Jacob Peters, Logan Kilpatrick, Roy Lee, Erik Torenberg, Jack Whitaker, Trump Laying Groundwork to Blame Powell for Downturn, Boeing to Sell Some of Its Navigation Business in $10.55B Deal, History of Thoma Bravo, Oil Companies Have Bold Plans to Fix Their Water Problem

You're watching TV. VN Today's Tuesday, April 22, 2025. We are live from the temple of technology, the fortress of finance, the capital of capital. This show starts now. We got a bunch of massive news. The timeline's in turmoil. There's deals getting done and the stock market is way, way up, folks. Way up. People said we couldn't come back. They said it was so over these days. It was not over these days.

A simple rumor might move the market trillion.

Yeah, look at, look at Tesla stock right now. People are like, oh, Tesla. Tesla's done for. Tesla's done for. What? It's up 3%. It's up 3%. Tesla stock. There's a lot of, there's a lot of great news. We're talking about prize bulls today. We're talking about Thoma Bravo buying some Boeing assets. We're talking about tariffs. And what's going on with Jerome Powell. Trump is laying the groundwork to blame Powell for any downturn. I was thinking about the market. I was thinking that we need to just take out billboards just for the market, broadly, the global economy, the American economy needs to buy billboards on economy. Just an ad that just says go long. That's it. It should be taken out. It should be paid for by the government. They should do it on adquick.com out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising only Ad Quick combines technology, out of home expertise and data to enable efficient, seamless ad buying across the globe. What do you think? You think that's a crazy idea?

I'm still laughing about the Trump Powell dynamic.

Yeah.

The idea that, let's move on to that. Trump is, you know, basically doing what every VC would like, which is just demanding lower rates.

Yes, yes.

Ignore the 10 year, ignore the 30 years.

Yeah. People are saying, oh, the VCs bought the top with Trump. He's not doing what they want him to do. He's doing exactly what they want to do. This is all 5D chess to get lower rates. If we get lower rates, we go to the moon. This is great. The central bank's legitimacy is at risk. His president attacks the Fed for cutting rates before the election, but not now. I got a message on signal from someone that was just like our two year treasury was junk status today. Oh, no, not good.

Maybe what Trump is, you know this, this, he read it as central bank centralizing. Verticalizing.

Verticalizing.

Bank verticalizing.

The Fed privatizing. Yeah. I mean, OpenAI went from nonprofit to for profit. Seemed like it went pretty well. Could we like our institutions are more.

Malleable than you think.

Can we sack the Fed? I think that might be the next step here. President Trump is signaling that he will blame the Federal Reserve for any economic weakness that doesn't result, that results from his trade war. If the central bank bank doesn't cut interest rates soon in the process, he might also be seeking to delegitimize the historically independent institution in a way that could undermine its effectiveness, says the Wall Street Journal. In a social media post on Monday, Trump repeated last week's demand that the Fed reduce interest rates. Now there is virtually no inflation, he said, blasting Fed chair Jerome Powell. Mr. Too late and a major loser.

Whatever, whatever anyone thinks about Trump, they have to admit that he's good at coining. Coining. He's good at nicknames. Mr. Too late, quote unquote a major loser.

Powell has always been too late. He misspelled it, I guess in this post because the Wall Street Journal puts in in brackets sic sick for, for misspelling. Except when it came to the election period when he lowered in order to help sleepy Joe Biden and later Kamala get elected. But Common didn't get elected. So it's kind of odd.

It's amazing that the market can be up in a 24 hour period where Trump is attacking the Fed.

We're undefeated. That's why it's that simple. Jordy, I don't know what else you need to hear. His truth social post developed one of Trump's long standing beliefs about the Fed, that it should be more responsive to what the President wants. His statement and those of other advisors allege that the institution, far from being above beltway politics, has already become politicized. This is what I was saying where we should give Jane Street Direct right. Access to the law and to the government and they should just optimize for the stock market value. And so they should just be high frequency lawmaking is what I would call it. And so you just change the law, change the interest rates, just do whatever you can to just maximize shareholder value at all times.

I think that's kind of like Jim, you know Jim, is it Jim Simmons, right?

Yeah.

If Jim had had right access to the Fed, he could have.

It would be a golden age for trust the computer turbo long.

Trust the computer.

Yeah, trust the computer. By Trump's account, Powell worked with, worked to help Biden during his term and is now unwilling to provide the same support to his own second term agenda. He put no weight on the fact that Trump appointed Powell to the role in 2018, that Powell worked closely with his administration in 2020 to provide unprecedented support when the pandemic hit, or that the Fed was prepared to settle Biden with a recession in 2023 by raising interest rates sharply to bring down inflation. Wall Street Journal Putting Trump in the truth zone a little bit here, but we'll see where it goes.

Could be the poly market, will Trump remove Powell in 2025 is still only at a 20% chance. It is jumped dramatically from yeah, I.

Mean, if you're tracking this stuff, there's a lot of noise on either side because it's a highly partisan issue. But that is why I like Polymar. Obviously they're a sponsor of the show. But I think that, you know, the one thing that we've learned from the last few years is that these prediction markets are not politically biased because people just want to make money when they're in there. And so it's a much stronger signal, in my opinion. Anyway, the next Wall Street Journal story happens to be Boeing is selling some of its navigation business in a $10.55 billion deal. Ring that size Gong Jordy. The agreement includes the sale of Jepsen Foreflight Air Data and Oz Runway software. Investment firm Thoma Bravo, the Arlington, Virginia based aerospace giant said Tuesday that the definitive agreement includes several assets that provide digital tools and services for aviation operations, such as Jepsen, a provider of navigation charts and flight planning for pilots and airlines and Foreflight, another flight planning and navigation app that helps with route optimization, weather tracking and flight management. That has been a big issue. There was this crazy backup about a year ago. Do you remember this? Where Southwest was was trying to do like all the different routing and everything got knocked offline and it was all just because they had this like, you know, kludgy system that was far too big. It's a. Yeah, I mean, yeah, it's.

Interesting to think about how much Bravo.

Goes into a basically asset.

When people think of Boeing, they don't associate it with quality. Right. They went, you know, they've been suffering through a PR crisis, a quality crisis, whatever you want to call it. But it's interesting to think about this set of software providers as basically being critical infrastructure. Critical software infrastructure for aviation broadly.

Yeah. Let's go through a little bit of this. I want to do a little bit of a deep dive on Thoma Bravo because it's a name that comes up a lot. But I don't think people know the history of the company and they think it's one of those. Like they're not out there. They don't have a marketing organization really. They're kind of behind the scenes.

The deals tend to market themselves.

Yeah. And then every once in a while, while you'll see one of those threads that's like, this is the best secret company that no one knows about. Like, maybe you should start a competitor. It's like, no, you shouldn't. Have you ever thought about applying artificial intelligence to private equity? I don't think anyone's thought of that. Could be a good opportunity.

Good opportunity there.

Great opportunity.

No one's thinking about that.

Yeah, no one's thinking about that.

Why has no one thought of private equity? Has not at all been thinking about driving business efficiency with software for the last 20 years. They wouldn't even dare.

So Boeing is trying to slash costs and raise money as it burns billions of dollars a quarter and struggles with equality crisis in the wake of last year's fuselage panel blowout on Alaska Airlines flight. That was exciting. I there.

A lot of their losses are staggering.

Yeah. A lot of people are saying, I'm not flying Boeing. And I always said, if it ain't Boeing, I ain't going. Because oil. Yeah, because. Because as a white collar worker, as someone who, you know, typically, you know, I'm not on the front lines, I'm not in a trench war, but I feel like I would fight a trench war for Boeing, for, for Boeing, for ramp, for bezel, for wander. I think people believe that I need some excitement in my life. And so if I get on a plane, it's normally very anodyne, but if there's a, if there's a risk, there's real risk. People know I'm putting my life on the line business. All of a sudden it's real. That fires me.

No. And this is why Nathan Fielder's new show, the rehearsal, is fantastic because it's all about aviation safety. The timing is perfect. I think what people. I didn't have full respect for this. I do now because we've had a number of guests on the shows, on the show just how difficult it is to manufacture large commercial aircraft. China has not been able to really get their national champion to any type of real scale. It is extremely, extremely, extremely difficult.

The phone.

We should support Boeing. Yeah, I support Boeing.

I completely agree. Yeah. I mean, the phones, the fact that they're small, I think does make it way, way easier, which is silly because it's a really complex device, but it just is Smaller. And so that means you can move them around a bunch of different, you know, manufacturing lines very efficiently. And then also it's very low stakes. There have been phones where the batteries have melted and the phones have exploded and people would just be like, oh, my phone's hot, I'm putting it over there. Yeah, they survived, but that cannot happen on a plane. And so it's just a completely different safety infrastructure. And then we talked to the, talk to a couple of founders that said that one of the key SpaceX innovations was let's make the motor, the rocket engine, so small that it can fit in the back of like a truck bed as opposed to something huge that needs a crane. And every time you're working with something that's that massive, your supply chain is now three different companies instead of 30. And every time you need to move anything, it's very expensive. So.

Chief executive of Boeing Kelly Ortberg last year said he would cut 17,000 jobs. He also raised more than 24 billion in equity to keep the company afloat.

Good fundraise. Honestly, that's numbers. You know, you got to give it up to a guy who's, who's putting up big fundraising numbers.

Yeah. Executives have been exploring asset sales that could bring in much needed cash while shedding non core or underperforming units. An approach Ortberg has described as prun the jet maker's portfolio rather than overhauling it. Analysts say the sale is a mixed bag. It delivers much needed cash, but given that Jeppesen is profitable, could come at the expense of longer term profits. As part of the agreement, Boeing will keep its core digital capabilities that use aircraft and fleet specific data to provide fleet maintenance, diagnostics and repair services to its commercial and defense customers.

Yep, they're selling Air Data, which specializes in aircraft leasing, maintenance and asset management, digital solutions and OZ Runways, Boeing's Australia based provider that helps pilots with planning, briefing flight plans and navigation. Digital aviation solutions segment employs about 3,900 employees across its global operations, a figure that includes those employed in the business that will remain within Boeing and those included in the sale. So it's kind of an aggregate number and the transaction is expected to close by the end of the year. And if they're trying to, you know, sell, sell bottom flight software all over the country, they got to get on numeral.

That's right.

They got to put your sales tax on autopilot, baby. Spend less than five minutes per month on sales tax compliance. Go to numeral Benchmark Series A, Benchmark Series A.

Go Check out numero thank you to numeral supporting the show.

Quick background on Thoma Bravo. Started in the 80s, Stanley Golder and Carl D. Thoma founded golder, Thoma & Co. In Chicago. Golder had already made a name at First Chicago Corp. Where he backed early successes like Federal Express, FedEx and helped open pension fund investment to private equity. Carl Tomo was a Stanford MBA from rural Oklahoma and he shared Golder's vision of a gentler approach to leverage buyouts. It's going to be gentle, gentle, just a gentle LBO activate Go golden retriever mode. Yeah, he's being very nice. Together they pioneered the bill, the buy and build strategy. Rather than hostile takeovers or asset stripping, they acquired small businesses and grew them through add on acquisitions. So this is very much in line with like technology powered private equity but back in the 80s so they're saying we are going to LBO, we are going to use the tools of modern finance but instead of just asset sales, strip, hostile takeover, cost cutting, like the traditional, like the bad, like the, oh, it's private equity so rough. They're thinking of more of like a growth mindset. So they brought a growth mindset to private equity basically.

Yeah. And bringing it up since it was part of the conversation yesterday we had David Tish on talking about venture roll ups basically. And one of the reasons we were kind of joking about it is that there's been many, many, many players in software private equity for a long time.

For a long time who are buying.

Businesses and saying that we're going to leverage software and even saying that we're going to leverage artificial intelligence to make these businesses more efficient. So the idea that people in venture are going to come in and out Fox Private Equity, which is cutthroat, efficient, professionalized anyways. Yeah, I do believe there's opportunities. There very clearly are opportunities. But it's not a. Oh no, it's.

Not a blue ocean market.

Yeah, it's not a blue ocean.

Yeah. And it's funny because you know Thoma, he's known for being a savvy investor but he has this folksy demeanor because both of his parents were ranchers. He's from Oklahoma and kind of like, you know, good old, you know, Oklahoma boy. And so he was able to kind of like match that folksy demeanor to these friendlier buyouts that are focused more on long term expansion. And so in the early years they applied these buy and build across fragmented industries, buying up niche companies and rolling them into bigger platforms. Very much.

Boeing deal. Yeah, they're they're buying an existing basket of assets and I'm assuming they're going to add to it.

Exactly.

And then eventually they'll probably take it public.

And so this approach is common now in private equity, but it was novel at the time and it earned Golder and Thoma credit as its originator. So they're like the originators of the roll up, the private equity roll up, the one that we like know and love today and, and often, often profile. The firm partnered with incumbent managers and avoided the 1980s stereotype of the ruthless corporate raider. By the mid-80s, their success attracted new talent. In 84, Brian Cressy, a 4First Chicago colleague of Golder, the other founder of the firm, joined the partnership. The firm was renamed Golder, Toma and Cressy, making the first of several name evolutions. If you're working at an investment firm, maybe you're an associate at some VC firm.

Try to get your name, get your.

Name on the firm, get your name added to the firm. Exactly.

Yeah. So like if you were an associate at Sequoia today, you might.

I was pitching Founders Fund. I was like Founders Fund and Cougin Founders Fund. That was what I was like. This is where I'd like this to go.

Yeah, yeah, there's, there's plenty of precedent there.

Right, Totally.

Kleiner Perkins.

Kleiner Perkins Caulfield Buyers.

Yep.

And yeah, you know, who knows, maybe it'll be Kleiner Perkins, Randall and Lee Marie.

Yep.

Braswell. Because they are the new blood over at kp, if you haven't been paying attention. Anyway, Stan Golder became a legendary figure in private equity. He chaired industry associations and helped legitimize PE and pension portfolios. That's really big for asset accumulation and getting bigger deal sizes done. You need a ton of LP dollars. And so once the pensions come in, they have trillions of dollars under, under management across all these different pensions. And he helped pitch PE as a reasonable asset class, which now it's like the most obvious venture is the one we're talking about. And then there's even more like, oh.

Can, can pensions be crypto private equity, totally broadly. And then venture is a fraction of that.

Yep.

And these, you know, pension funds are over, you know, deploying in PE just simply because it's more stable and there's a lot of other reason for it.

But so, so Golder is really key in legitimizing private equity in these pension portfolios. Carl Thoma has this mix of like Midwest pragmatism and Stanford training. Like he is a serious deal maker, but so he emerges as like this creative dealmaker who also prefers building companies over just financial engineering. And so a lot of companies like, you know, it's all about like the, the waterfall, how they're going to pay down the debt payments and like create value there. He's more about that company building mindset. And then Brian Cressy, the third guy on the team at the time, he brings this jd MBA from Harvard and a particular eye for health care investments. So they make some, they make some interesting deals there in the early stages.

So the three of them, they have, they were collaborative, growth oriented, focused on specific sectors where they could rinse and repeat acquisitions. And by the late eight Rinse and repeat.

One of my favorite things to do and consolidate.

Yep, there's nothing like a little consolidation with your.

When I think of rinsing and repeat, I just think of one hand washing the other. Just one of my favorite things.

It really is.

I love it.

By the late 80s, the firm which was now managing several small funds had proven the efficient efficacy of consolidating businesses and which is, you know, broadly a template that they would continue to use.

Yeah, and so they add another bro to the, to the crew. They go to GTCR way before Tom and Bravo Golder, Thoma Cressy and Rohner Rauner. I don't know how to pronounce that. They bring on a promising young exec, Bruce Rahner. And he'd risen to partner. His name was added in 1987. GTCR became one of Chicago's top buyout shops, investing through the late 80s LBO boom and navigating the early 90s recession. They specialize in roll ups across industries like healthcare, media, financial services. And by the mid-1990s they had some differing visions among the senior partners and the firm. Success had created these like small, strong personalities and strategic debates, as often happens. And so there's like this culture clash a little bit between the original founders and then the newer generation. This happens a lot in funds because you know, you're like the partnership is bought in, but you got to bring in new blood. But they're going to want to do something in a different way and that's going to lead to some culture clashes. And so in 1980, in 1998, GTCR's leadership decided to part ways, splitting the form, splitting the firm into two different entities. So they actually split the firm. On one side you have Stan Golder and Bruce Rauner. They stay with gtcr which continued focusing on varied Industries from a Chicago base. On the other hand, Carl on the other, Carl Thoma and Brian Kressy spun out to form Thoma Cressy Equity Partners, taking a team to pursue their own investment focus. And the split was amicable, but they had strategic differences and they wanted to try different approaches. And so GTCR pursued the broader mandate and then Golder passed away in 2000. But GTCR lived on.

Yeah, GTCR lived on. And what I love about going to private equity websites, these firms websites, is that in venture you'll have a fund with like 10 million AUM and they'll be like we back and build the future.

Yeah, it's like it's got a video, it's got like every company they've ever.

Done transforming business to build value and they have like 200 billion AUM.

Some might say that VCs should do that more often. It's great. And so basically like the incarnation of Thoma Bravo that we're thinking about now, Carl Thoma and Brian Kressy, they, they really focus on tcep. That's Thoma Cressy Equity Partners. It's a standalone firm in 1998 and they're continuing this buy and build model but with a fresh canvas. And so Kressy has the healthcare expertise. He's steering some of the investments toward health services. And Thomas looking at fragmented business services and emerging tech niches. Still very technology driven. And then this is where we get to Bravo.

Boom.

Orlando Bravo, great name. Enters the picture in 1998.

Comes out of Stanford, Stanford JD and NBA first round draft pick to the private equity ranks. He made this is a good, this is a good lesson. He had been frantically cold calling PE firms looking for a job after roughly a hundred, a hundred calls.

Wow.

His resume caught Carl Thomas attention and they quote unquote hit it off, dude. He was 27 years.

99 Puerto Rican JDMBA has quit right before their 100 cold call to get that PE job.

The the existing partners said it was the smartest investment they ever made.

That's awesome.

He was 27 at that point and became an apprentice.

Yep. And so Toma Cressy, Brian Cressy, the co founder of Tomo Cressy is a seasoned deal maker with a potent with a penchant for healthcare deals and a reputation as an industry consolidation guru. He's educated at University of Washington and Orlando. Bravo is raised in Puerto Rico. He'd been junior tennis champion who attended Florida Tennis Academy in his teens. He returned home for high school, then excelled at Brown before heading to Stanford by the tome. By the time he joined Carl Thoma in 1998, Bravo's drive was evident. The same drive that would soon reshape the firm's direction. I love these like deep dives on these obscure firms. So the new firm Thoma Cressey entered the dot com era cautiously, but caught attention. But even caution couldn't spare it from early missteps. Basically everyone lost some money in the dot com bust a little bit here and there.

What's. What's a few billion among friends?

Indeed, Orlando Bravo's first assignment in the late 90s were tech related investments that turned sour. In his late 20s, Bravo led to startup deals Nervwire and Eclipse Networks just as the tech bubble was peaking. When the bubble burst around 2000, Bravo's first few deals were disasters. Losing most of the $100 million invested in. That's pretty crazy to go from. I mean that's the nature of pe. Like you go from Stanford to PE and even though you're, you know, like an associate or like new to the firm, you're deploying big money and it doesn't go well.

It's rough. Schwartzman's first investment at Blackstone where like I'm pretty sure that his first deal like went terribly. Yeah, so there's like, there's basically precedent at this point of PE size lords like you know, basically fumbling the first deal and then just coming back in a, in a big way.

Learning a lot. That's why I've been asking some of the VCs that come on, like what was your first deal like? What did you learn from that? Like, I think that's an interesting line of questioning.

And then there's some, some who are, we've had on the show and they're like, my first three deals were unicorns. Justin Maris was like this, like, it was like his first investment was like went public or something like that.

Yeah, but you learn different lessons from that. But Bravo said, I learned I didn't want to invest in risky things ever again. He's like, I was permanently risk off after the, the dot com crash. It was too painful to live through. This hard lesson would shape the firm's strategy. Rather than chasing raw startups, Bravo realized they could use their capital to buy established companies with steady revenues, especially in software, and apply the build and the buy and build playbook there. And so they pivot to software. This happens in the early 20s. Even though they're getting burned in the dot com on startups, they realize that there's incredible value in technology and software. And so the insight was that the economics of software were just so powerful. It was like no other industry, very obviously. Bravo. Later said in 2002, he spearheaded their first software buyout, Profit 21, which was a niche ERP software provider for distributors. Tech buyouts were uncommon then because most of these were still venture backed. They were on the IPO train.

IPO lenders at the time, a lender was a lot more willing and excited to lend against a real estate portfolio, a fleet totally vehicles, things like that. Right. So lending against software that where. Where they were like, what are we really lending against? How is this secured? It's secured, you know, on the.

And so they did it without. Without lenders really. I mean, lenders were pretty wary of these tech buyouts. And so Toma Cressy had to structure this profit 21 acquisition with almost no leverage, which, you know, you hate to see because we love leverage. But they also brought in their first operating partner, experienced software executives to turn the. To help turn the company around. So they have a deal team and then they also have an operating team. Once they buy the company, they actually help install executives that can go in and start growing the business and optimizing things. Because a lot of times the companies that they're buying, founders might be out, they might be a little burned out. The company might not be running as efficiently. It's kind of just like, hey, it's humming along, it's profitable, but it's not as good as it could be. So they want to make it great.

And the firm's job is to place immense pressure on the management team to hit very aggressive goals.

Yep. Strauss did something similar with, with Take Two and the GTA franchise. He came in, that company was sitting on incredible intellectual property. They owned 2k games, like all of the different basketball games. And then also gta, like the greatest gaming franchise maybe of all time. But it was just like, it was just a creative mess. Like they would just like have fun. And they were under. They were under like FTC investigation and SEC investigation. Like they, they weren't even like trying to cook the books. They were just so sloppy and messy. They didn't care about the books. And so their accounting was all off. And there were all these different lawsuits going on. And Strauss came in, wind up buying the company for like kind of $0. It was a crazy deal.

We crazy.

We should dig into all that. But basically he gets the. He gets the company and immediately starts running it like a professional business because he's a beast of an operator. And so Prophet 21, this first tech acquisition, did really, really well. So they exited with a 4.7x return on investment. And this was an early win in software with minimal debt and just hands on operational fixes. And it really cemented the firm's new direction.

So middling outcome if you're a venture capital firm, but if you're a PE firm that's going to a bunch of.

Those and it feels repeatable at this point. Feels repeatable like there are other companies that are in profit. 21's like, like segment and, and that playbook can be run again and again. So Orlando Bravo, he's just 30 years old. He gets promoted to partner in 2001. On the strength of those efforts, being.

Promoted to partner at 30 in 2001 just sounds amazing. Sounds amazing. No, the timing is perfect to go on this generational run in software.

Oh yeah, yeah, yeah, yeah. I mean timing is, timing is a lot, but it might not be everything. But he really nailed it there. And so software deals started piling up. Orlando Bravo's influence within the firm grew. By 2005, Carl Thoma and Orlando Bravo had recruited a trio of new talent. Scott Krebel, Holden Spot and Seth Borough joined the investment team to focus on software sectors. All three of them are with the firm today as managing partners. One of them came from Summit Partners, the other had experience at Morgan Stanley and the last one was also at Morgan Stan at Summit Partners and history of investment banking. So a pretty common path into private equity from banking and other deal making organizations. So this, so this. As they're growing the team, they can also scale up their deal flow. In 2007, they rename the firm because they love Orlando Bravo. The firm is renamed Thoma Cressy Bravo. Overnight success. A year later, 2008, co founder Brian Cressy decided to depart. Cressy spun off with a team to form Cressy & Co. Refocusing on healthcare investments. Because Thoma Bravo of course is doing tech stuff and he's doing healthcare and they're, and they're just slightly different strategies. So they split the firms and then the firm renames to Thoma Bravo LLC. Officially born 2008 an overnight success. And today they're buying Boeing assets for $10 billion running kind of the same playbook. It's a boring software company that's just profitable, growing.

But a series of software companies, yeah, a whole bunch go bolt on stuff.

Too and just continue to grow that they're not dipping their toe in the, in the super hot, high growth startup market, they're going for just, hey, there's some great software assets, they're installed a bunch of places, it's critical. They built a bunch of stuff. This business is good, we can make it better. Yeah.

And I'm sure they'll look at venture assets that are eventually, you know, maybe they don't reach escape velocity, get to, you know, 100 million of ARR, but not quite breaking out. But they will be very sort of aggressive in terms of valuing these businesses. And certainly, you know, if, if Thoma Bravo is buying your company to bolt on to an existing sort of roll up, very unlikely they'll give you a revenue, you know, 100x revenue multiple. It could very well be a 1x. It could be less than that, could be more if you're growing quickly and have a real path to generating cash flows.

But as they, as they scale up, they start doing more and more ambitious projects. They eventually scale from, you know, mid sized PE firm into just like a complete heavyweight in tech buyouts. In 2012 they do a $1.3 billion take private a Bluecoat Systems, a cybersecurity company. And Bluecoat had solid technology but needed a strategic overhaul. And Thoma Bravo takes it private, improves operations and later sells it for four and a half billion in 2015. So three years they go from 1.3 billion to 4.5 billion. And of course at this point they're also able to use leverage because they have better access to the debt markets. And so they're even, they're making even more money. I'm sure you're trying to pull up a size gong of some sort.

I'm trying to pull up a lever.

Up, but, but they pull up this risk on, but they, but they basically got a pattern. They buy a public tech company, they optimize it privately and then sell or IPO at a much, much higher valuation. And this is, this is the whole, you know, take private strategy is like it's very hard to completely turn the cruise ship or the battleship in the public markets because your stock's just going to get completely hammered while you go down for a couple quarters because you're saying, hey, there's a business over here that's really, really damaging us. It's low margin, but it's going to hurt our revenues. And if somebody's looking at you on a revenue multiple, they're going to be upset about that. Or you know, there could be a number of different things that could look like red flags. In the public market. But if you have a couple years to rebuild in private, you have, you can, you can just take more risk. You can go risk on and risk on.

Yeah. The other thing that they're doing, just because a large part of our listener base is venture, by using leverage, they can get a much higher return on their equity. So if they're buying a company for a billion dollars, they might in some circumstances only put up, you know, $200 million.

Right.

So when they, they turn that $200 million into a 4 billion, you know, $4 billion outcome, it can be very meaningful.

So there's, there's one more funny deal we got to go into by 2018. Thoma Bravo is doing regularly doing multibillion dollar deals. They're, they're in the same conversation as Silver Lake and the other big tech buyout firms in partnership with Silver Lake. In 2016, they buy SolarWinds, this IT management software company. Are you familiar with SolarWinds at all? Okay, so SolarWinds is IT management software. They will go in the network, watch for what deployment's happening. It's like kind of middleware for deploying software at a large enterprise. But there was a hack where it was a very, very bad SolarWinds hack. Do you hear about this? And so basically someone injected something into SolarWinds. So then that was what's called a supply chain hack. So every company that had SolarWinds was now vulnerable. And it was like a really, really brutal attack. And it was funny because I was doing it, I was trying to understand like the history of SolarWinds. And I found the founder who had built the company, sold it like exited like years and years ago. And he had gone on Shark Tank to pitch a cooler, like a, like a, like an actual cooler that you could put like beers in legend. Because he was like, yeah, I activate golden retriever mode. It's truly golden retriever mode. Mine's. So he, he started this cooler called the Coolest. And it was, it was a cooler that you put ice in, but then it also had a fan. So it like provide you air conditioning when you're hanging out with your buddies, watching the baseball game or something. He was clearly like post exit founder, just like hanging out with the kids. Like, yeah, wouldn't it be cool if like we had a better cooler? And so he goes on there, he pitches it, he explains that it's like a thousand dollars or something. Because of course he's like, oh yeah, a cooler, like, what does that cost? Like a thousand dollars? But he Tells the sharks that he's like, yeah, I founded Solar Winds. And you'd think that would be like total bull signal, right? You know, just like, okay, this guy built a billion dollar business. Like yeah, he's probably can figure out like the cooler market. But all the sharks pass, they all say no, they all say they're out. Anyway, fascinating little side, side tangent.

Anyway, yeah, the unfortunately coolest cooler shut down after a five year saga. 20,000 people that backed up the Kickstarter actually get the brutal.

Yeah, very rough. But Anyway, I mean SolarWinds wound up being a great company and Thoma Bravo I'm sure made a bunch of money and then they had the hack and I'm sure they rebuilt from there. But all of that is to say that like Orlando Bravo became known as, you know, an incredible dealmaker. He was on the COVID of Forbes in 2019. They called him Wall Street's best deal maker. Pretty great. He was the first Puerto Rican born billionaire in finance. He was on the Forbes 400 list. The Financial Times nicknamed him the King of SaaS. We love that. A lot of people vying for that at a lot of venture capital firms. But you're going to have to go up against Orlando Bravo, the king of SaaS, the best deal maker in the world to really, really own that name. Bravo's war chest grew. They got a fresh $12.6 billion fund. Now they're eyeing a 10 billion plus deals. And we just saw that with Boeing, they did a $10 billion deal. How'd they do that? They raised a massive, massive fund. And there's a bunch of other interesting deals that they've done. But they're doing mega deals.

Yeah. Just to give you a sense of some of their bigger deals, they did proofpoint at 12.3 billion. The Boeing digital aviation is actually their second largest which hasn't obviously closed yet. But anaplan 10.4 real page 10.2, sail point 6.9 medallia was at 6.4. Acquisition bin darktrace 5.3 sophos click imperva. Yeah, Absolute size lords. You don't need to do that many of these deals.

Yeah.

To put up some very large.

Although there is something unique about the Boeing deal that was announced today is that this is kind of the start of a new strategy for Thoma Bravo. We've seen a lot of traditional private equity deals where they buy a private company, do an LBO and grow and buy and buy and build that buy and build strategy. Then they start doing the take private turnaround. Strategy. They take a single digit billion dollar public company, take it private, change the strategy, try and sell it later, or take it public again, exit the position. But they also are starting to do carve outs in 2023, 2024. And that's what the Boeing deal is. They're carving out a piece of Boeing's business and then, you know, packaging that up as an entirely new business. And I mean, it is a different operational challenge because it's not operating completely independently. And so, you know, you're going from being a Boeing employee to being an employee of a new company, a digital aviation software portfolio that's owned by Toma Bravo that will eventually have a brand and be like a, you know, cobbled together from all these different assets. Anyway, let's move on to our next story. The oil patches Manhattan Project, how to fix its gargantuan water problem. I thought this was interesting. I had no idea the ratio of oil to water when they are fracking. So for every, for every barrel of, for every barrel of crude oil that's pumped, they are now producing four barrels of water. And so this is on, this is happening in West Texas and New Mexico around fracking. The, the Permian Basin is the, is the location. And so there's a big question about what do you do with the gargantuan amounts of noxious water that they produce because it's gross and you need to filter it or treat it if you want to put it back in the water supply. So typically what they do is they just pump it back into the ground. And so if you go a few slides forward, there's a graphic of what they do. They're taking oil, oil rich shale, which is how you frack. So you blow, I think like air and water into the ground. You suck up the oil that's there. The oil's very, it's not like a clean pool of oil. There's a whole bunch of other stuff in there. You pump all that up. This is about two miles down. Then they kind of filter out the oil, take the oil out and then they pump the water back down, three miles down. But that's causing earthquakes. And so people are upset about that. They're playing God. We don't like that. We don't like earthquakes because they're pumping so much.

Just like a word. Yeah, yeah. So we can kind of go through this. So.

So they're trying to evaporate the water, which is interesting.

Yeah. So they're basically producing all this wastewater. It's just sort of like sitting There in a pond and then they have a system to effectively try to get it, just disappear it, disappear it into the atmosphere. So there's a picture here. I don't know if we can pull it up but you can see it's a fascinating image. So there's these evaporators hum on a huge saltwater pond in the middle of the biggest oil field in the us they are part of an experiment by Exxon Mobil to address one of the challenges facing Frackers in the Permian basin. And.

All these crazy economic projects to, to, to process all the side like you know, waste products from this. But it's all part of, you know, the goal to help unleash American energy. And you know, I'm generally in favor of figuring out new ways. I mean fracking was in many ways like a miracle in terms of America's energy independence. Very controversial.

The meme that's like America's like you know, struggling and then we just discover like immense, oh no, we're out of rare earth.

Yeah, oh no, we're out of rare earth elements. And then it's like, oh, we found the largest deposit ever in like Utah. Companies in recent years have made strides in treating brine and recycling it for their operations. But more water flows back to the surface than they can use. Meanwhile, as the volumes of liquid they can pump in the ground have shrunk as companies have started to run out of underground space and regulators have imposed limits on disposal to prevent earthquakes, enter the evaporators. Exxon, which is the largest Permian producer, started testing the machines about a year ago as a, as a pilot project. The device is manufactured by Colorado based RWI Enhanced Evaporation. A little hard tech company. Got to get the founder on. They blow air down on the pond.

Probably been like around 200 years for sure. Evaporating for about, you know, who knows.

Who knows, Maybe RWI is just like, you know, seed stage startup. They just went through YC, you never know. Yeah, don't judge. One machine costs $46,000 and consumes about as much electricity as a wet dry vacuum cleaner. RWI estimates that between 20% to 50% more liquid gets vaporized that way compared with natural evaporation. And it's interesting because like if this water truly is like underground, is it something that when it's brought up in the atmosphere it's going to wind up like if it gets purified and evaporated, does it wind up going into clouds? Does it wind up getting seeded? And does it wind up making the Land in that area more verdant because there's more water, or was it already considered in that equation because it's kind of groundwater, or was it buried so deep it doesn't.

I mean, these things. Like the primary thing here is environmental concerns, right?

Totally.

If you're a farmer trying to grow organic, you know, food, or you have cattle oil raining down on you, Oil.

Water, sounds like acid rain.

Sounds, sounds bad. But I'm sure that RWI would argue that, you know, there's some chemical process that means that the water itself is, you know, potentially just as pure as rainwater. Yeah, it's hard to tell.

I mean, evaporation is pretty effective. It's separating things out. That's how it's done in.

But this is like a very long running trend where, you know, looking at the production side for groundwater in these areas, specifically for oil and gas production, for a very long time, if you owned a piece of land, you were legally allowed to pull as much water as you wanted out of the ground. And what happened is regulators, governments, states, et cetera, realized that no water is a shared resource. There's effectively rivers that run underground that are, you know, tied to aquifers. Those aquifers can stretch across multiple states. Right. They're massive. And so, you know, one private company, it seems like, broadly, you know, we need a change to regulation and energy. You know, across like, you know, we've had a number of nuclear founders on.

But the nuclear thing is huge for desalination.

Yeah.

It seems like almost impossible and a perfect match because you have such concentrated energy. You can just throw the nuclear power plant right next to the desalination plant. You have all the energy can run 24,7. Like it's perfectly matched as opposed to a lot of other systems.

Yeah, One of the. Yeah. The issue with this fracked water is that it's salt water.

Yeah, yeah.

And that means that you can't just go spray it on plants or you can't put it on crops. It will just kill everything.

Yeah, it's bad. So this is interesting. Last year, Permian drillers discarded roughly $5.5 billion billion barrels of water by pumping it back down into the ground. Right. So 5.5 billion barrels a year. That's what I want you to keep in your mind. 5.5 billion barrels a year. So they're doing a, so an injection.

Well, 42 gallons per barrel, by the way.

Okay. So an injection well typically guzzles between 10,010, 25,000 barrels of water a day and an an evaporator working in optimal, optimal positions, optimal conditions, vaporizes about 32 barrels an hour. And so now Exxon is trying to build a commercial sized desalination facility operating in the Permian by the end of the year. Last month they, they, they commenced a pilot project. But the testing that's happening, the desalination technology is doing 20 barrels a day. That's the pilot. So 20 barrels a day is, is 700 barrels a year compared to not making a dent, compared to 5.5 billion? Yeah, like we're off by so many orders of magnitude. But at the same time, like, you have to start small and you have to, and you have to, you know, run the test to see can you actually purify out all the toxic chemicals in the water and does the actual scientific process work. And then it becomes an economic equation of, of what happens. So they are scaling up, they're going to do a $25 million desalination facility with an initial capacity of 10,000 barrels produced a day. And then, and there's plans to build a plant that's 10 times bigger next year.

Yes, this is the challenge. So generally with oil production, you think it's just about how do we get this out of the ground? Yep, it's how do we get enough water to support this process and then what do we do with that water after the process to dispose of it. And you're being regulated on both sides. Right. I have a portfolio company called Resource Monitor that helps oil and gas companies basically stay compliant on the production side. So they're producing all this water and they get budgets from various groups on how much water they can actually produce. But that's only, you know, one part of the problem here.

Yeah. So the goal is to bring the cost of purifying a barrel down to 75 cents, which is slightly more than what it costs to flush the wall, flush it down the well there. This 25 million desalination facility is going to do 10,000 barrels a day, which is 3 million a year. But remember we're 5 billion. Yeah, we're producing last year and then they want to build one that's 10x bigger. So that'll get you to 30 million, but you're still two orders of magnitude off. Two orders of magnitude 100 times. They're going to like, if they build this 10x plant, they will only be doing 1% that they're pumping down into the ground. It's actually crazy, the scale of this thing anyway, you know, they're trying to scale up and there's a bunch of companies that are working on this. Anyway, if you want to go hang out in Texas, book a wanderer.

Find your happy place. Find your happy place.

Book a wander with inspiring views, hotel, great amenities, dreamy beds, top tier cleaning and 247 concierge service.

It's a vacation home, but better.

And in most of those homes, you're going to find really, really nice lighting. And that's the topic of our next story. Offices are ditching harsh fluorescent lights. New tech is on the way. I think this is going to be extremely controversial because the new tech, it doesn't sound lindy. And so we're going to have a debate over whether or not the path to better lighting is more advanced technology or do we need to go back? Do we need to go back to incandescent candlelight?

They were going to say every office will be required to have a warm.

Fireplace, a warm hearth.

A hearth.

A hearth. Yes.

We're going back to hearths.

We should go back to that.

I was joking the other day. I think, you know, on the topic of lights, I think Apple, to really differentiate, should come out with an iPhone UV that sort of gently tans your face.

That sounds like a real product. The iPhone UV.

The iPhone UV. It gently tans your face while you use it.

Yes.

And I think they've got a hit on their hands at least in Los Angeles.

Yeah, yeah. They do the blue light filter. They can take the blue light out. Why not add some UV light in? Yeah, I love it. From faux skylights to circadian tuned systems. Lighting upgrades are a priority for companies trying to lure employees back to the workplace.

Faux faux skylights.

I know the faux skylights are crazy, but it's going to be really big when I build my Batcave that's three stories down deep into the ground because you're going to want 24, 7. It's going to be like Las Vegas where like you can't tell what time it is and you just get lost in the. It's going to. It's going to have like a kind of severance vibe. That's what I'm going for in my basement when I build. Glaring fluorescent lights in the office are on the way out. The technology is coming in. Promise to do much more than make everyone look better. Improved and potentially more healthy. Lighting is high on the list for companies and building owners trying to lure employees back to offices after an era of remote work. They are investing in new technology such as faux skylights that mimic natural light, complete with a virtual sun and moon and adjustable illumination systems designed to sync within play circadian rhythms. I wonder how long until this becomes a culture war issue because, you know, that air conditioning thing became a culture war.

Incandescent light bulbs were banned.

Yes, they're. Yeah. Extremely hard to get in California. I've been struggling with this for a long time.

Sort of like re legalize them.

Yes. Hear about this. But that sounds cool. I like an incandescent light bulb. I'm a fan. I like a tungsten bulb. We've known for a long time that natural light is better and makes people feel better. So it's not a completely crazy idea. Says professor at Wharton.

So aside from the psychological benefits, research studies have shown that light can can have an impact on non visual brain function during cognitive tasks, particularly those that involve sustained attention. Office lighting revamps are expensive. Installing some of these technologies can add 20 to 30% to the cost of a project, those in the industry say. And it could take time for them to become mainstream. I'm assuming that's 10 to 30% more expensive than the existing light solution.

You know, Stanley Kubrick shot a film entirely using candlelight. And he had to collaborate with NASA to make a new lens that could absorb even more light. So he could shoot in darkness, essentially. And now modern filmmaking techniques, technology has gotten so good that the cameras that we shoot on can basically shoot in the dark. And so I think for the next set, we might want to consider just a warm hearth, a nice fire.

That's right. Something there.

There's something there. Some nice. A candelabra that we just light and that lights our face. It'd be a very different look from your typical new show, but I think that's what would make the show special.

Well, once we go to 24 hours a day, yeah, we're gonna want to be. We're gonna obviously have eight sleeps on the floor. We'll be able to sleep, you know, in cycles for the subathon. Yeah, yeah, yeah. So there's something there. So programming the day playing into post Covid wellness trends, Office designers are exploring so called circadian rhythm lighting to sync with the body's circadian rhythms, the biological clocks inside our cells. That time when we sleep and wake, expect to see illumination that can be tuned by intensity brighter or dimmer and color temperature cooler or warmer throughout the day to mimic the light outdoors.

So I want Huberman's take on this. I want Brian Johnson's take on this. I want Soulbras take on this.

Marc Andreessen notoriously has gone to war with Huberman said, I'm going to use my phone.

That is one of my favorite interactions on the Internet. Their bromance is fantastic.

Amazing.

It's hilarious. Anyway, yes, you got to be using, at the very least, warm white 2700 Kelvin bulbs. You can't be walking around in the.

The bright fluorescent lighting's important. I mean, the issue with LEDs is there's the refresh rate, the flicker, right, which is not visible to the human eye, but when you, if you sit on a camera, it'll drive you inside.

I, I firmly believe that efforts to develop such lighting took off after researchers in the early 2000s discovered photosensitive cells in the retina that detect light generally below the level of our awareness. These photoreceptors, independent of vision, can affect biology and behavior, researchers find. So I mean, really, what it depends is not, it's not just the one size fits all. It's like, do you want an insane work culture? Do you want to drive your employees insane? Well then maybe you should go with the craziest, most strobing LEDs constantly. So when your team is in the office, they're ripping their hair.

Chris from Hadrian on lights out factories.

Right?

What about lights out offices? The only light is from screens, from your email machine, just.

Yeah, blasting anything to get you to work harder. Anyway, you know, I imagine that the lighting is pretty good if you're at, if you're at a, an auction for a championship bowl. We should do that story before our guest hops on in six minutes. The vicious sport of landing a prize bowl at auction. With herds thinning, finding the right stud is a high status game. That's why you come to this show, folks. That's right, tech business. This is the business of the technology of prize fighting bulls. With herd's thinning, finding the right stud is a high stakes game. But how do you tell a $45,000 bull and an $8,000 bull apart? I know a lot of you have been asking that question. Well, we got the answer from you courtesy of the Wall Street Journal.

When Randall Grimius shows up at an auction, everyone knows there's a prize bowl in the barn. John, the 56 year old rancher has an eye that is the envy of America's livestock industry. Never more so than now. The US cattle supply is thinner than it has been in 75 years, sending prices soaring for bulls with the tools to repopulate a herd. Ranchers travel to auctions across the country in search of the right bull and they can't afford to mistake a dude for a stud.

I had no idea that there was a population crisis among the bulls I.

Almost had 75 years ago.

Humans.

I have no idea to a crisis. So when Grimius's private jet touched down here last month and he strolled into a barn at TD Angus Ranch, all eyes were on him. Which one did he like? Grimius would keep them waiting. After 283 bulls were scooped up, his prize came charging out onto the show ring. Number 284 had what he likes, a longer neck, a chest that looks like it can add more weight, and a backside with a nice arch. We're talking about bulls here. To be clear, Dremius figured the bull could fetch as much as 60,000 and he was prepared to pay up.

Sales like this one can make or break a rancher's year, and as a result, they are filled with the kind of tension and gamesmanship often associated with art auctions or the NFL draft in North Platte that day, the average selling price was about $10,000, up from a year ago and double what it was seven years ago. According to the rancher running the sale. He and his wife Dana spend hundreds of thousands of hours preparing his roster of bulls and putting together the catalog. They drew ultrasounds on the bulls to compile stats such as marbling score, which determines the potential tenderness of a future cut.

They're doing more diligence on bulls than the average VC does on $100 million check for sure.

No, this is a mature industry. This is very, very serious. Their paycheck comes once a year. During the sale, ranchers pour through the data and analyze images of a sales catalog. Rare is the bull that hits the boxes based on his genes, frame and testicular fortitude. Scouts also look for intangible traits such as if he looks powerfully made or has the requisite sass and swagger. Founder? No, they are in founder mode to spread his seed. Sean Lowry is a 6th generation Nebraska rancher and as part of the Mildell Ranch, one of the oldest running ranching operations in the state. He looks at the lineage of the bull, who the mother and father were and certain physical traits. Not too big, with near perfect feet for wandering around his 3,000 acres and large testicles that won't freeze during the winter. It has to have that look. You just know it. He can't be too tall, can't be too small. We might. We like them long. We like them deep. This isn't the Wall Street Journal, folks. This is an important industry. It's Fascinating. Up close, auctions get messy. The bulls occasionally defecate and if a tail swings at the right time, it flings it into the crowd like a killer whale, splashing the onlookers at SeaWorld.

We gotta, we gotta go, we gotta.

Go and see one of these bull auctions. You know, I follow an account that does breakdowns on horses for horse racing and the technology that they use to do due diligence on horses on thoroughbreds is far more advanced than anything that you'll find in a docsend in Silicon Valley. They match the gate, they have these computer vision algorithms that show the different proportions of the horse. It's incredibly detailed, and the horses can get well up into the high six figures. So the bidding started at 5,000 before quickly climbing to 15,000, 20,000, 40,000 and soon 55,000. Your man has to beat 55,000. Come on, Randy. He said, trying to get Grimius to bid. Grimace didn't bite. He knew his prize was later in the day.

It's interesting, you know, the same dynamic plays out in Venture, right? The sort of like, oh, the second that Sequoia issues a term sheet, then every other.

Oh, everyone else gotta get in.

Yeah, yeah, we always wanted to, wanted to do this. And it's an interesting dynamic where in theory, once he's starting to bid, everyone else should just sort of like pile in and try to get the one that he wants.

So even some of the ranchers are sending other people. So Lowry's people know him, so he sent his foreman into the bleachers to do the bidding so he wouldn't get recognized because people know, oh, he's got a good eye. He's the Sequoia of bull bidding.

Yes, yes. So he says. Sometimes I will get emotional, I will get pissed and it will cost me thousands of dollars. I didn't intend to spend the best in this business. These cowboys are awful prideful.

Yep. Well, I would love to get one of these ranchers on ramp because time is money, save both easy to use, corporate cards, bill payments, accounting, and a whole lot more all in one place. And if they're flying out to different ranching bull auctions, they're going to need to be expense expensing flights, booking hotels if they don't have the private jet already. And ramp travel would be a great fit for these guys. That's right. So if you are a rancher, get on ramp today.

Do it.

Coming in to the studio, we have Roy, who has been tearing up the timeline. We're very happy to have him join. How you doing, Roy?

Welcome.

Welcome to the show, brothers.

What's up brother? Great to have you.

How have the last few days been for you? Can you take us through the brief pre history here of what happened with Columbia and then we'll get into what happened with your launch.

Yeah, I mean earlier this semester or earlier this year, I built this tool called interview Coder to let you cheat on your technical interviews for software engineering jobs like leetcode style interviews. I filmed myself using this to get a job at Amazon. I recorded it, posted it online and Columbia saw Amazon reported me to Columbia. Amazon is mad. Columbia is mad. And this ends up being a spat that I sort of publicize on my Twitter becomes this big spectacle and I eventually get kicked out of Columbia or suspended for a year and blacklisted from most big tech companies.

What was the original plan, Big Matt? Was the original plan a publicity stunt or did you actually want the job at Amazon?

I was never intending on taking a job at Amazon. The, the, the impetus for everything was I did a bunch of legal questions thinking that I would work at a big tech company one day. I really hated it. And at a certain point I kind of just thought I really want to build companies is what I want to do with my life. So this just seems like the optimal route for everything. I can make this big protest against leetcode and at the same time I can do something that I suspect will be super viral and just give me a distribution channel to build off.

Yeah, that makes sense.

It's crazy. I mean there's many people in Venture that have spent 10 plus years trying to build a following here and the growth of your account alone in the last few months has just been insane to watch. And yeah, absolutely gives you an edge as you now come in.

So take us through the product, what you launched and how that video came together.

Yeah, so I mean Cluli is supposed to be the, I guess the ultimate experience layer for AI in a world where models are truly multimodal and you can sort of have an AI that remembers the last 10 years about your life. Nobody's going to be on a chatbot. Chatgpt.com, where are they going to be on? They're going to be on Cluli. And this is what we hope to build and this is what we are building. We sort of filmed this launch video to be like a vision for the ultimate end state of what does true AI in everything look like? Like a true AI maximalist life 10 years out in the future. What does that look like. And it ended up coming together really well and I think it resonated well with the world. Went very viral and very controversial, but, yeah, very controversial.

How did you. You went against the norm. You launched 2pm Pacific on Easter. Did you just launch when you were ready or was that planned at all?

Yeah, I mean it was 420 and it was sort of in brand with like me being like the little like punk college kid. Like I launched on 420, might as well.

Okay, yeah, yeah, yeah. What about. Has any of the pushback been correct? Can you steel, man? Any of the pushback. Is it bad to cheat?

I think, I think there's two worlds of like, there's. There's two big arguments for the pushback. The first is this is dystopian and this sort of destroys what it means to be human. And I disagree with that pretty fundamentally. I think every time technology has advanced our capabilities, people have said the same thing. This destroys what it means to be human. But ultimately that never ends up being the case. We just become more efficient as a species. And the traits that make us human are not the traits that sort of like AI can fill in the blank for. The second large area of pushback is this is cheating. And cheating is unethical. I think it's sort of the phrase cheat on everything is left intentionally vague. I mean, what exactly does cheat on everything even mean? You can cheat on a test, but can't really cheat on a sales call. You can't cheat on a meeting. You can't cheat on a conversation. What cluli or what AI allows is sort of like an unfair advantage that is so unfair that it feels like cheating. Imagine you're in a sales call at point. This, this tool, this genius tool that knows everything about you, your company, your clients. Anytime a technical question is asked or an objection is asked immediately, it just knows and just can give you the right answer. Your human intuition just looks at that and thinks, wow, this is not fair, this is cheating. But I mean, ultimately this is where the world is headed. And really this just makes us 100 times more efficient.

Yeah, I love it. I mean, in many ways, business is like, feels like a sport in some ways. Yet there's sort of laws that govern corporations and different, different markets. But there's nothing wrong with giving yourself every possible advantage to win. And so you should absolutely just use every tool available to you to win.

Yeah, talk through the product. Version one seems like maybe a web app or an iPhone app. But then it seems like there's a Augmented reality vision in the future. But how are you thinking about that? Because you know there's a monopoly in Apple products. There's a monopoly on foundation models. Now, like where are you seeing yourself breakthrough? Are you sitting on top of different systems or trying to build something from scratch?

Right, right now the vision, the version of the app that we have is just a desktop app, has complete access to your screen and your system audio. So it sees everything you're seeing and it hears everything you're hearing and can help with that context. Ultimately though, what we want, the end state of the product is a chip inside your brain that lets you use AGI to think that is the ultimate end state. And the way we get there will be sort of like variable. If the models get significantly better, significantly fast, the chips get better significantly better super fast, then it's sort of like the way we get there is subject to change. Right now we are building a really, really good desktop app that can be the player, ultimate player two for your computer.

Yeah. What would you, how do you respond to like the criticism that like maybe you're over optimizing for distribution ahead of product. You're, you're going viral. Like you're frustrating people, you're being controversial and like maybe you should just be heads down and like go build something great and then you know the business will build up slowly over time. And this is like, oh, you're like clout chasing is like the criticism.

I think there's a lot of people that say distribution is the final mode. In fact, everybody says this distribution is the last mode. Anything can be built. And if you truly believe this, then you would behave exactly how I'm behaving. That's a good point.

That's a really good point. But specifically there are different modes of distribution. Right. You could have found a distribution angle that frustrated people less or was less edgy. Right. And so is the need to be edgy. Is that a product of the way our social networks work or the way our distribution like moats already exist? Like there's already a, like the Humane team was able to get distribution and attention by kind of aping an Apple ad and they were able to get a distribution. You went a very different direction. Are you like a product of modernity? I suppose? Yeah.

Yeah, I would think so. I think I have a very unique and I think a very strong viral sense. I've been intuition about what makes things go viral and what things will go viral. And for me that's like pretty edgy. And I would probably think and most people probably agree the video wasn't nearly as controversial. It wouldn't do 10 million views in two days.

I agree.

Yep, that makes sense. Talk about how the round came together in the process there. I remember you first started going viral and I imagine it was just your DMs, you know, flooded by, you know, everybody pushing back, being like, you know, this is, this is wrong. But I think you were smart to pick, like, a common sort of, like, enemy. Like, people generally are sort of anti university right now. They're sort of anti elite code. But talk about how the, how the round came together and, and yeah, I'm curious because that, that kind of, like, you basically did a, you know, indirect roadshow where you had the attention of everyone in tech for, you know, a period of time.

It was a really messy round and I don't think I can advise most people on fundraising. The round in total lasted less than 24 hours.

Yeah, I remember that. You just, like, posted. I think I saw one post and then you're like, okay, the round's done.

Our pitch and our entire deck changed twice in the middle of the round. And the only thing we came in really knowing was, I'm super hot right now. We can build a bigger company and right now is the best time to get money. In reality, in the future, there were only two worlds. One, I fell off and I can't raise again, or two, I succeed massively and all of a sudden the extra 5, 10% dilution here, if we fuck up, it means nothing.

Yeah.

How do you think about flexibility at the product level? It seems like you have a very clear vision of how to unlock AI for individuals. Broadly, it sounds like starting in the workplace, but are you flexible in terms of what that sort of exact implementation looks like? What kind of different niches? I can see the application in, sales, et cetera. But how are you thinking about sort of adapting now that you have this flood of customer demand and attention now? You need to turn it into durable revenue and things like that.

Yeah, I mean, this is something that there's like a really, really, hopefully viral experiment that I'm going to try that will be the first of its kind. I'll just announce this right now. We're probably going to hire about 100 interns and we're going to turn them into like sort of the ultimate content farm over the summer. So we like the most motivated high school and college kids. I really, truly believe if you're over the age of 23, you probably don't have the viral Sense that you need to go like consistently massively viral. We're hoping to have this gigantic content farm and every single one of them will be sort of assigned a different use case for the product. You guys are going to advertise this product for sales calls and you guys are going to just like ship out content for sales. You guys are going to advertise this for meetings and you guys are going to advertise a deep research feature and sort of like the consistent virality and attention on the different use cases that will make it what's lasting.

I mean, do you have a suspicion as to which use case is most profitable in the midterm? Because, I mean, the Riz app already exists for messaging people on dating apps. Deep research allows, you know, basically everyone to already cheat on their research papers if they have to write research papers. There are copilots all over the place and you're kind of pitching like an omni copilot, at least in the short term. Are you still. Is your formula like go viral and test everything and then find a new niche and then double down on that and then. And maybe we're talking to you next year. And you're like, yeah, we found it, we cracked it and we are cheat on sales calls and we're great for SDRs and we've kind of dropped all of the other things. Or do you really want this to be everything for everyone on day one?

Everything for everyone on day one is a bit unrealistic right now. The two things that we're really zoning in on are meetings, like virtual meetings like this, and also sales calls. But it's entirely possible that every single use case flops doesn't go viral. Isn't helpful except for one random use case in which case people like quintuple down on that. But the end state is AI for everyone, for everything.

I want to go deeper on the actual hacking your way into products to make using the product easier. Talk to me about getting an iPhone app. Is there a way that you can hack your way into the camera button with a shortcut or the action button on the iPhone? Meta Ray bans. Is there a deal that you can do to take over for that? Like, it feels like most of the hardware providers have very sharp elbows around their ecosystem. Some of that's breaking with the latest FTC lawsuits and maybe they're more open to it in the future. Also, like the failure or like the setbacks to Apple intelligence have kind of raised questions about like, hey, should that Siri button be remappable? To other things. How are you seeing the landscape around hardware evolve? Because that feels really, really important to you. If you don't want to go build it yourself, burn $100 million trying to build the next Apple product.

Yeah, I don't actually think that we'll, I doubt that we'll ever be integrated into the iPhone. I don't actually know that that is the best modality. Even if we could, I think most people, I mean friend.com, omi like everyone is sort of betting on the idea that there will be like this new hardware element that, that is like a companion. I think that's if we were to delve into hardware, that would be most realistic as the next step. But what I really would like to do is sort of like beat out neuralink and just sort of just directly skip all that and get to the chip inside your brain. That is the true end state is what we want anyways.

Yeah, don't ask the neuralink guys about timelines then.

Can you talk about what the general, while you were at Columbia, what the vibe was on campus? I'm assuming everybody's using chat gbt, but do they know, like, do they have a sense, like, is this, is there.

Tyler Cowan, like, has, has completely embraced AI in his, I believe, graduate level economics courses where he says, yeah, go have ChatGPT, write the paper, then dig into it and teach me something from it. It seems like he has a very positive view on AI in education. What's been your experience?

Yeah, and, and, and getting into that more. Is there a general fear about AI on campus? Are people like worried, oh, job displacement, job displacement, things like that. Or are they just excited to leverage it to grow and be better at their jobs, et cetera?

There's definitely concern, but I think the most interesting thing here that most adults probably don't realize is exactly how many people are using AI. I mean, the percentages get even more skewed at the higher level schools. But I will say, out of every single person I've met at Columbia campus, there is not a single undergraduate who hasn't cheated on at least one assignment using AI. And the vast majority of CS majors.

At like, you should tell them to kick everybody out.

Kick everybody out.

Everybody out.

Just whistleblower.

The slate. Yeah, whistleblower. Columbia whistleblower.

No, no, Columbia. Cheating is okay. It's trolling that gets you in trouble.

Yeah.

And you don't have fun.

Don't have fun. Don't expose technological changes. You will be blocked.

Who are your inspirations? Are you like a Nathan Fielder type guy. I feel like there's someone that you look to in your virality who inspires you.

Bill Burr. Nathan Fielder. Those guys are so funny. Dave Chappelle. I mean, I was big in that. There's a lot of Asian content creators that are funny, too.

That's awesome. Last question, Jordy.

No, I love it. Who are you? Have you put together a team of former classmates? Have you gotten anyone else to bail with you? What does your team look like today?

Yeah, so over half the team is friends that I met from community college, actually, and the other people are my co founder who dropped out, and also the guy who's probably going to be valedictorian of Columbia.

There we go.

Are you worried about any serious backlash from Colombia? Because I saw the thing where, like, they told you, don't share this document. You shared it. It feels like, like they find out you have 5 million bucks, they sue you.

Like, I just want to go out on the lens. I will. I will give money to the Roy Lee defense. So we got you. We got you.

I'm anti cheating in the literal sense, but I like. I like building, and I also like trolling and comedy. So I'm like, 50. 50 on you, I guess. Are you worried?

I'm not as reckless as people think. I read the documents very carefully before disclosing the confidential, and there's, like, it was not legal. These are the worst case to get expelled, and for me, probably the best case.

Yeah. Yeah, exactly. Well, I think I would be okay with you getting kicked out of Columbia, but I would be upset if they really tried to put.

I'm going to go out on a limb, and I'm going to say I believe there's a real chance that you eventually go back and give the graduation speech at Humble. You know, you're gonna have a. You're gonna have a crazy arc, and I'm excited to witness it.

I hope so. I hope so.

Yeah. Good luck.

Love it.

Hopefully there's not too many crazy biz dev deals between you and success, because I feel like if. If it comes down to it, and it's like, in order to win, you have to partner with Apple. You might have to clean it up a little bit, but good luck to you. I'm sure you'll figure it out. And thank you so much.

Congratulations.

This is a very exciting story, and I love when anyone blows up the Internet like you did.

Yeah. Congratulations on. On all the momentum in the round and excited to have you back on soon.

Yeah, fantastic. Thank you guys, we'll talk to you later.

Cheers.

Bye.

Later.

Next up, we got Jacob from superpower announcing a $30 million Series A, B, C, D. Series A, Series A.

And also a Suse Ventures.

Back to back.

Suse back to back. Chad Day.

It's Chad Day.

Shout out. It's Chad.

Yeah.

Chad Day. April 22nd. He just will forever be known as Chad.

I'm a. I invest in Chad's. That's his investment thesis. The end.

The end. We got Jacob here.

Let's bring him in. Jacob, how you feeling? How you doing? Should we ring the size gong for you preemptively? Congratulations on the round. How's it going, Jordy?

Gentlemen. Great to see you guys.

Great to see you.

Good to see you. What's happening? Give us the breakdown. What are you announcing? And give us the high level pitch for superpower.

$30 million Series A. It's our biggest capitalization to date. Capital is no longer constrained, and we're building a super team to reinvent healthcare.

Okay, crazy. Give us a backstory.

How does it start for the consumer? Get loud.

I was gonna say let's go back a little bit.

Yeah. Let's start with the backstory.

2023, you had a rough year. You want to share that?

Oh, yeah.

How that kind of catalyzed.

Superpower Rewinding the clock. It was 2022, actually, and that year, I almost lost my life. Life to reverse healthcare incentives and a system that doesn't necessarily help people be proactive and take control. So that was when I was building my last company. I was diagnosed with an autoimmune disorder. It's one called Crohn's, which those listeners might be. Might be familiar with. 50 million Americans have autoimmune disease, 2/3 of which are undiagnosed. And in my case, it led me to being hospitalized for close to four months, had multiple surgeries, lost part of my stomach, got stuck with a multimillion dollar bill. And you realize really quickly that the thing that health systems are designed to do from a business model perspective is make the most money. So that's build pharmaceuticals or surgery versus getting at the root cause of what's actually driving complex diseases in my case. So I was really more seen as a way for them to make a lucrative billing cash flow versus actually getting to the root of what was ailing me.

Talk about how that led into Superpower. I remember we had a. I think we had lunch just after that period. I remember you were like. It felt like you were almost still in a daze. Because you just like almost, you know, spent a year almost dying, but you knew from, you know, basically right at that moment kind of what you wanted to do.

It actually comes back to Twitter. So I posted about my hospital story and it went really, it went mega viral. And as a result I got connected to a handful of these like high end concierge doctors who basically work with the tech billionaire class and they charge like 50 to 100k for their clinics. And what you do when you're a patient at these practices is they test everything in your body, leave no stones unturned, they'll sit down with you on a whiteboard for four hours, connect the dots across every little thing in your health and then pair with a full time team to basically put your health care on autopilot. So if you're fortunate enough to be in a financial position or in the know to be a patient one of these practices, you're basically never going to die of chronic disease. You're going to look like, you know, the memes of Bezos and Zuck that are super yolked. You know, I know the doctors that probably do their peptide regimens.

You think it's just peptides, peptides or is there secret juice?

I can't reveal too much, but you realize really quickly that there's a gap between healthcare for the best and healthcare for the rest. And obviously being a technologist and a brand builder, it just became very obvious that there was a big opportunity here to democratize once I went on my own healing journey.

Do you think that founders should like, I feel like there's this balance between founders need to be performant, you need to have high energy, you need to be able to oftentimes go 20 meetings in a single day, whatever that looks like. You basically have a life, you know, the intensity in many ways of a professional athlete where what do you think the sweet spot is for founders in terms of, or investors in terms of caring about their health but not letting it sort of like take over their entire life. I went through a period in college when I had a bit more time where it felt like 60% of my brain power was just going to lifting and eating and things like that. And obviously it's not sustainable if you're trying to run a company and things like that. So I'm curious what you think the kind of sweet spot is in terms of wanting to be high performance, wanting to be healthy, wanting to not be accelerating your aging, things like that.

It's quite a quandary, right, because we obviously pride ourselves on being a team. We even joke that our office is the world's healthiest office yet. Sometimes we still have to put in the hours and we have the engineering team closing up on the floor for the evening. But yeah, it really I think is an opportunity to usher in a new paradigm shift where we can put health at the forefront of the conversation. I think we're actually about to have our first board meeting here this upcoming quarter and we plan to have some statistics on the health of our founders and our team in our, in our board. So we want to kind of set the lead, the vanguard and what it looks like to, to have health be like a tracked foundation just as you would, you know, your amplitude or your stripe data are all the metrics that matter for business.

Yeah, I was joking. John and I gave a sort of humorous talk in Miami last year and we were talking about the case for like VC platform team should just be like, basically like doping. Yeah, like helping, helping their portfolios just like what's your creatine? What's your creatine? You know, how much are you working out?

What's your eight sleep score?

Looks like we need to add a little bit of tea in the mix.

Yeah.

Well, I think someone's going to launch a fund with this thesis where, you know, maybe it'll be me. I don't know.

Unironically.

No, I don't think it's. I think it's a very real. I joked about this, but I think it's very real. A lot of venture funds, especially if you're niche, you need some type of edge. Some people are like, oh, we're going to help you with sales, we'll help you with recruiting, we'll help you with your next round. But just saying like we're going to.

Help you, help you with your one rep max.

Help you with your 1000 max. Exactly.

Thousand pound ventures.

Talk about the sort of opportunity in AI specifically for Superpower. You guys have started with biomarkers. How do you plan to leverage that to kind of of unlock value on the data side and all that?

So in the limit, something that we deeply believe is everyone will have a healthcare super app on their phone. And today a consumer health experience is deeply fragmented. Consumers have to run around town to a bunch of different places and it's all disconnected. And the front door to health is something like ChatGPT or Google or web Empty. But the problem with those platforms is they don't really know much about you and they definitely don't know everything about medicine. So what that sort of culminates in with what we're building is what we think will basically be an AI doctor in everyone's pocket. So we're kind of aggregating all of your medical records and health data, making it super easy to test your whole body and combining that with all the world's medical knowledge, which does not necessarily exist in foundation models today. Each foundation model is sort of trained on a select aspect of the healthcare and medical literature universe. So there's a lot of creative ways to get a full picture on what's actually happening at the edge of science and medicine. When you put all this together, you have a recipe for a really unique company that we think one day will be something that a large majority of Americans own. And healthcare is ripe and it's demanding of better consumer experience. We've seen the consumer experience being reinvented for every other aspect of our lives. But health care is sort of the last domino, domino to fall. And we want to be basically the predominant company to bring this to the market.

How do you think about the interaction with LabCorp? It's a $18 billion company, kind of stocks up and stocks down, kind of up 60% over the last five years. Obviously, when you're doing lab testing, you kind of got to build on top of the railroad that's already there. But how does that relationship evolve over time?

Yeah, labs are a super commoditized business. What's really happening and what's exciting to pay attention to is innovation in testing. So today it's actually kind of a cumbersome process. You have to have like a nurse come to your house, you have to go to a lab corp, they test your blood, they send it off to another facility. It takes like, you know, eight or nine tubes to get a full enough panel and picture and then a week to come back. And there's probably like a dozen or so friction points there. So something like Theranos over the next few years probably is not that far off. And thankfully we're building at the application layer. So we have to be best in the world at building a trustworthy brand, low cost customer acquisition, and a really amazing AI doctor product.

What is your takeaway from the Theranos story? Do you think that there's any sort of misread on that historical anecdote? We've done a deep dive and we were like, like there's more nuance.

The issue is don't apply build fast and break things to consumer health.

Yep.

Healthcare doesn't move at the speed of Code is all. There's a certain reverence you have to have for the human body as a healthcare founder, which makes the zuck adage a bit tougher to apply.

Yeah. What about interactions with the fda? I assume that there's oversight around. You get the lab markers done with Lab Corp or Quest or something and then you're interpreting that and you're at the application layer doing AI data analysis, all sorts of good stuff. But at a certain point, actually making a recommendation about someone's health is probably regulated. What does that look like and how will it evolve over time?

Yes, we're not quite in a world yet where AI and the algorithm can make a medical diagnosis or a recommendation. So the system that we've architected and the paradigm that we're in just as an industry is basically AI with human in the loop. So anytime it gets to a point where a human has to intervene, we do plug in a doctor, a doctor that can help you with that, which helps us avoid any sort of messy FDA regulation that makes sense.

Do you see a world in the future where the average company, maybe outside of our tech bubble is giving budget to employees specifically for preventative health insurance broadly is a pretty standard benefit, but feels like preventative health is like, you know, potentially the next place that employers want to invest?

Undoubtedly. So one of the challenges in healthcare today is because the average American is transitioning jobs every two to three years and healthcare is tethered to your employer. That means it's just a game of bag passing where the insurers don't really have an incentive to underwrite anything that's a bit more long term or preventative or optimization focused, like getting your testosterone checked, checked out. So in that world, the insurers don't necessarily want you to get access to things like superpower and have it, have it be covered. So that's where employers will ultimately step in and potentially start to cover these types of things as supplemental benefits because they're going to drive clear employee retention acquisition in a market where it's only more competitive to get the best, to get the best people.

What's an underrated supplement right now? It feels like, you know, magnesium. Magnesium's hot.

TIA takes six different types of magnesium.

I also take six different.

It takes six different types.

I'm only on four. Those are rookie brutal. What do you think the next kind of magnesium? I. I've been surprised to see creatine in the timeline so much just because it seems like something it's lindy. People have been taking it Forever.

Methylene blue is in the timeline.

Methylene blue. I'm, I'm, I'm 50. 50.

Yeah, yeah. But, but, but. What's your take, Jacob?

I got one for you. Oral BPC 157.

I've been on oral BPC 157. Oh, yeah, this is the Wolverine peptide.

Oh, yeah, it's from the Wolverine protocol.

Yeah.

Okay, 157.

No, this is, this is what. It's sort of. Is it semi like there. There's interesting thing right now where there's, like, substances that are banned by various, like, squad organizations and leagues that, as a CEO, you can just take. Right. So, like, if a pro athlete is, like, wanting to take something but can't because it's very effective, but it's so effective it's maybe made illegal. If you're a CEO or a capital allocator, why not get on some PPC157?

In Silicon Valley, performance enhancing drugs are encouraged.

Yep, that's true.

Yeah. It's an interesting time right now. I mean, it feels like these sort of like, psychedelics, you know, have long been a part of Silicon Valley culture. But I think that performance drugs, not just exogenous testosterone, but I think they will just become more and more popular. It's going to move beyond. Okay, founders are on. You know, maybe they're on caffeine or nicotine and creatine, but onto, like, really optimizing peptides in the way that, you know, you mentioned it, people like Bezos are probably doing to some degree better sleep.

Yeah. Makes no sense.

But anyways, great to have you on, Jacob. Very, very exciting.

Congratulations.

Anything else? Anything you want to plug before. Before we end?

Gentlemen, I. I appreciate the. The time, but maybe before I leave, I'll give you both a quick sneak preview of our AI doctor product that we're launching very shortly. So, Jordy, if you have any questions for the algorithm, maybe how to boost just that, testosterone.

There we go.

What's the. Yeah. How much BPC1.57 can I take before I explode? What is the LD50 of BPC157? Because I'm going to the max. I want to look exactly like Wolverine.

John has. John has the highest natural T levels of. I think.

Yeah, but imagine how much higher they could be if I was in the Wolverine stack.

If John. If John 2x is t, it would be potentially so.

I mean, obviously foundation model plugged into that, but then also built on top of your own data so you can query your own lab results and get customized recommendations. That the idea.

Exactly.

And then as soon as it, as soon as it like makes a firm recommendation, kicks you over to a doctor before it starts violating FDA rules basically.

Exactly. The way to think about it is the world's best doctors will spend hours and hours with you on whiteboard connecting all the dots in your health. But that computation doesn't scale at a higher price point. So we're democratizing it.

That's awesome. Love to see it.

Love it. Awesome. Jacob, congrats to you and the whole team. Cheers.

Well, speaking of AI, we're having Logan Kilpatrick from Google on there we go.

Talk about for this one a lot of different stuff. Logan has been on a tear.

He has great poster and as soon as he is here we will bring him into the studio. But maybe in the meantime we'll tell you about bezel. Go to getbezel.com, your bezel concierge is available to source any watch on the planet for you. Seriously, any watch. And I mean while we're also on it, we did not get a chance to talk about Eight Sleep. Go to Eight Sleep.comtbpn Get a Pod 4 Ultra. It has a five year warranty through a 30 night risk free trial, free returns and free shipping. And we will go back to the show. Now let's bring Logan into the studio. How you doing Logan? Let's see, we're bringing him in. How you doing?

I'm doing great. It's been a great busy last six months of AI stuff so I'm trying.

To stay alive just the last six months. I feel like every six days is huge in the AI world. It really is like the best place to do content around or just read about or listen to podcasts about. The AI world is just so fertile. Regardless of what you think about like P doom and acceleration and all that, just in terms of like the applications, the deals that are getting done. It's fascinating. So yeah, what, what are you watching today? What are you watching this week? What's most interesting?

Yeah, that's a good question. I think continued momentum of 2.5 pro on the Gemini side. I think obviously a bunch of new open AI models which has been awesome to see. It's also been back to your point about how much fertility there is in like different AI stuff. I think if you look like 2 years ago it was really just the models and like the model cadence of launching was like actually quite slow relative to like products. And now we have all these products which people are really excited about and like the product innovation actually happens a lot faster. So it's like acceleration across the model category, but also across all the product category. And like there's just, there's too much to keep up with at this point.

It's impossible. Are you generally feeling the acceleration? Because I feel like, like we are seeing acceleration on the product side and certainly in the fragmentation of models and the specialization of these models. But in terms of just like massive order of magnitude breakthroughs, I feel like when we went from three GPT3 to GPT4, that was a huge leap. We passed the Turing Test. ChatGPT was huge. And then since then it's been more incremental. Extremely valuable, extremely great. I love it. But I haven't, I haven't seen as many of those viral moments. Studio Ghibli accepted probably.

Yeah. I actually think I'll push you on this point, which is I think we've had more of those large moments than I think people appreciate. And I think it's just like, it's actually hard to appreciate some of those moments if there isn't a product experience that brings it to life. And I actually think that's been a lot of the gap. It's like if you look at multimodal, the fact that the model can like with better, better than just from a multimodal input perspective, better than humans are at like most vision tasks, the number of products and like things that that unlocks is like truly mind blowing. If you look at two years ago, what you would have had to do to make a, make something work in that ecosystem and like that is from an order of magnitude of impact, like massive. Maybe it's not as big as like text, but it's still this like huge, massive amount. And like we're continuing to see that with like, like, you know, now the models are really good at tools and now the models can actually generate images and audio and video and all this stuff. So I, I think we're getting those. I also think our expectations have just gone up so much that we're like, if the thing isn't, you know, brushing my teeth for me, then like, oh, it's not, it's no longer.

Yeah. Yesterday we read a post from Near Cyan and it was a, it was a screenshot of the definition of AGI. Read it out.

So as a reminder of how far AGI goalposts have moved. And it's a screenshot. 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. And it's funny because like, okay, everything we're doing everything except baking you a cake.

Even then it'll give you a great recipe and it'll give you a recipe for any type of cake you could possibly imagine. A sheep sized cake, you can do anything. Anyway, I want to talk about this idea of the Pareto frontier in AI models. Sean, previous guest on the show mentioned that Google has been very good at delivering not just high quality models, but affordable models. Has that been a deliberate strategy to try and create the best model at every different price point? Or is that just a natural outgrowth of the engineering culture and the scale of being a hyperscaler?

Yeah, that's a great question. I think a lot of this has been an intentional decision. I think if you look at specifically 1.5, the Flash series is really where we sort of landed this point the most. I think recently which 2.5 Pro, it's been the first time that we've actually had like truly one of the most intelligent models available. And relative from a cost perspective it's still super affordable. But I think it also just like why we've been able to do that and why we focus on it is like, goes back to like, you know, Google controls from a product perspective like all the way to how the models are delivered, to how the models are trained down to the silicon. So like you can make decisions assuming a bunch of those things are going to be true, which is like a lot of folks don't have the flexibility to make those, those decisions. And, and the beautiful thing is like I think this, this point goes underscored which is like what does this mean? It means that builders have the freedom to do stuff. It's like not that like Google has this really great advantage and the, you know, thing we do with the advantages, find out how to milk money out of people. It's like we have this advantage. And what does it mean? It means the world gets cheaper AI models and they get to go and build the products and like the margin for people building AI products actually goes up every like the farther you push the paro frontier, the more money builders get to make. Which is like such a interesting and like unique thing about this AI moment that I actually don't think has been true in a lot of these other platform shifts that have happened in the past.

Yeah, I want to dig in there. Google's in a unique position in that it's a consumer tech giant, but also a scaled infrastructure provider with GCP and.

You could see, not to mention a B2B player. I mean, I don't know a single.

Startup that does run on Google Workspace 100%. And so, and so you like Ben Thompson was just talking yesterday about, he's really pushing OpenAI to just go full consumer and let Microsoft handle all of the B2B stuff. Don't let the API load take away from serving your consumers with Google. There's probably some sort of tension there, but what are you excited about on, on the B2B side? And this idea of like, oh, if I build a wrapper, is Google going to just steamroll me? This is kind of like an old meme, but now it seems like the best time ever to build on top of the 2.5 or any of these different models that have great cost and scores and benchmarks and whatnot. So what message are you sending to kind of the developer community?

Yeah, so two things. One, our reaction to your first comment, which is around is there value in doing both consumer enterprise and some of these other things? I think my push for companies, if you're in the position to be able to do that, and there's a bunch of nuance to this because obviously OpenAI as an example, is extremely well capitalized, et cetera, et cetera. They have the means to do this and do it well. But for companies that can. I think part of my core worldview is a lot of the reason that ChatGPT has been as successful as it has is because there was an API business built around it. And if you think about it through this lens of, of what the API business did was allow the world, allow this massive proliferation of AI products to educate the masses that people are interested in this stuff. And then at the end of the day, who has the world's best AI product? I think some people maybe argue it's ChatGPT, maybe it's another product, but you sort of whet the appetite of the world that, oh, I can actually do these things and it's in my product surface or et cetera, et cetera. And all that's enabled by the API. And then when you look for like, okay, what's the best way for me to use this product? Maybe it's one of those consumer products made by one of the larger labs. And I think that that playbook actually works a lot. And that's why I'm extremely bullish for people who are sort of doing both of these things. I think to your, to your question about like, where's the value for builders today? I 100% agree with you. I think there's so much value to be created at the application layer. If you look at, I think about these like three curves at the same time, there's like on one hand, the cost of AI going down into the right, you know, cost of AI down 99% over the last two years. The intelligence of AI is up and to the right. Like models continue to get smarter and better with test time, compute and scaling and stuff. At the same time that the models are getting smarter, the costs are going down, consumer understanding of AI is going up. And then in parallel to that, as consumer understanding is going up, as the models are getting better and cheaper, consumer willingness to pay for AI products is also going up. And I think there's this, like, it's this beautiful, like you actually could not ask for a better set of four lines on a graph than those four things. If you're building a product, it's cheaper for you to build the product. Your customers are willing to pay more, there's more customers and the tool that's actually enabling the value creation is just getting better for free. Like you don't have to do anything, it just gets better for you. And like, I don't think there's been a time in human history where for builders, all four of those things have happened at the same time. So I'm super, like, I literally wake up every day excited because people are building companies and all this is happening for them.

How do you think about balancing benchmarks and capabilities? Right. Google's consistently been a leader, yet at the same time, every consumer at this point has experienced a new model coming out, performing well on benchmarks, just sort of like broadly not talking about any one lab, but then being sort of disappointed with the actual experience with the model. And I'm sure you've spent a lot of time thinking about this.

Yeah, this is one I think for folks who haven't thought about this, evals are just really hard. It's like such a hard problem. And actually if you abstract evals out of like, like AI and into everyday life, like you become. And maybe I'm like too eval pilled at this point, but I think about just like random problems in life are truly eval problems. And like we look at them as this like very human thing and actually they're eval and like the sort of really weak version of this is if anyone's had a job and like have gone through like performance review, like performance reviews aren't eval, are they a super scientific eval? No, they're actually a pretty crappy eval.

In a lot of ways if folks.

Have gone through performance reviews. And yet like, that is the core foundation of like how human career growth goes in a lot of ways. Like, there's a lot, like evals are generally a really hard problem for AI. They're also extremely hard. And I think to answer the question specifically Jordi, about like, what does that mean for people who have this sort of disconnect between capabilities and what the evals say? I think this goes to like why there's so many like vibe evals. And if you look at like Ella Marina as a good example example of this, like Elle Marina is basically capturing vibes. It's like, how do people feel about this thing? It's not scientific. They're not like not actually eviling that the model is saying things that are true. It's like, how do humans feel about this response? And I think that's incredibly important. Is that the only thing that matters? Like, certainly not. But I think more and more you see launches happening where like the vibes are really important in addition to the actual quality of the models being important. And I do think you could do both of these things. In some cases there's tension, but I think you have to do both if you want to be successful.

How do you think about the different buckets of foundational research that are happening? Do you believe in the data wall, the pre training scaling rule, like kind of hitting diminishing marginal returns? We've talked to a lot of folks who are extremely excited about reinforcement, learning, reasoning, going a lot further there, program synthesis, these kind of topics, even just like, just more tool use. Let's bring more tools in. Google has a million tools and a million interesting APIs, both internally and some externally. It feels like there's a lot of low hanging fruit there. But what excites you on the research side these days is just let's build an even bigger data center. You guys probably already have the biggest ones in the world, but you could obviously go bigger or is it more algorithm based? How are you thinking about the future of the foundation model landscape developing?

Yeah, I think two points. One, I think there's never been more opportunities to push the frontier. I think all those examples that you just described because the models are evolving more than just being models and there's systems that have tools and all this other stuff together, I think it just increases the number of opportunities for scale and for the models to get better. So I think that's one of the positive things we'll continue to see a lot of growth specifically because there's so many dimensions that you could make the models better at. But I think if you look at an example of this in practice, 2.5 Pro is actually an example where it wasn't just RL scaling that made that model better. Yes, RL was part of the story, but there was also a bunch of pre training innovation and principally there was a ton of post training and pre training innovation. So I think it's not that companies are going to continue to see value created across all of those. And the really magical thing is like, and this is why, like I don't, I don't subscribe to the like pre training is, you know, dead and all that stuff because the more work that you can do at the pre training level, those capabilities as you do post training and as you give the models RL capability, it's like the capability is like amplified almost exponentially. So like if you can make the model 3% better at the post training level, when you actually finally do all the reasoning work and the model has to reason through really complicated problems, it's like many multiples of bang for your buck. Because of that, I think we need to continue to do the innovation across all levels and that's exactly what we're doing right now.

I know you probably can't talk about specifics, but one of my favorite Google stories is that crazy anecdote about the V8 JavaScript engine. I think the it might be apocryphal, but it's like a bunch of Google engineers go out to like Iceland or something, spend like a month building a new JavaScript runtime. It builds Node and winds up being like the foundation of like the Chrome browser. I'm interested to hear like what is your take on just lower level optimization? Obviously Google's already doing the tpu, but in terms of just, maybe even just squeezing extra performance out of inference, we saw this with Deepseek. It seemed like they did not just one or two breakthroughs in terms of kind of cost performance optimizations, but they did a ton. Is that type of work happening at Google? Do you want to see more of it? Is it an exciting area or is it just like, oh yeah, that's just something that we're going to have to do. It's going to have to happen at some point, but it's not as critical as some of the other stuff that's happening in the industry right now.

Yeah, you should ask our inference engineers who are working like 24 hours a day. I think like 2.5 Pro has actually been like a fundamental example of this. Like all of this stuff matters. Like, I think if you don't, if you're not doing it, like the. Especially with larger models and especially with models that have lots of demand, like, there's no world where you can get away with not putting a large order of magnitude of investment into inference. And like, I think credit to our team who's actually working around the clock right now to make it so that people can Keep scaling with 2.5 Pro because there's so much demand and we're having to like, you know, as a artifact of the constraints that we're under, like we're having to innovate and like, solve new problems and come up with things to like, find ways to make 2.5 Pro more scalable from an inference perspective. So it's awesome to watch that happen.

Yeah.

Where do you want to see more, you know, knowing 2.5 pro's, you know, capabilities probably better than anyone else, where do you want to see more developer activity?

Yeah, I think the thread right now that has the most excitement is around coding. Just because, like developers love coding. There's like so much. The whole vibe coding thing is a real phenomenon. I think I continue to be interested in like all the multimodal stuff. Like there's just so many products and like, I think back to early in my career when I trained computer vision models and like deployed them and like the amount of time that it took and the amount of resources to, to do that relative to today where you can literally just write a prompt and send images or videos to the model and have it do those tasks with basically near or better accuracy than you would get from domain specific models is absolutely fascinating. I think we haven't actually seen that wave of multimodal startups that are building on top of this stuff. And I think that includes audio things. I think the audio ecosystem is still pretty nascent. I think the foundation is being laid for that. People saw this with Gemini Live, people saw this with the ChatGPT version of the product that came out, but I don't think we've seen across other product services, people actually invest in real time audio and real time video and image stuff. And I think that's the next iteration of the UX of how people are going to interact with AI models. And the foundation is all there. It's just like the lag of how long it takes people to build interesting products. It just takes 12 months or something like that. For that to happen.

Yeah. I mean, speaking of, like, building new products, I love the Paul Bucho, Paul Buchheit story of building Gmail. Is this like, almost like April Fool's project. And then you see a, you see a seed of that in the Notebook LM project. What's the culture like around the idea of like 20% time? Does that even exist anymore? And then like, if I joined Google, could I just go and say, like, hey, I'm going to go like, build an AI native email client. It might destroy Gmail, but, you know, we'll figure it out. Or is that something that, like, you know, we're going to need to think about? Because, like, Gmail's mature, but there's still like a. You know, right now Gemini is like kind of being vended into Gmail. But, you know, maybe there's an entirely new paradigm at some point. How do these like, side projects and 20% time work at Google these days?

Yeah, that's a great question. I think my 200% project is on all the Gemini developer stuff. So I do think people, people are doing 20% projects, which I think is great. Like, I think if you're, if you have freedom to do that, like you should. And that's how Google's going to come up with innovation. I think for Notebook LM specifically, it came out of Google Labs and like Google Labs, the whole point is come up with new product services. So not just, not just Notebook LM actually, but there's like a whole, like Whisk. If folks have seen Whisk, it's like a video image generation platform that came out of that actually AI Studio, the product that I work on, came out of Labs originally and Josh Woodward's team. So I think there is like a whole lot of innovation that's being seeded out of that group. And again, it's like the big bold bets that like, you wouldn't see coming out of other, you know, potentially other product areas because it just like takes time to build these products from scratch and oftentimes time, time that they don't have. But I'm super happy because Josh Woodward, who leads the Google Labs team, now also leads the Gemini app team. So I think we're going to see that fusion of all these new ideas and product spaces. Because him and his team sit so close to the blank slate. Let's build any product to solve problems that people have. Now that they also run the Gemini app, I think we're going to see a ton of explosion. You should have Josh on. He's one of my favorite people.

Yeah, we'd love to.

How do you think about helping? How do you think about almost like prompting new consumer behaviors? Because I feel like every day on X you'll see somebody that's like, you know, I saw somebody post, oh, I'm doing, you know, basically like run it, you know, doing a prompt every day about like a specific industry. Like, you know, pull together, you know, the most important headlines and news from this industry. And I'm like, oh, that's really valuable to what we're doing. We should just sort of like get into the office in the morning, adopt that and do that. That's something I wasn't really thinking about. People are so used to like, you know, this sort of idea of like just getting the, you know, they'll like adopt a model for like one specific thing and then they just like do that. Maybe they veer out of it a little bit. But how do you think about getting users to just like be more creative? Obviously is helpful when a developer builds an application to like prompt a new consumer behavior. But how do you think about that? Kind of at the application layer at Google.

Yeah, Actually my personal take on this is I think this is a bug of this current AI moment where if you look at what is the ideal case, the ideal case is the models and the products pull out what they need to from the user in order to create value for them. And I think if you look at how all AI products basically work today, you as the user, the burden is on you to create value with this tool. And I think that just like one inherently like limits, you know, the number of people who are going to get value. But two is also just like a shitty experience. Honestly, like I hate like this is my biggest qualm with AI tools, which is like you have to go for, for most AI tools, you have to go to and like make this like sizable investment in order to get anything out of this. I think like a couple notable exceptions to this is like deep research. I can just fire off the like random question that I, that I have about how something works and then I'm given a 50 page report inside the Gemini app and then I can one click turn that into an audio, like a Notebook LM Audio overview. And like that's great because like as a user I don't need to make this like large order of magnitude of investment. The model does all the work for me. And I think as we see more experiences like that, like I'm super excited. So like I'm Almost. And this is maybe too, like, absolutist of, like, a product perspective. But, like, I will not build a product that, like, we have to try to convince a consumer to change their behavior. Because I think actually the promise of AI is that. That these tools are going to be able to pull this context out of you and you should just go and build that product. And I think the models are actually good enough in a lot of ways to help you do that today without having to rely on a user, hopefully having the right behavior to make that product successful.

It's an interesting thing where I feel like users are so trained on software doing a specific thing, that this dynamic of software and the application being able to act like a smart friend or a smart coworker that knows infinite more information about a bunch of different subjects and then can help you accomplish tasks is very different than this, sort of. And I just feel like even. Even as, you know, somebody who's, you know, I've. Now, I'm not 30 yet, but I've basically spent 20 years using software that behaves in a very specific way. And I need to just, like, totally reimagine how to use software.

I think the push needs to be, though, that, like, you don't have to reimagine. Like, I think about this all the time. Like, the thing that I would love is the AI tools that I have today interact with me. Like, I already interact with software today. Like, shoot me a text, shoot me an email, call me on the phone. Like, I'm already doing that all day. Like, you could. There are ways, I think, to bridge that experience gap where, like, you don't need to convince. You don't need to go into a new flow. And I actually think if we fast forward like 10 years, I do think there's going to be a lot of those experiences which, like, look eerily similar to the way that they do today because it's just, like, so ingrained in, like, human culture, like, how, like, texting is a great example of this.

Yeah, yeah. Like, I want to push notification from Gemini that says, hey, you're talking with Logan later. Be sure to ask him about this funny story, you know, and then it's like, boom. And I didn't even have to. I didn't have to.

Everything in AI, we're kind of reinventing from first principles. Like, even. Just, like, the idea of, like, the cron job, we're, like, adding that back in. And now there'll be like, a whole new cycle from, like, oh, like the AI apps got Cron jobs this week. Like, that's incredible. And it's like, yeah, but this has been around for a long time. But it really does transform the experience. I mean, speaking of, I want to know more about some of your specific workflows that you're enjoying. You mentioned deep research into NotebookLM. Is that something that you're able to do within aistudio.google.com and run it all there, or is there like a copy paste step? Because I've had to do that before where I've been like, okay, I got a deep research report. It's not reading it to me here, at least in ChatGPT. I need to take it over to Speechify and get it to read it to me there. But obviously AI Studio is a little bit more prosumer. I feel like there's a lot. I mean the temperature is there. There's like still some buttons that are almost like developer terminology. So. So walk me through some of your favorite AI use cases in AI Studio and what you're getting the most value out of so people can just kind of copy your prompts.

Yeah, John, I think this is actually a great reminder for folks like AI Studio is a developer product. Like, so we're building it for developers. And like the use case that we're trying to build for is like showcase all the models raw capabilities so that you understand what the models are capable of so that you can go and build great products yourself. Like, we're actually not so like, like Deep Research as like a great example of this. Like deep Research is built on top of a bunch of capabilities that the model has, which is like native search functionality, tool calling, et cetera, et cetera. And that's available in the Gemini app. So if you're, you know, you want the like polished consumer experience or even prosumer experience, honestly, like the Gemini app has that functionality. It has audio overviews. It's like a fully baked product. AI Studio is like give you the rawest possible experience. And like some consumer AI enthusiasts like that experience, which is why they come to AI Studio. But like, generally we're trying to showcase frontier capabilities, show you the art of the possible so that you can go and build the products that you really like. So I do spend a bunch of my time from doing work perspective inside of the Gemini app. Canvas is another one of them. Vibe coding inside of Canvas inside the Gemini app is a lot of fun.

Someone needs to vibe code a Google Reader. This would be the most viral thing ever. I don't know if you're familiar with Google Reader.

Probably before my time it was like.

An RSS reader and Google shut it down and like it had like a thousand true fans and so they were like so upset about it. I was using it as fun but I understood that they didn't need it. But anyway, continue.

We'll see what we can do. Maybe we'll, maybe we'll bring Google Reader back as a vibe coded that you.

Would destroy the Internet. That'd be the greatest marketing for everything that you're doing if you could bring back Google Reader. Anyway, sorry, I want to, I to want to let him finish about his, his. His like most interesting like AI use cases and what's, what's fun and what's in your, what's in your everyday carry in the AI world.

Yeah, I think the only other one that I'll mention is in AI this is something that's specific in AI Studio right now and we'll, we'll hopefully have it in the Gemini app and other places is we have this like live API or this real time mode where you can go and screen share and share and like show this the model what you see on your screen. I think this gets to like all the points that I was getting at before about like, like why is this such a magical experience? It's because right now the product experience of using AI is I need to go and find all the context that's relevant for the model and get it into this text box somewhere or get it into this list of files somewhere. And like the beautiful thing about screen sharing is like all of the context that I need the model to do stuff with is already on my computer. I'm looking at it somewhere on my computer. I looked at it today or yesterday or right now like just let me show the model what I see and have it do address. So I've been playing around with a bunch of pair programming examples like that and just generally critiquing work that I've done and having the model sort of watching and with my permission able to see the things that I see and talk to it is a super cool, very futuristic feeling experience.

That's awesome.

Last question, switching gears a little bit. Do you have any ignoring your work at Google and and on Gemini, do you have any takes on AI hardware? Do we need new hardware devices? Is it an area that you're excited about or how do you think about that generally?

Yeah, I think on both sides from an enterprise and consumers. I think there's a lot of opportunity and I think in the Platform shift. It makes sense to try to build something, I think. Does it end up working? I don't have the crystal ball, but I think on the enterprise side, the opportunity is, is you go in and build hardware that makes LLMs a lot faster and more efficient, and I think that's warranted and somebody should do that work.

And then on the even consumer side. Yeah. I'm curious. We had the founder of Clulee, which has been going viral before you, and he was talking about how the end state is just being embedded into the brain directly. But.

But, yeah, I mean, you can feel free to pass on this question, but the founder of Clulee, he applied for a job at Amazon. He cheated on the leetcode questions. If he were applying to be on your team, you caught him cheating. What's the punishment? Is he on the team or is he out forever?

I think we've actually been looking at doing AI assisted interviews and not AI assisted.

Like, I think.

I think the world needs both right now. It makes perfect sense to evaluate both.

Yeah, yeah. Kind of an interesting. I mean, he was doing it as like a publicity stunt, basically trolling. Obviously, I don't endorse actually cheating on real interviews, but it is interesting that, like, you will have to adapt, just like the teacher will have to adapt that was previously assigning research papers that can be one shot by ChatGPT.

No, it's an interesting way to test how somebody works individually.

Totally.

Right. Single player and talking about AI assisted as a sort of like, multiplayer experience. How do you collaborate with other people? Right. And that's like a really good eval, as you said.

And in a world where the tools, like, actually make a difference in how much you can do, like, can you use the tools? I think that's like a fundamental question that I don't think a lot of people ask in these job interviews. Like, are you AI assisted in what you're doing today? And if you're not, like, you know, it's a. There's. There's a delta in your output if you are AI assisted versus not across coding, across every discipline right now.

Totally awesome. Well, thank you. This has been awesome. Come back. I'm sure you're going to have many big announcements this year. Always welcome to. Come on and jam with us. Thank you for making the time.

Bye, guys. See you soon.

We got Eric Torenberg coming in the studio in just a minute. He's Andreessen Horowitz's latest general partner, gp. Good friend of us, good friend of the show. Known him for years and excited to, to dig into his new role and do a little some personnel news segment. We got a massive trade deal, you know, first round draft pick, many times in his career. Max contract, probably four year deal, you know, one year clip, who knows. Great to have you. Good to have you here.

What's going on?

Beautiful logo in the back. Welcome to the stream. How you doing, Eric?

Thank you. A long time listener, first time caller. Thanks for, thanks for having me on guys. Huge fan.

Yeah, yeah.

Great to see you.

Take us through the anatomy of the deal. Did they, did they sit down with your parents, tell you, hey, we're taking them to the big leagues? How did it come together? I mean I imagine you're close with a lot of folks over there for a long time, but is there anything you can share about how someone becomes a general partner at a storied venture capital firm?

They brought a briefcase to my parents house and yeah, you know, just been working the family for years.

Yeah, yeah, I love it, I love it. But yeah, I mean, I mean seriously, I mean you've known the team, team for a long time. What, what, what, what were the conversations like and how did it all come together?

It's funny, part of me wants to ask like, why didn't you ask me this a few years ago? Why didn't they try to recruit me a few years ago?

Sure.

But it's kind of like when someone amazing asks you out, don't ask too many questions, just, just say yes.

Sure, sure, sure.

My philosophy. But basically what happened was so Mark and I have been close for a long time and every year I basically, you know, sort of give him a State of the union on my, on my career and how I'm thinking about things. And this year I was like, hey, I know I want to marry Venture into what I'm doing. I have this media company, we've got sort of this founder social network thing. And everything around my career has been either investing or building communities, networks, media for founders.

Yep.

And so I was just like, I want to do it again but I'm figuring out what was the right structure, how to do that. I could just start something, I could join something early. And then Mark's like, why don't you just do this at a 16Z?

That's awesome.

And I was like, I hadn't really considered it because such a big firm, you know, so specialized. I'm a generalist investor, you know, a more talent driven early stage. And he, and I think like what I fit in at 700 person firm like. And he's like, let's, let's talk about it with Ben. So then me, Ben and Mark have a bunch of conversations. Katherine's evolved too. The other partners get involved and basically they had had a desire to go much bigger on, on, on, on content, like separate from me. And they kind of liked what I was up to at Turpentine with sort of this network approach. And they crafted the right dual role that's a mix of investing and a mix of kind of media network stuff.

Stuff.

And that's how over a few month period, we just kept falling in love with each other, even more in love with the opportunity. And so here I am.

No, there's this thing in venture, specifically investors. They spend all their time working with founders and they think, I need to be a founder. I have to start my own firm. And then you realize you can potentially have a thousand times more impact if you join a platform and make it better and leverage all of those resources. So I think it makes a ton of sense. I want to go back, like way in your early days. How did you get so good at networking? I think it's like you're probably like, you know.

The best to ever do it.

The Michael Jordan of networking. Yeah, I don't say that lightly. It's extremely impressive. And I'm curious, like, you know, if you identified early that you were just good at it or it just felt like riding a bike and you didn't. Yeah, you know, it just was totally natural.

Yeah. First of all, just say I appreciate the compliment. And no one who's good at it wants to be known as the thing that they.

Oh yeah, sure.

They want it to be like, like Delian's got a good network, but it's like a byproduct of the stuff that he does. And so, so yeah, I would say hopefully similarly too. I mean, I think the, the way I realized it, I was doing this music tech company out of college, Rap fm. It was kind of a. It was like chat roulette for rap battles. It made no sense as a, as a business, but it was just kind of a out of college project. We somehow raised the money for it. This is when Twitch, Twitch was getting off the ground. People were like, hey, Twitch for music, maybe that'll work. And live Justin TV, live video, etc. Etc. And I got people noticed that I had the skill for evangelism, like getting people excited about things, attracting talented people, you know, what do great founders do? They attract capital and labor. Right. And so I, I was I had some skill for that, even though the idea was dumb and people were like, hey, you. You have something here. And then. But I didn't put it together until product hunt, which is the thing I joined next, where like. And, you know, Ryan was CEO and he really, really got that off the ground. But I helped him sort of like, bring that out of thin air, like, you know, create a strong community and network. And in that period, I was like, this is my superpower. I like, up until that point, up until age 24, 25, I hadn't identified a superpower that I had. And I was just like, I'm just going to triple down on this. And so then Journey on Deck and Village and what is it? I think it's just like a desire to like an obsession with people, like, who is everybody? What are they doing? But then also desire to help them and think about sort of people dynamics. But then also this. That's like highest level. But then the next level is like build communities and networks that sort of help each other, where people can help each other, like even when you're sleeping. And so that's what I spent a lot of time thinking about and doing.

I want to talk about media, but first let's talk about some of the industries that you're interested in. On the investing side. Andreessen has a fund for every vertical now. Bio, gaming, defense, crypto, enterprise. What's interesting to you and is there any crossover? We kind of have this take. Like, media can be fun and lucrative, but media is really hard to invest in. If you want to invest in media, you gotta be on the platform side. You gotta be in Spotify, TikTok, Instagram, Twitter, Facebook. Like, those were the power law outcomes in media. People don't really think about them as media, but if you were in YouTube early, you did very well. Very hard to invest in. In companies that are more in the middle. What are you seeing in terms of, are you excited about any investments on the media side? And then also what are you excited about in the other section sectors of the Andreessen portfolio?

So I think Jessica Lesson really sort of helped popularize sort of the bootstrapped media company.

Sure.

That that turpentine has followed. I think you guys are following. I think it just, it doesn't make sense for. For this kind of business for the reasons that you're. You sort of indicated. But people can do very well. And so I, in general, you know, because I did a music company, a lot of people pitched me music. I'm like I don't like this business because people, I do media people pitch me media. I don't want to invest in media companies but I do want to, I do want to build a lot of media at Injuries and Horowitz.

Sure, sure, sure.

Yeah. And I do want to partner with a lot of independent creators like yourselves, like the Lenny Rutczycis, like the Harry Stubbings, like, like you know, all these guys who are building, you know, really awesome cash flow businesses, super lean, making a ton of profit.

Sure.

Well, and sorry to interrupt. One thing I think is interesting is that venture require venture outcomes require scale. Yet media and one of the things that makes media is amazing is, is anti scale, right? It's like having, for us it's like having CNBC meets X, right? It's like that's, it's a niche thing but it's great, you know, for a very core audience. And on that note, I think you've done this very well with Turpentine in terms of like verticalizing out and being like, hey, there's this sort of show on a niche topic and it may only be interesting to 50,000 people in the whole world, but those 50,000 people, like that's the show, they're like waiting for it to drop, right? Or it's, or it's a, a group chat that only has 50 people but it has maybe more activity for those 50 people than any other social platform that they use. So can you talk about how you think about sizing sort of projects? Right. Because not everything that should be done should be massive, right?

100%. It's interesting. This is business industry dive. That really taught me about something. It's a business that not a lot of people know about, but it's immensely successful. A lot of people when they think about media businesses of last 15 years, they think about like Buzzfeed and Vox and it's kind of like you know, upworthy. Raised a bunch of money in the 2010s and totally crashed. Right? There was, you know, there was a bunch of venture firms, you know, this one included doing sort of, you know, consumer media businesses. And people thought, you know, they were going to ride the platforms and they were, they were big, you know, they were growing. But then sort of the, you know, as you alluded to the platforms, you know, took the value is where the value was. It was in the distribution, not in the, and these were just like content farms on top of them. But an under told part of that story is that business media has actually done pretty well this Company Industry Dive, which is just a collection of niche trade publications. So, so things like utilities, weight, HR pharma, just like valuable niche like newsletters, sold for $500 million, I believe to Informa, which I believe is like a $10 billion trade show company.

Wow.

So business, media, business events, there's quite a good business there in trade stuff on the B2B side. Because if you have the leading HR publication and you have 50,000, even 5,000 decision makers reading or listening to your thing, that becomes a great channel for people who are trying to sell to that audience to reach them. And they're willing to. If making one sale can be tens of thousands of dollars for them, they're willing to spend quite a lot to reach that audience. So the, the, so the premiums on the CPM are, are just fantastic. And so, and Sean Griffey, the CEO of Industry Dive, has been like educating the market on this. And so I heard him and I, and I, then I looked at his. I think they're incredible at business and incredible at sales. I, I wasn't like blown away by the content itself. You know, they're a great business and they built something much bigger than I have. But I was like, wow, I think more people could do this. And the Business Workweek also is, is doing this, this, and I wanted to do sort of a Silicon Valley take on that of like, you know, Lenny Rajeski is, is the, is the goat of this for product managers, the newsletter. Yeah. I think he's almost had like a million subscribers and he's printing cash. And I was like, hey, there's going to be a Lenny for, for HR. There's going to be a Lenny for CFOs, there's going to be a Lenny for every position in every sector. I want to, I want to create that. I want to create this roll up. And we started on the podcast side because that's what I know. I think that there was gap in the market for like, you know, the best of X. And we did that. I think, I think we had, you know, reasonable success. And I was excited about adding additional businesses or business models on top of that, investing being one of them. And I think Async is the best place to do it.

Makes sense. What do you think about the different business models in media between ad sales, subscriptions, monetizing through trade shows or merch or products I've seen. I'm a big fan of Doug demuro. Demuro. He kind of like, you know, value captured at the very end of building massive Scale with cars and bids. His online auction platform for cool cars made in the modern era. Yes, I'm a fan, I know this whole tagline. But, but in general, like what, what, what. What business models do you think work in tech? What business models do you think work in other industries in. In trade publications versus more traditional journalism? How are you thinking about the landscape of like monetization of media?

Well, yeah, it's, it's really fascinating question. It depends on what niche. Like if you, if you're, if you're as big as someone like Mr. Beast, you want like a mass market thing. Yeah, even Mr. Beast. I do wonder if. And I'm friends with him and I think he's genius, but I do wonder if that's the right. If that's the most optimal business to be like. And I think he's also getting to gaming too. But like, should Mr. Beast have like sort of a cash app competitor?

I was pitching a vpn. Beast vpn because he has a global audience. Low churn, high margin. It's not. VPNs are not suitable for venture backing. Typically it's all marketing. That's the entire expense is just getting people to install a vpn. So, you know, it doesn't matter where his audience is, they can sign up for the vpn. Yeah, yeah, silly. But I don't know, probably not a good fit.

But you guys had the founder of Honey on, who's a very good friend of mine and he's building a really great business I just invested in on the ad blocker side. But like Mr. Beast was saying that he brought a lot of Honey's traffic and so should he have created a Honey competitor back? Like there's got to be something that's bigger. Yeah, there's better margins, you know, than total, than chocolate. That's more defensible.

Well, there's an interesting, there's an interesting thing with media which is like this idea of value, value creation versus value capture. And it's possible with media to create a massive amount of value, but not fully be able to capture it. That being said, one of the best ways to capture value is to just put out amazing content and then invest in the companies that sort of come around from that. So I think that people have had this idea of media of one of the best business models for media being investing yet. That doesn't mean starting a solo GP fund and just having a podcast necessarily. It can look a lot of different ways. And that's why I'm excited about turpentine in the context of a 16Z because you can make the best podcast about biotech and it's less about how do we scale this to, you know, millions of ad revenue and more so like how do we just have the most important conversations in biotech happen on this, you know, podcast and then invest in some of those companies and see the return from that.

Yeah, I know you're still like second day on the job, but I'd love to know kind of how you are thinking about the current A16Z media landscape. People talk about like, oh, future was kind of, you know, didn't get, didn't roll out the way they wanted. At the same time it's like if the named partner can go on Joe Rogan, like you're kind of winning. And so, you know, I think about like the Joe Rogan appearance is like probably worth a thousand at bats that maybe you know, are strikeouts or whatever. But you know, how do you balance the. Let's build an intermediate like a in house media product versus let's empower the team to go and make a statement on other shows. Like what Mark did with, with, with the, with the Rogan appearance.

Totally. Yeah, it's a, it's a fascinating question. So I'm still, I'm still getting up to speed with the exact history, but my outsider version of it is that the, the, the future. Well, let me step back. What I love about Andreessen and it's not limited to Andreessen, but that they, they try a bunch of stuff. Yeah, like you guys, right, like tvpn, you know, you guys had a few different iterations before coming to this, this one that worked and people don't see that. You know, like you're making video content for years before this. And Jordy, you get all sorts of like amazing branded content and doing all sorts of experiments and you guys tried it with different people first and you figured out the format that works like a couple years in or a few months in. So similarly, I think future was a good idea and I think we'll. It's possible there's some version of that that, that comes back. You know, they already do a lot of long form content.

I love their everyday carry for founders where they would just ask the, they would just ask the founders in the portfolio, hey, like tell us what apps you have on your phone right now.

Yeah.

And that was it. And it was just like a listicle of like, okay, the founder of, you know, some amazing company like Databricks, like what's he using on it for his Email client and it's like that's just interesting. I don't know. It's like yeah, it's like total insider baseball. It's totally like oh, it's only Andreessa portfolio companies or whatever. But like I don't care. I just want to know like what these people are using. It's interesting. I don't know.

Totally. So, so it, they took a first stab. I think there were a lot of great things about it. I think it also coincided with sort of the Andreessen decentralizing into. Into different funds. Like they used to be main fund and now they're sort of different funds. And so there's some org complexity perhaps around that. I think there's much more buy in and much more like maturity in the org to do something like it. Again, that's not immediate priority for me. I'm on the content side separate from investing. I'm more focused on the, on the podcasting to begin with.

Sure.

But to your. So your question around own shows versus creators. I think we're gonna have a mix. So we, we have some flagship shows right now with the Ben and Mark show. Then we're gonna have vertical shows relative to the funds.

Totally.

But then I want to sort of really grow the Turpentine network. And you know, the limitations of Turpentine were that we were a bootstrap business so we have to make money from other shows. But. And Teresa doesn't have those same limitations. So we want to like do something like an affiliate network where we can partner with amazing shows, help them get distribution, help them make more money and kind of make it a no brainer for them to be part of this sort of broader podcast network that just sort of extends our influence and friends. And I think what's interesting is that if this works in podcasting, there isn't like a premier tech podcast network that works with like the best shows. Like, and there are some, you know, I love what Ashanasi is doing. That's only like, that's like seven shows. Those shows are great and I love, you know, the HubSpot's doing some good stuff. But like, you know, Lenny's not on a network or Keshe is not an hour. There's a bunch of people because they don't need to be. But, but if you can make it a no brainer, I think there's something interesting there. And if that works in podcasting, maybe you can work with newsletter writers, maybe you can work with YouTube creators more broadly. This kind of like Extended like, I love what Slow is doing. They have a creator fund.

There was a super, super cool Andreessen games video that was produced by Secret Tape, which runs this video game documentary channel called noclip. So they will do like the full history, the most definitive documentary about like Half Life Life or Counter Strike. And they'll go and interview all the people that worked on it. These really, really amazing things. And it was actually a viral video. Like it got almost 500,000 views. And it's. This is why games like Baldur's Gate 3 are so rare. Just like a deep dive on the history of Baldur's Gate, this like great role playing game. And I just saw this and I was like, oh, it's awesome that they found the right match of like the team behind noclip and these documentary secretary. Like, they're great at creating and Clearly Andreessen Games A16Z Games was just like, go, run with it. And it worked out really, really well. So I love the idea of like that partnership model you've described.

What do you think about the infrastructure around group chats? Right? Like every. Nope, nobody wants to download another app. But at the same time, like, you do run into limitations. Everybody that's built. You've built a number of communities, right. And I'm sure you've like, hit the limits on. On Slack, hit the limits on, you know, run into issues on Discord. You know, Signal has its limitations. WhatsApp, like, how do. How do you think about scaling these sort of like vertical, you know, group chat? Like if you product. A group chat is just like a. It's a curated social network. Right. And how do you think about the infrastructure surrounding that? You think there's opportunities there?

Yeah. So first is zooming out. I think a lot of the last interesting, most interesting conversations over the last five years to me have been in group chats and I've been in some with you guys where that's happened. And I think it's just because, you know, Twitter X just social in general became a little bit too noisy, a little bit too public. And you needed to have these kind of like private spaces just to have conversations without a bunch of people sort of like getting in the. Getting in the reply. And you know, there could have been a world where Twitter that just happened in the DMs, but for whatever reason that it moved out to different, different group chats. And so. But the. The platforms are not really built for, you know, Signal, WhatsApp. They're not really built for like hundreds of People in a chat, right? And you know, they get notifications for every message. The identity is messed up.

Sometimes John Coogan just adds a bunch of random friends. On a Christmas Eve, you have to text me and say, hey, are you going to stop or are you going to keep going, John? Because I made you an admin when this is a lot smaller and there's much more powerful people in the chat now, why are you inviting all your friends?

Yeah, that was back when I cared, when I tried to moderate the chat, that since, you know, biology just. Biology goes biology and I can't.

Ye goes full biology all the time. It's great. That's what you live for.

So I, I've thought about this for, for a long time and I worked for Sriram when he was at Andreessen because he built out their group chat operation. They basically have dozens of group chats, different verticals, different categories. In WhatsApp, it's all separate chats. There's no like master directory. Like so I mean what it should be is like a real social network of like a thousand super interesting people and you can cross promote and it should be sort of, you know, like interoperable in some way with certain permissions. WhatsApp's not built for it right now. We've just optimized for ease of use. I think think that in the next five years like someone is gonna build a group chat social network where every day, well, you guys cover the current thing every day, but Twitter is too slow in the way that like, like Twitter sort of obsoleted the New York the traditional media by just being way faster. And I think there's going to be something that's even way faster than Twitter and by that like clubhouse got into it a little bit. Whereas like it's basically like the beef of the day day. Like every day someone gets in a fight or there's some drama and there's going to be a platform where they just fight live that, that I feel like that's just gonna happen. Like I remember with Mike Solana and Chester Booty like Infinite Entertainment and, and so group chat is just so much more.

I mean Vlad Tenev and Elon Musk, like.

So I was actually working on a product.

Product, sure.

That was going to be like pub house for group chats where, where you chat live with a public audience. You can sort of tier the permission gates and there's a speaker and an audience really had some magic. But I think, I actually think, you know, people said they got too big and they did. But and, you know, they're pioneers, so kudos to them. But I think that also the audio format's a bit hard. You can't, like, scroll audio the way you could scroll text. And so I think group chat format, that is the right one. I was working on it, but then I, you know, spent time with. With Marc Addressin and decided to have other plans. And I also met another team that I. I'm not gonna announce here yet, but surely to them and when they're ready now, they will. Who's building this? And I think it's exciting product. I think the. As you said, Jordy, the bar for a new app is really high, but there's a bunch of different ways that WhatsApp and Signal just aren't built for it. And I think you could do a 10x better product there.

So I'm curious.

No, I was asking in hopes that you were incubating or funding or.

He found it.

Something there. Well, you found the right one, it sounds like. But yeah, it just seems like such an obvious opportunity. When I hear about you running multiple groups, I'm just like, wow, it sounds really exhausting. The second that you get even more. Even just one is a lot.

Yeah.

Excited to see that roll out.

I have a hot take I want you to react. Back to. Market maps are underrated.

Oh, interesting. Flesh out the case.

I just think that they got really, like, overhyped and they were kind. So I mean, the basic map, the basic mechanism of a market map is it's inherently viral. Because when Andreessen puts out a market map of, like, all the gaming startups, like, every gaming founder is going to be on that list, they're all going to repost it. And so it's just naturally like bait for the algorithm that it's going to get a lot of attention. A lot of quote tweets, oh, thanks so much for including me. Right. But then it became, like, very, like, cringy. And it was like, no, you should. You should be, like, thinking more deterministically about the future. You should be more aggressive. You should be thinking more about even, like, bigger problems, like the far future, the world. But, you know, I've gone back to market maps and I think there's maybe something interesting there just to kind of take you on a tour of all the different approaches when there is uncertainty about something like AI at the application layer and how that's applying even to legal. Like, everyone kind of knows Harvey, but there's probably seven different companies in the legal AI space. Probably 50, 70 and they're all taking slightly different approaches. And it's kind of a nice, like little window into this industry that you might not be immersed in. And so it creates some value for, you know, keeps the associates busy, keeps the partners busy. But it's also just maybe, maybe we can get past the, the criticism that like, oh, market maps are too basic and cringe and maybe just go to like, hey, actually they make sense. If you read a Goldman Sachs report or Morgan Stanley report on Wall street, you would often see something that looks like a market map. It's just instantiated in equity research. Right. Or equity capital markets research.

I'll go further. So I agree with you. But I'll one up you and say I think lists are underrated. Like Forbes has trained us to think that yes, yes, yes, lists suck or they're obviously always gamed or everyone's gonna go to jail if they're on a list. Hypothetically speaking. But you know, we've joked about sort of the, like the Forbes 29 under 29.

Yeah, yeah, yeah, I think you should do that. I mean, I don't know if it's best suited. Maybe we do it.

Maybe we do it but collaborate or something. But discovery, discover, like knowing what people think about people is really important. And it's what we do all the time. We're like, who's good? You know, who's emerging? Who should we pay more attention to? And I think that functionality, sort of like market maps, we've, like, the execution has gotten sloppy and so we sort of throw the baby out with the bathwater. But those things, they do perform best, which is why they get gamed. But if they're good, they're.

They're really valuable. Totally. Yeah. Yeah. We're actually going to do a Midas List competitor. It's going to be 100 of the top VCs. It's a hundred thousand dollars to be on the list. A million dollars if you want to be on the top 10. But yeah, just email Jordi if you want to be on that list. If you're listening, we'd love to have you.

I love your whole corporate media like rant.

Oh yeah. Independent media is dead. Corporate media is the future. Yeah, you're either backed by a trillion dollar venture fund or you're shilling for ramp and bezel and ad quick and numeral and asleep and wander. You're one of the others.

On a more. On a more serious note, I'm curious if you're seeing from group chats the edge that you used to be able to get from the Internet. Like Internet used to be a place you could, you know Blake Robbins talks about hanging out on the edge of the Internet like but, but you could be in these sort of different sub communities and sort of discover somebody. And you know we had this, this kid, this 21 year old named Roy who like rocketed to like almost 80,000 followers in like a few months.

Serious.

And historically that would have been like some, you know, maybe he would have have had got gotten kicked out of Columbia and like two people would have heard about it on X. Yeah. No way. But now it's like information moves so quickly. Is it you know, are you seeing group chats as like the sort of where you get an edge? Right. Because it's like you know, more niche down. There's like less, there's less noise, there's less attention. Maybe if there's a thousand people in the group chat. Like you know it's, there's less like almost like leakage like how do you. Where you do. Where do you think about?

So it's really interesting. So a few years ago when people were more sort of centralized on Twitter there was more of a desire to. It was critical to go to group chats because someone was quicker to cancel you or call you out or there was just more friction. But social media has Balkanized a bit. The whole blue sky exodus sort of, you know, people are threads, whatever people leaving X like it's a bit. And then Elon sort of, you know with his sort of new impact on sort of the like free speech dynamic or even just like everything's about politics all the time. So people are more comfortable speaking up on X. But they're. Because they're more comfortable speaking up in public, they're also more comfortable speaking up in private. So I've seen what happens is these like eight people group chat chats, you know me and John had a great one for like a couple years are now there's less of a need for them. It disbanded now they're now we're in like multi hundred people group chats because.

Yeah.

Or more public and I think it's cool that you know we have people who disagree. Like we have this you know one chat where our good friend Mark Cuban gets, gets in you know, great debates.

You know I thought you weren't supposed to say people's names in that chat. I thought the whole reason was Chatham House rule. A you know, billionaire, somewhat left wing. He was lampooned on Silicon Valley.

Yeah. Reality show. Yeah. Pitches he, he Went on a podcast with Vivek. They had a debate. So this is public because they, they said their names. They did a debate on Di in our chat and then they took it to the podcast.

Oh, that's cool.

They mentioned the chat. So I'm comfortable mentioning their names as. As people who've had debates. And it's just fascinating. Like, you know, he doesn't want to go on Twitter because he gets dunked on a billion times in chat. He'll get dunked on, but with more thoroughness.

Sure, sure, sure.

And we all learn from it. He gets some dunks in too. And that, that's the dynamic you just won't see anywhere else. And I didn't even see it a few years ago because you wouldn't even think to put people who disagree in the same chat. So. So, yeah, I'm still seeing the Alpha.

Well, the most important group chat to me is the one that's just me and you, Eric. Our one on one group chat. That's the best group chat in my. In my DMs. Thank you so much for coming on. This is fantastic.

Hey, Eric, little request. You're the first Andreessen partner to come on the show. Let's get the rest on.

Let's get the rest.

Thank you for.

I'm here to, you know, only Nixon can go to China. Only Tornberg can go to tbpa. I'm here to broker the relationship. Relationship.

Are you, are you Kissinger or Nixon in this analogy? I think you're kissing.

Great to have you.

You sneak in through the back door and then Nixon makes his arrival.

Yeah, we're very excited to. To. To watch you work and collaborate. And congratulations again on the move.

We'll talk to you soon. Bye.

Bye.

Next up, we got Jack Whitaker coming in to the studio, the author of the fantastic substack bunny Hopping. I wonder if that's a reference to Counter Strike. I'm a big fan of bunny hopping. I don't know if you ever did that or if that was before your time.

Like a BMX reference too.

Oh, yeah, yeah, yeah. You can bunny hop on a BMX bike. But he wrote a great post. Pre training isn't dead, it's just resting. GPZ 4.5, the value of Reinforcement Learning and the Economics of Frontier Training. So welcome to the stream. Jack, how are you doing?

Boom.

Doing great.

It's great to be on the show.

Thanks for coming on.

A little context for everyone, Jack. Jack is helping us with our distribution strategy, so thanks for all the support. Jack. It's great to have you on the show. Probably first of many, I guess.

But I love the post and I'd love for you to take us through it. What inspired this? You kick it off with a couple of the reactions to GPT 4.5. The one that's popping out to me is from Jack Morris says so GPT 4.5 is 10x bigger than 4.0 and only marginally better at most things. My read could be the beginning of the end for scaling laws. What happened here? Did we run out of data? Or do scaling laws not capture model behavior on tasks we really care about? What inspired you to write this post?

Yeah, definitely. So a lot of me and my friends really like GPT 4.5 and we kind of had this high taste tester mentality where we thought it came out really well and we were kind of confused why people were underwhelmed by it. But a lot of the reason people were underwhelmed by it were the actual benchmarks. You can look and you can see it did worse than you'd expect. So me and Trevor were like, well, did it do worse than you would naively expect on the benchmarks? Have we actually graphed out a log linear law to this scale and seen what performance we'd expect on aime on everything else? And when we actually did this, we saw that it was about in line with benchmarks, a little bit better, a little bit worse. And we thought this was a really important conclusion. I think what a lot of people don't realize is that these are log linear laws. If you double the amount of compute that goes into AI model, you're not going to get double the score on the math benchmark. This is something that we expect that as compute gets larger, as build outs get faster, we're going to get much better models, but not just because you can double model strength with doubling the amount of compute.

So what is the implication for that? What model should people be defaulting to in the ChatGPT app? I think that that's the thing I want to start with is should people just trust you and say I don't care what people say online, I gotta pick 4.5 from the dropdown. Even if I can't tell, I will be getting better results. Or is there more nuance there with some of the reinforcement learning that's happening on top and some of the reasoning models that might take things to the next level even if the underlying model is weaker and cheaper?

Definitely, yeah. Well, I think the central claim here is that pre training will continue to work as we're able to build it out. Not that the pre trained models are the best right now. I think OpenAI's O3 is the best model we've ever seen. It uses RL on every single type of tool use. It uses RL on chain of thought. It is quite a small model and it came out really impressive.

Is O3 built on 4 or 4.5? I'm kind of confused at this point.

Yeah, there's no public information on it. Me and Trevor did some estimates based on the token speed that comes out and it seems like it's quite a small model. Smaller than GPT4.

Interesting, interesting.

Bigger than four. Oh, mini.

Okay, interesting. So is this something that we're expecting them to optimize over time and eventually distill 4.5 or maybe just scale up the inference chips to the point where they can run an O3.04 style model on top of 4.5?

Yeah, as you scale up the inference and as you scale up compute build outs, you could take something the size of 4.5 and you can do O3 style training on it. And I think that's going to be a really, really exceptional model. I think a lot of the point of the piece was that you have a lot of axes on which you can improve AI and none of them are obviously showing diminishing returns. So there's just tremendous potential to make models better and there really is no wall.

But what about the economics? At a certain point you need an order of magnitude. This is log linear, of course, so you need order of magnitude more compute. We're getting into the $500 billion data center. At a certain point you get to 5 trillion and you're talking about a meaningful portion of global GDP. And if the results are oh, it goes from 128 IQ to 130, the economics don't really pencil out. What's your take on will we just see a pre training winter just for purely economic considerations?

Yeah, and I think that's what we're seeing right now. But another thing is that even as we have like it would be really expensive to train a model 10 times bigger than G 4.5 now and probably like impossible to serve. But in a couple of years we're going to see the type of algorithmic efficiency and we're going to see the type of chip improvements that make a model at this scale much more feasible.

When you say algorithmic efficiency, are you talking about the type of optimizations that happen with deep seq on kind of memory inconnect the FP8, those types of inference optimizations at the actual inference level? Or are you talking about the actual design of the algorithm as it's trained or the design of the model?

Yeah, basically on every level. I'm really referencing Dario's excellent piece about Deep SEQ and export controls where he says that Deep SEQ is really good model, but we do just see these continuous algorithmic improvements as we go. So sort of the functional ooms of compute are also scaling even if your compute isn't scaling.

Talk about switching gears for a second. What is the, what's the vibe on the Stanford campus right now? Is there a risk that everybody drops out to work on AI? I imagine it's like a constant conversation.

Yeah, I wish it was honestly talked about a lot more. There's a lot of people, a lot of my friends around campus like Mohit Agarwal and Jacob and Tamaki, you know, who are super aware of this stuff and are always kind of pushing things forward and thinking about these things all the time. But in terms of just the populace getting used to AI and getting involved in it, it's just been a really slow and continuous crawl upward. I'm a CS major, I end up talking to a lot of CS majors and they're not fully internalizing what the model suite is going to look like. Everyone thinks that the models are going to get better around the same kind of paradigm and level, and no one is ever thinking we have O3 now. What's GPT5 going to look like in a few months? What's GPT6 going to look like next year?

What are you thinking GPT5 will look like? Are we just talking about another order of magnitude on pre training flops, or is there more to it than that?

Yeah, so my naive guess is that GPT5 is going to be a model that uses all the clever training techniques that OpenAI and Anthropic have worked out around RL, but it's scaled up significantly from these pretty small models. Sonet 3.5 is pretty small. I think the O series is quite small as well. One thing that I think is the Most interesting about O3 is that it has a lot of these agentic properties that we've been seeking for so long, but it has them in this kind of narrow sense where it can agentically call tools, it can agentically browse the Internet, but it's not necessarily agentically going and doing a whole project. And I think that trajectory is one to watch as you look at GPT5, because you're going to see it being more and more agentic, just very naturally as context expands and as the model expands.

Yeah, Tyler Cowan said O3 is AGI. We had someone on the show yesterday who said we have 10 minute AGI, but that's not necessarily 8 hour AGI or 24 hour AGI. How do you think about the length of reasoning chains and kind of that new frontier of optimization? Maybe we've hit the intelligence curve, but we need the agent Icness to continue for a long time.

Yeah, I basically think that's right. The 10 minute AGI take is exactly right. I mean, the AGI debate hinges a lot on what definition you use. Obviously the Microsoft CEO came on Door Cash a few months ago and said, I'll only believe it's AGI when the GDP goes up by however much percent. I think we're starting to see models that are very general and they're very intelligent and they can do a lot of the things that you might have naively described an AGI to be able to do, but they still don't really have this full capacity yet. I think a lot of this stuff just gets worked out as we kind of improve our current techniques though. And isn't necessarily some barrier, some key problem that needs to be solved.

Are undergrad CS majors bullish or bearish on wrappers, or trying to go for the application layer trying to do a startup? Or are the best and brightest saying, hey, there's no way we're going to win, let's go work for a lab?

Yeah, I think a lot of the smartest people I know really want to work for labs, but I think they're almost too bearish on startups and on wrappers in that a smart wrapper can take a model and kind of scale up with it. And I think this is what we've seen from places like Cursor. You improve as the model improves. If you're making a wrapper, that's a bet on models not getting better.

You're doing a lot of prompt engineering and, and you're really working to create the scaffolding to try and make the model better instead of just saying, okay, how do we, how do we get distribution? How do we get the user experience? And then product gets better.

Very light wrappers of the last few years, I think a lot of them relied on consumers not being aware of ChatGPT's capabilities.

I mean, there's some apps in the app that are literally like AI.

Yeah, there's still like billions of dollars of revenue out there. That's basically they just happened to acquire a customer before OpenAI did or another lab.

Yeah. Can you tell us any more about just the mood among CS majors around the opportunity in startups broadly?

Yeah, I may write about this pretty soon, but I do think the startup culture at Stanford is really not what it used to be. There was sort of this halcyon era at Stanford where it seemed like there was so much energy around startups and now it really feels more like people are doing their startups as summer projects and people aren't committing to them in the way that you really want to see. I think that if some Stanford student came to me and said, I want advice on what I should be doing this summer, I wouldn't tell them to go start a company. I would tell them to go work for Ramp. I would tell them to go work for Cursor, I would tell them to go see one of these incredible organizations, look at how they work, and then take this knowledge to go start a company. I think too many people are doing these things as like side projects and not fully committing to them.

Yeah, we talked to somebody who is referencing the early Facebook days at Harvard where if you were an undergrad at Harvard or Stanford and you were interested in startups, like going to Facebook was the expression of that. Now if you're interested in startups, like there's a $2 million seed round just waiting for you and you will be a founder, even though you could go join a 10 person or even 100 person startup, get a lot of that startup experience. So do you think venture capitalists are to blame here or is it something cultural or should we lay it on the university who's to blame?

Yeah, there's no actor who really made this bad. But the fundamental issue is that startups became too high prestige too fast and like doing real things and really building things didn't gain that same kind of prestige. This is a lot of actually what I valued most about My Time at DoyCash podcast, which is where I worked last summer, was that Dorkesh felt like a startup. You know, we had all of this energy, all of this attention that a startup had, but at the same time, obviously we're doing a podcast, you know, we're executing at a very high level, but it's a podcast. And I think getting to work with someone like Dorkesh, who has this like, agency and this knowledge and this drive to make things better and make his content incredible, make his questions incredible, was something you can Learn a lot from, you know, so it becoming higher prestige to have like, like stealth startup in your bio than it is to have like. I'm like working for Nat Friedman this summer is like pretty lame.

Yeah, I think that'll shift. I mean, working for Nat Friedman's pretty cool.

Working for Nat Friedman's pretty cool.

I think it will catch up.

Yeah. The benefit is we have a generation of people that are finding out just how hard startups are and there's not land somewhere. Yeah, they'll land somewhere. But also realizing that if you're going to start a company once you know how hard it is, you really, really, really need to pick.

Yeah.

Pick ideas carefully.

Totally. Can you give me your read on the last two episodes of Dwarkash? He had AI 2027 and then AI 57. 2057 or something. Are you AGI pilled? Are you feeling the AGI? What's going on over within your world?

Yeah, for sure. I actually, I mean, I think the Epoch people are fantastic and I also think the AI 2027 people are very smart. And I sympathies to both sides here. You know, I think model capabilities will grow very quickly and I think it's much less clear how this will translate into the economy growing really fast. You know, I was in an interview recently and someone asked me, say, jack, you keep telling us AI is going to be good. I think AI is already good. Why hasn't it changed the economy? I was like, I don't really know. It seems like the naive economic model says that diffusion of technologies takes a really long time. And it seems like intuitively that wouldn't be true for software, but practically it seems like it is. So I think the AI 2027 people might be mostly right on how fast things are going to grow and how fast the model is going to get smart. And then the Epoch people might have a really good sense of like, oh, but really getting this into the sewer sector, getting this to disperse across the economy in a way that changes things fundamentally is a much longer issue.

Yeah, I mean, maybe it's just like a human issue. You could kind of comp it to. I mean, you go back to like the PayPal days, like the Internet got fast enough to transfer money very quickly, and then the percentage of money that was transferred digitally grew very slowly because it's human behavior.

And it was only last year that stripe became 1% of world GDP transactions.

You know, and that's Stripe. And they're like the Power Law winner in the category. Yeah, it's Crazy. Anyway, Jordy, you got any other questions?

Not this second but Jack is.

Yeah.

We gotta have you back.

Every time you pop up back on give us the breakdown. This was fantastic. Thanks so much.

And Jack's coming to LA soon.

Oh, fantastic. Looking forward to meeting you in person.

Yeah, for sure. We'll see you at the new studio.

See you at the studio.

Thanks for coming on, Jack. Bye to see you.

Great to be on guys. Thanks.

See ya.

Talk to you soon. Should we go through some timeline posts and then get out of here? Matt Wang says I find he's quoting he posted quote I find that super subject matter experts can sometimes be very bad at predicting the things they're an expert in. That is because they're overweight their own expertise. Interesting.

I think we should deep dive this.

This chat with Domer, the number one trader on polymarket. Interesting. Kind of like an anti. It's not anti wisdom of the crowds because that's polymarket. But there's something. There's something there that I mean highly relevant to the AI discussion where everyone has a different prediction, they all have a different set of experiences and expertise and then also conflicts of interest and all sorts of things. But we should dig into that post. Joe Weisenthal shares that markets are surging on this headline. Bessant sees de escalation of China situation unsustainable S p now up 2.7% I didn't markets.

Markets love when a situation is unsustainable.

Yeah, we're de escalating but unsustainably. Who knows. Anyway, we got some big news in the media world. Evan Armstrong has walked away from his cushy writing job at Every to launch his startup. Today he's going founder mode founder. He says the leverage is his big swing. Starting a company while parenting a newborn feels a little insane. But I couldn't keep this idea inside me anymore. It had to exist. So congrats to Evan for taking the lead into the arena. Out of one arena into the other. Maybe it'll be a public company one day. Maybe you'll be able to buy the stock on public.com investing. For those that take it seriously, they got multi asset and he's got to.

Be the first substack to spac.

Yeah, I'd love to see. Anyway, we wanted to give a little congratulations to CC Gong. She shares a life update eight months after she went viral for supporting her YC boyfriend. I don't know if you saw that. Eight months ago she posted some photo saying like my boyfriend's nyc. I Cooked him dinner and it went like very viral. But he proposed this last weekend by bringing together a hundred of their friends and family to surprise her with a stand up comedy show that she had to perform in retriever mode. It's fantastic. She says. I posted the tweet in jest, but it sparked a global gender debate about women being invisible emotional labor sidekicks to men's visible professional success. In actuality, my fiance is my secret weapon. So congratulations to cece on the engagement. I hope the wedding planning is fun and enjoy. And I hope his company starts ripping. You know, if it's not ripping already. He's. He went through yc. Hopefully it's just up and to the right from here.

Marriage is the greatest investment you'll ever make. It is one of the most important.

It is Calvin. Kevin says never buying regular zins again. 5 pound bucket of horse nicotine from tractor supply. Never underperforming or having a foggy mind ever again. I am the happy hashtag boss. Lipping half a horse dose and I scroll so that.

So that people can.

It's the next. The next slide is. Is queued up for the mustang horse nicotine packets. If you pull up the next slide.

Do you know about this is. Is nicotine consumption in the horse community?

No. Wait. Do you understand the riff on this? So. So basically someone got horse electrolytes.

Yeah. And was like this horse aid.

Horse Gatorade went mega viral. And so now people are spinning off on that. This is clearly AI generated.

Oh, okay. Okay. I saw this. Way too far for it. I saw it and I was like, John is the size of an average horse.

Maybe I should do this.

We gotta get Lucy to do some horse nicotine.

There were other jokes about this. There was horse creatine. People were spinning off on it.

Got it.

There's a variety of options.

Wow. I got AGIs here.

Yeah, AGIs here. Oh, this is big news. The star defense tech founder Matt Grimm was. Was spotted soaking up some sun at his Costa Mesa headquarters. He is of course the.

We have engineers everywhere.

And he stunned in a perfectly tailored three piece suit.

You can't step out of your office without one of our.

We have paparazzi everywhere. We're bringing the paparazzi to technology.

And Ben had a good idea. He said need TVPN to start a weekly segment showcasing the best tech, business and finance fits of the week. What league fits does for the NBA for the high cost work fits. Maybe even throw in a yearly awards segment.

Oh, we already did that. We already did that. We already did the best fitted in tech. Aiden Gomez was the runner up. I believe Alex Karp won for his. For his general overall style, but also his fantastic Patek Philippe aquanaut with the gold strap.

Well, great idea, Ben.

Or the orange strap. We already talked about Clulee, but there's a lot of backlash. I thought it was a great interview. Interview. I thought. I thought it was interesting. It is a little. What's interesting is that I don't find his actual product that dystopian. The idea of having augmented reality glasses that I think he finessed the Internet.

For a bunch of attention.

Yeah, he finessed the Internet.

I think he's going to leverage it very well.

The most dystopian thing is that he's clearly a talented founder. He can't just say, I'm building augmented reality AI app. He has to go and put it in these provocative terms. That's actually the kind of more disturbing thing.

And he wants to get to a implant, effectively a chip for your brain, but he's got to build enterprise SaaS to get there.

Yes, I love that.

And that's a good lesson for everyone.

Well, speaking of a lesson, Sam. Lesson said. I think we should.

Let's actually save this for tomorrow.

Okay. Yeah, let's bring him on, go through it. Yeah, it'd be great to invite him on and talk through what to do as a seed investor and his tldr. We will go to a post from Bezel. We already did the ad read, but they had a great post. Cartier said brand everything and they launched a horse headband that's branded. I love it. Camel drapery. Branded grass. Not yet, but they're working on it. Maybe we should do a TBPN horse headband or camel drapery for the folks in the audience who have horses and cameras. Camels. I think it'd be great.

Yeah.

Put some ads on there, like the jacket.

We should do a TVPN camel drapery or horse headband.

Horse drapery. Yeah, livery for your horse. I love it. Anyway, shout out to Michael in Hawaii. He says, doing my duty and TBPN pilling my Hawaii. One big screen at a time. Size gong, in full effect. Thank you, Michael, for putting us up on the largest TV I've ever seen. This must be a projector of some sort. But I thought. This is an awesome post. Thank you so much for sharing us on the big screen. We love to see the show on TVs and in offices. We love when we're just passively on in the background we'll get the subtitles going at some point. The live. Like what you see in the live transcription? Yeah, live transcription. I'm sure we can do much better than what the standard is on tv. That'd be great. Also another post from Rahul. Been on the show. Big fan of him. He says with intense focus.

Really wearing the suit everywhere.

It's fantastic.

It's amazing. I'm so happy because he works in finance artificial intelligence. So glad he's dressing the part.

Finance artificial. With intense focus you can build a superior product. He's sharing a text message that he got from a friend, I believe, or a customer. Just tried Julius for my first real use case. I've always been annoyed that the eight sleep app only gives you the last year of data. I found out that I could get a full export from them and ended up with like 10 megs of JSON. I tried visualizing the data with ChatGPT and Claude and they just couldn't manage it. I decided to try with Julius and immediately nailed everything I asked for. Keep up the great work man. I love that. And promotion for eight sleep. Use code tvpn.

Use it.

Fantastic.

And then download Julius.

He also was on a plane and he downloaded all my YouTube analytics and Julius analytics on that and showed that.

Put you under pressure Scope.

I've been in the trenches. Content treasures. Yeah, I think the first year I got like a couple hundred thousand views and then it was like 17 million three years later it was great, great, great run.

Anyway, this post from Natsuki, I don't know if it's. It seems like it might have been Photoshop, but it was funny. Hey chat GPT. Look under there. Underwear. LOL. Made you say underwear. Haha. Well played. Say home. Home. Latitude 52.3974 this looks like an ad.

For Gamdom or whatever.

Why they put a gambling ad. No, no, no, no. This is a way. So. So this is a hack that betting companies are doing.

Wait, but why is this. Why is. Why is this AI poster posting about gambling? I feel like that's such a.

No no. So, so basically what's going on here? I bet Natsuki, he just posts a lot of content like this. Gambling companies I think are allowed to watermark. Yeah, they pay for watermark on a lot of posts.

Weird, weird strategy. Anyway, last shout out and then we'll wrap up the show. Mass, you know him from the viral swing gate up in San Francisco. We covered on the show. There was a swing on a tree. It broke. He he said you can just do things and built a new swing and then that was taken down went back and forth. I called it the most important political issue of our modern day. I said that unironically but he just wanted to give a huge shout out to Daniel Strachman, Danielle Strachman and 1517 Fund. They are the goats because he's been looking for COMPUTE and he got some. He said we were just approved for $100,000 in AWS credit it thanks Mass for working so hard on that and huge thanks to Danielle for hooking us up. So he got some, he got some credits and he's going to be training a DECA billion parameter time series digital twin of the global economy. The future is predicting the future. Are you ready? Anon. So congrats to Mass for working on stuff. I think he's working in the stock market prediction, hedge fund prediction. Very interesting area to apply artificial intelligence to obviously a lot of data and I wanted to give him a shout out on the show. Anyway, we've had a fantastic show. Thank you for watching, thank you for listening and we will see you tomorrow. Have a great rest of your Tuesday.

Enjoy your Tuesday. Goodbye Chad Day.