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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TVVN. Today is Tuesday, 04/22/2025. We are live from the Temple Of Technology.
Speaker 2:The forge of finance. The capital of capital.
Speaker 1:This show starts now. We got a bunch of massive news. There's there they there's the timeline's in turmoil. There's deals getting done, and the stock market is way, way up, folks. Way up.
Speaker 1:People said we couldn't come back. They said it was so over.
Speaker 2:These days It was not over. These days, rumor, A simple rumor might move the market trillions.
Speaker 1:Yeah. Look at look at Tesla stock right now. People are like, oh, Tesla Tesla's done for. Tesla's done for. Woah.
Speaker 1: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 prized bulls today.
Speaker 1:We're talking about Toma 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 I was thinking about the market. I was thinking that we need to just take out billboards just for the market broadly.
Speaker 1:The global economy. The American economy needs to buy billboards. It's not ad quick. Just an ad that just says go long. That's it.
Speaker 1: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.
Speaker 1:Only AdQuick 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?
Speaker 2:I think it's great idea. I'm still laughing about the Trump Powell dynamic. Yep. The idea that
Speaker 1:Let's move on to that.
Speaker 2:Trump is, you know, basically doing what every VC would like, which is just demanding lower rates.
Speaker 1:Yes. Yes.
Speaker 2:Yes. Ignore the ten year. Ignore the thirty year. Yes.
Speaker 1:People are saying, oh, the VC's 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 five d chess to get lower rates. If we get lower rates, we're going to the moon.
Speaker 1:This is great. Central bank's legitimacy is at risk as 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.
Speaker 2:Oh, no. Not good. Maybe what Trump is, you know, this this he he wrote it as central bank Yep. Centralizing, verticalizing Verticalizing.
Speaker 1:Verticalizing banking. Verticalizing the Fed. Privatizing the Fed. Yeah. Oh.
Speaker 1:I mean, OpenAI went from nonprofit to for profit. Seemed like it went pretty well. Could we like
Speaker 2:Our institutions are more malleable than you think.
Speaker 1:Could we sack the Fed? I think that might be the 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 doesn't cut interest rates soon. In the process, he might also be seeking to de 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.
Speaker 1:Now there is virtually no inflation, he said blasting Fed chair Jerome Powell. Mister Too Late and a major loser.
Speaker 2:Whatever you whatever anyone thinks about Trump, they have to admit that he He's good
Speaker 1:at coining.
Speaker 2:Coining. He's good at nicknames. Mister Too Late, quote, unquote, a major loser.
Speaker 1:Powell has always been too late. He misspelled it, I guess, in this post because the Wall Street Journal puts in in, in brackets s I c sick for for misspelling. Except when it came to the election period when he lowered in order to help sleepy Joe Biden and later Comma get elected. But Comma didn't get elected, so it's kind of odd.
Speaker 2:It's amazing that the market can be up in a twenty four hour period where Trump is attacking Who hurt
Speaker 1:the Fed? Undefeated. That's why. It's it's that simple, Jordy. I don't know what else you need to hear.
Speaker 1: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 advisers alleged 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, 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.
Speaker 1:Think
Speaker 2:that's main strategy. Know, Jim is it Jim Simmons? Right? If Jim had had right access to the Fed, he could've
Speaker 1:he could've been maybe golden age for
Speaker 2:Trust the computer. Turbo long. Trust the computer.
Speaker 1: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.
Speaker 2:Could this all be ahead The Polymarket will Trump remove Powell in 2025 is still only at a 20% chance. It has jumped dramatically from Yeah. Mean, you're tracking this stuff, there's
Speaker 3:a lot
Speaker 1:of noise on either side because it's a highly partisan issue. But that is why I like Polymarket generally. 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 are are not politically biased because people just wanna make money when they're in there. And so it's a much stronger signal, in my opinion.
Speaker 1:Anyway, the next WallStreetJournalcom story happens to be Boeing is selling some of its navigation business in a $10,550,000,000 deal. Ring that size, Gong Jordi. The agreement of includes the sale of Jepsen, ForeFlight, AirData, and OzRunway assets to 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.
Speaker 1: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, you know, kludgy system that was far too big. It's a yeah. I mean,
Speaker 2:people don't know how to solve a basically, when people think of Boeing, they don't associate it with quality. Right? They went to you know, they've been suffering through a PR crisis, a quality crisis, whatever you want to call it.
Speaker 4:Yep.
Speaker 2:But it's interesting to think about this set of software providers as basically being critical infrastructure, critical software infrastructure for aviation broadly.
Speaker 1:Yeah. Let's go through a little bit of this. I want to do a little bit of a deep dive on Tomo 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.
Speaker 2:The deals tend to market themselves.
Speaker 1:Yeah. And and then every once in 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?
Speaker 1:I don't think anyone's thought of that. This could be a good opportunity.
Speaker 2:Good opportunity there. A great opportunity. One's thinking about Really fun task.
Speaker 1:Yeah. No one's thinking about Why has no one thought
Speaker 5:about that?
Speaker 2:Private equity has not at all been thinking about driving business efficiency with software for the last twenty years. They wouldn't even dare.
Speaker 1:So Boeing is trying to slash costs and raise money as it burns billions of dollars a quarter and struggles with a quality crisis in the wake of last year's fuselage panel blowout on on Alaska Airlines flight. That was exciting. I
Speaker 2:Their a lot of people are Their losses are staggering.
Speaker 1:Yeah. Lot of people are saying, I'm not flying Boeing. And I always said, if it ain't Boeing, I ain't going. Boyle. Boyle.
Speaker 1: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
Speaker 2:for Boeing.
Speaker 1:For for Boeing, for ramp, for bezel, for Wander.
Speaker 2:I I think people
Speaker 1: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 through. I'm putting my life on the line
Speaker 2:I'm through.
Speaker 1:Business, and all of a sudden it's real, that fires me up.
Speaker 2:No, and this is why Nathan Fielder's new show, The Rehearsal Yep. Is fantastic because it's all about aviation safety. The timing is perfect. 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. Yep.
Speaker 2:On the show just how difficult it is to manufacture large commercial It's crazy. China has not been able to really get their national champion to any type of real scale. Yeah. Is extremely, extremely difficult. Yeah.
Speaker 2:Phones We should support Boeing. I support Boeing.
Speaker 1: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.
Speaker 1: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. It's fine.
Speaker 1:They 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 talked to a couple 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, a truck bed as opposed to something huge that needs a crane. And and every time you're working with something that's that massive, your supply chain is now three different companies instead of 30.
Speaker 1:And every time you need to move anything, it's very expensive. Yeah.
Speaker 2:Chief executive of Boeing, Kelly Ortberg, last year said he would cut 17,000 jobs. He also raised more than 24,000,000,000 in equity to keep the company
Speaker 1:good fundraise, honestly. That's Yeah. Big numbers. You know? Another You gotta give it up to a guy who's who's putting up big fundraising numbers.
Speaker 2:Yeah. Executives have been exploring asset sales that could bring in much needed cash while shedding noncore or underperforming units and approach Ortberg has described as pruning 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 that Jepson 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.
Speaker 1:Yep. They're selling AirData, which specializes in aircraft leasing, maintenance, and asset management, digital solutions, and OzRunways, 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 and those included in the sales. 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 flight software all over the country, they gotta get on Numeral.
Speaker 1:That's right. Gotta put
Speaker 2:your sales tax
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Speaker 2:Go check out Numeral. Thank you to Numeral for supporting the show.
Speaker 1:Quick background on Thoma Bravo. Started in the eighties, Stanley Golder and Carl d Thoma founded Golder Thoma and Company 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 Toma was a Stanford MBA from rural Oklahoma, and he shared Golder's vision of a gentler approach to leverage buyouts. It's gonna be gentle.
Speaker 1:Gentle. Just a gentle LBO. Activate gold golden retriever mode. Yeah. He's being very nice.
Speaker 1: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 eighties. So they're saying, we're we are gonna LBO. We are gonna use the tools of modern finance.
Speaker 1:But instead of just asset sales strip, hostile takeover, cost cutting, like, traditional, like, the bad like, the, oh, it's private equity is so rough, They're thinking of more of like a growth mindset. So they brought a growth mindset to private equity, basically.
Speaker 2:Yeah. And bring it up since it was part of the conversation. Yesterday, had David Tishan talking about venture roll ups, basically. Yep. 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.
Speaker 1:Oh, for a long time. It's businesses
Speaker 2:and saying that we're gonna leverage software and even saying that we're gonna leverage artificial intelligence Yeah. To make these businesses more efficient. So the idea that people in venture are gonna come in and outfox private equity, which is cutthroat Yeah. Efficient, professionalized. Anyways Yeah.
Speaker 2:I I do believe there's opportunities. Yeah. There very clearly are opportunities. Totally. But it's not a, oh, no one's It's a
Speaker 1:blue ocean market.
Speaker 2:Yeah. It's not a blue Totally.
Speaker 1: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 so he's kinda 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
Speaker 2:much as the roll Boeing deal Yeah. They're they're buying an existing basket of assets, and I'm assuming they're gonna add to it. Exactly. Then eventually, they'll probably take it public
Speaker 4:again.
Speaker 1:And so the this approach is common now in private equity, but it was novel at the time, and it earned Golder and TOMA 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 nineteen eighties stereotype of the ruthless corporate raider. By the mid eighties, their success attracted new talent. In '84, Brian Cressy, a a first Chicago colleague of Golder, the other founder of the firm, joined the partnership.
Speaker 1:The firm was renamed Golder, Thoma, 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.
Speaker 2:Try to get your name
Speaker 4:added the Get your
Speaker 1:name added to the firm.
Speaker 2:Exactly. Like if you were an associate at Sequoia today, you might I was pitching founders I
Speaker 1:was like, fun and Kugen. Founders Fund and Kugen. That that that was what I I was like, this is where I'd like this to go.
Speaker 2:Yep. Yeah. And there's there's plenty of precedent there. Right? Yeah.
Speaker 2:Totally reasonable. Kleiner Perkins.
Speaker 1:Right? Kleiner Perkins, Caulfield Byers.
Speaker 2:Yep.
Speaker 1:And, yeah, you know, who knows? Maybe it'll be Kleiner Perkins, Randall, and Lee Marie
Speaker 2:Yep.
Speaker 1:Braswell. Because they are Love it. 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.
Speaker 1: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. And venture is the one we're talking about.
Speaker 1:And then Yeah. There's even more like, okay. Can pensions get
Speaker 2:private equity Totally. Broadly. Yep. And then venture is a fraction of that.
Speaker 4:Yep.
Speaker 2:And these, you know
Speaker 1:Yep.
Speaker 2:Pension funds are are over, you know, deploying in in PE just simply because it's more stable and and there's a lot of other reason for that.
Speaker 1:So so Golder is really key in in legitimizing private equity in these pension portfolios. Carl Thoma has this mix of, like, Midwest pragmatism and Stanford training. Like, is a serious dealmaker. 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 gonna pay down the debt payments and, like, create value there.
Speaker 1:He's more about that company building mindset. And then Brian Kressy, the third guy on the team at at the time, he brings this JD MBA from Harvard and a and a particular eye for health care investments. So they make some they make some interesting deals there in the early stages.
Speaker 2:So the three of them
Speaker 4:Yep.
Speaker 2:They have they were collaborative, growth oriented, focused on specific sectors where they could rinse and repeat acquisitions and by the late
Speaker 6:Rinse and
Speaker 2:repeat. Rinse and repeat.
Speaker 1:That's one of my favorite things to do.
Speaker 2:And consolidate. Yep. There's nothing like a little consolidation
Speaker 4:Yeah. With your When
Speaker 1:I think of rinsing and repeat it, I just think of one hand washing the other. It's one of my favorite things.
Speaker 2:It really is.
Speaker 4:I love it.
Speaker 2:By the late eighties, the firm, which was now managing several small funds, had proven the efficient efficacy of consolidating businesses and which is broadly a template that they would continue to use.
Speaker 1:Yeah. And so they add another bro to the to the crew. There
Speaker 2:we go.
Speaker 1:They go to GTCR. Great This is 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 Rauner, and he'd risen to partner.
Speaker 1:His name was added in 1987. GTCR became one of Chicago's top buyout shops investing through the late eighties LBO boom and navigating the early nineties recession. They specialize in roll ups across industries like health care, media, financial services. And by the mid-1990s, they had some differing visions among the senior partners, and the firm's success had created these 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.
Speaker 1:This happens a lot in funds because, you know, you're you're like, the the partnership is bought in, but you gotta bring in new blood, but they're gonna wanna do some something in a different way, and that's gonna lead to some culture clashes. And so in 1980 in 1998, GTCR's leadership decided to part ways, splitting the far 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 its Chicago base.
Speaker 1:On the other hand, Carl on the other, Carl Thoma and Brian Kressy spun out to form Thoma Kressy 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 February, but GTCR lived on.
Speaker 2: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 10,000,000 AUM. Yep. And they'll be like, we back and build the future.
Speaker 1:Yeah. It's like it's got a video. It's got like every company that would be like
Speaker 2:transforming business to build value. That's when they have like 200,000,000,000 AUM or like Some
Speaker 1:might say that VC should do that more often. It's great. And so, basically, like, the the the the the incarnation of Toma Bravo that we're thinking about now, Carl Toma and Brian Cressi, they they really focus on TCEP. That's Toma Cressi Equity Partners. It's a stand alone firm in 1998, and they're continuing this buy and build model but with a fresh canvas.
Speaker 1:And so, Cressi has the health care ex expertise. He's steering some of the investments toward health services, and Thoma's looking at fragmented business services and emerging tech niches, still very technology driven. Yep. And then this is where we get to Bravo.
Speaker 2:Boom.
Speaker 1:Orlando Bravo, great name, enters the picture in 1998. Comes out of Stanford.
Speaker 2:Stanford, JD, and NBA.
Speaker 1:First round draft pick to the private equity ranks.
Speaker 2:He he made Orlando Bravo. This is a good this is a good lesson. Yep. He had been frantically cold calling PE firms looking for a job. After roughly a hundred a hundred calls Wow.
Speaker 2:His resume caught Carl Tomas attention and they quote unquote hit it off. Dude. He was 27 years old.
Speaker 1:99%. JDMBA has quit right before their one hundredth cold call to get that PE job.
Speaker 2: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.
Speaker 1:Yep. And so Toma Cressi, Brian Cressi, the co founder of Toma Cressi, is a seasoned dealmaker with a with a penchant for health care deals and a reputation as an industry consolidation guru. He's educated at University of Washington in 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.
Speaker 1:By the tome by the time he joined Carl Tomah 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, Tomacresi, entered the .com era cautiously, but caught attention, but even caution couldn't spare it from early missteps. Basically, everyone lost some money in the .com bust.
Speaker 2:A little bit here and there. What's what's a few billion among friends?
Speaker 1:Indeed. Orlando Bravo's first assignment in the late nineties were tech related investments that turned sour in his late twenties. Bravo, led two startup deals, NerveWire and Eclipse Networks. Just as the tech bubble was peaking when the bubble burst around February, Bravo's first few deals were disasters, losing most of the $100,000,000 invested. That's pretty crazy to go from I mean, that's the nature of PE.
Speaker 1:Like, you you 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
Speaker 2:and it doesn't go What's other thing
Speaker 1:with It's rough.
Speaker 2:Schwartzman's first investment at Blackstone where I'm I'm pretty sure that his first deal like went terribly. Yep. So there's like, there's basically precedent at this point of PE size lords. Yeah. It's like, you know, basically fumbling the first deal and then just coming back in a big way.
Speaker 1:Learning a lot. That's why I've been asking some of the VCs that come on, what was your first deal? Like, what did you learn from that? Like, I think that's an interesting line of questioning.
Speaker 2:And then there's some Some people that we've had on the show and they're like, my first three deals were unicorns. Justin Merritt's was like this.
Speaker 1:Like, it
Speaker 2:was like his first investment was like, went public or
Speaker 4:something like that.
Speaker 1: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 dot com crash. It was too painful to live through.
Speaker 1: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 twenties. Good timing.
Speaker 1:Though they're getting burned in the .com on the start ups, they realize that there's incredible value in technology and and and 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 02/2002, he spearheaded their first software buyout, Profit twenty one, which is a niche ERP software provider for for distributors. Tech buyouts were uncommon then because most of these were still venture backed.
Speaker 1:They were on the IPO train. IPOs closed. The same
Speaker 2:time, a lender was a lot more willing and excited to lend against a real estate portfolio Totally. A fleet of 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?
Speaker 2:It's it's secured, you know, on the And
Speaker 1:so they did it without without lenders, really. I mean, lenders were pretty wary of these tech buyouts. And so Thoma Cressi 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 executive, to turn the to help turn the company around. So they have a deal team, and then they also have an operating team.
Speaker 1:Once they buy the company, they actually help install install executives that can go in and and start growing the business and and optimizing things. Because a lot of a lot of times, the companies that they're buying, founders might be out. They might be a little burned out. They're the the company might not be running as efficiently. It's kind of just like, hey.
Speaker 1:It's humming along. It's it's it's profitable, but it's not as good as it could be. So they wanna make it great.
Speaker 2:And the firm's job is to place immense pressure on the management team
Speaker 1:Yep.
Speaker 2:To hit very aggressive goals.
Speaker 1:Yep. Strauss Zelnick did something similar with, with Take Two and the GTA franchise. He came in. That company was sitting on incredible intellectual property. They owned, two k games, like all of the different basketball games, and then also GTA, like the greatest gaming franchise maybe of all time.
Speaker 1:But it was just like it was just a creative mess. Like, they were just like, have fun, and they were under they were under, like, f f e 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.
Speaker 1:And there were all these different lawsuits going on, and Strauss came in, wind up buying the company for, like, kind of 0 doll it was a crazy deal. Should 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 he's a beast of an operator. And so Profit twenty one, this first tech, acquisition, did really, really well. So they exited with a 4.7 x return on investment, and this was an early win in software, with minimal debt and just hands on operational fixes, and and it some it really cemented the firm's new direction.
Speaker 1:So
Speaker 2:Middling outcome if you're a venture capital firm. But if you're a PE firm, that's gonna do, you know, a bunch of those.
Speaker 1:Yeah. And it and it feels repeatable at this losing money. Feels repeatable.
Speaker 5:Like, there
Speaker 1:are other companies that are in profit twenty one'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 02/2001 on the strength of those efforts he allows.
Speaker 2:Being promoted to partner at 30 in 02/2001 just sounds amazing. Sounds amazing. No. The timing is perfect to go on this generational run-in software.
Speaker 1:Oh, yeah. Yeah. Yeah. Yeah. I mean, timing is timing is a lot, but it might not be everything, but he he really nailed it there.
Speaker 1:And so, software deals started piling up. Orlando Bravo's influence within the firm grew. By by 02/2005, Carl Tomah and Orlando Bravo had recruited a trio of new talent. Scott Krebbel, Holden Spot, and Seth Borrow joined the investment team to focus on software sectors. All three of them are with the firm today as managing partners.
Speaker 1:One of them came from, Summit Partners. The other had experience at Morgan Stanley, and, the last one was also at Morgan at at Summit Partners and a history of investment banking. So a pretty common path into private equity from banking, and other deal making organizations. So this so this the as they're growing the team, they can also scale up their deal flow. 02/2007, they renamed the firm because they they love, Orlando Bravo.
Speaker 1:The firm is renamed Toma Cressi Bravo. Overnight success. A year later, 02/2008, cofounder Brian Cressi decided to depart. Cressi spun off with a team to form Cressi and Company, refocusing on health care investments because Toma Bravo, of course, is doing tech stuff and he's doing health care, and they're and they're just slightly different strategies. So they split the firms, and then the firm renames to Tomo Bravo LLC, officially born 02/2008, an overnight success.
Speaker 1:And today, they're buying Boeing assets for $10,000,000,000 running kind of the same playbook. It's a boring it's a boring software company that's just profitable, growing. But A series
Speaker 2:of software companies that
Speaker 1:they can just go bolt on
Speaker 2:and stuff too.
Speaker 1:And and just continue to 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.
Speaker 1:They built a bunch of stuff. This business is good. We can make it better.
Speaker 2:So Yep. 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, a hundred million of ARR, but not quite breaking But they will be very sort of aggressive in terms of valuing these businesses. And certainly, you know, if if Tomo Bravo is buying your company to bolt on to an existing sort of roll up, very unlikely they'll give you a revenue mo you know, a hundred x revenue multiple. Yep. Could very well be a one x.
Speaker 2:Yep. Could be less than that. Could be more if you're growing quickly and and have a a real path to generating cash But
Speaker 1:they as they scale up, they start doing more and more ambitious projects. They eventually scale from, you know, midsized PE firm into just, like, a complete heavyweight in tech buyouts. In 2012, they do a $1,300,000,000 take private of Blue Coat Systems, a cybersecurity company. And Blue Coat had solid technology but needed a strategic overhaul, and Tomo Bravo takes it private, improves operations, and later sells it for 4 and a half billion in 2015. So three years, they go from 1,300,000,000.0 to 4,500,000,000.0.
Speaker 1: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.
Speaker 2:I was trying to pull up a lever up button.
Speaker 1:But they pull up this
Speaker 4:they Risk on.
Speaker 1:Risk on. But they but they they basically got a pattern. They buy a public tech company. They optimize it privately and then sell or IPO at a much a 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 gonna get completely hammered while you go down for a couple quarters because you're saying, hey.
Speaker 1:There's a business over here that's really, really damaging us. It's low margin, but it's gonna hurt our revenues. And if somebody's op looking at you on a revenue multiple, they're gonna be upset about that. Or, there could be a number of different things that could look like red flags in the public market. But if you have a couple of years to rebuild in private, you can just take more risk.
Speaker 1:You can go risk on.
Speaker 2:Risk on. Yeah, the other thing that they're doing, just because a large part of our listener base is venture.
Speaker 1:They're
Speaker 2:Yep. They're by 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, $200,000,000, So when they turn that $200,000,000 into a 4,000,000,000, you know, $4,000,000,000 outcome, it can be very meaningful.
Speaker 1:So there's one more funny deal we got to go into. By 02/2018, Tomo Bravo is doing regularly doing multibillion dollar deals. They're they're in the same conversation as Silver Lake and their 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?
Speaker 1:No. Okay. So SolarWinds, is 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.
Speaker 1:But, there was a hack where it it was a very, very bad Oh. SolarWinds hack. Did you hear about 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.
Speaker 1: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 you could put like beers in.
Speaker 2:Watch it.
Speaker 1:Because he was like, yeah, I I Activate golden retriever mode. It's truly golden retriever mode mindset. 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 would 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. Yeah, wouldn't it be cool if like we had a better cooler?
Speaker 1: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. Cooler. Like, what does that cost? Like, a thousand dollars or something? But he tells the sharks that he's like, yeah.
Speaker 1:I founded SolarWinds. And you'd think that would be like total bull signal. Right? You're just like, okay, this guy built a billion dollar business like Yeah. He's probably can figure out like the cooler market.
Speaker 1:But all the sharks pass. They all say no. They all say they're out. Anyway, fascinating little side side tangent. Anyway.
Speaker 2:Yeah. The unfortunately, coolest cooler shutdown after a five year saga.
Speaker 1:Oh, no.
Speaker 2:And 20,000 people that backed the Kickstarter didn't actually get the
Speaker 1:Oh, that's brutal. Very rough. But anyway, I mean, SolarWinds wound up being a great company and and Tomo 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 all all of that is to say that, like, Orlando Bravo became known as, you know, an incredible dealmaker. He was on the cover of Forbes in 2019.
Speaker 1:They called him Wall Street's best dealmaker. Pretty great. He was the first Puerto Rican born billionaire in finance. He was on the Forbes four hundred list. The Financial Times nicknamed him the king of SaaS.
Speaker 1:We love that. A lot of people vying for that. Yep. At at at, you know, a lot of venture capital firms, but you're gonna have to go up against Orlando Bravo, the king of SaaS, the best deal maker in the world, to really, really own that own that name. Bravo's war chest grew.
Speaker 1:They got a fresh $12,600,000,000 fund. Now they're eyeing a 10,000,000,000 plus deals, and we just saw that with Boeing. They did a $10,000,000,000 deal. How they do that? They raised a massive, massive fund.
Speaker 1:And there's a bunch of other interesting deals that they've done, but they're doing mega deals.
Speaker 2:Yeah. Just to give you a sense of some of their bigger deals, they did Proofpoint at 12,300,000,000.0.
Speaker 4:Yep.
Speaker 2:The Boeing digital aviation is actually their second largest, which hasn't, you know, obviously closed yet. Yeah. Anaplan Anaplan, two billion. Ten point four. RealPage, ten point two.
Speaker 2:SailPoint, six point nine. Medallia was at 6.4.
Speaker 1:Acquisition binge.
Speaker 2:Darktrace, five point three. Sophos, Click, Imperva. Yeah. Absolute size lords. You don't need to do that many of these deals Yeah.
Speaker 2:To put up some very large numbers.
Speaker 1:There 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 Tomo Bravo. We've seen a lot of, traditional private equity deals where they buy a private company, do an LBO and and grow and buy and buy and build, that buy and build strategy. Then they start doing the take private turnaround strategy where 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, '20 '20 '4, and that's what the Boeing deal is. They're carving out a piece of Boeing's business and then in you know, packaging that up as an entirely new business.
Speaker 1:And 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 a bow an employee of a new company, a digital aviation software portfolio that's owned by Tomba Bravo that will eventually have a brand and be a p like a 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.
Speaker 1: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 Permian Basin is the is is is 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 or treat it if you wanna put it back in the water supply.
Speaker 1:So Yep. 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 there's a graphic of what they do. They're taking they're taking oil, oil rich shale, which is how you frac. So you blow, I think, like, air and water into the ground.
Speaker 1:You suck up the oil that's there. The oil is 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.
Speaker 1: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
Speaker 2:so much I guess this like a word. Yeah. Yeah. So we can kind of go through this. Yep.
Speaker 2:So
Speaker 1:they're trying to evaporate the water.
Speaker 2: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 you can pull it up but you can see
Speaker 1:It's a fascinating image. So there's
Speaker 2:these These evaporators 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. Yep. And
Speaker 1:All these crazy economic projects 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 I'm generally in favor of figuring out new ways. I mean, fracking was in many ways like a miracle in terms of Yeah. America's energy independence.
Speaker 1:You know, you
Speaker 2:even get of meme that's like America's like, you know, struggling and then we just discover like Oh, immense like Oh, no. We're out of rare earth.
Speaker 1: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.
Speaker 1: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 we gotta get the founder on. They blow air down on the pond.
Speaker 2:It's been, like, around
Speaker 1:Oh, yeah.
Speaker 2:Two hundred years.
Speaker 1:For sure.
Speaker 2:Is evaporating for about, you know,
Speaker 1:coming up on Who knows? Maybe RWI is just like, you know, seed stage startup. They just went through YC. You never know.
Speaker 4:Yeah. Don't judge.
Speaker 1: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 gonna 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?
Speaker 1:Or was it already considered in that equation because it's kind of groundwater? Or was it been buried so deep it doesn't happen?
Speaker 2:Mean, these things, like the primary thing here is environmental concerns. Right? Totally. If you're a farmer trying to grow organic food or you have cattle you know, a mile away. Mailing raining down on you.
Speaker 2:Oil water.
Speaker 1:Sounds like acid rain.
Speaker 2:Sounds sounds bad. But I'm sure that RWI would argue that
Speaker 4:Yep.
Speaker 2: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.
Speaker 1:I mean, evaporation's pretty effective. It's separating things out.
Speaker 2:That's what
Speaker 1:it's done in
Speaker 2:But this is like a very flash. A long running trend where 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 you were legally allowed to pull as much water as you wanted out of the ground.
Speaker 4:Yep.
Speaker 2:And what happened is regulators, governments, states, etcetera, 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.
Speaker 2:So, you know, one private company that that 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
Speaker 1:The nuclear thing is huge for desalination. Yeah. It seems like almost impossible. And and a perfect match because you have such concentrated energy. You can just throw the nuclear power plant right next to the desalination plant.
Speaker 1:You have all the energy. It can run 20 fourseven. Like, it's perfectly matched as opposed to a lot of other systems.
Speaker 2:Yeah. One of the issue with this fracked water is that it's salt water. Yeah. Oh, yeah. And and that means that you can't just go spray it on plants or you can't put it on crops.
Speaker 2:Will just kill everything. Yeah.
Speaker 1:It's bad. So this is interesting. Last year, Permian drillers discarded roughly 5,500,000,000 doll billion barrels of water, by pumping it back down into the ground. Right? So 5,500,000,000 barrels a year.
Speaker 1:That's what I want you to keep in your mind. 5,500,000,000 barrels a year. So they're doing a, so an injection well typically
Speaker 2:two gallons per barrel, by the way.
Speaker 1:Okay. So, an injection well typically gustles between 35,000 barrels of water a day. An an an evaporator working in optimal positions, optimal conditions vaporizes about 32 barrels an hour. And so now Exxon is trying to build a commercial size desalination facility operating in the Permian by the end of the year. Last month, they they they they commenced a pilot, project, but the the the the testing that's happening, the desalination technology is doing 20 barrels a day.
Speaker 1:That's the pilot. So 20 barrels a day is is what It's not really making sense. Hundred barrels a year compared to
Speaker 2:Not making a dent.
Speaker 1:Yeah. Hundred compared to 5,500,000,000. Yeah. Like, they we're we're off by so many orders of magnitude. But at the same time, like, 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?
Speaker 1:And does the actual scientific process work? And then it becomes an economic equation of of of what happens. So they are scaling up. They're gonna do a $25,000,000 desalination facility with an initial capacity of 10,000 barrels produced a day. Yeah.
Speaker 1:And then and there's plans to build a plant that's 10 times bigger next year.
Speaker 2:Yeah. This is the challenge. So generally with oil production Yep. You think it's just about how do we get this out of the ground?
Speaker 1:Yep.
Speaker 2:It's how do we get enough water to support this process?
Speaker 4:Yep.
Speaker 2:And then what do we do with that water after the process Yep. To dispose of it? Yep. And you're being regulated on both sides. Yep.
Speaker 2:Right? I have a portfolio company called
Speaker 5:Yeah.
Speaker 2:Resource Monitor that that helps oil and gas companies basically stay compliant on the production side. So they're producing all this water and they get, you know, budgets, you know, from from various groups on, you know, how much water they can actually produce. But that's only, you know, one part of the problem here.
Speaker 1:Yeah. So the goal is to bring the cost of purifying a barrel down to 75¢, which is slightly more than what it costs to flush the wall flush it down the well. There the this 25,000,000 desalination facility, is gonna do 10,000 barrels a day, which is, 3,000,000 a year. But remember, we're 5,000,000,000
Speaker 2:Yeah.
Speaker 1:That we're producing last year. And then they wanna build one that's 10 x bigger, so that'll get you to 30,000,000. But you're still two orders of magnitude off. Two orders of magnitude, a hundred times they're gonna like, if they build this 10 x plant, they will only be doing 1% that they're pumping down into the ground. It's it's actually crazy, the scale of this thing.
Speaker 1:Anyway, they're the the you know, they're they're trying to scale up, there's a bunch of companies that are working on this. Anyway, if you wanna go hang out in Texas, book a wander. Find
Speaker 2:your happy place. Find your happy place.
Speaker 1:Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, and twenty four seven concierge service.
Speaker 2:It's a vacation home, but better.
Speaker 1:And in most of those homes, you're gonna 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 gonna be extremely controversial because, the new tech, it doesn't sound Lindy. And so we're gonna have a debate over whether or not the the the path to better lighting is more advanced technology, or do we need to go back?
Speaker 1:Do we need to go back to incandescent? Was gonna say
Speaker 2:sunlight. Every office will be required to have a warm fireplace.
Speaker 1:It's a warm a warm hearth.
Speaker 2:A hearth. A hearth. Yes. We're going back to hearths. We should go
Speaker 1:to was joking
Speaker 2:the other day, I think, you know, on the topic of lights, I think Apple, to really differentiate
Speaker 1:Yes. Should come
Speaker 2:out with an iPhone UV that sort of gently tans your face.
Speaker 1:That sounds like a real product. Yeah. The iPhone UV.
Speaker 2:The iPhone UV, it gently tans your face Yes. While you use it.
Speaker 1:Yes.
Speaker 2:And, I think they've got a hit on their hands, at least in Los Angeles.
Speaker 1:Yeah. Yeah. They do the blue light filter. They can take the blue light out. Why not add some UV light in?
Speaker 1: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 skylights. I know.
Speaker 1:The faux skylights are crazy, but it's going to be really big when I build my Batcave that's three stories deep into the ground. It's going to be really Because you're going to want 20 fourseven 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 gonna it's gonna have, like, a kind of severance vibe. That's what I'm going for in my basement when I build. Smart. Glaring fluorescent lights in the office or on the way out, The technologies coming in promise to do much more than make everyone look better.
Speaker 1: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 technologies such as faux skylights that mimic natural light, compete with, complete with a virtual sun and moon, and adjustable illumination systems designed to sync with in place of Cadian rhythms. I think I wonder how long until this becomes a culture war issue. Because you know the air conditioning thing became a huge
Speaker 2:culture war issue. Incandescent light bulbs were banned.
Speaker 1:Yes. They're Yeah. They're hard to get in California. I've been struggling with this for long
Speaker 2:sort of like re legalize them Yes.
Speaker 1:I guess. Didn't hear about this, but that sounds cool. I I I like an incandescent light bulb. I'm a fan. I like a tungsten bulb.
Speaker 1: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 a Yeah. Professor at Wharton.
Speaker 2: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 Yeah. Light solution.
Speaker 1: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 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 wanna consider just a warm hearth, a nice fire. That's right.
Speaker 2:There's something there.
Speaker 1:There's something there. Some 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
Speaker 2:make the show Well, once we go to twenty four hours a day
Speaker 4:Yeah.
Speaker 2:We're gonna wanna be we're gonna obviously have eight sleeps on the floor. Yes, We'll be able to sleep Yes. You know, in cycles
Speaker 1:For the subathon.
Speaker 2: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.
Speaker 3:Mhmm.
Speaker 2: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 favorite
Speaker 1:this. Huberman's take on this. I want Brian Johnson's take on this. I want Solbra's take
Speaker 7:on this.
Speaker 2:Marc Andreessen notoriously has gone to war with Huberman. Yes. Said, I'm gonna use my phone Yes.
Speaker 4:That sort of mess.
Speaker 1:That is one my favorite interactions on the Internet. Max, but it is. Their their bromance is fantastic.
Speaker 2:It's amazing.
Speaker 1:Yeah. It's hilarious. Anyway, yes. You you you gotta be using, at the very least, warm white 2,700 Kelvin bulbs. You can't be walking around in the in the bright fluorescent Lighting's important.
Speaker 1:Mean, the
Speaker 2:issue with LEDs is there's The refresh rate. The flicker Yeah. Flicker. Which is not visible to the human eye. Yep.
Speaker 2:But when you if you
Speaker 1:But it makes you use
Speaker 2:it on camera. It'll make it'll drive you insane.
Speaker 1:It drives you I I I firmly believe that. Efforts to develop such lighting took off after researchers in the early two thousands 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 found. So, I mean, really, it depends is not is not just the one size fits all. It's like, do you want an do you want an insane work culture?
Speaker 1:Do you wanna 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 Or Yeah. They're ripping their hair
Speaker 2:Adrian on a on a lights out factories. Right? What about lights out offices? Dots, see light is from screens.
Speaker 4:From screens.
Speaker 2:From your email machine. Just blasting
Speaker 1: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 prized bull at auction. With herds thinning, finding the right stud is a high status game.
Speaker 1:That's why you come to this show, folks.
Speaker 2:That's right.
Speaker 1:Tech business, this is the business of the technology of prizefighting bulls. With herds 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.
Speaker 2:When Randall Grimius shows up at an auction, everyone knows there's a prize bull 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 seventy five 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 dud for a I
Speaker 1:had no idea that there was a population crisis among the bulls. I only Yes.
Speaker 2:It was happening seventy five years ago.
Speaker 1:Humans. I had no idea.
Speaker 2:To a crisis. So when Grimius' private jet Yeah. 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.
Speaker 1:I love this article.
Speaker 2:After 283 bowls were scooped up, his prize came charging out onto the show ring. Number two eighty four 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. Grimius figured the bull could fetch as much as 60,000 and he was prepared to pay up.
Speaker 1: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, spent 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 of state.
Speaker 2:They're doing diligence on bulls than the average VC does on a hundred million dollar check. For sure. Like, check.
Speaker 1: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 sales catalog.
Speaker 1:Rare is the bull that hits the boxes based on his jeans 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 mode. They are in founder mode to spread his seed. Sean Lowry, is a sixth generation Nebraska rancher and is part of the Mill Dell Ranch, one of the oldest running ranching operations in the state.
Speaker 1:He looks at the lineage of the bull, who the mother and father were in 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. He can't be too small.
Speaker 1:We might we like them long. We like them deep. This is in the Wall Street Journal, folks. This is an important industry. It's fascinating.
Speaker 1: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.
Speaker 2:We gotta we gotta go. We gotta go.
Speaker 1:We gotta go and, see one of these bull auctions. You know, I I follow an account that does breakdowns on horses Yep. 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 dock's end in Silicon Valley. They they they they match the gate.
Speaker 1: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 6 figures. So, the bidding started at 5,000 before quickly climbing to 15,000, 20 thousand, 40 thousand, and soon 55,000. Your man has to beat 55,000. Come on, Randy, he said, trying to get Grimius to bid.
Speaker 1:Grimius didn't bite. He knew his prize was later in the day.
Speaker 2:It's interesting, know, the same dynamic plays out in Venture, right? Sort of like, oh, the second that Sequoia issues a term sheet, then every other Yeah. Always wanted to do Yeah. And it's an interesting dynamic where, in theory, once he's starting to bid Yep. Everyone else should just sort of, like, pile in and Yep.
Speaker 2:And try to get the one that he wants.
Speaker 1:Even some of the the ranchers are sending other people. So, Lowry's people know him. Wow. So he sent his foreman into the bleachers to do the bidding, so he wouldn't get recognized because people thought, oh, he's got a good eye. He's the Sequoia of bull bidding.
Speaker 2:Yes. Yes. So He says, sometimes I will get emotional, I will get pissed it will cost me thousands of dollars I didn't intend to spend.
Speaker 1:It's the best.
Speaker 2:I already said, in this business, these cowboys are awful prideful.
Speaker 1: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 gonna 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.
Speaker 1:And, coming into the studio, we have Roy, who has been tearing up the timeline. We're very happy to have him join. How are doing,
Speaker 2:Roy? Welcome.
Speaker 4:Welcome to the show.
Speaker 6:What's up, brothers?
Speaker 1:What's up?
Speaker 2:Brother, great to have you.
Speaker 1:How have the last few days been for you? Can you take us through, the brief prehistory here of what happened with Columbia, and then we'll get into what happened with your launch?
Speaker 6: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 LeeCode, Sell 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.
Speaker 6:Columbia is mad, and this ends up being a spat that I sort of publicized on my Twitter. It becomes this big spectacle, and I eventually get kicked out of Columbia or suspended for a year and, blacklisted from most big tech companies.
Speaker 1:Was the original Big mad.
Speaker 2:Plan? Big mad.
Speaker 1:Wait. What what what was the original plan a publicity stunt, or did you actually want the job at Amazon?
Speaker 6:I I I was never intending on taking the 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 kinda just thought, I really wanna build companies. This is what I wanna do with my life.
Speaker 1:So
Speaker 6:this is just seems like the the optimal route for everything. I can make this big protest against LeetCode, at the same time, I can do something that I suspect will be super viral and just give me, like, a distribution channel to build off.
Speaker 1:Yeah. That makes a
Speaker 2:lot sense. Crazy. I mean, there's there's many people in venture that have spent, you know, ten plus years trying to build a following here and and and, you know, the 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 Yeah. You know, come and
Speaker 1:So take us through the product, what you launched, and how that video came together.
Speaker 6:Yeah. So, I mean, Cluely 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 ten years about your life. Nobody's gonna be on a chatbot, chat with dtt.com. Where are they gonna be on? They're gonna be on Cluly, and this is what we hope to build, and this is what we are building.
Speaker 6:We sort of filmed this launch video to be like a a vision for the ultimate end state of what does true AI in everything look like. Like like a true AI maximalist life ten years out in the future. What does that look like? And it ended up coming together real real really well, and it I I think it resonated well with the world. Went very viral and very controversial.
Speaker 6:But
Speaker 1:Yeah. Very controversial.
Speaker 2:How did you you went against, you know, the norm. You launched, 2PM Pacific on a sun on on Easter. Were were did you just launch, when when you were ready, or was that was that planned at all?
Speaker 6:Yeah. I mean, it was 04:20, and it was sort of in brand with, like, me being, like, the the little, like, punk college kid. Like, I launched on 04:20. Might as well.
Speaker 1:Okay. Yeah.
Speaker 2:Yeah. Yeah. Yeah. Makes sense.
Speaker 1:Yeah. What about has any of the pushback been, correct? Can you steel man any of the pushback? Is it bad to cheat?
Speaker 6:I think I think there's two worlds of or, 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 and I 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.
Speaker 6:But, ultimately, like, that never ends up being the 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 the 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.
Speaker 6: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 Clueli or what AI allows is sort of, like, an unfair advantage that is so unfair that it feels like cheating.
Speaker 6:Imagine you're in a sales call at this tool, this it's, like, 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 this is not fair. This is cheating.
Speaker 6:But, I mean, ultimately, this is where the world is headed, and, really, this just, like, makes us a hundred times more efficient.
Speaker 2:Yep. Yep. You know, I love it. I mean, in in many ways, business is, you know, feels like a sport in some ways, yet there's sort of laws that govern, you know, corporations and, you know, different different markets. But there's nothing there's nothing wrong with giving yourself every possible advantage
Speaker 5:Yep.
Speaker 2:To win. And so you should absolutely just use every tool available Yeah. To win.
Speaker 1: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 That's not. It seems like there's like a augmented reality vision in the future. But how are you thinking about that?
Speaker 1:Because, you know, there's a monopoly in Apple products. There's a monopoly on foundation models now. Like, where are you seeing yourself break through? Are you sitting on top of different systems or trying to build something from scratch?
Speaker 6:Right. Right now, the the vision, the the the version of the app that we have is just a desktop app. Mhmm. 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.
Speaker 6:Mhmm. 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 that is the ultimate end state. And the way we get there will be sort of, like, like, variable up. Like, if if the models get significantly better, significantly fast, the chips get better significantly better, super fast, then, it's sort of like, like, the way we get there is is is is subject to change.
Speaker 6:Right now, we are building a really, really good desktop app that can be the play ultimate player too for your computer.
Speaker 1:Yeah. What would you, how do 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.
Speaker 1:And, like, maybe you should just be heads down and, like, go build something great. And then, you know, the the the the business will build up slowly over time. And this is like, oh, you're, like, clout chasing is, like, the criticism.
Speaker 6: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 And if you truly believe this, then you would behave exactly how I'm behaving.
Speaker 4:That's a good point.
Speaker 1:That's a really good point. But but but specifically, like, the there are different there are different modes of distribution. Right? Like, you could you could have found a distribution angle that frustrated people less, right, or was less edgy. Right?
Speaker 1:And and so, is is is the need to be edgy, is that a product of the way our social networks work or the way our our distribution, like, moats already exist? Like, there's already a like, the 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. Is that are you a, like, a product of the of modernity, I suppose?
Speaker 6:Yeah. Yeah. I I I would think so. I think I I have a very unique, and I'm I I I think a very strong viral sense. I have an intuition about what makes things go viral and what things will go viral.
Speaker 6: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 10,000,000 views in two days.
Speaker 1:I agree.
Speaker 4:Yep. Yep. That
Speaker 1:makes sense.
Speaker 2:Talk about how the round came together in the process there.
Speaker 1:Oh,
Speaker 2:yeah. 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. 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.
Speaker 2:But talk about how the how the round came together and and yeah, I'm 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 a period of time.
Speaker 6: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 twenty four hours.
Speaker 2:Yeah. I remember that. You just, like, posted I think I saw one post, and then you're like, okay. The round's done.
Speaker 4:That's awesome.
Speaker 6:We we our 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. Real 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.
Speaker 6:And all of a sudden, like, the extra 10% dilution here if we fuck up is like it means nothing.
Speaker 2:Yeah. How do you how do you think about sort of, like, flexibility at the product level? Like, it seems like you have a very clear vision of how to unlock AI for individuals broadly. And it sounds like starting in the workplace. But are you flexible in terms of what that sort of exact implementation looks like?
Speaker 2:What kind of, you know, different niches? I can see the application in sales, etcetera. But but how are you thinking about sort of adapting now that you have, like, this flood of customer demand and attention? Now you need to, like, you know, turn it into durable revenue and things like that.
Speaker 6:Yeah. I mean, this is something that that that that there 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 gonna hire about a hundred interns, and we're gonna turn them into, like, sort of the ultimate content farm over the summer. So we're, like, the most motivated high school and college kids.
Speaker 6: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. Sure.
Speaker 1:We're we're
Speaker 6:hoping that have this, like, gigantic content form, and every single one of them will be sort of assigned a different use case for the product. Sure. You are going to advertise this product for sales calls, and you guys are gonna just, like, ship out content for sales. You guys gonna are gonna advertise this for meetings, and you're gonna you guys are gonna advertise the deep research feature, and and and sort of, like, the consistent spirality and attention on the different, use cases will, that that will make it less lasting.
Speaker 1:Do do I mean, do you have do you have a suspicion as to which which use case is most profitable in the 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.
Speaker 5:Right.
Speaker 1:Do do are 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 maybe we're talking to you next year, and you're like, yeah. We've we we found it. We cracked it, and we are we are cheat on sales calls. And we're and we're, you know, great for SDRs, and we've kind of dropped all of the other things, or, or do you really want this to be everything for everyone on day one?
Speaker 6:Everything for everyone on day one is a bit unrealistic. Right now, the two things that we're really zoning in on are are are meetings, like virtual meetings like this and, also sales calls. Mhmm. But it's entirely possible that every single use case flops doesn't go viral isn't helpful except for one random use case Sure. In which case, we'll, like, quintuple down on that.
Speaker 6:Yeah. But the the end state is, you know, like, AI for everyone, for everything.
Speaker 1:I I I wanna go deeper on the actual, like, 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 with a shortcut or the the action button on the iPhone, Meta Ray Bans. Is there a a deal that you can do to take over for that? Like, it feels like most of the hardware providers are have very sharp elbows around their ecosystem.
Speaker 1:Some of that's breaking with the latest, you know, FTC lawsuits, and maybe they're more open to it in the future. Also, like, the the failure or, like, the the 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 the landscape around hardware evolve? Because that feels really, really important to you if you don't wanna go build it yourself, burn a hundred million dollars trying to build the next Apple product.
Speaker 6:Yeah. I I I don't actually think that, we'll we I I 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 I think most people I mean, friend.com, Omi, like like, everyone is sort of betting on the idea that there will be, like, this new hardware element that
Speaker 4:Yep.
Speaker 6:That that that is, like, a companion. I think that's if we were to delve into hardware, that would be most realistic. Mhmm. That's, like, 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.
Speaker 6:That is the true end state is what we want anyways.
Speaker 1:Yeah. Don't ask the Neuralink guys about timelines then.
Speaker 2:Can you talk about what the general you know, while you were at Columbia, what the vibe was on campus? I'm assuming everybody's using ChatGPT, but do they know like, do they have a sense like, is this is there an
Speaker 1:The Tyler Cowen, 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?
Speaker 2: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 and be better at their jobs, etcetera?
Speaker 6:There 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 the 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's not a single undergraduate who hasn't cheated on at least one assignment using AI. And the vast majority of CS majors at, like, literally
Speaker 2:You should tell them to kick everybody out.
Speaker 1:Kick everybody
Speaker 2:out. Kick everybody out. Just Yeah. Whistleblow. Clear the slate.
Speaker 2:Yeah. Whistleblow. Columbia whistleblower
Speaker 1:of Columbia, cheating's okay. It's trolling that gets you in trouble. Yeah. Don't have fun.
Speaker 2:Don't have fun. Don't expose Yes. Funny technological changes. You will be
Speaker 1:Yeah.
Speaker 2:You'll be blocked.
Speaker 1:Who who who are your who are your inspirations? Are you like a Nathan Fielder type guy? I feel like there's someone that, you look to in your in your, virality. Who inspires you?
Speaker 6:Bill Byrne, Nathan Fielder, those guys are are are so funny. Dave Chappelle, I mean, like, I was I was big in that. There's like a lot of, like, Asian content creators Sure. That that that are that are funny too.
Speaker 1:That's awesome. Last question, Jordy?
Speaker 2:No. I love it. Who are you do you have have you put together a team of of you know, former classmates? Have you gotten anyone else to to bail with you? What what does your team look like today?
Speaker 6:Yeah. So over half the team is friends I met from community college, actually. And the other people are my cofounder who dropped out and also the guy who's probably gonna be valedictorian of Colombia.
Speaker 2:There we go. That's that's Are
Speaker 5:you are
Speaker 1:are are you worried about any, like, 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 $5,000,000. They sue you.
Speaker 1:Like, the
Speaker 2:I just wanna go out on the lens. I will I will I will give money to the Roy Lee defense fund. So you you we got you. We got you.
Speaker 1:I I I I'm anti cheating in the literal sense, but I I I like I like building and and I also like trolling and comedy. So, I'm, like, fifty fifty on you, I guess. I'm not How are you worried?
Speaker 6:I'm not as reckless as people think. I read the documents very carefully before disclosing the the confidential, and there's, like it it was not legal. These are the worst get expelled.
Speaker 1:And Yep.
Speaker 6:For me, that's probably the best case.
Speaker 1:Yeah. Yeah. Exactly. I I I I I think I would be okay with you getting kicked out of Colombia, but I would be upset if they really tried to put
Speaker 2:I'm gonna out on a limb and I'm gonna say I I I believe there's a real chance that you eventually go back and give the graduation speech at
Speaker 1:It's possible.
Speaker 2:You know? It's possible. You're gonna have a you're gonna have a crazy arc and I'm I'm excited to witness it.
Speaker 6:I hope so. I hope so.
Speaker 1:Yeah. Good luck.
Speaker 2:Love it.
Speaker 1: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 for your patience. This is a very exciting story.
Speaker 1:And I love when anyone blows up the Internet like you did.
Speaker 2:Yeah. Congratulations on on all the momentum in the round and excited to have you back on soon.
Speaker 4:Yeah. Fantastic. Thank you, guys.
Speaker 3:We'll talk
Speaker 2:to later, Roy. Cheers. Bye. Later.
Speaker 1:Next up, we got Jacob from Superpower announcing a $30,000,000 series a, b, c, d
Speaker 2:Series a?
Speaker 1:Series a.
Speaker 2:Series a? That's And also a Sousa Ventures.
Speaker 1:Back to back Sousa.
Speaker 2:Back to back. It's Sousa Day. It's Chad day. Shout out. It's Chad.
Speaker 2:Yeah. Chad day.
Speaker 1:He's easy.
Speaker 2:April 22. He's just We'll forever be known as Chad.
Speaker 1:I'm a Chad. I invest in Chad's. That's his that's his investment thesis. The end.
Speaker 2:The end. We got Jacob here.
Speaker 1:Let's bring him in. Jacob, how you feeling? How you doing? Should we ring The size gone for you preemptively. Congratulations on the round.
Speaker 1:How's it going?
Speaker 3:Gone. Jordy, gentlemen, great to see you guys.
Speaker 2:Great to see you. Good to What's happening?
Speaker 1:Give us the breakdown. What are you announcing? And give us the the high level pitch for superpower.
Speaker 3:Thirty million dollar series a. It's our biggest capitalization to date. Capital is no longer a constraint, and we're building a super team to reinvent health care.
Speaker 2:K. Crazy. Give us a backstory.
Speaker 1:How does it start for the consumer? Get lapsed up?
Speaker 2:I was gonna say let's go back a little bit. Yeah.
Speaker 1:Let's start with backstory.
Speaker 2:2023, you had a had a rough year. You wanna you wanna share that? Oh, yeah. That'd How that kind of catalyzed, superpower?
Speaker 3:Rewinding the clock. It was 2022, actually. And, that year, I almost lost my life to reverse health care incentives and a system that doesn't necessarily help people be proactive and take control. So was when I was building my last company, I was diagnosed with an autoimmune disorder. It's one called Crohn's, which those of us might be might be familiar with.
Speaker 3:Fifty million Americans have autoimmune disease, two thirds 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, you know, 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, like, what's actually driving complex diseases in my case. So I was really, you know, more seen as a way for them to make a loo lucrative, billing, you know, cash flow versus versus actually getting to the root of of what was ailing me.
Speaker 2:Talk about yeah. 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're just like almost, you know, spent a year almost dying. But you knew from, you know, basically right at that moment kinda what you wanted to do.
Speaker 3:It it actually comes back to Twitter. So I posted about my hospital story, and it went real 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.
Speaker 1:Yeah.
Speaker 3:And they charge, like, 50 to a hundred k for their clinics. And what you do when you're a patient with these practices is they test everything in your body, leave no stones unturned. They'll, like, 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 on autopilot. So if you're fortunate enough to be in a financial position or in the know to be a patient in one of these practices, you're basically never gonna die of chronic disease. You're gonna look like, you know, the memes of Bezos and Zuck that are super yoked.
Speaker 3:You know, I know the doctors that probably do their peptide regimens.
Speaker 2:You think it's just peptides? You use peptides, or is there
Speaker 1:It's a jujitsu. Secret
Speaker 4:juice? Jujitsu.
Speaker 3:I 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. Obviously being a technologist and a brand builder, it just became very obvious that there was a big opportunity here to to to democratize once I went on my own healing journey.
Speaker 2: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?
Speaker 2:I've I went through a period in in college when I had a bit more time where it felt like 60% of my brain power which is like going to like lifting and eating and things like that. And obviously, it's not sustainable if you're trying to run a company and and things like that. So I'm curious what you think the kind of like sweet spot is in terms of, you know, wanting to be high performance, wanting to be healthy, wanting to not be like, you know, age, you know, accelerating your aging, things like that.
Speaker 3:It's 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, you know, sometimes we still have to put in the hours and we have the engineering team closing
Speaker 1:up on
Speaker 3:the floor.
Speaker 2:Oh, that's great.
Speaker 4:I don't think
Speaker 1:it's too early. For for the evening. Yeah.
Speaker 3: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. You know, I think we're back 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 wanna kinda set the lead the vanguard in what it 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 or all the metrics that matter for business.
Speaker 2:Yeah. I was joking. John and I gave a sort of humorous talk in Miami last year. We were talking about the case for like VC platform teams should just be like basically like doping Yeah. Helping helping their portfolios just like What's your creatine?
Speaker 2:Yeah. What's your creatine? Yeah. You know,
Speaker 1:what How much are you working out? What's your eight sleep score?
Speaker 2:Looks like we need to add a little bit of tea in the mix. Yeah. So what
Speaker 3:I think someone's gonna launch a fund with this thesis where you know, help Maybe it'll be me. I don't
Speaker 1:know. Unironically?
Speaker 2:No. I don't think it's I I think it's very real you know, I 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 gonna help you with sales. We'll help you with recruiting.
Speaker 2:We'll help you with your next round. But just saying, like, we're gonna
Speaker 1:help you Help you with your one rep max. Help you with your one rep Exactly. Thousand pound ventures.
Speaker 2:Talk about talk about the 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 unlock value on the data side and and all that?
Speaker 3:So in the limit, something that we deeply believe is everyone will have a health care super app on their phone. And today, a consumer health experience is deeply fragmented. You know, consumers have to run around town to a bunch of different places, and it's all disconnected. And the front door to health is, you know, something like Chatuchi BT or or Google or WebMD. But the problem with those platforms is they don't really know much about you, and they definitely don't know everything about medicine.
Speaker 3:So what that sort of culminates in with with what we're building is what we think will basically be an AI doctor in everyone's pocket. So we're kinda 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 the health care 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 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.
Speaker 3:And health care is is ripe, and it's it's, you know, demanding of better consumer experience. We've seen the consumer experience being re reinvented for, you know, every other aspect of our lives, but health care is sort of the last domino domino to fall. And we wanna be basically the predominant company to to to bring this to to the market.
Speaker 1:How do you think about the interaction with LabCorp? It's an $18,000,000,000 company, kind of, you know, stocks up and stocks down, like kind of, you know, up 60% over the last five years, obviously. When you're doing lab testing, like, kind of got to build on top of, the railroad that's already there. But how does that relationship evolve over time?
Speaker 3: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. Yeah.
Speaker 3: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.
Speaker 3:And there's probably, like, a dozen or so friction points there. So something like Theranos over
Speaker 4:the next
Speaker 3:few 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 a trustworthy brand, low cost customer acquisition, and a really amazing AI doctor product.
Speaker 1:And What what is your takeaway from the Theranos story? Do you think that there's any, like, sort of misread on that historical, like, anecdote? Like, we've we've we've done, a deep dive, we were, there's more nuance issues don't
Speaker 2:apply, build fast, and break things to consumer health.
Speaker 3:Yep. Health care 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 health care founder, which makes the the, you know, the the the Zuck adage a bit tougher to apply.
Speaker 1:Yeah. What about the what what about interactions with the FDA? I'm I I assume that there's oversight around, you know, 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?
Speaker 3:Yes. So 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
Speaker 2:is Mhmm.
Speaker 3:Basically AI with human.
Speaker 1:Sure.
Speaker 3:So anytime it gets to a point where a human has to intervene, we do plug in a doctor on
Speaker 1:A doctor.
Speaker 2:Got it.
Speaker 3:That help you with that, which helps us avoid any sort of messy FDA regulation.
Speaker 1:That makes sense. Got it.
Speaker 2:Do you see a world in the future where the average company maybe outside of our tech bubble is like giving budget to employees specifically for preventative health? Right? Like sort of 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?
Speaker 3:Undoubtedly. So one of the challenges in health care today is because the average American is transitioning jobs every two to three years and health care is tethered to your employer Mhmm. 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 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 gonna drive clear employee retention, acquisition in a market where it's only more competitive to get the best to get the best people.
Speaker 2:What's, what's an underrated supplement right now? It feels like, you know, magnesium magnesium's hot.
Speaker 1:The tea takes six different types of magnesium.
Speaker 2:I take it. I take it.
Speaker 3:I also take six different types of
Speaker 1:You take six different types
Speaker 2:of I'm only on four. You're only on Those are rookie nerds.
Speaker 1:What
Speaker 2:do you think the next kind of magnesium? I I I've been surprised to see creatine in the timeline so much Yep. Just because it seems like It's
Speaker 4:very Lindy.
Speaker 2:It's Lindy. People have been taking it forever.
Speaker 1:Methylene blue is in the timeline pretty much.
Speaker 2:Blue. I'm I'm I'm fifty fifty.
Speaker 1:Yeah. Yeah. Yeah. But but but what's your take, Jacob?
Speaker 3:I got one for you. Oral BPC one five seven.
Speaker 2:Been on oral BPC one five seven. Oh, yeah? This is the Wolverine peptide.
Speaker 3:Oh, yeah. 40 tip. It's from the Wolverine protocol.
Speaker 2:Yeah. Okay. One five seven. Now this 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, sports Like, Wada. Organizations and leagues that as a CEO, you can just take.
Speaker 2:Right? So, like, if a pro athlete is, like, wanting to take something but can't Yeah. Because it's very effective, but it's so effective, it's maybe made illegal.
Speaker 5:In the
Speaker 2:world of sports, why not? Yeah. If you're a CEO or capital allocator, why not get on some PPC one five seven. Interesting.
Speaker 3:In Silicon Valley, Performance Enhancing Drugs are encouraged.
Speaker 1:Yep. That's true.
Speaker 2:Yeah, it's an interesting time right now. I mean, feels like these sort of like psychedelics like, 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 Accruent. Where it's gonna move beyond, okay, founders are on, you know, maybe they're on caffeine or nicotine and creatine, but on onto like really optimizing peptides in the way that, you know, you mentioned it, people like Yeah. Bezos are are probably doing to some degree.
Speaker 1:Better sleep. Yeah.
Speaker 6:Makes a lot
Speaker 1:of sense.
Speaker 2:But anyways Yeah.
Speaker 7:Great to
Speaker 2:have on, Jacob. Very very exciting. Congratulations. Anything else? Anything you wanna plug before before we end?
Speaker 3:Gentlemen, I I appreciate the 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 that testosterone.
Speaker 2:There we go.
Speaker 1:What's the yeah. How much BPC one five seven can I take before I explode? What is the LD fifty of BPC one five seven? Because I'm going to the max. I wanna look exactly like Wolverine.
Speaker 2:John has Wolverine. John has the natural t levels of, I think
Speaker 1:Yeah. But imagine how much higher they could be if I was in the Wolverine stack. That's the If
Speaker 2:John if John two x's t, it would be potentially world I
Speaker 1: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. Is that the idea?
Speaker 3:Exactly. And then
Speaker 1:And then as
Speaker 3:soon as their
Speaker 1:own personal model. Soon as it, like, makes a firm recommendation, kicks you over to a to a doctor before it starts violating FDA rules, basically.
Speaker 3:Exactly. The way to think about it is the world's best doctors will spend hours and hours with you on whiteboards connecting all the dots in your health, but that computation doesn't scale at a at a at a higher price point, so we're democratizing it.
Speaker 1:That's awesome. Love to see it.
Speaker 2:Love it. Awesome, Jacob.
Speaker 1:Congrats to you and the
Speaker 2:whole team. Well, speaking of
Speaker 1:AI, we're, having Logan Kilpatrick from Google on. There we go. I'm very excited
Speaker 2:for this one.
Speaker 1:A lot of different stuff.
Speaker 2:Logan has been on a tear.
Speaker 1:He has great poster. And as soon as he or 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.
Speaker 1: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 8Sleep.com/TBPN. Get a Pod four Ultra. It has a five year warranty through a thirty night risk free trial, free returns, and free shipping.
Speaker 1:And in and we will go back to the show. Now let's bring Logan into the studio. How are doing, Logan? Let's see. We're bringing him in.
Speaker 1:How are doing?
Speaker 5:I'm doing great. It's been a great, busy last six months of AI stuff, so I'm trying to stay alive.
Speaker 1:Just the last six months? I feel like every six days is, is huge in the AI world. It really is, like, the best place to do content around or just read about or or listen to podcasts about. Like, 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.
Speaker 1:So, yeah, what what what are you watching today? What are you watching this week? What's most interesting?
Speaker 5: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.
Speaker 5:I think if you look, like, two 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.
Speaker 5:It's it's impossible.
Speaker 1:Are you generally feeling the acceleration? Because I feel like we we are seeing acceleration on the product side and certainly in the the fragmentation of models and the and the, like, the the specialization of these models. But in terms of just, like, massive order of magnitude breakthroughs, I feel like when we went from three GPT three to GPT four, that was a huge leap. We passed the Turing test. ChatGPT was huge.
Speaker 1: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, like, viral moments Studio Ghibli accepted probably.
Speaker 5:Yeah. I I actually think I'll 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 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, like, multimodal, like, fact that the models can, like, with better better than just from a multimodal input perspective, better than humans are at, like, most vision tasks.
Speaker 5:Like, the number of products and, like, things 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 and, like, we're continuing to see that with, 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.
Speaker 5: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 impressive.
Speaker 1:Yeah. Yeah. Yesterday, we read a post from, Nir, Cyan, and, it was a it was a screenshot of the definition of AGI. Read it out.
Speaker 2:So it's a reminder of how far AGI goalposts have moved, and and it's a screenshot that 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.
Speaker 1:Yeah. 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. Yeah. A sheep sized cake. Like, it could do anything.
Speaker 1:Anyway, I wanna talk about this, this idea of, like, 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 at every different price point, or is that just a natural outgrowth of the engineering culture and the scale of, you know, being a hyperscaler?
Speaker 5:Yeah. That's a great question. I think a lot of this has been an intentional decision. I think if you look at, like, specifically 1.5, like, the flash series is really where we sort of landed this point the most. I think recently with 2.5 Pro, it's been the first time that we've actually had, like, truly the one of the most intelligent models available.
Speaker 5:And relative from a cost perspective, it's still super affordable. 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 decisions. Makes makes sense. And and the beautiful thing is, like, I think this this point goes underscored, which is, like, what does this mean?
Speaker 5: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.
Speaker 5:And, like, the margin for people building AI products actually goes up every like, the farther you push the Pareto 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.
Speaker 1:Yeah. I I I wanna dig in there. Google's in a unique position in that it's a con consumer tech giant, but also a scaled infrastructure provider with GCP. And you could see
Speaker 2:Not to mention a b to b player. I mean, I don't know a single startup that doesn't run
Speaker 1:on Google Workspace. 100%. Right. And so and so you, the the the 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 b to b stuff. Don't let the API load take away from serving your consumers.
Speaker 1:In goo with with Google, there's probably some sort of tension there. But what are you excited about on the on the b to b side and this idea of like, you know, oh, if I build a wrapper, is Google gonna like just steamroll me? This is kind of like an old meme. But now, you know, it seems like the best time ever to build on top of the, like, two two point five or any of these different models that have great cost and and, and, like, scores and what and benchmarks and whatnot. So, what what message are you sending to kind of the the developer community?
Speaker 5:Yeah. So two two things. One, our reaction to your first comment, which is around, like, is there value in doing both consumer enterprise and some of these other things? I think my push for a company is, like, if you're in the position to be able to do that, and, like, there's a bunch of nuance to this because, obviously, OpenAI as an example is, like, extremely well capitalized, etcetera, etcetera. Like, they have the means to do this and do it well.
Speaker 5: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 what the API business did was, like, allow the world allow this, like, massive proliferation of AI products to educate the masses that people are interested in this stuff. And then, like, at the end of the day, who has the world's best AI product? I think, like, you know, some people maybe argue it's ChatGPT, maybe it's another product, but, like, you sort of wet the appetite of the world that, like, oh, I can actually do these things and it's, you know, in my product surface or etcetera, etcetera, and all that's enabled by the API. Then when you look for, like, okay.
Speaker 5:What's the best way for me to use this product? Maybe it's one of those consumer products made by one of the 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 I think to your to your question about, like, where's the value for builders today, I a % agree with you. I think there's so much value to be created at the application layer.
Speaker 5:If you look at I I think about these, like, three curves at the same time. There's, 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 into the right. Like, models continue to get smarter and better with test time compute and scaling and stuff.
Speaker 5: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 a product.
Speaker 5:Your customers are willing to pay more. There's more customers, and the tool that's actually enabling 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.
Speaker 5:So I'm I'm super so, like, I I literally wake up every day excited because people are building companies, and and all this is happening for them.
Speaker 2:How do you, how do you think about balancing, you know, benchmarks and capabilities? Mhmm. 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, you know, just sort of like broadly, not not talking about any one lab, but then being sort of disappointed with the actual, like, experience with the model. Mhmm.
Speaker 2:And I'm sure you've spent a lot of time thinking about this.
Speaker 5: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, like, if you abstract evals out of, like, AI and into everyday life, like, you become and maybe I'm, like, too eval pill 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.
Speaker 5:And, actually, they're eval and then, like, those 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. Like, are they a super scientific eval? Like, no. They're actually a
Speaker 1:pretty crappy eval in a lot of ways.
Speaker 5:The folks have gone through performance reviews, and yet, like, that is the core foundation of, like, how human, you know, 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 I think to answer the question specifically, Jordy, about, like, what what does that mean for people who have this sort of disconnect between capabilities and what the eval say, I think this goes to, like, why there's so many, like, vibe evals. And if you look at, like, Ella Marina is a good example of this.
Speaker 5:Like, Ella 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 evalling that the model is saying things that are true. It's like, how do humans feel about this response?
Speaker 5: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 long clips 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.
Speaker 5:In some cases, there's there's tension, but
Speaker 1:I think you have to
Speaker 5:do both if you wanna be successful. Totally.
Speaker 1:How do you think about the different buckets of foundational research that are happening? Do you believe in the the data wall, the pretraining scaling rule, like, kind of, you know, 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.
Speaker 1: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 or is it more algorithm based?
Speaker 1:How are you thinking about the future of the foundation model landscape developing?
Speaker 5:Yeah. I I think two points. One, I think there's never been more opportunities to push the frontier. Like, I think all those examples that you just described, like, because the models are evolving more than just big models and, like, they're actually there's, like, systems that have tools and all this other stuff together. Mhmm.
Speaker 5:I I think it it just increases the number of opportunities for scale and for the models to get better. So I think that's, like, 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. Mhmm. But I think if you look at, like, a a an example of this in practice, like, 2.5 pro is actually an example where it wasn't just, like, RL scaling that made that model better.
Speaker 5:Yes. RL was part of the story, but, like, there was also a bunch of pre training innovation. And, principally, there was a ton of of post training post training and pre training innovation. So I think, like, it's not that companies are going to continue to see value created across all of those. And the 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 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.
Speaker 5: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, like, has to reason through really complicated problems, it's like you it's like many multiples of bang for your buck because of that. So, like, I think we need to continue to do the innovation across all levels. And, like, that's what exactly what we're doing right now.
Speaker 1:I I know you probably can't talk about specifics, but, one of my favorite Google stories is that crazy anecdote about the v eight 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 it winds up being, 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.
Speaker 1: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, you know, optimizations, but they did a ton. Is that type of work happening at Google? Do you wanna see more of it? Is it is it an exciting area, or is it just like, oh, yeah.
Speaker 1:That's just something that we're gonna happen we're gonna have to do. It's gonna 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.
Speaker 5:Yeah. You you should ask our our inference engineers who are who are working, like, twenty four hours a day. I think, like, 2.5 Pro has actually been, like, a fun 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 into inference.
Speaker 5:And, like, I think credit to our our team who's, like, 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 an 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 it's awesome to watch that happen.
Speaker 2:Yeah. Where where do you wanna see more you know, knowing 2.5 pro's, you know, capabilities probably better than anyone else, where do you wanna see more developer activity?
Speaker 5:Yeah. I think the 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 is a real phenomenon. I I think I continue to be interested in, like, all the multimodal stuff.
Speaker 5: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 do that relative to the to today where you can literally just write a prompt and send images or videos to the model and have it do those tasks, like, with basically, you know, near or better accuracy than you would get from domain specific models is absolutely fascinating. Like, I think we're we we haven't actually seen that wave of, like, multimodal startups that are, like, building on top of this stuff. And and I think that includes, like, audio things.
Speaker 5:Like, I I think the audio ecosystem is, like, still pretty nascent. Like, I think the foundation is being laid for that. Like, you know, 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, like, across other product services. People actually invest in, like, real time audio and real time video and image stuff.
Speaker 5:And I think that's, like, 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. Like, it just takes, like, twelve months or something like that for that to happen.
Speaker 1:Yeah. I mean, speaking of, like, building new products, I love the Paul Buchoy Paul Buchoyd story of building Gmail. Is this, like, almost like April fools, project? And then you see a you see a seed of that in the NotebookLM project. What's the culture like around the idea of, like, 20% time?
Speaker 1:Does that even exist anymore? And then, like like, if if I joined Google, could I just go and say, like, hey. I'm gonna 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 gonna need to think about because, like, Gmail's mature.
Speaker 1:But there's still, like, a you know, right now, Gemini is, like, kinda 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?
Speaker 5:Yeah. That's a great question. I think my my 200% project is is on all the Gemini developer stuff. So I I do think 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 gonna come up with innovation.
Speaker 5:Yeah. I think for NotebookLM specifically, it came out of Google Labs. And, like, Google Labs, the the whole point is come up with new product services. So not just not just NotebookLM actually, but there's, like, a whole, like, Wisk. If folks have seen Wisk, it's like a video image generation platform that came out of that.
Speaker 5: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 they 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 gonna see that, like, fusion of all of these, like, new ideas and product spaces, because him and his team sit so close to, like, the blank slate.
Speaker 5:Let's build any product to solve problems that people have. Now that they also run the Gemini app, I think we're gonna see, like, a a ton of explosion. You should have Josh on. He's he's one of my favorite people.
Speaker 1:Yeah. Yeah. We'd love to.
Speaker 2:How do you think about getting 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 Yeah. 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. Yeah.
Speaker 2:We should just sort of like get into the office in the morning, adopt that, and do that. Yeah. 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.
Speaker 2:But how do you think about getting users to just, like, be more creative? Obviously, it's helpful when a developer builds an application to, like, prompt a new consumer behavior. But how do you think about that kind of at at the application layer at at Google?
Speaker 5:Yeah. I I actually my personal take on this is I think this is a bug of this current AI moment where, like, the if you look at, like, what is the ideal case, the ideal case is the models and the products, like, pull out what they need to from the user in order to create value for them. And I think if you look at, like, 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 gonna get value. But two is also it's like a shitty experience, honestly.
Speaker 5:Like, I hate like, this is my biggest problem 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 Mhmm. Random question that I that I have about how something works, and then I'm given a 50 page research report inside the Gemini app, and then I can one click turn that into an audio, like a Notebook LM audio overview. Like, that's great because, like, as a user, I don't need to make this, like, large order of magnitude of investment.
Speaker 5:The model does all the work for me. And I think as we see more experiences like that, like, I'm 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 these tools are going to be able to, like, pull this context out of you, and you should just go and build that product. And, like, I think the models are actually good enough in a lot of ways to help you do that today without having to, like, rely on a user, hopefully, having the right behavior for Yeah.
Speaker 5:To to make that product successful.
Speaker 2:You know, it's an interesting thing where I feel like users are so trained on, like, software doing a specific thing that this dynamic of software and this sort of 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 and I just feel like even even as, you know, somebody who's, you know, I've now I'm I'm not 30 yet, but I've basically spent twenty years using software that behaves in a very specific way, and I need to just, like, totally reimagine how to use software.
Speaker 1:Mhmm. I I think the
Speaker 5: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.
Speaker 5: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've if we fast forward, like, ten years, I do think there's gonna 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.
Speaker 2:Yeah. Yeah. Like, I wanna 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.
Speaker 2:And I didn't even have to
Speaker 1:I didn't
Speaker 2:have to.
Speaker 1: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, like, 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.
Speaker 1:But this has been around for a long time, but it really does transform the experience. I mean, speaking of I I wanna know more about you 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 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.
Speaker 1:I got a deep research report. It's not reading it to me here, at least in Chateaputee. I need to take it over to Speechify and get it to read it to me there. How I but, obviously, AI Studio is a little bit more prosumer, I feel like. There's a lot I mean, the temperature is there.
Speaker 1:There's, like, still some some some buttons that are, you know, almost like developer to like, terminology. So walk me through some of your favorite AI use cases in AI Studio and and what you're getting the most value out of so people can just kinda copy your prompts.
Speaker 5: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 Mhmm. Showcase all the models' raw capabilities Sure.
Speaker 5:So that you understand what the models are capable of so that you can go and build great products Like, we're actually not so, like, deep research is, 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, etcetera, etcetera. And that's available on 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. Sure.
Speaker 5: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, like, frontier capabilities, show you the art of the possible so that you can go and build the products that you really like.
Speaker 5:Yeah. So I do spend a bunch of my time from, like, a like, doing work perspective inside of the Gemini app. You know, Canvas is another one of them. Like, vibe coding inside of Canvas, inside the Gemini app is a lot of fun.
Speaker 1:Someone needs to vibe code a Google reader. This would be the most viral thing ever. Don't know. Are you familiar with Google reader?
Speaker 2:Probably before my time.
Speaker 1:It was like an RSS reader, and then and Google shut it down. And, like, it had, like, a thousand true fans, and so they were, like, so upset about it. I I I was using it. It was fun. But, you know, I understood that they didn't need it.
Speaker 1:But, anyway, I'll continue.
Speaker 5:For you. We'll see what we can do. Maybe we'll Yeah. Maybe we'll bring Google Reader back as a vibe coded app.
Speaker 7:That would
Speaker 1:be that would you would destroy the Internet. That would be the the greatest marketing for for everything that you're doing if you could bring back Google Reader. Anyway, sorry. Switching? You're I I I wanna I wanna let him finish about his Yeah.
Speaker 1:His his, like, most interesting, like, AI use cases and what's fun and what's in your what's in your everyday carry in the AI world.
Speaker 5:Yeah. I 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 could 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, 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 I'm looking at it somewhere on my computer.
Speaker 5:I looked at it today or yesterday or right now. Like, just let me show the model what I see and have it do interesting stuff. So I've been playing around with a bunch of, like, pair programming examples like that, and just, like, generally, like, 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 is a super cool, like, very futuristic feeling experience. That's awesome.
Speaker 2:Last question, switching gears a little bit. Do you have any you know, ignoring your work at Google and and on Gemini, you have any takes on AI hardware? Do we need new hardware devices? Is it, is it an area that you're excited about? Or or, you know, what how do you think about that generally?
Speaker 5:Yeah. I I think on both sides from an enterprise and consumer side, I think there's a lot of opportunity. And I think in the platform shift, like, it makes sense to try to build something. I think, like, does it end up working? I don't have the the crystal ball, but I think on the enterprise side, the opportunity is you go in and build, you know, hardware that makes LMs a lot faster and more efficient.
Speaker 5:And I think that's warranted, and somebody should do that work.
Speaker 2:And then on the even even, yeah, consumer side, yeah, I'm curious. You know, we had we had, like, the the the founder of Cluely, which has been going viral on, before you, he was talking about how, you know, the end state is just being embedded into into the brain, directly. But, but, yeah, I'm excited.
Speaker 1:I I mean, I mean, you you can feel free to pass on this question, but the founder of Cluelie, he applied for a job at Amazon. He cheated on the lead code questions. If 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?
Speaker 5:I I think we've actually, been looking at doing, like, AI assisted interviews and not AI assisted interview. Like, I think I think the world needs both right now. Makes perfect sense to evaluate both.
Speaker 1:Yeah. Yeah. Kind of interesting. Mean, yeah, he was doing it as, a publicity stunt, basically, trolling. Obviously, I don't endorse actually cheating on real interviews.
Speaker 1: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
Speaker 2:and 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.
Speaker 2:How do you collaborate with other people. Right? And that's like a a really good eval as you said.
Speaker 5: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 versus not across coding, across every discipline right now.
Speaker 2:Totally. Awesome. Well, thank you so awesome. Come back. I'm sure you're gonna have, many big announcements this year.
Speaker 2:Always welcome, to come on and and jam with us. Thank you for making the time.
Speaker 5:Bye, guys. See you soon.
Speaker 1:Sector. We got Eric Thornburg coming in the studio in just a minute. He's, Andrew Steinhoritz, the latest, general
Speaker 2:partner. GP.
Speaker 1:Good friend of us, good friend of the show. Known him for years and, excited 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 cliff. Who knows who who messing with you?
Speaker 5:Great to
Speaker 1:have you What's going on? Beautiful logo in the back. Welcome to the stream. How are doing, Eric?
Speaker 4:Thank you. A long time listener, first time caller. Thanks for thanks for having me on, guys. Huge fan.
Speaker 5:Yeah. Great to
Speaker 1:see 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.
Speaker 1:But Totally. Is there anything you could share about how someone becomes a general partner at a storied venture capital firm?
Speaker 4:They they brought a briefcase to my parents' house. Yep. And, yeah, you know, just been working the family for years.
Speaker 1:Yeah. Yeah. I I love it. I love it. But, I mean I mean, seriously, I mean, you you you've you've you've known the team for a long time.
Speaker 1:What what were the conversations like, and, how did it all come together?
Speaker 4: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?
Speaker 1:Sure.
Speaker 4:But, it's kind of like when someone amazing asks you out, don't ask too many questions. Just Sure. Just say yes. Sure.
Speaker 1:Sure. Sure.
Speaker 4:My 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 wanna marry venture into what I'm doing.
Speaker 4:I 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 wanna do it again, but I'm figuring out what what is the right structure, how how to do that.
Speaker 4:I could just start something. I could join something early. And then Mark's like, why don't you just do this at a 16 z? That's awesome. And I was like, I I hadn't really considered it because it's such a big firm, you know, so specialized.
Speaker 4:I'm a generalist investor, you know, a more talent, you know, driven early stage. And he and I think, like, would I fit in at, you know, 700% firm, like 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. Catherine's evolved too. The other partners get involved.
Speaker 4:And, basically, they had had a desire to go much bigger on on on on content Cool. Like, separate from me. And they kind of liked what I was up to at Terpentine with sort of this network approach. Yep. And they crafted the right dual role that's a mix of investing and a mix of kinda media network stuff.
Speaker 4:And I that that that's how over a few month period, we just, you know, like, kept falling in love with each other even more, in love with the opportunity, and so here I am.
Speaker 2:No. There's this there's this thing in in in venture, specifically investors. They spend all their time working with founders and they and they and they think, I need to be a founder. Like, I have to start my own firm. And then you realize, like, you can potentially have, like, a thousand times more impact if you join a platform Yep.
Speaker 2:And make it better Yep. And leverage all of those resources. So I I think it makes a ton of sense. I have I I wanna go back like way way in in your early days. How did you how did you get so good at networking?
Speaker 2:I think it's like a you're probably like, you know, the best to ever do it. The Michael Jordan of networking. And Has everyone Yeah. I don't I don't say that lightly. No, seriously.
Speaker 2:It's it's, you know, 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 it just was totally natural.
Speaker 4:Yeah. What is interesting? First of I'll just say, I appreciate the compliment, and no one who's good at it wants to be known as the thing that
Speaker 1:Oh, yeah. Sure.
Speaker 4:That they want it to be like like, Deleon's got a good network, but it's like a byproduct of the stuff they've got.
Speaker 1:Sure. Sure.
Speaker 4:And and so, yeah, we we, I I would say hopefully, it's similarly too. I mean, I think the the way I realized it, I was doing this music tech company out of college, Rap. F m. It was kind of a retarded idea. It was like chat roulette for rap battles.
Speaker 4:It it it it made no sense as a as a business, but it was just kind of a out of college project. We were somehow raised some money for it. This is when Twitch Twitch was getting off the ground. People were like, hey, Twitch for music. Maybe that'll work.
Speaker 4:And live Justin TV, live video, etcetera. 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?
Speaker 4:And so I I was I had some skill for that even though the idea was dumb and people were like, hey. You you you have something here. And then but I didn't put it together until product time, which is the thing I joined Next where, like and, you know, Ryan was CEO. He really got that off the ground. But I I helped him sort of, like, bring that out of thin air, like, you know, create a strong community network.
Speaker 4:And in that period, I was like, this is my superpower. I I like, up until that point, up until age 24, 20 five, I hadn't identified a superpower that I had, and I was just like, I'm just gonna triple down on this. And so then starting OnDeck and Village. And and what is it? I think it's just, like, a desire to like, an obsession with people.
Speaker 4:Like, who is everybody? What are they doing? But then also desire to help them and think about sort of people dynamics and but then also this that's, at, 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
Speaker 1:of time thinking about and and doing. Wanna 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. Crypto enterprise. What's interesting to you?
Speaker 1:And is there any crossover? We we kind of have this take, like, media can be fun and lucrative, but media is really hard to invest in. If you wanna invest in media, you gotta be on the platform side. You gotta be in Spotify, TikTok, Instagram, Twitter, Facebook. Like, those are the power law outcomes in media.
Speaker 1:People don't really think about them as media. But if you were in in YouTube early, you 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?
Speaker 4:So I I think Jessica Lessen really sort of high helped popularize sort of the bootstrapped media company Sure. That that Terpentine has followed. I think you you guys are following. I 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. Yeah.
Speaker 4:And so I, in general you know, because I did a music company, a lot people pitch me music. I'm like, I don't like this business. Sure. Business because people I I do media. People pitch me media.
Speaker 4:Yep. I don't wanna invest in in in media companies, but I do want to I do wanna build a lot of media out of Drews and Horowitz.
Speaker 1:Sure. Sure. Sure.
Speaker 4:Yeah. I I and I do want to partner with a lot of independent creators, like yourselves, like the Lenny Richiskis, like the Happy Stebbings, 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.
Speaker 2:Cool. And and sorry to interrupt. One thing I think is interesting is that venture venture outcomes require scale, yet media and and one of the things that makes media is amazing is anti scale. Right? It's like having for us, it's like having CNBC meets x.
Speaker 2:Right?
Speaker 1:It's like That's like that's
Speaker 2:a big 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 Mhmm. 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? Yep.
Speaker 2:Or it's or it's a a group chat that only has 50 people, but it has, you know, maybe like more Yeah. Activity for that those 50 people than any other social platform that they use. So can you talk about how you think about like sizing sort of like projects. Right? Because not everything that should be done should be massive.
Speaker 2:Right?
Speaker 4:A hundred percent. The it's interesting. There's this business industry dive that really, taught me about something. It's a business that not a lot of people know about, but it's immense ly successful. A lot of people, when they think about media businesses of last fifteen years, they think about, like, BuzzFeed and Mhmm.
Speaker 4:Fox, and, it's kind of, like, you know, Upworthy. Businesses raised a bunch of money in the twenty tens and totally crashed. Right? There was the you know, there was a bunch of venture firms, You know, this one included do it doing sort of, you know, consumer media businesses. And people thought, you know, they were gonna ride the platforms, and they were they were big.
Speaker 4:You know, they were growing, but then sort of the you know, as as you alluded to the platforms, you know, took the value. Which is where the value was. It was in distribution, not in the and these were just, content farms on on top of them. But an undertold 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 publication.
Speaker 4:So things like utilities, weight, HR, pharma, just like, valuable niche, like, newsletters, sold for $500,000,000, I believe, to Informa, which I I believe is, a $10,000,000,000 trade show company.
Speaker 6:Wow.
Speaker 4:So business media, business events
Speaker 1:Yeah.
Speaker 4:There's there's quite a good business there, in in trade stuff on the b to b side because, you know, if you have the leading HR publication and, you know, you have 50,000, even 5,000, you know, decision makers reading or listening to your thing, that becomes a great channel for people who are trying to sell to that audience to, to reach them. And and they're willing to if if it if if they if making one sale can be tens of thousands of dollars for them, they're they're willing to to spend quite quite a lot to to to reach that audience. So 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.
Speaker 4:I think they're incredible at sales. I 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.
Speaker 4:And the the business work week also is is is doing this. And I wanted to do sort of a Silicon Valley take on that of, like, you know, Lenny Verczewski is is the is the goat of this for product managers, the newsletter. Yeah. I think he's almost at, like, a million subscribers. Yep.
Speaker 4:You know? And he's printing cash. And I was like, hey. There's gonna be a Lenny for for HR. There's gonna be a Lenny for CFOs.
Speaker 4:There's gonna be a Lenny for every position in every sector. I wanna I wanna create that. I wanna 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 Mhmm.
Speaker 4:You know, the best of 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
Speaker 1:Sure.
Speaker 4:Investing in being one of them. And I think ACC is the best place to do it.
Speaker 1: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. 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.
Speaker 1: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?
Speaker 4:Well, yeah, it's it's it's really fascinating question. It depends on what niche. Like, if if you're if you're as big as someone like MrBeast, you want, like, a mass market thing. But you talk to the bar. Yeah.
Speaker 4:Yeah. Even MrBeast, I do wonder if and I'm I'm friends with him, and I I think he's genius. But I I do wonder if that's the right if that's the most optimal business to be up. Like, and I think he's also getting to gaming too, but, like, should mister Beast have, like, sort of a Cash App competitor? Or like or
Speaker 1:I I 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 backing typically. It's all marketing. That's the entire expense is just getting people to install a VPN. So Yeah.
Speaker 1:You know, it doesn't matter where his audience is. They can sign up for the VPN.
Speaker 4:Yeah. Yeah.
Speaker 1:Silly, but I don't know. Probably not a good fit, but
Speaker 4:it was But you guys had the founder of Honey on who's who's a very good friend of mine and and he's building a really great business I just invested in. Pig. On the AdBlocker side, but like Yep. Mr. Goose was saying that he brought a lot of Honey's traffic.
Speaker 4:And so should he have created a Honey competitor back in the like, there's gotta be something that's bigger Yeah. That has better margins, you know, than Totally. Than chocolate. That's more defensible.
Speaker 7:Well, there's an interesting
Speaker 1:Yeah.
Speaker 2:There's an interesting thing with media, which is like this idea of value value creation versus value capture.
Speaker 1:Mhmm.
Speaker 2: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 Yep. That people have had this idea of media of one of the best business models for media being investing
Speaker 1:Yep.
Speaker 2:Yet that doesn't mean, you know, starting a solo GP fund and just having a podcast necessarily. Like, it can look a lot of different ways and that's why I'm I'm excited about turpentine in the context of
Speaker 1:Yeah.
Speaker 2:A 16 z because you can make the best podcast about biotech. Yep. And you're it's less about That's how do we how do we, you know, 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 Yeah. And and see the the return from that.
Speaker 1:Yeah. I I I know you're still, like, you know, second day on the job, but I'd love to know kind of how you are thinking about the current a 16 z 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. Yeah.
Speaker 1:And so, you know, I 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 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 the with the Rogan appearance. Totally.
Speaker 4:Yeah. It's a it's a fascinating question. So I'm still I'm still getting up to speed with
Speaker 1:Yeah.
Speaker 4:Yeah. With the 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 Mhmm. And it's not limited to Andreessen, but that they they try a bunch of stuff.
Speaker 4:Yeah. Like like you guys. Right? Like, TPPN, you know, you guys had a few different iterations Totally. Before coming to this this one that worked.
Speaker 4:Yep. And people don't see that, you know No. No. No. Like, you're making video content for for years before this, and and, Jordy, you make all sorts of, like, amazing, branded content and doing all sorts of experiments, and and you guys tried it with different people first, and you figured out the format that works.
Speaker 4:Yep. You'd Yep. Like, a couple years in or a few months in. So, similarly, I think future was a good idea. Yeah.
Speaker 4: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,
Speaker 1:but 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.
Speaker 1:The founder of, you know, some amazing company like Databricks, like, what's he using on a 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.
Speaker 1:It's totally like, oh, it's only Andreessen portfolio companies or whatever. But, like, I don't care. I just wanna know, like, what these people are using. It's interesting. I
Speaker 2:don't know.
Speaker 4:Totally. So so it took they took a first stab. I I I think there were a lot of great things about it. I think it also coincided with sort of the increase in, decentralizing into into different funds. Right?
Speaker 4: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 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 I'm I'm on the content side, separate from investing, I'm more focused on the on the podcasting to begin with.
Speaker 4:Sure. But, to your so I I I to your question around, own shows versus creators, I think we're gonna have a mix. So we we we have some flagship shows right now with the Ben and Mark show, with a z show, then we're gonna have vertical shows relative to the funds. Totally. But then I wanna sort of really grow the Terpentine network.
Speaker 4:Yep. And, you know, the limitations of turpentine were that we were a bootstrap business, so we have to make money from other shows.
Speaker 1:Yep.
Speaker 4:But and Jason doesn't have those same limitations. So we wanna, like, do something like an affiliate network where we can partner with amazing shows, help them get distribution, help them make more money, and kinda 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 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 or what Ashantis is doing, but that's only, like that's, seven show. Those shows are great.
Speaker 4:And I love you know, the HubSpot's doing some good stuff, but, like, you know, Lenny's not on a network. Dorkesh is not on network. There's a bunch of people and 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 it can work with newsletter writers.
Speaker 4:Maybe it can work with YouTube creators more broadly, just kind of like extended like, love what Slow is doing. They have a creator fund. It's fantastic.
Speaker 1: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 or Counter Strike. And they'll go and interview all the people that worked on it, and 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 three are so rare.
Speaker 1: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, like, they're like it's it's awesome that they like they that they they found the right match of like the the the team behind No Clip and these documentary secret tape. Like, they're great at creating. And clearly, Andrew's in games, a 16 z games was just like, go run with it. And it worked out really, really well.
Speaker 1:So I I I love the idea of, like, that that partnership model you've you've described.
Speaker 2:What what do you think about the infrastructure around group chats? Right? Like, every every no nobody wants to download another app, but at the same time, like, you do run into limitations. Everybody that's built on you know, you've built a number of communities. Right?
Speaker 2:And I'm sure you've, like, hit the limits on Slack, hit the limits on you know, run into issues on Discord, you know, Signal has its limitations. Mhmm. 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? Mhmm.
Speaker 2:And how how do you think about the infrastructure surrounding that? Do you think there's opportunities there?
Speaker 4:Yeah. So first is is is zooming out. I think a lot of the last interesting most interesting conversations over the last five years to me have have been in group chats, and I've been in some with you guys where where 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 replies. And, you know, there could have been a world where Twitter that just happened in the DMs, but would for whatever reason, that that that it moved out to different different group chats.
Speaker 4: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.
Speaker 1:Sometimes John Coogan just adds a bunch of random friends on a Christmas Eve.
Speaker 4:I know
Speaker 1:that. You have to text me and say, hey. Are you, gonna stop, or are you gonna 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 aren't you advising all your friends?
Speaker 4: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 Yep.
Speaker 1:He goes full biology all the time. It's great. I mean, that's that's what you live for.
Speaker 4:Oh. So I, I've thought about this for for a long time, and I worked for Shri Ram, 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, it would it should be as, like, a real social network of, like, a thousand super interesting people, and you could Mhmm.
Speaker 4: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 I 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. Mhmm.
Speaker 4: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.
Speaker 1:Mhmm.
Speaker 4:And I think there's gonna be something that's even way faster than Twitter. And by that like, Clubhouse got into it a little bit where it's like it's basically like the beef of the day. Like, every day someone gets in a fight or there's some drama, and there's gonna be a platform where they just fight live. That that that I feel like that's just gonna happen. Like, I remember in our house with Mike Solana and Chesa Boudin, like Oh, that's infinite entertainment.
Speaker 4:And and and so group chat is just so much more live.
Speaker 1:Vlad Tenev and Elon Musk. Like, that was iconic. Yeah.
Speaker 4:So so I I was actually working on a product
Speaker 1:Sure.
Speaker 4:That was gonna be, like, pub house for group shots where where you chat live with a public audience. You you can sort of tier the permission gates, there's a speaker and audience.
Speaker 2:That's fantastic.
Speaker 4:Really had some magic. But I think I actually think, you know, people said they got too big, and 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.
Speaker 4:And so I think group chat format is the right one. I was working on it, but then I, you know, spent time with with Marc Andreessen and decided to have other plans. And I also met another team that I I'm not gonna announce here yet, but Sure. Introduce you to them. And when they're ready now, they they will, who's building this.
Speaker 1:That's cool. And I
Speaker 4:I I think it's a pretty exciting product. I think the, as you said, Jordy, the bar for a new app is really high. Mhmm. 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 a 10 x better product there.
Speaker 1:So I'm Yeah.
Speaker 2:No. I was asking in hopes that you were incubating or or funding or Oh,
Speaker 5:he found it.
Speaker 1:Something there. He found it.
Speaker 2:Well, you you you found it. You found the right one, it sounds like. But but, yeah, it just seems like such an obvious opportunity when
Speaker 5:it when
Speaker 2:Yeah. When I hear about you running, you know, multiple groups
Speaker 4:Yeah.
Speaker 2:I'm just like, wow. It sounds really exhausting the second that you get even more even just one is a lot.
Speaker 1:Yeah. Yeah.
Speaker 2:So Even one is a lot. Excited to see that roll out.
Speaker 1:I have a hot take I want you to react to. Market maps are underrated.
Speaker 4:Oh, interesting. Flush out the case.
Speaker 1:I just think that, they got really, like, overhyped and they were kind so, I mean, the basic 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 gonna be on that list. All gonna repost it. And so it's just naturally, like, bait for the algorithm that it's gonna get a lot of attention, lot of quote tweets. Oh, thanks so much for including me. Right?
Speaker 1:But then it became, like, very, like, cringey, it was like, no. You should be 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 the the far future, the world. But but, you know, I've I've 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.
Speaker 1:Like, everyone kind of knows Harvey, but there's probably seven different companies in the legal AI space. Probably 50. Yeah. 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.
Speaker 1: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.
Speaker 4:I'll go further. I I agree with you, but I'll I'll I'll I went up you and say, I I think lists are underrated. Like, Forbes has trained us to think that
Speaker 1:Yes. Yes. Yes.
Speaker 4:You know, the lists suck or they're they're obviously always gamed or
Speaker 1:or
Speaker 4:everyone's gonna
Speaker 1:go to
Speaker 4:jail if they're on a list. Yes. Hypothetically speaking. Yes. But, you know, we've joked about sort of the or you're like, like, the Forbes twenty nine under 29 or
Speaker 5:something like Yeah.
Speaker 1:I think you should do that. I mean, I don't know if it makes sense now.
Speaker 4:Is as suited
Speaker 1:to Maybe we do it. Maybe we
Speaker 4:do it. Or maybe collaborate or something. But discovery discovered like, knowing what people think about people is really important. It's it's what we do all the time. We're like,
Speaker 1:who's good?
Speaker 4:You know? Who who's emerging? Who should we pay more attention to? Yeah. And I think that functionality, sort of like market maps, we've like, the execution has gotten sloppy, and so we sort of thrown the baby out with the bathwater.
Speaker 4:But, those things, they do perform best, which is why they get gamed. If they're good, they're they're really valuable.
Speaker 1:They're valuable. Totally. Yeah. Yeah. We're actually gonna do a Midas list It's gonna be a hundred of the top VCs.
Speaker 1:It's a hundred thousand dollars to be on the list, a million dollars if you wanna be
Speaker 5:on the top 10.
Speaker 1:But, yeah, just, email Jordy if you wanna be on that list, if you're listening. We'd love to have you.
Speaker 4:Dude, that's funny. I love your whole corporate media, like, rant.
Speaker 1:Oh, yeah. Independent media is dead. Corporate media is the future. Yeah. You're either backed by a trillion dollar venture fund or Exactly.
Speaker 1:You're you're shilling for ramp and bezel and Adquick and Numeral and Asleep and Wander. You know, one of the others.
Speaker 2:On a more on a more serious note, I'm 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. Oh, yeah. But 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
Speaker 1:Roy.
Speaker 2:Yeah. Who like rocketed to like 80,000 followers in like a few months. Serious. And historically, that would have been like some, you know, maybe he would have had got gotten kicked out of Columbia and like two people would have heard about it on Yeah. No way.
Speaker 2: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.
Speaker 2:There's less attention. Maybe if there's a thousand people in the group chat Mhmm. Like, you know, it's there's less like almost like leakage. Sure. Like, how do you where where do you think about
Speaker 4:So it's it's really interesting. So a few years ago when people were more sort of centralized on on on Twitter, there was more of a desire to, to you know, it was critical to go to group chats because some someone, would sort of was quicker to cancel you or call you out or there's just, like, more friction. But social media has balkanized a bit. Right? The whole blue sky exodus
Speaker 2:Yeah.
Speaker 4:Sort of, you know, people are in 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 is it, like, free speech dynamic or even just, like, everything's about politics all 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 Mhmm. I've seen what happens is these, like, eight people group chats.
Speaker 4:You know, me and John had a a great one for, like, a couple years. Are there's less of a need for them. It it disbanded. Now they're now we're in, like, multi hundred people group chats because Yeah. People are more public.
Speaker 4: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?
Speaker 1:I thought you weren't supposed to say people's names in that chat. I thought the whole reason was Chatham Hound's rules. Yeah. He's to say a a a a, you know, billionaire
Speaker 2:Marverse owner.
Speaker 1:Somewhat left wing who Yeah. He he was lampooned on Silicon Valley.
Speaker 4:Yeah. Reality show. Yeah. Yeah. Yeah.
Speaker 4:Pitches. He, he went on a podcast with Vivek. They had a debate. So this is public because they they I I I I think I said their names. They did a debate on DEI in our chat, and then they took to the podcast.
Speaker 4:Oh, that's cool. They they mentioned the chat. So I'm I'm comfortable mentioning their names, as as people who've had debates. And it's just fascinating. Like, you know, he doesn't wanna go on Twitter because he gets dunked on a billion times.
Speaker 4:Sure. In in chat, he'll get dunked on, but with more thorough thoroughness.
Speaker 1:Sure. Sure. Sure. Sure.
Speaker 5:And and
Speaker 4:we all learn from
Speaker 1:it. And and
Speaker 4: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 Yeah. In the same chat. So so, yeah, I'm still seeing the alpha.
Speaker 1: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.
Speaker 2:Hey, Eric. Little request. You're the first Andreessen partner to come on the show. Let's get the rest on.
Speaker 1:Let's get rest need a lot.
Speaker 2:We need lot more. You for
Speaker 1:I'm here to
Speaker 4:yo. Only Nixon can go to China. Only Tornburg can go to TBPN. To broker the relationship. Then we're
Speaker 1:Are you are you Kissinger or Nixon in this analogy? Yeah. It's a good question.
Speaker 5:Still not I think you're Kissinger. Great to have you.
Speaker 1:You sneak in through the back door, and then and then Nixon makes his arrival.
Speaker 5:Nice and met you. Yeah.
Speaker 2:We're we're very excited to to to watch you work and collaborate and It's fantastic. Congratulations again on the move. It's awesome.
Speaker 1:We'll talk
Speaker 4:to you soon. Much, guys.
Speaker 2:Cheers. Take care. Bye. Bye.
Speaker 1: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.
Speaker 2:Is that like a BMX reference too?
Speaker 1:Oh, yeah. Yeah. Yeah. You can bunny hop on a BMX bike. But he wrote a great post, Pre training isn't dead.
Speaker 1:It's just resting. G p c 4.5, the value of reinforcement learning and the economics of fun frontier training. So welcome to the stream, Jack. How are you doing?
Speaker 2:Boom. Doing great. It's great
Speaker 7:to be on the show.
Speaker 1:Thanks for coming on.
Speaker 2:A little context for everyone. Jack is helping us with our distribution strategy. Yep. So thanks for all the support, Jack. It's great to have you on the show.
Speaker 2:Probably first of many, guess.
Speaker 1:But, I love the post, and I'd love for you to take us through it. What 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. He says, so GPT 4.5 is 10 x bigger than four o and only marginally better at most things.
Speaker 1: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?
Speaker 7:Yeah. Definitely. So so a lot of me and my friends really like GP 4.5, and we're 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. Mhmm. But a lot of the reason people were underwhelmed by it were the actual benchmarks.
Speaker 7:You can look and you can see it did worse than you'd expect.
Speaker 4:Yep.
Speaker 7: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 seeing what performance we'd expect on AIME on everything else. You know? Mhmm. And when we actually did this, we saw that it was about in line with benchmarks.
Speaker 7:You know? 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 gonna get double the score on the math benchmark.
Speaker 7:You know? This is something that we expect that as as compute gets larger, as build outs get faster, you know, we're gonna get much better models, but not just because you can double model strength with doubling the amount of compute.
Speaker 1:So what is the, what is the implication for for that? Like, what model should people be defaulting to in the ChatGPT app? I think that's the, that that's the thing I wanna start with is, should people just trust you and say, you know, I don't care what people say online. I gotta pick 4.5 from the drop down. Even if I can't tell, I will be getting better results, or 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 kind of take things to the next level even if the underlying model is, weaker and cheaper?
Speaker 7:Definitely. Yeah. Well, I think the central claim here is that pretraining will continue to work as we're able to build it out, not that the pretrained models are the best right now. Yep. I think OpenAI's o three is the best model we've ever seen.
Speaker 7:It uses r l on every single type of tool use. It uses r l on chain of thought. Yep. It is quite a small model, it cannot
Speaker 1:really Is o three built on four or 4.5? I'm kind of confused at this point.
Speaker 7:Yeah. There's 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 g p
Speaker 2:t 4
Speaker 7:Interesting. Bigger than four o mini.
Speaker 1:Okay. Interesting. So is this something that we're expecting them to, optimize over time and eventually distill 4.5 in or maybe just scale up the inference chips to the point where they can run an o three, o four style model on top of 4.5?
Speaker 7: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 o three style training on it. And I think that's gonna be a really, really exceptional model. Mhmm. I think a lot of the point of the piece was that you have, like, a lot of axes on which you can improve AI, and none of them are obviously showing diminishing returns.
Speaker 7:So there's just tremendous potential to make models better, and there really is no wall.
Speaker 1:But what about the what what about the economics? At a certain point, you, you know, you need an order of magnitude. This is log linear, of course, so you need an order of magnitude more compute. We're getting into the $500,000,000,000 data center. At a certain point, you get to 5,000,000,000,000, and you're talking about a meaningful portion of global GDP.
Speaker 1:And if the if the results are, oh, it goes from a 28 IQ to a 30, The economics don't really pencil out. What's your take on on will we just see a pre training winter just for purely economic considerations?
Speaker 7:Yeah. And I I 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 p 4.5 now and probably, like, impossible to serve.
Speaker 3:Mhmm. But in
Speaker 7:a couple years, we're gonna see the type of algorithmic efficiency, and we're gonna see the type of chip improvements that make a model of this scale much more feasible.
Speaker 1:Mhmm. When you say algorithmic efficiency, are you talking about the type of, optimizations that happen with DeepSeek on kind of memory interconnect, the the FPA, that 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?
Speaker 7:Yeah. Basically, on every level. I'm really referencing, Dario's excellent piece about deepseq and exploit controls
Speaker 5:Yep.
Speaker 7:Where he says that, deepseq is really good model, know, but we do just see these continuous algorithmic improvements as we go, you know? Mhmm. So sort of the the functional ooms of compute are also scaling even if your compute isn't scaling.
Speaker 1:Mhmm. Mhmm.
Speaker 2:Talk about switching gears for a second. What what is the what's the vibe on the Stanford campus right now? Is is is there a risk that everybody drops out to work on AI? I imagine I imagine it's like a constant conversation.
Speaker 7:Yeah. I 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 Intamaki, you know, who are super aware of this stuff, you know, and they're and and they're always kind of pushing things forward and thinking about these things all the time. But in terms of just, like, the populace getting used to AI and getting involved in it, it's just been a really slow and continuous crawl upward. You know?
Speaker 7:I 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 gonna look like. Everyone thinks that the models are gonna get better around the same kind of paradigm and level, you know, and no one is ever thinking, we have OathMe now. What's GPT five gonna look like in a few months? What's GPT six gonna look like next year?
Speaker 1:What are you thinking g p t five will look like? Are we just talking about, another order of magnitude on pretraining flops, or is there more to it than that?
Speaker 7:Yeah. So so my my naive guess is that g p five is gonna be a model that uses all the clever training techniques that OpenAI and Anthropic have worked out around RL Mhmm. But it's scaled up significantly from these pretty small models. Sonnet 3.5 is pretty small. I think the OC range is quite small as well.
Speaker 7:One thing that I think is the most interesting about o three is that has a lot of these agentic properties that we've been seeking so lot 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, like, agentically going and doing a whole project. You know? And I think that trajectory is one to watch as as you look at GT five because you're gonna see it being more and more agentic just very naturally as context expands and as the model expands.
Speaker 1:Yeah. Tyler Cowen said, o three is AGI. We had someone on the show yesterday who said, we have ten minute AGI, but that's not necessarily eight hour AGI or twenty four hour AGI. How do you think about the length of reasoning chains and and and kind of that new frontier of optimization. Maybe we've hit the intelligence curve, but we need the agenticness to continue for a long time.
Speaker 7:Yeah. I I basically think that's right. The the the ten minute AGI take is exactly right. Exactly right. I mean, the AGI debate hinges a lot on what definition you use.
Speaker 7:Obviously, the Microsoft CEO came on DoorDash a few months ago Yeah. And said, I'll only believe it's AGI when the GDP goes up by however much percent. You know? Yep. I think we're starting to see models that are very general, and they're very intelligent.
Speaker 7:You know? And they can do a lot of the things that you might have naively described in AGI to be able to do, but they still don't really have this, like, 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, like, some barrier, some key problem that needs to be solved.
Speaker 1:Are, undergrad CS majors, bullish or bearish on, like, rappers or trying to go for the application later, trying to do a start up, or or are the best and brightest saying, hey. There's no way we're gonna win. Let's go work for a lab.
Speaker 7:Yeah. I think a lot of the smartest people I know really wanna work for labs, but I think they're almost too bearish on start ups and on wrappers. You know? And that a smart wrapper can take a model and kind of scale up with it. You know?
Speaker 7:And I think this is what we've seen from places like Cursor. Yep. You you improve as the model improves. If you're making a wrapper that's a bet on models not getting better, you know? Yeah.
Speaker 7:Yeah.
Speaker 1:Yeah. Is cheap. Prompt engineering and and you're really working to I do create this 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 Yeah.
Speaker 1:Great. Then the product gets better.
Speaker 2:Light wrappers of the last few years. I think a lot of them relied on consumers not being aware of ChatGPT's capabilities.
Speaker 1:I mean, there's some apps The apps where they're literally like ChatAI.
Speaker 2:Yeah. There's still like billions of dollars of revenue out there that's basically they just happen to acquire a customer
Speaker 1:Yep.
Speaker 2:Before OpenAI did or or another another Mhmm. Lab. Mhmm.
Speaker 1:Yeah. Can can you tell us any more about just the the mood among CS majors around the opportunity in startups broadly.
Speaker 7:Yeah. I I I may write about this pretty soon, but I I I do think the startup culture at Stanford is is really not what it used to be. You know? There there was sort of this, like, Halcyon era at Stanford where it seems like there was so much energy around startups, and now it really feels more like people are doing their startups in summer projects, and people aren't committing to them in the way that you really wanna see. Mhmm.
Speaker 7:I think that if 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 committed
Speaker 4:to them.
Speaker 1: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 $2,000,000 seed round just waiting for you, and you will be a founder even though you could go join a 10 person or even a hundred 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?
Speaker 7:Who's the Yeah. There's no actor who really made this bad, but the fundamental issue is that startups became too high prestige, too fast. Yep. 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 Doykesh Podcast, which is where I worked last summer.
Speaker 7:Yeah. Was that Doykesh 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 we're we're doing a podcast.
Speaker 7:You know? We're executing at a very high level, but it's a podcast. And I think getting to work with someone like Doorkash 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, stealth showed up in your bio than it is to have, like, I'm, like, working for Nat Friedman this summer is, like, pretty lame.
Speaker 7:Uh-huh.
Speaker 1:Yeah. I think that'll shift. I mean, working for Nat Friedman's pretty cool. I I I Working for Nat Friedman. I think it will it it will catch up.
Speaker 2:Yeah. The benefit is we have a generation of people that are finding out just how hard startups are, and there's not there's
Speaker 5:not And
Speaker 1:they'll land somewhere.
Speaker 2:Yeah. They'll land somewhere, but also realizing that if you're gonna start a company, once you know how hard it is, you really, really, really need to pick Yeah. Pick ideas carefully.
Speaker 1:Yep. Totally. Can you give me your read on the last two episodes of Dwarf Cash? He had AI 2027 and then AI 57 2057 or something. Are you AGI pilled?
Speaker 1:Are you feeling the AGI? What what what's going on over with in your world?
Speaker 7:Yeah. For sure. I actually I mean, I think the epoch people are fantastic, and I also think the AI twenty twenty seven people are very smart. And I I sympathize to both sides here. You know?
Speaker 7:I think model capabilities will grow very quickly. Mhmm. And I think it's much less clear how this will translate into the economy growing really fast. You know? I was I was in an interview recently, and someone asked me, say, Jack, you keep telling us AI is gonna be good.
Speaker 7:I think AI is already good. You know? Why hasn't it changed the economy? I was like, I I I don't really know. You know?
Speaker 7:It seems like the naive economic model says the 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. You know? So I think the AI 2027 people might be mostly right on how fast, things are gonna grow and how fast the model is gonna get smart. And then the epoch people might have a really good sense of, like, oh, but really getting this into the sewage sector, getting this to disperse across the economy in a way that changes things fundamentally is is a much longer issue.
Speaker 1:Yeah. I mean, maybe it's just like a human issue. You could kinda 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.
Speaker 7:And And and it was only it was only last year that Stripe became 1% of World GDP transactions.
Speaker 2:You know?
Speaker 1: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?
Speaker 2:Not this second, but, Jack is
Speaker 1:great to have you back. Every time you publish
Speaker 2:regular thing.
Speaker 1:Pop back on. Give us the breakdown. This was fantastic. Thanks so much.
Speaker 2:And, Jack's coming to LA soon.
Speaker 1:Oh, fantastic. Looking forward to meeting you in person. Yeah. For sure.
Speaker 2:We'll see you
Speaker 1:at the new studio. See you at the St. Paul's Great
Speaker 2:coming on, Jack. Glad to see you.
Speaker 4:Great to
Speaker 7:see you on, guys. Thanks.
Speaker 1:See you. 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 he posted a quote.
Speaker 1: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.
Speaker 2:I think we should deep dive this
Speaker 1: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 a different set of, experiences and and expertise and then also, conflicts of interest and all sorts of things. But we should dig into that post.
Speaker 1:Joe Wiesenthal shares that markets are surging on this headline. Besant sees de escalation of China, situation unsustainable. S and P now up 2.7%. I didn't Markets Markets love.
Speaker 2:Markets love when a situation is unsustainable.
Speaker 1: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 own startup today.
Speaker 1:He's going founder mode.
Speaker 4:Founder mode.
Speaker 1: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 leap into the arena, out of one arena into the other. Maybe it'll be a public company day to one day.
Speaker 1:Maybe you'll be able to buy the stock on public.cominvesting for those that take it seriously. They got multi asset investing.
Speaker 2:It's gotta be the first substack to SPAC.
Speaker 1:Yeah. I love SPAC. Anyway, we wanted to give a little congratulations to Cici 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.
Speaker 1:I missed it. She she posted some photo saying, like, I I I I my boyfriend's in YC. I cooked him dinner, and it went, like, very viral. He but he proposed this last weekend by bringing together a hundred of their friends and to surprise her with a stand up comedy show that she had to perform in. Go golden retriever mode.
Speaker 1: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 enjoyable.
Speaker 1: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.
Speaker 2:Marriage is the greatest investment you'll ever make.
Speaker 1:It is. One of
Speaker 2:the most important.
Speaker 1:It is. Calvin, Kevin says, never buying regular Zins again. Five pound bucket of horse nicotine from Tractor Supply. Never underperforming or having a foggy mind ever again. I am the hashtag boss, lipping half a horse dose that I feel scroll
Speaker 2:so that so that
Speaker 1:people can see this. The next the next slide is is queued up for the Mustang horse nicotine packets. If you pull up the next slide
Speaker 2:Do you know about this? Is is nicotine consumption in the horse community
Speaker 1:a big thing? No. Is it wait. Wait. Do you understand the riff on this?
Speaker 1:So so, basically, someone got horse electrolytes Yeah. Yeah. And it was
Speaker 2:like, this is horse
Speaker 1:aid, horse Gatorade went mega viral. And so now people are spinning off on that. This is clearly AI generated.
Speaker 2:Oh, okay. Okay.
Speaker 5:This is
Speaker 2:AI generated. Saw this way too far for it. I I saw it, and I was like, John, is this size of an animal? A horse.
Speaker 1:Maybe I should do this.
Speaker 2:We gotta get Lucy to do some horse There
Speaker 1:were other jokes about this. There was horse creatine. People were spinning off on it.
Speaker 2:Got it. Got There's a
Speaker 1:variety of of
Speaker 2:Wow. I got, AGI is here.
Speaker 1:Yeah. AGI is here. Oh, this is big news. The star defense tech founder, Matt Grimm, was spotted Spotted. Soaking up some sun at his Costa Mesa headquarters.
Speaker 1:He is, of course, the
Speaker 2:We have Vaziers
Speaker 1:everywhere. And he's stunned in a perfectly tailored three piece suit.
Speaker 2:You can't step out of your office without one of our
Speaker 1:We have paparazzi everywhere. We're bringing the paparazzi to technology.
Speaker 2:And Ben had a good idea. He said, need TBPN to start a weekly segment showcasing the tech business and finance fits of the week, what league fits does for the NBA. We need for the
Speaker 1:High class work work
Speaker 2:fits, maybe even throw in a yearly awards segment.
Speaker 1:Oh, we already did that. We already did that. We already did the best fitted in tech.
Speaker 2:Who what
Speaker 1:Aiden Gomez was the runner-up. Believe Alex Karp won for his Alright. For that. For his general overall style, but also his fantastic Patek Philippe Aquanaut with the gold strap.
Speaker 2:Well, great idea, Ben.
Speaker 1:Or the orange strap. We already talked about Clue Lee, but there's a lot of backlash. I thought it was a great interview. I thought I thought it was interesting. It is a little like, what's interesting is that I don't find his actual product that dystopian, the idea of having augmented reality glasses that, I think
Speaker 2:he finessed the Internet
Speaker 1:for
Speaker 2:a bunch
Speaker 1:of Yeah. He finessed the Internet.
Speaker 2:And I think he's gonna leverage it very well.
Speaker 1:The 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
Speaker 2:distanping And he he wants to get to, you know, a implant effectively, a chip for your brain, but he's gotta build enterprise SaaS to get there.
Speaker 1:Yes. I love it.
Speaker 2:And and that's a good lesson for Well,
Speaker 1:speaking of a lesson, a Sam lesson said
Speaker 2:I think we should save these actually save this for tomorrow.
Speaker 1:Okay. Yeah. Let's bring him on.
Speaker 2:Go go through it properly.
Speaker 1:Yeah. It'd be great to invite him on and and 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, a horse headband that's branded.
Speaker 1: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 camels. I think it'd be great.
Speaker 1:Yeah. Put some ads on there, like the jacket. We
Speaker 2:should do a TBPN
Speaker 1:horse camel drapery
Speaker 2:Horse drapery.
Speaker 1:Yeah. Horse drapery. Yeah. Livery for your I love it. Anyway, shout out to Michael in Hawaii.
Speaker 1:He says, doing my duty and TBPN pilling my Hawaii one big screen at a time. SeizGong 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 was an awesome post. Thank you so much for sharing us on the big screen.
Speaker 1:We love to see the show on TVs and in 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 like what you see in the chat.
Speaker 2:Live transcription.
Speaker 1:Yeah. Live transcription. I'm sure we can do much better than what, the the standard is on TV. Yep. That'd be great.
Speaker 1:Also, another post from Rahul. Been on the show. Big fan of him. He says with intense focus He's really
Speaker 2:wearing the suit everywhere.
Speaker 1:It's fantastic.
Speaker 2:It's amazing. I'm so Especially because he works in finance artificial intelligence. So I'm glad he's dressing the part.
Speaker 1: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.
Speaker 1: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, 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.
Speaker 1:And promotion for Eight Sleep, use code t b p n.
Speaker 2:Use it. Fantastic. And then download Julius.
Speaker 1:Also That's crazy. Was on a plane and he downloaded all my YouTube analytics and
Speaker 2:Oh, that
Speaker 1:was crazy. Did Julius analytics on that and showed that You put
Speaker 2:it in the trenches. Trenches.
Speaker 1:I've been in the trenches.
Speaker 2:Content trenches.
Speaker 1:Yeah. I think the first year I got like a couple hundred thousand views, and then it was, like, seventeen million three years later. Was great. Great great run. Anyway
Speaker 2:This post from Nat Suki. I don't know if it's it seems like it might have been photoshopped, but it was funny. Hey, chat GBT. Look under there. Underwear.
Speaker 2:LOL. Made you say underwear. Well played. Say home. Home.
Speaker 2:Latitude. 52.3974.
Speaker 1:This is like an ad for gamdom or whatever.
Speaker 2:Why did they put this? Gambling ad. No. No. No.
Speaker 2:No. This is a way so so this is a hack that Okay. Betting companies are doing where they're
Speaker 1:why is this why is why is this AI poster posting about gambling? I feel like that's such No.
Speaker 2:No. So basically Yeah.
Speaker 1:What's going on here?
Speaker 2:I bet Natsuki just posts a lot of
Speaker 1:content like Sure.
Speaker 2:And some of other I think, allowed allowed to watermark? Yeah. They pay for a watermark on a lot of posts,
Speaker 1:which is just a Weird. Anyway, last shout out and then we'll wrap up the show. Mass, you know him from the, the viral swing gate up in San Francisco we covered on the show. There was a swing on a tree. It broke.
Speaker 1: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 Strackman, Danielle Strackman, and fifteen seventeen Fund. They are the GOATs because, he's been looking for compute, he got some.
Speaker 1:He said we were just approved for a hundred thousand dollars in AWS credit. 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?
Speaker 1: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.
Speaker 1:Thank you for watching. Thank you for listening, and we will see you tomorrow. Excited for tomorrow. Great rest of your Tuesday.
Speaker 2:Enjoy your Tuesday. Goodbye. Chad day.