yet. Like Siri is still pretty bad. You can get like the meta AI assistant is actually pretty good if you're wearing like the meta glasses but you have to wear the glasses to use it. And so I actually think the horizontal like experiences are addressable by startups now because I think, I think the big tech companies are just going to be too conservative. And then in terms of like the experience that I want, I mean I don't actually want, I don't really want. I'm like pretty good at email. I'm like I'm, I'm a very diligent person. I like go through all of my emails. I get a lot of them. Reading them is like pretty fast. I don't need it to be summarized. If someone sends me a really long email like I'm probably not going to read it anyway. Like I don't need it summarized. Like it is a negative signal if you send a very long email. The hard work is replying to them. And if something could just give like Read the thing and like write exactly what I was going to write. That would be an amazing experience, especially if that worked on mobile because like composing on mobile is a total pain in the ass.

Yep.

So I'm amazed someone hasn't built that yet. It doesn't seem like there seem like there are a lot of hard problems out there. That does not seem like the hardest problem. And so I'm surprised.

Yeah, I mean we're seeing a lot of like bolt on AI narratives in the public markets. Are you seeing the AI narratives take hold in the fundraising around like scale ups, growth stage companies that aren't AI native companies but they make so much sense in the context of, of AI?

I don't know. That's a good question. Like I think AI is like very core to notion, for instance. And so I think notion has like a, has like a very deep advantage here and I think it's just like the next evolution of notion, I think. I don't know, I don't know if I have enough data points on this. I mean the thing about AI in my view is like it is not to. I never went to business school so I may get the definitions of all this wrong. It's a layperson's understanding. But like in the sustaining versus disruptive innovation, I think AI is like pretty clearly a sustaining innovation in almost all cases.

Sure.

I think it like might be disruptive to Google and so assuming like a scale up is still competent and can still build new product, I think they can just kind of adopt this stuff as opposed to being disrupted by it.

Yeah, this is the salesforce for mobile was just Salesforce.

Yeah.

And so yeah, you could imagine that Salesforce AI winds up working potentially or at least they'll hold on to that for a while. But it is a fun time because at least, at the very least it's like a new battle for everyone to fight out. Like you know, the Gmail team needs to pay attention because notion's coming for them. I love to see it.

Do you recommend sabbaticals?

Oh yeah, I most definitely do. I had never. So I had like worked continuously from when I was 14 years old. I like worked at a startup in high school and college and then I took off like a week between college and Microsoft and like three days between Microsoft and Facebook and a week between, maybe it was 10 days between Facebook and Sequoia. I took off almost two years. I say took off because I kept like 15 boards and so I was on like 30 hours of board board meetings and one on ones a week. But it was still amazing. I got to like play baseball with my kids almost every day now. They're pretty good at baseball. I knew nothing about baseball. And so now I know something. And I was, I think I was terrified that I would just be like, irrelevant after taking some time off, but I don't know, maybe I am. But it was like, it was, it was very amazing. And I just like, I would rather like getting to hang out with my kids is like the best thing in the world.

So I feel like saying that you're on a sabbatical allows you to release the fomo, which, like, as an investor, there's probably no stronger force, right? It's like the founder wants to talk and probably why, why, why conviction and why, why partner with Sarah? I have a bunch of like, you know, guesses, but I, I'm assuming you could have basically gone anywhere, you know, any firm, you know, raised 500 million out the gates on your own, you know, whatever. So curious to hear.

Well, I've known Sarah for a long time, almost a decade though I recently discovered that she sent me like a LinkedIn message in like December 2016, which I did not see until like two weeks ago.

Amazing.

But I thankfully ran into her and I in other contexts. And I think my theory on, I'd spend a bunch of time thinking about emerging managers and like, what is the right strategy for starting a new firm. And I think, I think one thing that is underappreciated, or maybe I certainly underappreciated for a long time is the degree to which, like venture firms, you know, there's this funny thing where like, people who work in venture kind of get like a little bit ruffled when you call their thing a company instead of a firm, because it's not a company, it's a firm. But you know what, like firms and companies are like first cousins and they're, they're all just organizations. And I think that, you know, if you're doing a startup, generally you don't say, I have an exception to this. But generally you don't say like, I'm just going to go like, build the next Google like that. That seems like a kind of crazy thing to do. You, like, you start off with a market that seems kind of small, you dominate that market, then you expand to like the next year of market and the next year of market and suddenly you build something gigantic. And I think the same thing is true in venture. Like, it's hard to just go out of the gate and be like, I'm going to be the next gigantic global multistage firm. I think you got to like pick a market and go dominate that market and then sort of expand from there. And if you look at over the past like 10, 15, 20 years, the folks that I think have done this well, it's like Matt at Paradigm with crypto, it's Mickey at Ribbon with Fintech. I. And so I, you know, I was clearly going to be a thing, the most important thing over like the next 10 or 20 years. And so I think building a firm focused on AI and intelligent software and becoming the sort of preferred partner for founders in that category and then expanding from there seemed like the optimal strategy. And I think that's very much the founding thesis of conviction. And I think like Sarah and Panav and the team here, we're off to an amazing start. So I've known them for a while. I think the thesis makes a ton of sense and it's really fun. I think like one thing that is underappreciated in venture, back to this like firms versus company thing is like venture is fundamentally predicated on the idea that there are things that like a two year old startup can do that like are hard for a 50 year old company. But then when you like. But venture is like not always that introspective about itself. So I think there is a belief that there are things that like a two, three, four year old startup that is in founder mode can do that maybe a 30, 40, 50, 60, 70 year old venture firm cannot.

So, so, so, so when's the IPO? I know it's going out. General Catalyst. We're hearing rumors about conviction Q4. I'd like to see them.

How have you. What's your broad. I'd love to give you a few minutes to talk about enterprise adoption of AI. We talked last week about how Johnson and Johnson had basically, basically piloted, you know, 30 plus different AI tools. It might have been like 300, I might have it off by like an order of magnitude. It was like they basically tried hundreds of tools across different teams.

It was called like the thousands of people.

And then they've just been, you know, basically culling, you know, a bunch of stuff that was cool but didn't quite work. What are you seeing as somebody who is, I'm sure at times a big buyer on the other side at the Facebook?

Well, I mean certainly there are, there are things that are working. Like obviously cursor. Cursor is working in a gigantic way. I think Harvey's working in a gigantic way Decagon and Sierra seem like they're doing really, really well. I caught some of the conversation you were having with David right before this and you guys were talking about rappers a little bit. I, like, I, I don't love the term rappers. And to me there's like back to like the bottom, middle, top thing. You can kind of like, if you're going to build an interesting company, I think you either have to attack it from. You have the handful of researchers that can literally push the state of the art forward, which is like maybe eight organizations in the world or you know and understand and like love and can serve a type of customer better than anyone else in the world and just like build down from the customer. So you're either like building up from the technology, you're building down from the customer. And so I, I mean, I think that the companies that are working, I think just like deep, just have really good taste and like deeply understand what their buyers like, what the customers need and are figuring out how to like adapt the technology to that. And then I think there's a bunch of folks that are like, not, are kind of like hypothesizing what people might need but don't, don't like viscerally understand it either because they haven't worked in it or they're just like, they haven't figured it out yet. And I think that's the stuff that is probably churning. But I mean, I think it's kind of standard at this point in the cycle. Like some things, some things are working, some things are not. I think more things will work. I think the defining characteristic will be like a deep focus on the customer, like the buyer and like building a great product for them.

Do you expect big tech broadly to get more and more acquisitive? We were talking with David too, around just this era, maybe 10, 15 years ago, when you had companies buying a single big tech company, even a Twitter would buy many, many, many companies and it was probably healthy for the ecosystem broadly. And then, you know, now, you know, on the show last week, we spent a bunch of time talking about, you know, the FTCs, you know, what they're doing to meta around something that happened, you know, many, many, you know, over a decade ago. But I'm curious, you know, what, what's your outlook on, on M and A?

I mean, I hope so. I mean, I think all the, I think it all got shut down just due to government action and I think like missing misplaced government action. I mean, I think there hasn't really Been anything interesting on the consumer front in over a decade? Like, probably. I mean, if you ignore TikTok and TikTok has like a million asterisks next to it there, I mean, it's basically chachi beauty, I guess. And ChatGPT is obviously super interesting, but there haven't been, you know, if you look at the 2008, 2009, 2010 era, there was Instagram, there was Snapchat, there was WhatsApp, there was Uber, there was Lyft, there was DoorDash, there was Instacart. And part of that is just like the mobile phone and obviously like all the change that that ushered in. But I think part of the problem is especially starting around Maybe it's probably 2016, 2017, there was just this crackdown on the ability to do acquisitions by big tech. And I mean, especially for consumer. Consumer has this property that, like, very, very, very few things are going to work, but if it works, it works really big. But if it doesn't work, it's often like really talented entrepreneurial founders that can then either like take what they've built to a larger company and adapt it for that, or work on something else at that larger company. And if you shut down the outs for those consumer companies, like, eventually people just stop funding them. So like every year some venture capitalist is like, this is the year that consumer is back. And I just, I don't think consumer will fully be back until either there's like some massive platform shift or like those companies can get acquired.

Speaking of, speaking of consumer, I'd be interested to get your thoughts on consumer agents. I was talking with a founder last week that had an idea for a consumer agent in the insurance space and it was a great idea. Seemed like it'd be very, very valuable product. And I knew. Right. I basically explained. My point of view is that even if OpenAI is not explicitly saying that they're going to do this specific use case, the sort of natural evolution is that at some point you will be able to use OpenAI to do a series of tasks. Like he was describing. How do you think of the. Do you see opportunities in consumer agents broadly, or given the foundation models, sort of emphasis on the application layer and building consumer products, that it's sort of a dangerous path to be building on.

Yeah, I thought for a while there seems like there's some intrinsic tension between, between being a great research lab and being a great product company. Like the, with the exception of OpenAI, like most of the other folks haven't shipped that much Product Anthropic is starting to ship some product and then OpenAI has had some complexity over the past couple of years. I, I think, I know, I think there may just be some like intrinsic tension between being great at research and great at product. And I think that is good news for founders that are building like horizontal products. And so I do think, I mean, this is kind of like the email thing. There's no, there's no great like AI assistant yet for people. And it seems like it is a thing that is possible to build. I think the more general purpose you are, like if you are building something literally for multiple billions of people, I think the higher the likelihood that you are like in a really square dead conflict with the foundation model providers. But I think, I mean this goes back to the like building down from the customer. If there's some set of customers you can go build for, that is even hundreds of millions of people. I think, I know like a company, a lab like OpenAI has, they have so many important things to work on. There has to be. I have incredible respect for OpenAI. But it's like if you have some strict stack ranking of the teams within OpenAI, only 10 problems can have the top 10 teams on it. And so if you are doing anything after the top 10 problems that they have, then you're by definition don't have one of the top 10 teams working on it. And that seems like an opportunity. Opportunity for a startup opportunity.

Yeah.

Well, great conversation.

I have a lot more questions.

Yeah, yeah, we, we'd love to have you back soon because I mean, you can just talk about everything that's going on. It's amazing. We really appreciate you taking the time. So. Yeah, thanks so much for having me.

Okay, have a good.

We'll talk to you soon. Bye.

Bye.

Next up we got Edward Mayer from. I'm going to mispronounce it. It's. I think it's Machina Labs. I got it wrong the last time I tried to pronounce a word like that. But we'll hear it from him. He's got a bunch of interesting topics and he is going to talk to us about a bunch of stuff. Let's bring Ed in and then we will have him introduce the company so I don't mess anything up and we'll go from there. Ed, how you doing? Hey guys, good to see you.

What's going on?

Would you mind just kicking it off a little background on the company, maybe how you pronounce it? It's Machina Labs, right?

Yeah.

You're Right. Machina Labs.

Fantastic. And yeah, just give us a brief overview for the listeners. Yeah, for sure. I think mocking Labs is a response.

To something that maybe actually Peter Thiel said once. I don't want to butcher it, but it's along the lines of we wanted flying cars. We ended up getting 140 characters. Which kind of comes down to the cornerstone of like, okay, software develops really fast, hardware doesn't. I think some people interpret that as something that says, oh, we don't have as much glass still in the hardware side.

But reality is there's a lot of.

Technological challenges in terms of building hardware.

So what we're trying to do at.

Machina Labs is just making that much easier. Right. If you're a software developer, two people can develop a program, rent server from aws, Amazon, deploy it. If you want to build a hardware, you pretty much have to go build a factory.

Right.

And that's why development timelines are like seven years, nine years. So what we're doing at Machina is we're using robotics and artificial intelligence to build basically what we call a robotic craftsman. And it's a robotic system that can do different types of manufacturing operations. And it's powered by AI, basically can figure out how to pick up different tools, do different types of operation to make different types of parts, physical parts, without anybody having to program it or having to handhold it or build tools for it.

And can you talk about the specific kind of, like, first instantiation of the thesis? I saw Justin lopass over at basepower posting, and it looked like he used a picture of your warehouse. Is that you guys? Is that right?

Yeah, it is us.

Oh, yeah. And so he breaks the new manufacturing space down into three categories. Manufacturing SaaS, companies make parts for other people. Companies and change the way the part is made. Companies. And which. Which one do you guys fit in? I think you're in the third. Right. Change the way the part is made. Developed a way to make stampings, complex geometry, form sheet metal parts without dies. And so can you break us down? Like, what is actually going on when this massive robotic arm is like pushing into this metal? Explain why this is important, how it works? Yeah.

So we wanted to build a system. We call it robocraftsman.

Right.

The idea is like, where do we get started? And we started sheet forming. Sheet forming is largest metal processing sector today. I think it's like $280 billion industry. Most of the metal parts you see day to day are sheet metal parts. Like, you're sitting in your car you're in the sea of sheet metal. Every other car body is sheet metal formed. Sheet metal parts or aircrafts are basically sheet metal cans.

But today it takes a very long.

Time to get your first batch of parts in sheet metal work.

Right.

You have to go make d, put them in giant stamping presses like four story tall buildings and then stamp your parts out. So our first kind of application to being sheet forming, we have two robots that form start from flat sheet of metal. Between two robots, they have these giant fingers that are super strong but they can basically push and pull on the metal that form it into a very complex shape without the need for any dies or tooling. Basically you get from idea to the first part in matter of hours. It's similar to how a potter forms a clay bowl with their fingers. They're coming into the sheet to form it and shape it into different shapes. So yes, it's a new paradigm, a new way of doing manufacturing. But it doesn't stop there. We're already doing trimming, we're doing slotting, hole making. So the robot can literally pick up another tool, figure out what it need to do with it to do the next operation and does that. So today does forming, it does a lot of subtractive work like trimming, holemaking. It also does a lot of qc.

Are you, do you get worried? There's been a ton of. There's been an explosion of new manufacturing startups over the last couple of years, you know, long since you guys started the company, many of which promising to automate with robots the creation of various products. We covered earlier today on the show just how hard it is to, to like manufacture for Nike to manufacture a shoe. Right. Which sounds somewhat trivial like you know, humans have been doing them for years. You should be able to, maybe we should be able to do it with machines. But then in practice it's like there's so many different factors down to temperature out of all. You know, when you look at manufacturing broadly, I'm assuming you have some type of framework for evaluating whether something like can be automated to the degree that people would like to see out of manufacturing or areas that basically shouldn't be touched. Right. Like something like shoes which have infinite sizes and a bunch of different factors.

Yeah, I think it's like a combination of three things like the market size opportunity and how technology ready it is to be kind of disrupted.

Right.

But also I think there's a lot of conversation around automation that is in the previous paradigm. I think for now, for the first time we have this concept of LLMs, this concept of we can actually reason very complex sequence of operations as long as we can train the robots on that sequence of operations? It comes down to what data do we have available to train the robots? We already figured out, okay, neural networks, LLMs, these transformers. If you give it enough data, it can actually learn a very complicated task. The real key was, okay, where do we generate enough data? Where do we have enough data to train it? Unfortunately, for a lot of manufacturing tasks, the data is not out there. You cannot train a very complicated model on it. For ChatGPT, the Internet had trove of free data that you could use to create a very complex kind of chatbot for us. Coming up with right sequence to make car doors or shoes doesn't exist. So the key is, can you actually provide a solution that can scale with limited amount of data, with human intervention and limited amount of data so you can deploy it in the field and get enough traction so we can have now enough data that comes from your machines to train your model? And that's where the ran after she formed.

Got it. Can you talk a little bit about the Nvidia announcement today? That's very exciting. Seems like it might be a little bit of like a side quest or is this like in the critical path to mass production?

Yeah, no.

Nvidia's today announcement was a kind of little fun thing we did. Nvidia is an investor in us.

Oh, cool.

Fundamentally, they are very interested in what we are trying to do, being able to capture data from physical phenomenon and build models that can manipulate the physical world. But I think we work with their artists in residence. It's actually those OpenAI's artists in resident that we work with Nvidia collaboratively to really turn just the artist is speaking to a system into a piece of art.

Right.

So Alex, the artist that we work with us, basically spoke what he wanted.

To build, what sculpture he wanted to.

Build, and the full stack of generating the code, running the robots all were done autonomously. So from speech, from intent, all the way to the physical part without anybody ever touching anything.

I love that. When the Studio Ghibli moment happened, I was taking some photos of my kids playsets, studio giblifying them and then immediately I wanted to print them out because I wanted to have some sort of physical instantiation. Just showing the phone was not satisfactory. So the idea of speaking words and then getting a sculpture out, that sounds really awesome and futuristic. Yeah, yeah, go.

How a lot of investment in humanoid robots lately. Many of those promising to Revolutionize manufacturing, replace human labor, automate the production of lots of things. As somebody who's been doing it with robots since 2019, how do you think of that form factor in the context of manufacturing?

Yeah, I'm actually super bullish on humanoids.

Right.

I think the question is, to your point, is it going to be, is the first application going to be in manufacturing? I don't think so.

Right.

I think the biggest problem, if you want to think of a startup as like what do you need to de risk first? The first thing you give an example of like Nike figuring out how to do the shoe manufacturing, the first thing is actually intelligence. We have kinematic frameworks for a long time. We could do what humans does in terms of kinematic freedom with industrial robots. We can actually do it more precisely with higher force with industrial robots, which was what we need in manufacturing setting. So the missing piece really was intelligence. So we're kind of a little bit intelligence first. Right. We don't need to solve the joints, we don't need to solve people walking around like robots walking around and having the human form factor. If you solve the intelligence, you have enough kinematic frameworks, which is industrial robots to do what you need to do. But that being said, I think, you know, humanoids is huge opportunity. Maybe not in manufacturing, but downstream and homes and all other places that can use humanoids.

What is, what is the, you know, I imagine you guys are beneficiary from some of the tariff stuff in some way, but on the actual machine side, are you in the industry seeing challenges of like, you know, how much of like the actual robots that you guys are leveraging are sourced outside of the country?

And Chris at Hadrian was saying like, yeah, my capex goes up by 10%, but the demand, demand has been way, way higher. So what's been your experience?

I mean, that's true. I mean like what we can, what we do here. So the challenge is for a lot of work that we do, and especially in the defense, aerospace defense, there is no industrial base, so we have to do it. So demand is always there. Now 70% of our BOM is off the shelf and we intentionally try to do that so that we can actually finance it easily.

Right.

Use multi push off the shelf equipment so that we can easily finance the full hardware stack. That being said, a lot of the hardware that we use is either produced in America or it's in very allied countries. For example, robots were produced in Japan, so the tariffs are a little bit more digestible there. But that being said, we are one of the very few manufacturing companies that are doing almost software like margins. So there is enough room for us to be able to absorb that cost and still have a very high value, high margin business.

Interesting is the idea. On that note is the idea we've seen some investors kind of strictly software investors kind of poke fun at VCs that are investing in manufacturing, you know, expecting software like margins. And there's sort of this sense that well, manufacturing hasn't for most things hasn't historically had software like margins. You're seeing it today. How do you think about the margin profile for advanced manufacturing over time? Even, you know, even in things that are like non chips. Right.

Yeah.

It's interesting arbitrage. I think there's a lot of people thinking about manufacturing solutions in different ways. I think you can think of it as automating what traditionally has been done. And I think that's usually end up being very low margin. But if you're creating something new that has some kind of arbitrage on either labor or has some kind of arbitrage on equipment in our case, whereas you don't have to make dyes and a single die for a car door can be up to a million dollars.

Right.

So for us we're faster but we.

Get rid of that asset.

So it allows us to have the at the same costparity, have higher margin. But I think down the road the margins could erode. And that's why we're thinking about it as a platform.

Right.

It's a robotic system that can do forming today. Tomorrow's going to do your next operator. It's going to do bending, it's going to do hemming, it's going to do forging.

Right.

So constantly expanding the capabilities of the system which allows you to sustain a very larger volume business as some of the margins of the older processes kind of erode.

Right.

Yeah. Last question. You mentioned that you might have a golden dome take. We did a little deep dive. There wasn't a lot to do dig into. I'm curious. It doesn't seem like it would interface with your business too much, but maybe you just have studied the industry. So what do you think is going on with the golden dome?

He's making an actual dome dome.

Yeah.

Make a physical dome out of gold.

To go over the United States.

I would love that.

If you like the blue get, you know, enjoy the blue above us while you can. It's going to just be all gold soon.

Yeah, yeah, yeah.

I mean there was like people Were talking about how it's like competing with a golden dome at Nor Dame, which is like actual thing in terms of the name naming conflict. No. So why do we actually fit into this paradigm? We work a lot with missile manufacturers.

Right.

And manufacturing components for them, the body of the missile for them. Hypersonics is one of the main enablers of how we can actually have defense against some of these missile attacks. So for hypersonics you need to start processing very complex materials, materials that are traditionally very hard to process things. High temperature alloys like nickel, titanium. And because of our robotic process locally manipulates the material, we have way more control to process the material without getting to failure. For example, we can form titanium sheets without tearing it in room temperature, which is traditionally not possible. I think there's a lot of interesting opportunities there for us and we're exploring with our primes that we work with. But yeah, I mean the whole concept of golden dome is going to be interesting. You know what I've heard last is it's going to be 7% of the DoD budget in the next two, three years.

Right.

Once it becomes programmatic.

Yeah.

So that's what I've been great. Obviously next year we're looking at like 20 billion on missile defense. But over long term, I think the plan is roughly 7% of defense budget. So it's going to be a huge opportunity and obviously I think something that's probably very necessary. But yeah, we can dive into details. But I don't know how much time you have.

No, no, no. I mean, I think we'll have to have you back on when there's more details that emerge and we actually get, you know, a deeper dive into how the, how the program record evolves, what the subcontractors might be looking at right now. All the, all the names parties are no comment. So there's not too much to dig into for good reason. But it'll be super interesting to see how this pans out. Jordy, anything?

No, this was great.

Yeah, we got to have you back on soon, but congratulations on the success and I'd love to come see the, the machines in action in person.

Yeah, really amazing.

You know, we're like, we were half an hour away from downtown, so. Downtown la.

So both of you. Yeah, that'd be awesome.

Let's do it. I want to, I want to do the show with, with a robot.

I want a robot to make us a bigger gong.

Yeah, biggest gong possible.

Gotta make it happen.

We gotta make it happen.

That'd be fantastic.

We actually do very Easily.

Yeah, I could imagine. It's a perfect. It's a match made to happen.

Our people will talk to your people.

Yeah, yeah. Our people will talk to your people. This is fantastic.

Thanks for coming on.

Thanks so much, Ed. We'll talk to you soon. Bye. Next up we got William Brown.

The idea of like a, like a 20 foot gong is very appealing to me.

Very appealing. That you could have watched be made from the raw material. Yes, Perfect. Be perfect. And I mean you could actually etch different things into it. There's so many cool things you could do with that technology. It's very, very awesome. Anyway, welcome to the show, Will.

How's it going?

Good to have you on here. Of your posts for a long time.

One of the top. Many people have said, one of the top posts. Poster of the year, I think.

Potential poster of the year for sure. He's been burning up the timeline. Jordi, where should we start?

I mean, I have a bunch of. I have a bunch of stuff that we can go through. I mean we can just dive into it.

Do you want to give a brief intro on yourself and who you are before we start? Maybe we should start there, started talking about the timeline.

Sure, yeah, Sounds good. I'm Will Brown. I'm a researcher at Morgan Stanley. By the way, nothing I say here is Morgan Stanley opinions. This is all me kind of just like sharing my thoughts. I am a researcher. I work a lot on stuff related to LLMs there. My background was in reinforcement learning theory. I did my PhD at Columbia. So I've been in New York City for a while. Big fan of New York City. Great things happening here all the time. And yeah, I also just like talking about the stuff on the Internet and participating in the open source community. There's lots of cool either projects or code bases or papers or models always coming out. And a lot of my job is needing to know all that stuff and being a liaison essentially from the Internet to the company where people want to understand, okay, what's the latest model for XYZ that I should be using? What's the right open source toolkit? Especially because at a big regulated company we need to understand the landscape, especially for things that are downloadable off the shelf without needing to onboard a vendor. Some things you onboard a vendor for. But it's also a much heavier lift and so we need to map the landscape of what's the right tool for the job, for everything LLM related. And so that's a large part of what I do. And it was also like my excuse for Being on Twitter all day, that's great.

It's a great excuse where you want to start. Where aside from X, like, where. Where are you getting signal without giving away. Without giving away all the alpha? Because I imagine, like, you know, by the time Dwarkesh has like done a podcast on something like, you know, it's been that most people have read the papers, you know, disseminated. It's not necessarily alpha.

There's a surprising amount of alpha still on X. Just from places where you don't. There's places. I have not found much alpha on LinkedIn, the group chats, the anons, the open source GitHub discussions. Lots of really good stuff is buried in a GitHub issue or a feature request where someone's like, hey, this thing would be cool.

Yeah.

And these ideas are just all over the Internet, but you got to, like, know where to look for them.

Yep. I want to talk about humor. You actually posted about this, like a month ago or two months ago. You said, it's interesting that 1.5 billion parameters is all you need to crush math competitions, but you need like 15 trillion to make the model be funny. Maybe humor is the right measure of true intelligence. And for a long time my eval has been, tell me a funny joke, and every time there's a new model, it's tearing up Axe. And I ask you to tell a funny joke, and it's always the worst joke I've ever heard. It's kind of an anti joke. But. But. But is that just a lack of. Of like, of labeled data essentially, or do you think there's something more. More like innately human to the idea of humor?

I mean, I think humor is like, really hard. And it's also very hard to. It is very hard to label. But I think it's also really hard to like, okay, this is like a big debate topic is like, would it like. I think people kind of assume, oh, just like train it on funny data. But, like, the things that make things funny are really subtle and pretty buried. I have a friend of mine, coworker, actually did this experiment where he, like, he tried to, like, have one model be a judge of, like, is this funny or not?

Yeah.

And what they do is they, like, lean into things that feel funny. And the results were actually kind of funny. But what it ended up just doing was swearing more. So, like, if you swear a lot, models think that's funny. And so there's all these kind of cheat code. Like, there's a lot of cheat codes.

Sure.

And rl and training these models is like the path of least resistance is to find the cheat code. But like real humor, like the people that to be really funny you have to be really smart. Like think of like your favorite comedian like Norm or Larry David or like all these people are like like really smart. You can tell from the way that they compose jokes there's an attention. Attention is in transformer attention of ideas that need to combine in a very sparse, precise way to make a good joke. You can't just shove things together. You kind of got to thread the needle to make a joke land. It's not a very coarse mechanism. And so I think GPT 4.5 is like ginormous model. Trillions of parameters most likely. And that like there's more room in the model to have these like little sparse connections materialize as you go through layers of the transformer. And I just haven't seen anything like that come from a smaller model.

How scale pilled are you based on the results from 4.5? Are you. Are you off to the races scales all you need or less in pilled or what?

I'm very RL scaling pilled. Like I'm not big transformer pilled really.

Like pre training wall real.

I think we don't like is if there's another 100 trillion tokens of data sitting out there ready to train on go for it. I don't know. Like one I think is like people should do some map and math about like how long until big GPUs are readily available and it's going to be a while before people can really run even deepseek R1. With easy resources you can kind of do it on one node. But the quality bump over things that are much smaller is just like we're hitting diminishing returns on capital investment is a lot of it. They're taken out of the API because the they can sell other things with the same GPUs and make more money as part of it. It's a lot of compute to keep a model up like that. It's slow and the things that it's better on are not that economically valuable. And so the sweet spot appears to be in this between 30 billion active parameters or parameters total and a couple hundred maybe. But I don't know that when Meta releases this behemoth model I don't think anyone's really going to run behemoth for their day to day stuff. It's just probably not going to be.

Worth it given that Tyler Cowen's calling O3AGI. The economic results of these big but not crazy big models seems to be pretty good running on a node. Should we be talking more about, hey, it's good enough, let's bake it into an asic. Let's just bring down the inference cost to basically zero, like we did with bitcoin hashing and whatnot. Like, is that the conversation we should be having or.

I mean, I think that's been. That's kind of been how, like, Grox or Samanova are, like, playing that game. Yeah. And I think, like, those businesses make a lot of sense. Like, they can kind of say, okay, this version of a transformer, we're going to be in this ballpark for a while. We can bake that into our plans a little bit, I think. What's the next way? 20, 25. Like, people have been saying, you're the agents, but, like, what I think that means is agentic RL. Like, we're realizing RL works. Like, the reason O3 is good is because it's trained to use tools. The way you train a model to use the right tool for the job is reinforcement learning. And they've said as much. Like, deep research, reinforcement learning. People have been throwing, like, random tools at models for two years and it only now works even though the models are the same. Like, GPT4 was a bigger model than a lot of the models are using now. It had just as much training data, but it was not, or at least doesn't seem to have been RL'd in this specific way. And so that's kind of like, my bet is, like, people are going to really want to train models to be agents. And I think you can get that to work well with a pretty small model.

Does that mean, like, a flourishing of RL'd big transformers for different tasks, or are we still searching for the God model that can do everything all at once?

Okay, I think there's a couple leaps. We need to have models that can do everything all at once for a super long amount of time. I tweeted something about this. I'm happy to call 0310 Minute AGI. And I think framing AGI in terms of length of time it takes a human to do a task is like, more reasonable than like a global framing. Like, sure, there's a bar of like, drop and replacement for a human that we are like, definitely not at yet, like, for general jobs, but most things a human can do in 10 minutes, you can, like, get O3 to do that pretty well. And so that's a very like, I.

Think there's even, even like a website like make a website in 10 minutes. Okay. You have a good human designer is like probably could whip pretty quickly. Yeah.

But not like an entire design system works together across all the different websites. Yeah. Makes a ton of sense. So, so, so seems like we're transformer maxing. We're RL maxing. Is there a new paradigm that you're excited about? Program synthesis? Are we bringing back symbol manipulation at some point? Like what, what are we going to pull from the tool chest to make this thing go to the next level? Level?

I mean I think it's just tool calls. I think when people say program synthesis we're already there. O3 is program synthesis but the programs are like JSON and Python. You can do a lot with that. I did some tests on ARCGI problems where you give the screenshot to O3 and it can basically figure it out in 10 minutes of zooming in and looking at the thing and then writing some code to see if it reproduces the thing and it doesn't nail it. But they haven't released the benchmark but I would guess it'll do reasonably well.

What are you seeing around AI adoption and finance broadly? I feel like we've been promised somebody can just press a button, generate the deck and generate 20 page investment memo. And are these types of, of you know, deep research style tools being used extremely heavily already or is there just even a greater now that they're being used? You know, hey, let's go spend our time talking to you know, three times as many experts so that we actually get proprietary kind of insight into the, into the business.

Great question and I think there's a couple different answers. I have. One is that like on one hand we at least have been pretty I think fast at certain things in adoption. Like the day GPT4 launched, Morgan Stanley had integrations because we had been working on it and these were like we had press releases for these of like we are ready to go. And so there are certain things where like initiatives can happen where effort comes together to make a thing ready to use but there's a long tail of smaller tasks that there's not a drop in replacement for. If there's a vendor it would take a long time to onboard them and it's not going to really solve the problem right away. And you could build something from scratch if you put a few people on for a few months. But like engineer hands are like few and far between. And so I think the deep Research is an example of a product that I would say like works really well for the thing it's built for. It doesn't quite do other stuff super well. If you wanted to give you a table of 50 very precise things, it's going to make some mistakes there because the report format has a lot more room for slop without it seeming noticeably bad. Microsoft PowerPoint Copilot is not great. It's not a thing that I have heard many people say saves them much time.

What are you.

Yeah, do you have, do you have any takes on enterprise AI adoption broadly? We were talking I think late last week about how Johnson and Johnson had tried hundreds of different tools. Like they went through the effort to just try a bunch of stuff because there was a top down mandate and now they're just like cutting probably 90% of it. And so all the startups that were like yeah, we have a pilot with.

J and J, it's going great. Like they won't churn. Well, 90% of them just churned maybe.

I mean like most of these pilots are very much intended to be turned. Like they're not, they're very much in a. They're not being rolled out broadly. They are coming through in a kind of walled off environment for people who are like going to be the beta testers. And so like we have a crew of people who like and I'm involved with this as well. Like they're as new stuff comes like online, we test it out, we give it feedback. Most of these do not convert because we're very willing to try stuff in terms of taking the call in terms of looking at a demo. But actually making a thing be part of the company wide workflow is a pretty heavy lift. Think of onboarding a cloud provider. A lot of the reason, maybe this is like one reason cloud providers have the margins that they do is because like moving clouds is really hard. Moving all your stuff from like AWS to Azure is a pain I think especially in regulated industries. Like a lot of software onboarding faces the same sort of hurdles where you can't just like bring it in and use it. You got to like go through a whole process and some companies are have kind of planned for that and some have not. So like one example is I think like a reason that Windsurf has been successful as a cursor competitor is they leave. They've leaned way harder on enterprise than Cursor has. Like they have really designed for enterprise integration whereas Cursor really has not.

Do you was a Windsurf news surprising to you at all or was that just obvious? OpenAI cares about coding and they should have a sort of of dedicated enterprise coding.

I mean it makes sense. Yeah. I think like to me it felt like a sign of there being some more friction with Microsoft because originally it was like, oh, they already have that, it's Copilot. And so this to me seems like them taking a step away from Microsoft. But I mean this is just speculation. It does make sense that it's Cursor and it is Windsurf and not. I mean they did try to buy Wind Cursor supposedly. Like I'm a cursor user.

I think it's great.

I haven't seen anything that really sold me on like go move to Windsurf. I'm sure it's fine. It's just like the bar to like Switch for me is like I need a thing to have a feature that's like killer that the other one doesn't have. And I have not seen that yet. But I'm sure they have plenty of good stuff.

Now that we're a couple months out from the deep SEQ moment, what is your takeaway? Is it something around kind of the optimization of inferencing these models or how have you processed that news now that we're a few months out?

Yeah, I mean they're like incredible at engineering. I think a lot of their open source releases have really like since R1 they've released a lot of code and details on their inference stack and training stack.

Even Sam Altman was suggesting like hey, if you work for a high frequency trading firm, come work at OpenAI. And I read that as like, oh, they want to optimize their models now.

Right. I think some of the big players have realized they didn't have to that much. Of course Deepseek is serving all of China on 2000 GPUs. It's kind of silly that Anthropic can't like has to have the warning about oh we have high limits, please try again later for like their paid users. Like that's. Whereas like the deep seat chat is literally free anywhere. And so I think some other people probably are working on upping their inference efficiency game. But it's also like hard because it's very model specific. Every model has its own quirks and you got to optimize around that. It's hard to like have things be reliable and fault tolerant and then also.

Just so you think you can't just port back like FP8 wasn't that one of the things or like the mixture of experts blocking all those different things. It seemed like there was some stuff that where it was like week two, we were getting analyses and I was like this will probably be open sourced and ported to LLAMA and all the others pretty quickly. But has it played out differently?

I mean to me the surprising thing was not any individual one thing. It's that each of these is maybe like a 30%, 50% gain, but they have like 10, 15 of them that all stack. And so getting all of these to stack nicely is what's hard.

That's interesting. That's a great take.

Yeah, that's interesting. What are you expecting out of Alibaba and Quinn?

Yeah.

3.

Oh, I mean I'm really excited. They make I think still the best model suites for doing research. So I do almost all of my experiments on Quentin models just because they have a bunch of them. There's so many versions for every different model size. There's seven different versions. There's a code one, a math one, a multimodal one, an audio one, a Bass instruct rl. They really are optimizing for user friendly open source model ecosystem in a way that LLAMA was doing last year. This current year we'll see if they can get their act together.

So are they also like RL pilled at this point and moving on?

I'm sure they are, yeah. They have a reasoning model. The reasoning model is not as impressive, but it is a pretty small one. It's like a 32 billion parameter model that does well on math competitions. I don't know that anyone has really bitten the RL bullet in the way that Deep Seq did early and then OpenAI has been doing lately where they're really kind of betting like OpenAI seems to be essentially betting on scaling up RL as the path and that it's not just longer reasoning, but it's reasoning integrated with system interaction. That's kind of the drum I've been trying to beat for a while. A lot of the open source work I've been doing is around multi turn tool calling rl. I think that we need better ecosystems for that. There's like very like there's starting to be more tools you can go use. But for a while there was just nothing that supported this. Everyone was very RLHF pilled for too long.

What do you think is going on with Llama 4? Did they just miss the memo about RL or is there something else at work?

I mean doing this stuff at a huge Company where a lot is on the line is hard and it's way easier to do nothing than something. And Meta also, like, doesn't have to print money off of their models. Like, they don't like. I think one analogy that I've been giving people is like, why did Amazon not win NLP? They had like 10,000 people in the Alexa team in 2018.

Yeah.

And they have just now released like, okay, language models and they're really betting on Anthropic to drive their revenue there.

How are you thinking about the trade war in the context of the data center supply chain? And is that even. Do you pay much attention to that or is it kind of. You're busy enough on the model side?

I do follow it. Yeah. I mean, I tend. I listen to Dylan Patel talk a lot of stuff. He's great. Semi analysis. It's hard for me to like, give a real take, I don't think. I think. I think it's like, important to keep an eye on. There's a lot of pieces of the supply chain that will get. It depends on what happens. Like, yeah, it's gonna get messy for sure. Probably. But I don't have like a. A hard stance.

You should become a VC and then you can just give it.

Yeah, yeah, exactly. You should flip over.

No, I just think it's funny. Like, in a year we'll be like, bro, we were worried about the wrong Transformers.

Yes, yes. The energy thing for sure. I have one last question. How's the culture at Morgan Stanley? I mean, it seems like talking to you, you sound like a Silicon Valley founder, but you're at a company that's over 100 years old. Is. Are you part of a new guard or has Morgan Stanley always been this way and you're just the first to kind of post about it? What's it like working there?

I'm definitely like the first to like tweet a lot about it. But like, the team I'm on has been around for maybe like, it's like a machine learning research team where we try to. We try to be like a version. A finance version of like an MSR or a Bell Labs or where you're like, sure, off keeping up with the research. We write, papers, we publish, we go to conferences. We tend to. We kind of hang around as like expert consultants and advise on a lot of efforts throughout the company. And so the company has definitely been like betting on machine learning for a while. I think we are like, probably ahead a lot of. A lot of like the quant firms in terms of the. How early we were on realizing deep learning was important and I think we've done a pretty good job at like keeping up with and following the like, Ellen craze. Like we were. We partnered with OpenAI before ChatGPT.

Wow.

Wild.

And.

Yeah, that's amazing.

Well, this was great. Let's make it a regular thing.

Yeah. Yeah, for sure. I definitely want to have you back when there's a new model release or something or new paper publish.

If I can do a quick plug. In June, I will be at the Engineer World's Fair in SF giving a talk as a follow up to my previous one.

Very cool. I think we're going. We'll see you there.

Oh, sweet. Awesome. See you there. Yeah. And then also I am doing a course of some kind soon. Official announcement pending. But you really want to like how to get rich quickly agents and RL stuff.

Okay.

And so if you DM me your email, I'll put you on the list for more info.

That sounds awesome.

Awesome.

Good luck with it. I'm excited.

Yeah, this has been great.

Yeah. Thanks so much. Thanks.

Thanks for coming on.

See you.

We'll talk to you later. Bye. Should we go through some timeline and then get out of here?

Yeah. You're a timeline addict.

There's. I mean, there's so many posts and we don't have enough time. There's so much in the. Monday is always a stack day because you have a whole weekend of posts to catch up on. Adam Rankin says you're coding at the bar. I'm drunk at the office. Respect to that. I love that. Aiden says the people I intellectually respect the most have quite lopsided output, input, ratio. They write, build, create more than they read, study or absorb. Geniuses are not sponges, they're volcanoes. I like that framing. That's interesting. I'm kind of going backwards. I think this one from Telmudic. The first time I heard of the gomad gallon of milk a day diet, I laughed. There's no way I'm halving my milk intake for a diet gomad. What are you. You cutting the idea that he's doing two gallons of milk a day? Hilarious to me. Timeline and turmoil. Timeline and turmoil. This weekend, Paul Graham taking shots of Palantir saying, you shouldn't work at Palantir. Gary Tan chimes in and says is now an awkward time to mention I helped come up with the very first Save the. The Save the Shire T shirt at Palantir. Very, very funny. You know, we love. We love palantir we love PG's writing and he is a foundational member of the tech elite. But he gets, he gets spicy with the political takes. He has strong political opinions and he brings him to the timeline and well.

I like that Gary and PG can have a little bit of fun.

Yeah, exactly.

Love to see it.

Web Dev Mason, always with some great takes. There's, there's some people. The blue origin story has really grown since we first covered it. Now people are very upset that Katy Perry went, said it was an affront to real astronauts. They didn't go all the way to space. They only went to the Karman line.

I saw people saying that, you know, how could you go to space when there's problems on Earth?

Yes.

Then you could also kind of extend that out to how could you do anything.

Exactly.

Problems on Earth.

Earth.

I think that's so funny because like, obviously it's like, why are you wasting money on space when there's people that are hungry? But we literally talked to a farmer who was like, starlink is increasing farming yields. It's like, no, actually like going to space and spending on like the crazy thing actually help people eat, which is great. But Web Dev Mason says, this is so sad. Dead culture stuff. Eject me into the timeline where she yanks the microphones in and shouts, I flew over our home world and saw us, the pale blue dot, the blessed sprouting seed of the Virgo supercluster. And I must report to every living soul that it is dope. So she wants she. Because the story is that Katy Perry now regrets going and says that there's been too much backlash. She says that she shouldn't have gone, but Mason says, no, own it. Go and celebrate it, because it is fantastic. Question about watches. We already talked about bezel, but is it appropriate to wear a Rolex GMT as an analyst, I love this answer. It says it depends. Imagine your first all nighter. There you are burning the midnight oil when you decide to take off your Rolex GMT and place it on your desk to allow your wrist better control over the almighty Excel shortcuts you are about to employ. You take a look around and what do you see? Every other analyst has placed their Patek Philippe Calatrava travel time in front of them for the exact same reason. Now, if you, sir, are capable of bearing the overwhelming feeling of shame that will inevitably conquer you, then by all means consider it absolutely appropriate.

Hilarious.

What a great post. It is hilarious. Anyway, we should cover the VCs, the what's going on in higher ed at some point. But there was a good post by Connor. He says VCs are attacking higher education. Trump squeezes higher ed funding. Universities sell PE holdings to fund their operations. VC funding dries up. I don't think this is actually going to happen. The news is that Yale is like selling off a portion of their venture capital portfolio, but I doubt that that really has an alternative funding landscape. And I don't think the university endowments are a major, major source. I think like pension funds are even bigger now and, and like sovereign wealth funds are even bigger.

Yeah. And also very likely, again, I doubt they're reacting to short term pressure. It's probably, you know, Yale selling $6 billion of secondaries probably is part of a larger strategy to generate liquidity on long duration and investments. Right.

So here are some posts that I want to follow up on. We'll highlight them today, but we'll either have these folks on the show or do deep dives on these topics. Person of Swag Adam says vibe sheeting Is this anything he's built Cursor for Microsoft Excel going into the lion's den competing directly with Microsoft Copilot. But we just heard it that some of the Microsoft Copilot products are falling behind a of lot a little bit. And so I thought it was fun that he was building a like a plugin just into Excel and I could imagine this becoming a great company. So excited to talk to him about that and dive in deeper. Also, there's a new planet. Delian mentioned this K2 18B. I did a whole deep research report on K2 18B. Very, very fascinating. Interesting. I had ChatGPT. I had ChatGPT tell me an entire speculative science fiction story about how we might get to K2 18B. Spoiler alert. It's going to be like 500 years to get there. Even at like 0.1 C or something like that, which is the speed of light because it's so far away. But a multi generational chef to understand.

How many episodes we could do in.

Five, we could do a lot.

Quite a lot.

Interestingly, I had ChatGPT. I was like tell me a sci fi story. And like why don't you just make me the character in it? And it was very weird. And it was like now you're in cryosleep for a hundred years. It was like now you're an old man, but because of life extension technologies you're 150 years old. And like, like all like your kids are now older than you because of this weird time thing. It was very fun. Very weird.

All right.

Not a perfect show. Anyway. Last one is notable. Cap, this is a leak from Arthur Rock. Arthur Rock, series B to browser base. Right. Paul Klein, who's been on the show, so I assume one last one.

Last one from near. I like this one very end reminder of how far AGI goalposts have moved. It's from an old book or something. It says an AGI could beat you at chess, tell you a story, bake you a cake, describe a sheep and name three things larger than a lobster. It's also solidly the stuff of science fiction, and most experts agree that AGI is many decades away from becoming reality, if it will become reality at all. So, wow. The last three models I use could describe a sheep.

Couldn't bake. The uk, though, couldn't make humanoids for that. But it can tell you how to bake a cake and it really can do all of those things and more. So, yeah, AGI is here. It's just.

Get on with your life unevenly distributed.

Yeah.

I was at the beach over the weekend and I was thinking to myself, I was looking around, I was like, none of these people are AGI pills. And then everybody went back to enjoying the beach.

Yeah, that's the nature of it. Anyways, thank you for watching today. We will see you tomorrow. We got a great show for you, bunch of news breaking, and we'll talk to you then. Bye.

Looking forward to it. Cheers.