Alex (3:40)

Is it an Austin based.

Jason Calacanis (3:42)

Can't say, can't say. I can't say, can't say, can't say. But it's like you know, five trips in six weeks or something crazy. So I'm going to be just all over the place but then back to the portfolio, my crazy schedule, you know, everybody wants to put a slot on my calendar. So then what happens is I wake up and it's just like oh my God, what are these seven meetings? So I just decided, you know, listening to Barry Diller's incredible autobiography the Summer and then I had, I had listened to Mike Ovitz's and I decided, you know what I, to try a different approach here. No more meetings from now on. Send me the founders mobile phone number and I'm going to do a Doug Leone Douglioni. Three times a year my phone would ring. This is you know, 15 years ago, whatever, when I was running startups and he just, Douglioni would come up my phone. Oh my God. I'd be like Douglioni, Holy Jesus.

Alex (4:39)

All.

Jason Calacanis (4:39)

Yeah, exactly. Well yeah. And I'm just like fumbling with the phone. Mr. Leone, how you doing? You know, and I, it would be like hey, do you know this person? Okay, yeah, we're looking at an investment in. It would be great if you can give him a back channel. Just let Them know your experience with us. And I'd be like, Absolutely, Mr. Leon. Okay, bye. You know, it's literally a 45 second thing. Or you'd be like, hey, you know, should we invest in this company? Or hey, this person wants to be a board member, they said they know you. I don't know. You know, it's just. It would be like that. Or other times it would be like, oh, this is incredible. Things happening in the world. This person is a fan of yours. Would you like to meet them? And I'd be like, yeah. Yes, sir, Mr. Leone.

Alex (5:17)

But short, very short.

Jason Calacanis (5:19)

Every time I take just tight, tight, short and tight. And you know, like, like a great espresso. And you know, that's. That was his thing. There's a Douglioni espresso call. That's what I call it. Espresso. So this is my espresso call strategy, inspired by Doug Leone. Now when they send me stuff that I gotta react to, I'm just like, include the founder's email and phone number. So the last couple days I tried this new strategy, which is no more meetings. Tell the founders I'll be in touch. That's it.

Alex (5:52)

And you just call them?

Jason Calacanis (5:53)

I just randomly call them?

Alex (5:55)

Yeah. No, I think this is a great strategy. I do this with friends using FaceTime video, and they absolutely hate it and I don't care at all.

Jason Calacanis (6:04)

So anyway, I've been doing this and I've recaptured so much time because none of these phone calls need to be 30 minutes on your calendar. I can do five. Four calls. Five calls. Four calls in the same amount of time.

Alex (6:13)

Oh, yeah.

Jason Calacanis (6:14)

And all of a sudden I'm so much more effective. I don't know how I didn't see this before, but anyway, it's working much better for me. But there's been like a little chaos. I can tell when the market is hot because people start acting strange. We are in or we're entering into peak market right now. And one of the things that happens in a peak market is people's morals, ethics, sharp elbows on all sides of the tables. You know, management teams to their founders, founders to their management teams, founders to their VCs, VCs to their founders, lawyers, everything. Everybody is getting a little chippy, okay? And arguing over things that don't matter, that aren't company building. But there's so much money in the system sloshing around that I'm getting pulled into all kinds of chaos all of a sudden.

Alex (7:08)

And I'm like, jason, by chippy you mean like in the basketball sense when they say it's getting chippy out there because the players are getting literally more physical. There's more bumping, more shoving, more correct rounds coming together.

Jason Calacanis (7:21)

You have a board seat. This other person wants to buy your shares. This person wants to take the whole round. This co founder is not pulling his weight. We want to fire him. It's just everything. It get chippy, chippy.

Alex (7:35)

And this is because there's so much money sloshing around because things are going so well is my, is my read of that.

Jason Calacanis (7:40)

So the opportunity space. Yeah, the opportunity space has widened. It's not, it's no longer, oh, we are going to get a thousand seats this year for our SaaS product. It's okay. We're going to take a category of work and automate it and make it 17 times faster for 90% less money. And so you start looking at what is possible right now. It's kind of like people underestimating how big Uber would become. Like none of us expected, like, oh, they're going to be doing a billion rides a month and the 10 billion rides a quarter, whatever it's, you know, turned out to be. It was like, yeah, we're going to shuttle people back and forth, you know, who want Lincoln Town cars in a more efficient fashion, not we're going to replace cars, et cetera. So that's the kind of of realization people are having is that the stakes have gone up. And in some ways, if you look at the NBA, you brought that up. People getting chippy on the court. It's kind of like, oh, the new TV deals are coming in next year and I don't know if you looked at it, but like the salary caps going up like getting a slot and getting, being a starter or getting a four year deal right next year with the salary cap, you know, going up so much. The, there's a lot more at stake. The stakes have gone up and we talked about the total addressable market and you took some notes on it. But people are starting to realize, oh, what's going on here is not the software business, not apps or services, it's the entire reinvention of labor and economy.

Alex (9:14)

Okay, actually that's a really good point because Marcus and I are working on this. And do you want to see what we have so far?

Jason Calacanis (9:20)

Sure. Okay. Yeah, Here we go. This is the TAM 1.0.1.

Alex (9:26)

There's a lot of fun things that we need to sort out here. Jason, you specifically asked us to take a look at working populations percent that are employed and then to essentially think about what's the current software spend against that population, and then what does that generate for TAM today? So just to walk you through, part of this developed nation population is about 1.4 billion. And then we pulled some data on working age, and then what percent of those people are employed. And then we had to make some assumptions like what percentage of those are daily software users. And then we applied your $3,000 per person per year spend to come up with numbers. Same thing for the developing world and so forth.

Jason Calacanis (10:06)

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Alex (11:26)

Yeah, and you get some pretty big numbers right now.

Jason Calacanis (11:28)

It's a trillion dollars. I see that across, yeah, developed world, 750 billion a year in potential spend. And then the developing nations with 6.8 billion people, you have 68% of the working age and 58% of working at time and their individual spend is but $240 a year in AI related software, robots, whatever, which is less than a dollar a day. And the $3,000 number is about $10 a day on AI spend. You know, you got a total TAM here of well over a trillion dollars. And that's just with my basic assumption that this is similar to sas, which could be a Completely wrong framing.

Alex (12:08)

Well, what we did was we also did consumer AI as part of this mix, thinking about the number of people that are doing personal AI usage because a lot of chat GPT has purchasing it for themselves. And then we had to bake in some other assumptions. For example, Marcus and I were just talking before the show about, well, how many of these jobs will survive because if AI does arrive, it makes people more efficient. You might assume there's going to be fewer people. So we had a 0.9 multiplier there. But there's just some more questions we need to sort out to get to what you're saying to get a better, more accurate number of what the TAM for AI is. But the back of the envelope stuff alone shows that today the possible market for AI powered software is essentially infinite for venture capital purposes. But we're going to make this tighter to some scenario analysis. But that's our start so far.

Jason Calacanis (12:55)

Yeah, not a bad start. And I think this is one view. This would be what we call in our firm and we teach at Founder University and at the accelerator, a bottom up tam. Hey, we're looking at the total number of people who work, we're looking at what they currently spend on SaaS software and just saying, hey, a baseline estimate, a minimum estimate, if you will. This is my minimum estimate is that we spend the same assess. It might turn out that the number of people employed goes down a bit. So maybe instead of 90% of people keeping their jobs, it's 80, but the spend is 15,000 a person, five times it. Because if, if you look at me yesterday, I signed up, I realized we weren't on the team plan for Claude, you know, we all had individual accounts. And then I was like, wait a second, there's projects inside producer Claude and the projects can be collaborative. So I just upgraded us and I'll get your invite out. But just yesterday Kabir and myself and Lon were working on some projects there. It's kind of like Google Notebook LM where you can kind of put in sources, but you have like a common workspace.

Alex (13:58)

Got it.

Jason Calacanis (13:59)

I was like, I don't know what this cost, I don't care. It's like, oh, you want to spend $30 a person? $360. Yes, yes. Because then I don't have to hire the 20, 22nd person at the company for 75K and I don't have to do an interview process. So very dangerous place to be in terms of hiring. If you look at it from, you know, a union, you know, a Senator, you know, looking at the world, you could be kind of scared from a business building perspective. Okay, do more with less. And I'd rather spend $15,000 on software for one of our producers than hire the $75,000 person and then have less people to manage. It's also del. Anyway, something's going on out there. This is the biggest opportunity of our lives. I think that this cohort of companies, these vintages of venture capital are going to break people's brains. I think all of the hand wringing about, oh, there's too many unicorns, there's too much. I think the outliers in this group are going to be trillion, 2 trillion, $3 trillion companies faster than it, you know, took Nvidia, Microsoft, Apple Meta, Tesla and Google to get there. It's just going to be a velocity that, a velocity to trillion that maybe we didn't consider. And I think the Mag 7 is going to turn into the Mag 70. I think they're going to be 70 trillion dollar companies like in tech. Because how.

Alex (15:32)

Give me a time frame on that. Because in a thousand years that's going to be true by definition.

Jason Calacanis (15:37)

I would, Yeah, I would say with, you know, it's going to take like a decade to build these. In some cases they'll be built in 5, 6, 7, 8 years. Like, or like OpenAI is going to be like the first XAI anthropic. You know, there's your first three. But I think there's going to be after those three, the other 67. So those three will happen in two years. I think we both agree maybe three, they'll all become trillion dollar companies in three years. And then we're going to see wave after wave after wave. Every category of software of work is going to become a trillion dollar company. That means backing into it. They got to have 50 billion, 100 billion, 200 billion in revenue. But let's just say, you know, in today's market, 20 times 10 or 20 times sales.

Alex (16:25)

So 50 to 100 billion in revenue.

Jason Calacanis (16:27)

Sure, something like that. And so start looking at companies and just say, can you see cursor getting to 50 billion? I can. Or some software development thing. Can you see a legal or tax company getting to 50 billion in revenue globally? Yes, yes, I can, I can see it now. Yeah, yeah.

Alex (16:45)

All right.

Jason Calacanis (16:45)

Well, speaking of which, our first story here is interesting, which means the two stories relate. I have to be ruthless about my time now because there's so many opportunities. And then this is kind of like the.com era where yeah, it could all blow up. There could be a blow off the top. Sure, why not? But there's going to be an Amazon and a Google and a couple of incredible companies in this cohort that if you make them, they would be like my Robinhood and my Uber investment. So now I'm like, wait a second. People said, oh, your Uber is going to be your biggest investment ever. And then, okay, Robinhood's coming on pretty strong here. It's like a half an Uber. I think those two might be dwarfed. I think I might hit something bigger. I think I might hit something bigger if I work hard.

Alex (17:30)

All right, well, I mean, Jason, you're famously lazy, so it's time to crack that whip on yourself and get back to work. All right, first up on the docket, deal raised $300 million. And Jason, we've talked about Deal on the show quite a lot this year, mostly because it's been locked in a spying dispute with Rippling, another company in the HR tech space. We read through its alleged activities. Yeah. And if you believe Rippling and they're telling the story, Deal effectively had a mole inside of Rippling and was using that to collect information that it was using to compete with them and also hire away their staff.

Jason Calacanis (18:06)

Crazy story.

Alex (18:08)

Yeah. And you and I were curious what was going to happen to the CEO Alex, over there, who I think you and I have both spoken to. And things slowly died down to the point to which people don't talk about this too much anymore. And now, at a reasonable remove, the company's back in the capital markets. A couple of short things here. It's a Series E led by Ribbit, A16Z and CoatU. And the company just reached a $1.2 billion yearly run rate in September. So they had their first nine figure month. And this is really awesome. They essentially had 15 to 17% EBITDA margins. So growing well, you know, way above IPO scale and adjusted profitability. A very impressive company, even given the shadow hanging over it. Yeah.

Jason Calacanis (18:51)

So I was just trading DMS with Deal. They had bought a firm that we were investors in. I believe it was. Gosh, we had two cap table software investments that kind of started bumping into each other. But I think it was cap based. Got bought by Deal. Yeah, it was cap base. And so in 2023, and then I think, think this is also public. There is a. Yeah, there. Cap base spun out now of Deal. So Main street is acquired. Cap base. So to the best of my understanding, I'm getting some clarity on this. I Own shares in Deal Cap Base is being spun out. This other group bought it, so we're not participating in that. Capace is a great piece of software. It was like we're going to do your, you know, Carta, like Cap Table. We're going to do everything leading up to it. Really talented founders. And it was just kind of a bummer because we had Capace and another Cap Table software company both get in the portfolio around the same time. And because we're an accelerator, we kind of don't like Y Combinator. We don't have a rule around. We just make one bet in a category because you can't when you're investing, especially in early stage startups like we do here at launch. Having the best, most up to date data at your fingertips. Well, it's essential. Listen, I'm smart, but I am not an expert in every single sector, industry or cutting edge technology. That's why our entire team is addicted to AlphaSense. Their market research platform has the data savvy investors need to understand what's happening in the market right now. And their AI interviewer has been trained on over 500 million business documents, making AlphaSense the single source of truth for investors. It's capable of pulling together analyst level deep dives on just about any topic in minutes. You want an example? Sure, I got one. We invest in a lot of robotic startups, especially companies that are automating warehouses, fulfillment centers, even making coffee. But did you know that the biggest challenge for these startups isn't building the machines that physically move around the packages? No, it's coordinating them with legacy systems and using those machines alongside finely tuned computer vision to monitor inventory and keep track of which supplies are running low. Know where I learned about all this? AlphaSense. It filled in all the gaps for me. And hey, we're going to start you off with a free trial right now. Go to alpha-sense.com twist that's alpha-sense.com twist for a free trial because literally a third of the companies during the accelerator, and let's say in the first year of the accelerator, they pivot to something else. Yeah, and a lot of times they pivot to something where they're like, oh, that person's doing something very interesting and it's working. I want to go follow them or become a fast follower or take your own spin in a section. So it was kind of a bummer because I think some of the founders, maybe even on both sides, were a little upset at me for it. And I was like, oh, guys, I say this going in. But anyway, congratulations to Cape on spinning out. And so all of this is to say that I have a tiny number of shares in this company deal. And I invited Alex, I just told him congratulations and then slid into his DMs. But he's going to come on the show next week, I think.

Alex (22:18)

Oh, fantastic. Well, at a $1.2 billion run rate, Jason, his company is now worth roughly 14x arrangements. And I just want to run the number of bikes. It seems low for the current era. Companies are quite expensive and this one has proven itself in global footprint and profitability just feels minor to me.

Jason Calacanis (22:36)

Private companies are a voting mechanism. Public markets are a weighing mechanism. Okay, so you're voting on the future when it's a private company. When they're public companies, then the real investors come in who are just like, tell me about the cash flow, tell me about the debt. Okay, let's do some discounted cash flow analysis. Okay, what's the growth rate? How do you, Are you going to expand the margin or is it going to contract? What are your, what's the competitive set here? We're no longer voting if DoorDash or Uber eats. You know, and Uber are, you know, got better management teams or better vision or, you know, people love them and their vibes are immaculate. It's just. How many, how many orders did you. What's the margin on the order? It's like just, we'll put it on the scale and then we'll make a decision. Now sometimes Palantir, Tesla, you know, open door strategy. Yeah, MicroStrategy, they can get disconnected from fundamentals and they're no longer being weighed. Very important for investors to understand when people have stopped weighing and they've started voting. It's totally valid to vote on a public company. You could say Alex Garp, the new CEO of Open Door, Keith Raboy getting involved, or Elana Tesla with the vision for Optimus means we should stop weighing this on the past vision or what's the current business model? And we should start voting on Optimus. We should start voting on open door 2.0. We should start voting on Alex Karp's ability to sell into governments and these huge deals are doing. Long story short, both of these companies rippling and deal are incredible businesses and they're from the era of SaaS.

Alex (24:26)

Very much so, yes.

Jason Calacanis (24:27)

And, you know, I think they charge on a per employee basis, but they will move into consumption, AI, disruptive products. I predict these are companies that have good enough management teams that they'll both start moving into the AI space. But I could see both of these companies becoming worth hundreds of billions of dollars and having a chance if they globally become the employer of record, the HR tech of record. Your entire stack. For companies, it's kind of like network effects. It's going to be really cost prohibitive to try to do what Rippling and Deal do and spin up your own. Unless you're, you know, Google or Tesla, in which case you will. But for everybody else below a $10 billion company, it might be just easier to. To use the Deal or Rippling stack. So congratulations. Both companies are great. I know the founder of Rippling had a big falling out with. A big falling out with David Sacks. So he blocks me and I guess I got caught up in that because Saxon are besties. But I really. I really like the founder of Rippling too. I think they're. They're both killers. Yeah. And whatever happened with the spying stuff. Yeah, it's unfortunate. Let the courts work it out.

Alex (25:39)

All right, one last data point on that. The rippling ARR number was 570 million earlier in 2025. So they're both companies that scale adjacent that could go public at will. So we look forward to those in 2029.

Jason Calacanis (25:53)

So you're saying Rippling has half the revenue?

Alex (25:55)

According to reporting that I could find, it's much smaller than Deal. But I don't really want to index too much on that because these are companies that handle a lot of payroll. And so I would be very curious to know the exact breakdown in. Okay, essentially GMV versus Net, if you will.

Jason Calacanis (26:10)

But they both have essentially the same $17 billion valuation. So that's fascinating. I wonder why the one with twice as much revenue doesn't get a double valuation. Or why the one with half as much revenue, if that's true, it's a private company. It's hard to get the information. Somebody can correct us if we're wrong. Yeah.

Alex (26:26)

So that's why I felt like their 14.4x multiple felt a little bit low because rippling is a $500 million valuation difference and roughly half the revenue. But.

Jason Calacanis (26:36)

And it's important. Oh, by the way, we forgot to do this. But, you know, they do hr, but it's more than just payroll. It's not just adp. They'll also do, like IT services. So, you know, if you want to, like, send people their laptop and, you know, make sure you understand what they're doing with their computers and all that stuff. Yeah, all that is kind of in this.

Alex (26:58)

Well, I look forward to you taking that company public and getting them off the off the bench.

Jason Calacanis (27:03)

Jason, both Twist 500 companies. Go to twist500.com and see the top 500 private companies. And for producer Marcus, if you could let us know what percentage of those companies have been on Twist. And then I want to view on twist500.com so twist500.com/, let's call it Twist. Then I want to see just who's been on Twist, who hasn't, and just make a running list of that and a link so people can easily see in the twist500 who's been on the show. Okay, let's keep going through docket.

Alex (27:37)

Yes. So there was a really interesting interview with Roloff Botha over on Uncapped. I think it's Jack Altman's show and you talked about this on Twitter. So I went ahead and watched it. And I think it's actually a fascinating kind of meditation on venture capital as an asset class or not. Jason, mind if I play the clip?

Jason Calacanis (27:55)

Sure.

Alex (27:55)

I'll see you on the other side in two and a half minutes, everybody. Unless Jason says stop, in which case.

Jason Calacanis (28:00)

Two and a half minutes. Okay, here we go.

Alex (28:02)

We can cut it off a little.

Jason Calacanis (28:03)

Bit or maybe I'll say pause if we need to pause on it.

Alex (28:05)

Precisely.

Roelof Botha (28:06)

I don't think venture is an asset class.

Jason Calacanis (28:08)

Why not?

Roelof Botha (28:09)

It doesn't support the numbers. So there was a lot of analysis back in the 1970s and 80s with the capital asset pricing model, and people figured out that there's this asset class that supposedly has uncorrelated returns and a bunch of asset managers deem that they need to invest a certain percentage of their endowment or foundation or pension fund into this thing called venture capital. If you look at the Data, they're basically 20 companies per year on average over the last 20, 30 years, then have ended up being worth in realized exits a billion dollars or more. Just 20 companies. Despite a lot more money plowing into venture capital, we haven't seen a material change in the number of companies that are outcomes that are that large. And I think part of that is that there's a lot more talent than really interesting ideas or interesting companies to be built. And I think we're spreading a lot of that talent thin right now, similar to what happened in 1999, by the way. So when you look at the data, the amount of money going into venture capital right now in America is in the order of $250 billion a year. And numbers, you know, these all estimates, let's just say it's $250 billion a year.

Alex (29:11)

A lot of exits.

Roelof Botha (29:12)

Well, let's just do some very simple arithmetic for a second. $250 billion going in every single year. If you assume that the firms generate 12% IRRs net net of fees and carry, which isn't that great, by the way. I mean, over the last three or four years, the NASDAQ has compounded at 16, 17%, let's just say 12%. Not spectacular. You're basically just average performance. You'd need a 3.7x roughly on 10 years, on a 7 year exit horizon. So I'm being a little bit aggressive. I mean, maybe it won't even be that good. So 3.7x on 250 billion, that approximates to a trillion dollars a year coming out. Coming out, by the way. That means. And that's what the investors own. So let's say that the investors own two thirds of the company. To make the arithmetic simple, that's 1.5 trillion annually. Company exit value.

Jason Calacanis (29:56)

Yes.

Roelof Botha (29:57)

Just think about that for a second. Where's that coming from? Well, Figma's worth. What? It's a lot, but it's 40ish billion.

Jason Calacanis (30:02)

I mean that's, let's say it's worth, you know, 0.03 trillion.

Roelof Botha (30:05)

So you know, if you start thinking in trillions and figma gets you 0.03 trillion, you need 30, 40, 50 figmas every year. Okay, okay, make that arithmetic work.

Jason Calacanis (30:17)

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Alex (32:07)

Goes on to say, oh, please, just go for it.

Jason Calacanis (32:08)

Well, no, I was gonna say he at the Oil and Summit gave exactly the same assessment of it. And a capital asset class as defined by Claude Producer. Claude says a capital asset class, or simply asset class, is a broad category of investments that share similar characteristics. Risk return profiles, that's the key. And behave similarly in the market. Traditional assets include equities, fixed income, cash, cash equivalents, real estate, commodities. And I asked Claude, is VC actually one? And he said yes and no. Great for splitting the difference. I think that's the debate here. So. Got that right. And sometimes it's considered its own distinct asset class due to its characteristic. But more people believe it's like a sub asset class of private equity or alternative invest alternatives. And the distinction matters because it's not super predictable. You have the J curve, as we've talked about this long investment, it's illiquid. You have this very feast or famine power law and active management is a key piece of it. Anyway, Ruloff is right and he makes a funny joke in there. He says it's a return free risk.

Alex (33:32)

Yeah, yeah. Return free risk. Yeah. He says you're better off investing in index funds or holding T bills. Brutal.

Jason Calacanis (33:39)

Well, and so then we get into the gamesmanship here. So we're all talking our books, we're all playing a chessboard. Sequoia is trying to keep the industry small, focused and elite because that's how they made all their big wins. Right? You don't want to Chase. So they're trying to keep their fund size the same so they can have that irr. They're not trying to do what Andreessen is doing, which is making giant funds that, you know, revert to the mean and have lower return profiles, but more money, more capital under management. So here's your tension, Alex, which is going to get have higher irr. It's probably going to be Sequoia because they're trying to keep it more boutique. Who's going to have more assets under management? Probably going to be Andreessen, Horowitz and these people just going big. But when you go big, you got to write big checks. You write big checks now you're in competition, you own less of the company, you got a worse deal. And so the industry, this relates to our opening preamble here, where we were talking about, hey, this could be the biggest tam. It could dwarf tams we've previously seen. So there's a big opportunity happening here. So who's Roelof speaking to? He's speaking to LPs. I think he's doing LP management. In this discussion of, hey, you are an LP in venture capital, but we also have this Sequoia Heritage kind of Sequoia fund. That's the public companies. So, hey, let's make a delineation here. There's venture, there's growth, and then there's us holding public equities. You are better off just owning the Mag 7 or owning the NASDAQ QQQ and just moving on with your life and not worrying. And you can just sleep at night because all of the stuff that comes out of Venture, this huge funnel of venture. Drip, drip drip created max 7. Drip drip drip created the broader NASDAQ index. So if you just buy a tech index, maybe you're better off. So there's too many players. I was talking to somebody who's been venture for 20 years plus and they said it's a different game. Now I'm doing seed investments, put 1 to 3 million in. So now there's so many competitors that we're one of four, five, six people in a hot deal. And the founders are great at pitching and hyping things up and creating a marketplace. In fact, Y Combinator launch techstars. We're good at teaching them how to do that.

Alex (36:10)

It's a key skill.

Jason Calacanis (36:10)

It's a key skill. They create this marketplace and then boom, you have seed funds sometimes coming in at a 30 million, 40 million valuation. The math does not math, Alex. You can't build a 3.4-5x fund. You're going to get ground down to a 1.5 to 2.5x fund. So he said, I think what I'm going to do is on my next fund, I'm just going to be strategically looking at what's breaking out and then just buying secondaries and just waiting for the breakouts and putting money into those. Because he's got a stellar reputation and knows everybody. And I was like, you know what? Yeah, game on the field changing. Smart move. You know what I did? I was like my competition in the accelerator space. I'm going to start a pre accelerator, right? Get in earlier, play a different game, Play a different game. Found a university starting in Saudi Arabia in Riyadh, November 3rd, 4th and 5th Mina launch co. We were supposed to do 25 companies in the first cohort. They asked us because there's so many applications to go to 50. I said, sure. Then I got asked yesterday, hey, or two days ago with my management team, can we go to 60? I said, absolutely not. They said, oh, come on. You know, my team's like, we got this 10 other companies. I said, absolutely not. And then I said, okay, fine, 60 this.

Alex (37:28)

It's a lot of companies, man.

Jason Calacanis (37:29)

It's a lot of companies. But it's also, it's, you know, what we do is so much work that most people aren't built for it. You have to be willing to work 60 hours a week to work in what I'm doing here. Like with the team, if you're going to work 40 or 50 hours a week, you're just, we can't pull it off because there's too many companies. We need to talk to them. So it is what it is.

Alex (37:49)

Jason, help me understand that the tension between there is sharp elbows because there's so much opportunity right now inside of startups and venture to Roloff's point that there are only so many breakout companies. And then also the fact that across every data set that I can see, the amount of money that VCs are raising is in pretty much precipitous decline. So it feels like there's either more money than I think in the market or more opportunity than I think think in the market. But I was seeing things kind of through a pessimistic light in the near term. But then your opening rift was it's the best time ever to be involved in technology. So what am I missing between those two poles that describes reality?

Jason Calacanis (38:28)

So your entry price matters and if the entry price is too high on Average. It's hard to do the portfolio management. One of these firms, let's say a $300 million firm, has 30 names in it, you know, and you wind up investing, you know, $10 million, and you own, on average, you know, 10% of each company. You get diluted down to 5%. Okay, so now I got 30 names, 5%. Let's say one becomes a $10 billion company. It's incredible. You just made $500 million. So your $300 million fund is not even 2X. You could have just put your money. Now you know how hard it is to hit a Decacorn. I mean, people are like, oh, Jcal, spray and pray, blah, blah, blah.

Roelof Botha (39:17)

Hey, man.

Jason Calacanis (39:18)

Number one company, 200 billion. Number two company, 100 billion. Please say more. Y Combinator. You want to dunk on me? Like, has Y Combinator had a company that broke 100 billion or 200 billion in valuation? I don't know. Maybe. I think it was Airbnb, their biggest. So it's really hard, and there's a lot of luck involved in this. And, like, you have to recognize it and realize the power law just rules your entire existence. And in that case, I just described a firm making 30 bets at market rates, their dilution, and then where they wind up, they have to hit. Now, let's say they do hit a $10 billion company and a $5 billion company. So you got 15 billion, and they have 5% of 15 billion. So now they have 750 million in returns. Congratulations, you're 2X. You still didn't beat the index. That's if you hit a $10 billion company and a $5 billion company. So you hit Instacart and you hit Reddit, and like, oh, my God, I'm a hero. Look at that. Like, every 15 companies, I hit a 5 or $10 billion thing. I'm a genius. It's just the math doesn't work. Now, if you had invested and you own 20% like you used to, and then you got diluted down to 10%, now you'd be 10% of 15 billion. You would be, you know, sitting pretty incredibly at 1.5 billion, and your $300 million fund would be 5x, and you'd be a legend. So entry price matters. And too many people chasing the same deals at too high A price means VCs lose, LPs lose. Who wins?

Alex (40:53)

Founders.

Jason Calacanis (40:55)

There you go.

Alex (40:56)

Hard to get out about that. I mean, you know, I mean, here's.

Jason Calacanis (40:59)

The reason why it's a problem. The. The reason It's a problem is we need to keep the business sustainable. And it really is Darwin. You ever like, you know, there's too many fish in the pond and the big fish start eating all the little fish. And then like, you know, all of a sudden the pond gets out of whack and some algae grows, but you know, everybody's eating each other, it's too violent. Then all of a sudden the ecosystem collapses, collapses. And then everybody dies. All of the dead carcasses go to the bottom of the lake and then the little fish and the minnows start growing because there's nobody eating them. And then you have to restart the entire cycle again. It happens in nature sometimes in lakes and bodies of water. And that happens in our industry too. So you'll see a lot of firms that are zombie firms that are walking dead right now. They're not making new investments, they're just managing their funds. And so there'll be a lot of that happening, a lot of turnover in the space. And I can tell you, you know, there's two reasons why these VC firms end. Number one, the principal like me, or let's say Sachs or whatever, they don't care to do secession planning or whatever. Maybe he does. You know, I'm working on it, it's a 10 year plan. But maybe they just say, you know what, enough, yeah, these, these bets I'm working on just shut the firm down and I'll just invest out of my own book. Which is what Chamath did, right? Famously. He's been very public about it. And the other reason is you can't raise the next fund because you return 1.5x or 2x and people are like, I don't know, I don't believe in venture anymore. The end.

Alex (42:33)

There's a great clip from Andreessen investor Brian Kim. He's part of their AI apps investing team, Jason and he talked, just talked to him yesterday.

Jason Calacanis (42:42)

He's coming on the show. Oh, nice guy.

Alex (42:44)

I'm just pulling clips of people you just talked to.

Jason Calacanis (42:46)

Love it.

Alex (42:47)

And this is all about momentum and what he kind of expects to see today and what's impressive. And then I want to get into the, the value of momentum and moats in startups. But first, let's play this 25 second clip from our man.

Jason Calacanis (43:02)

Soon to be friend of the if somebody came to me and came to us a 16C and said, oh, our company grew from zero to 2 million dollar in run rate in three months, are you interested? The answer is, holy, that's great. Let's dig in and understand, et cetera. Nowadays we grew from zero to two. I'm like, how, how, how fast? Like a month. I'm like, nah, it's being a little facetious, but okay.

Alex (43:29)

Yeah, so that's, that's the gist of this. Now this little riff from. From Brian got some notable pushback. Liz Wessel, she's a partner first round just was like, momentum is not a moat. Momentum is not a moat. Because his argument is that it is. I'm just curious about moats momentum and where you stand on this conversation and argument.

Jason Calacanis (43:48)

This is a really good poll because I hadn't seen any of this discussion. So we talked about earlier the size of Andreessen's fund, right? And they're putting a lot of work together. And then first rounds, the antithesis of that. They were designed by my friend Josh Koppelman, Howard Morgan and the team over there to put 250k checks in the first round. That's why they named first round. Pretty brilliant branding from. From the team over there. Long story short, you know, they, they are probably patient capital, and I think Andreessen is probably impatient capital on the spectrum. Just historically, philosophically, they literally name their incubator Speedrun. I think we've now got five or six of our founder, university and accelerated companies have gone to Speedrun. Having good experience, it's seems like a really good program. I gave a shout out to Paris program over the summer. My friend Mar over there and Pejmon and then Sequoia's Arc. I think Stephanie and, and Ruloff are working on that. And then you have 16Z's speedrun. All of these, I would say, including our programs, launch, accelerator, all a better option for founders now than Y Combinator. And that's not a dig at Y Combinator. I just put them in like the fifth slot now because I think you get a better deal economically and you get more bespoke experience and a lot more energy on your startup. It's again, not a dig to Y Combinator, but it's a bit of a factory. And I think that's kind of why people are saying, hey, maybe there's a better way. And I think that's why Y Combinator, frankly, is being a little defensive. We had a couple of these brouhahas coming up. They're kind of circling the wagons and attacking people and, you know, just, you know, it's kind of their vibe is to be a little cantankerous, but they're facing serious competition. And the Reason they're facing serious competition. And you know, I'm, I don't have a horse in this race or we're always filled up. You know, we do 100 investments a year. We have a hard time picking them because 20,000 applications, 100 investments, 1 in 200 chance of US investing. Like, gosh, I really want to invest in like 1 in 50. I think there's like 1 in 50. I would have just as good returns. So I have to build a bigger fund and a bigger team to do that. Putting it all aside, I talked a little bit before about it being a little chippy out there. The opportunity space expands, the velocity expands, competition expands. I was talking about this VC who was like, I just can't compete or I don't want to compete in a zero sum game where everybody loses or a game where everybody loses. That's not an infinite game. There's like a concept of an infinite game. The more you play, the more people who play just, everybody just does better and better. And then there's finite games. Venture in these seed rounds or series A is a very finite game. But before that, and then in the growth stage, it's not a finite game. It becomes an infinite game because there's an infinite number of people who want to transact to shares when they're public, and then there's an infinite number of people who want to start companies. So if you look at it like a barbell, Alex, you have infinite games on either end. When you're public, anybody can buy the stock. Or even for Andrew right now on secondary markets or SpaceX on secondary market stripe, you can just. There seems to be a lot of ability to get in and out of those shares with SPVs. And then in the beginning it's like founders like, please pay attention to me. Can anybody just return my call?

Alex (47:03)

Right?

Jason Calacanis (47:04)

But finite game in that middle section here. So there's a finite game going on here between Liz and Brian. The finite game is who gets that 500k check in, who gets that $1 million seed check in. And so one person is saying, hey, I, I believe X. And the person saying I believe Y. And they're in competition.

Alex (47:25)

But the momentum point, because Brian says right now momentum is the only moat. And Liz says momentum is not a moat. And then we have to also Nikun Kothari from fpv, FPV Ventures. And he says that the only moats out there are retention and a mission worth spending 10 plus years on. Now, in one hand, momentum in revenue terms, Jason, allows you to Raise more capital, hire more better people, do more marketing and maybe win a little bit faster, but it's not a panacea.

Jason Calacanis (47:53)

Yeah, so this is a really good point. Thanks for getting me back on track here. So I was explaining the game on the field. Now we'll get to the actual issue is it is momentum. Emote capital as a weapon. You know, the, I saw it firsthand with Uber. People just kept wanting to own Uber shares. The number of people who tried to buy my Uber shares at 5 billion, 10 billion, 20 billion, 30 billion, 40 billion, right up the stack was crazy. And then Travis's ability to raise capital and then that became a blocker. You invest in Uber, you can't invest in Lyft. You invest in, you know, deal. You're not going to be an investor in rippling or vice versa. So you can use capital as a weapon. And how that works is you can hire people at higher rates, you can spend more on marketing, and your, your customer acquisition costs can be higher because people are like, okay, you're going to be in the J curve, but when you get on the other side, you will be able to raise your prices, cut your costs, etc. And the, the war will end. Which is exactly what happened with ride sharing and other spaces. However, we had Lovable on the founder's smart, right. He's got a lot of competition. So you can make the argument with lovable and I'll have you make this argument. Make the argument for me, Alex of lovable. If they're momentum and cursor, take those two. Just think from first principles here for a second. You've heard both sides of the argument. Where, where would you say, hey, yeah, lovable and cursor have enough momentum that people can stop them and that's worth investing in or sustainable growth and having lock in other ways and building a company based on product market fit and reducing. Churn and having that discipline is a better way to go. Go ahead.

Alex (49:48)

So the question is, would I rather back Cursor and Lovable, which are pursuing essentially a very fast momentum based strategy or perhaps a more measured company in the same space that was taking a slower, less cash intensive approach, more methodical.

Jason Calacanis (50:02)

Yeah. Looking at Churn, you know, not trying to grow too fast, not spending $10 to make five, you know, spending $4 to make five or whatever it happens to be. Not selling hundred dollar bills for 50 bucks.

Alex (50:15)

Yeah. I think three years ago me would have said methodical. I think me now says I would back cursor and lovable compared to the other entrants in that space.

Jason Calacanis (50:24)

Yeah, there you go. So this could also be, as Bill Gurley always explains, hey, what's the game on the field right now? Yeah. So in the NBA in the 90s, defense won championships. Then Dantoni, seven seconds or less, people. Steph Curry shooting more threes. The Knicks coach, the new Knicks coach, Mike Brown, Tibbs, who preceded him and got us to the Eastern Conference finals. And the reward for that was getting fired was one of these defensive stall words. No offensive strat, you know, very little offensive strategy. Mike Brown said we're going to shoot 40 threes a game. So kind of getting to that Celtics level, threes per game, which I'm not crazy about watching, but I do want to win a chip.

Alex (51:07)

Very boring to watch.

Jason Calacanis (51:09)

It can be like a little Chuck fest or whatever.

Alex (51:10)

And I say that as a Warriors fan, to be clear. Like I, I know why we're doing this.

Jason Calacanis (51:15)

Yeah, yeah. But the warriors, you know, they just had such a beautiful style of play that I kind of forgive it because it wasn't as Chucky. And you had Klay Thompson, the Splash brothers and staff who were just. Because they could also drive the lane. Anyway, putting it all aside, you know, Draymond there, the Draymond show, that's I think what you have to think about. So it might be that Brian's right right now and our friend at first round, Liz and Nukunj Kothari are right last year and five years from now. So, you know, both things can be true.

Alex (51:53)

Nick Hoons, by the way, if people aren't familiar with him, was a previous investor at Khosla before spreading off onto his own fund. And Jason, just because I know you love to see charts about Uber, here is one that I just put together for you. And this right here is the break even free cash flow mark. And you can see that it started off their life as a public company way down in the red. And I've since been consistently going on. So this is the end of the J curve when you do begin to rip cash out of the business and oh Lord, isn't that a beautiful chart.

Jason Calacanis (52:21)

Yeah. And it gives you the, it gives you such optionality that I was talking to Dara at the all in Summit and I said, hey listen, you got, you're doing a $20 billion buyback. Why don't you put the $20 billion into buying a car company or you know, I don't know, wave or Neuro or you know, some self driving company buy Volkswagen, you know, you could Buy Volkswagen for, you know, some amount of money. You could buy another brand and then just build your own cars and build the full stack like Elon's doing. And it's like, we can do both. We can chew gum and walk. It's not an or, it's an end. And I was like, ooh, ooh, I love that answer. I love that answer. And, you know, he can decide to change his mind if he thinks the stock's worth, you know, most people think the stock's worth 110 right now or 120. Top analysts think 140, 150. The low analysts think, you know, 85 to 95. Where it sits now, putting it all aside, he can just decide, okay, in my mind, I think it's $120 stock I'm buying under that number. And when it gets above 120, I'm selling. And it's very interesting. Like Warren Buffett had and Charlie Munger had a ratio in which I think I saw this discussion on downtown Josh Brown's compound podcast. They would buy it if it was like a point three or something, some ratio. And it never got there because they publicly said, we're buying our own shares at this number. So I put in a floor where.

Alex (53:53)

Right, because self fulfilling prophecy, that's like a stable coin, like bounding, like people trying to keep it at the.

Jason Calacanis (53:59)

So I mean, literally one of the great things that Dara could say is anything under 115, we're buying the shares.

Alex (54:07)

Yeah.

Jason Calacanis (54:07)

You know, it's gonna go right to 115 or 110.

Alex (54:11)

Does that count as. Can you do that? Is that legal? Isn't there totally around. Okay.

Jason Calacanis (54:15)

All right. Yeah, I mean, listen, it's just we have a share buyback program. Here's where it gets triggered. At the ratio of our earnings, you know, our price earnings ratio. If our price earnings ratio is under 25 forward looking, we're a buyer. When we're above 25 price earning ratio, we're a holder. That's it.

Alex (54:33)

Yeah. By the way, just for people who are curious, Uber's worth nearly four times as much as Volkswagen. In case anyone wanted to know the. The ratio there.

Jason Calacanis (54:41)

Yeah. But I think if you buy Volkswagen, you're buying, you know, a challenged business and it could be distracting. As opposed to having 20 partners putting their cars into the network on a global bas. What else is on the docket?

Alex (54:53)

Next up is Anthropic introducing something called Skills. Now, usually, Jason, when an AI company drops an update or new technology, we have to read academic papers, we have to look at charts. It's all a little bit technical, a little bit jargony and a little bit far away. In this case, what Anthropic has built is deceptively simple. So a skill is essentially a little place where you can put information for your AI model to know. So if you are a company that has a certain style guide, you can put that into a skill. If there's a bit of data you want to have, you can put that into a skill. They're very lightweight, almost like signposts for AI models to be better tuned for you. And what Simon Wilson said about this is that they're very, very token efficient. So if you want to steer your AI model one way or the other, and you don't want to have to consume tons and tons of tokens to do so, this is a great way to do it. Now, we don't cover every single Update from the OpenAI's and the X aisle, but to me this was pretty bullish because it seems like a very simple way to possibly make applied AI in the enterprise quite a lot better. And I've been thinking about the split between Anthropic's growth, which is mostly predicated on its API, which is business sales, and OpenAI's own, which is mostly through ChatGPT, which is much more consumer weighted. And as we look at these two companies, Anthropic is currently at a roughly $7 billion run rate now, expecting to get to about 9 billion by the end of the year. And today OpenAI is about 13. And so it seems that Anthropic is somewhat quietly, through its improvement to its product and making things better for companies, catching up to OpenAI's historic growth. And so I think Skills is a good example of how they're thinking outside of the box to try to find new ways to make this stuff work better. And I expect us all to use this sort of stuff in the next year.

Jason Calacanis (56:43)

Yeah, so this is an interesting feature. It's kind of like memory, if you remember that feature in ChatGPT, I think 3.5, but much more advanced. So you might want to say for every time I do a research report, please give me create a Google sheet with the data in it, share it with Lon and Oliver and do this and email me a copy so I'm reminded and put it in my notion table to do this, whatever it is, and then you don't have to remember to put all that stuff in or I work at a venture capital firm that has the podcast this week in startups. We do three episodes a week. Please make sure you understand all the topics we discussed on the show. Yada, yada, yada, yada, yada. You get the idea. So that's, I think, an interesting way to look at this, which is saving time and saving money because it will cost less tokens. Not that that matters because I feel like all these products, you get more than enough tokens for business uses. So, yeah, well done.

Alex (57:52)

I think it's more of an anthropic API question. I think if you're pulling, you know, if you're pulling Claude from their APIs, then I think the token usage becomes a little bit more important. But I'm just impressed that we're still seeing this kind of gains. But there was a funny hacker news comment. I love to read the hacker news conversation about these things, Jason, and someone said, quote, I'm kind of in stitches over this. Claude's skills are dependent upon developers writing competent documentation and keeping it up to date, which most seemingly can't even do for actual code. They write, nevermind a brute force black box like an LLM. So perhaps we're going to introduce new and novel ways to have tech debt.

Jason Calacanis (58:26)

Yeah, if you think about this product, you know, it would be good if we had like some solid examples from Anthropic of it working, but because we're kind of like coming up with the ideas here. But you might have like you said a style or you said like, I think a style guide for writers. You might also have like a design guide, design language. So, okay, you know, we're launched, we have this design. And this weekend starts with this design language. Here are all those files. We have a corporate policy here, we have a corporate culture. Here are those documents. And then anytime we do something in the world like so you're writing a press release, make sure the style guide, the design guide and the design language and our culture document, analyze it and that we loop in the heads of each of those departments and just let them know what's going on. And if there are any. Really, it's just, you start thinking about it. It's kind of like building an operations team into the product. And then they're always vigilant. It's like having this vigilant group of sentries. Is that the term for guards that like adore centuries?

Alex (59:42)

Yeah, yeah.

Jason Calacanis (59:42)

It's like having these sentries in each part of the kingdom, the castles. And they're saying, hey, yeah, here's the standards for accounting. If you submit Something you, you can take clients, think about expense policy. You can take clients to lunch at up to $50 a person, but you can't take them to dinner unless they're already a customer who spends over a million dollars a year. And then you can take them up to twice a year, up to $500 a person. And then when you know some expense software runs, you, you know, have it run against the expense policy methodically.

Alex (60:19)

So are skills to AI models a bit like to do list for humans.

Jason Calacanis (60:24)

Or policy lists like employee handbooks? I guess it could be both. I guess is the way to look at it could be both. But all of this is to say collaboration inside of LLMs is still lacking. They're still building out the framework of how when we're like, notion has all this kind of dialed in and you know, it's a collaborative by, you know, from the bottom up. But LLMs were not built to be collaborative from the bottom up. And I was, I was talking to the CEO of Grammarly and Coda, which bought Superhuman. And they're going to be on the program, right? Yeah, and he's going to be on the program again to sort of talk about some of their new features and architecture. But what's super interesting about the design of these products. Sorry, I lost my train of thought. But anyway, I was talking to him about this sort of whole concept here. Oh, it was about multiplayer mode. Grammarly was always about making you a better writer. And I kept saying to him, like, and I've been saying this for two or three years, and I pay for Grammarly for everybody on the team. I'm like, it's great that Grammarly follows us around and we have the style guide and you can be professional, you can be concise and everybody's a better writer and less embarrassing stuff. But really what I want to do is be working on documents together. And I want the Grammarly to become the central hub of all knowledge because essentially it's like a keyboard logger. So if Grammarly, you know, is watching you write the document, somebody edit the document, another person putting the charts in the document, me doing the strikethrough or asking questions in it, we would have this knowledge base based on our keystrokes that Grammarly could go from being. Since it's following all of us all over the place, it could give us some grand view of the work happening in real time. Imagine if I could pull up Grammarly pulse. I'm just making something up here. But yeah, it would tell me like, hey, by, by the way people are working hard on the docket. They've got these four stories done and these two are worked on. You might want to consider that there was just breaking news about those six stories. You know, story number four, there's breaking news and the facts wrong. It could be running those we used to call cron jobs or running those agents against what's happening at the keyboard level, which is super creepy in some ways.

Alex (62:41)

Well, it's a work computer. I mean, if you told me to put it on my personal computer, I'd tell you to go F off. But like, I mean, on a work machine. We installed some software on our work machines. I won't get into details about that. And for the first, like two weeks, it was a little freaky.

Jason Calacanis (62:56)

Yeah.

Alex (62:57)

Because I mean, it does feel like I've got a miniature Jason on my shoulder asking me if that two minutes of YouTube during lunch is actually necessary. And the answer is yes. But then I realized that I don't care. It's fine. I don't mind. I'm busy.

Jason Calacanis (63:11)

Yeah, here's where it's become super helpful. And this software, I won't give a shout out to them anyway. They're not sponsors or whatever. And I may switch the software. So I don't want to create any hard feelings here. We just tried it for a year, but you have to lock your computers down. So I told everybody, keep your old computers. If they're under 500 bucks, I just gifted them to the employees. So we're going to get everybody new computers faster, which is good because if you have this kind of tracking software is really designed for finance companies, compliance based businesses, say doctors with hipaa. Don't use your work computer for anything that's not appropriate. What it also does is it obviously is tracking what you're doing. And you can do like crazy granular stuff. Like if you were using call center people, you could track down to the keystroke. We don't do that. It actually bogs the computer down. But you could. What happens ultimately is the people who are using it know how much they're working and what they spend their time in. And then as an organization, it rolls up to my management team. I don't have the time to look at this obviously, but it was a very interesting thing. When we installed it, it was to lock everything down because we have all these global partnerships I've been talking about. We need to lock this down because we also have every company's documents get sent to us. Like, you know, what if somebody's Cap table leaked like that does happen. It's the really bad look. If a venture firm is responsible that finance companies have to have a higher level of duty. Put that aside. Now you understand the organization is spending 42% of their time in Slack, 30% of their time in Notion, 6% of their time in grammar, whatever it is, you know, superhuman what they're spending their time on. You can measure it, you can manage it. What also came out of that was I was being told these three people are the hardest working people in the company. We need to promote them and give them raises. And those three people were not even in the top half. And the people in the top three, I knew one of them and the other two, I didn't know they were the all stars who were really making solid contributions. So it made me rethink compensation and it made me rethink bonuses. So I did something the last two years in our bonus structure. And it's a bonus. It doesn't get paid if I don't want to do it. It's just my money. I'm just. Sometimes I'll just pop a little bonus on people. And I said, you know what? Bonuses are no longer a percentage of your salary. That makes no sense to me. It should be based on, you know, when you work at a company like, oh, you get a 2% bonus, you get a 4% bonus, cost of living increase, all that stuff.

Alex (65:43)

It's kind of like I've lived and died by those numbers.

Jason Calacanis (65:45)

Yeah, I feel like it's so antiquated and antithetical to a high performance culture. So, you know, if you're running a basketball team, if somebody has the hot hand and they win you the game and they play better defense last night you're going to give them more minutes on Friday night, you're not going to give them more minutes next year. Like, what's that about? So I said, okay, every month take the bonus pool, the anticipated bonus pool for the year. And every month I want you to give me the three hardest working by effort, which the software can tell you, just the people who just put in the raw number of hours. And you can kind of check it. There's no gamesmanship of it, to be totally honest, but just amongst the top third of the company, who the top three hardest working people are. And then based on what they did, their impact. So that would recognize somebody who just works an average number of hours or even a below average number of hours. Pop conceivable, but they did something that really moved the needle forward. So you're recognizing the two things that actually make a difference in careers and businesses, effort and effectiveness. And people want to argue, well, I'm getting paid to do a certain output. If I do it in 10 hours, it should be the same if I do it in 100. And it's like that argument you hear when people basically f off at work and they're, you know, working an hour a day, they're like, well, I hit my numbers. That's all that matters. You're not paying me for 40 hours a week. It's like, well, we kind of are. It's in the documents.

Alex (67:12)

Literally. I am literally paying you for 40 hours a week. You want a peace job, that's fine. But you don't get benefits, which is.

Jason Calacanis (67:18)

Why the work from home thing is being unraveled and returned to office. Happens because there were a group of people who felt that way, and then they would then say, well, then I'll have three jobs. Because if you go down that logic, as long as I give them what they wanted as output, that matters, and man has, and then I just do it monthly.

Alex (67:34)

So it's. So everyone can get rewarded in weeks versus quarters. That's. That's good.

Jason Calacanis (67:39)

Literally, we started doing, I think, in August or September, and the people who got picked were like, thank you, this is incredible. And I got a, you know, a couple of grand. Instead of waiting to the end of the year to get five or ten grand or whatever, it is like, pretty dope. And then it sends the message I want for the culture of the company, which is give it your full effort, make sure you're effective and it's not just busy work. And I leave it up to you, yes. To decide if you want to do that. But we don't have to punch a clock. And, like, if you're doing busy work, who gives a shit? You know, Like, I had people who were like, instead of automating stuff, just doing stuff manually. So you have somebody who's incredibly expensive in the company doing customer support emails, and then there's people who make half as much and they're, like, doing this incredible stuff. And I'm like, okay, that's my job as the manager then to figure. Figure that disparity out.

Alex (68:32)

Now, Jason, speaking about doing half as much, I know you're carrying about half the weight that you used to.

Jason Calacanis (68:37)

Oh, yes, that's true. And you know, it's all because of Ro and my embracing GLP life. Look at you, Alex, with the perfect segue. Listen, I'm svelte I just got off the scale today. That's 172.

Alex (68:52)

Nice.

Jason Calacanis (68:53)

The amount of joy when I hit that scale, it's under 175. I feel it's just amazing. And you know what? The food noise went away, which means I'm crisper and better on the pod. Better arguments. I'm more in the zone when you're fat. And I was a fat bastard. Now Ro Co gives me the ability to say whatever I want, within reason. I became a fat bastard. And that's Brooklyn for obese. And it was very depressing for me. I don't get depressed about much when ski season ends, when the next season ends, or when my weight goes up. Those are the three things that make me sad. And what a great couple of years it's been for me because I lost 40 pounds thanks to GLPS. Go to RO CO and if you got insurance, you don't got insurance. They're going to help you. Either way, it's incredibly affordable. I didn't talk about it for the first three years, but this last year I was talking to the CEO of RO at an event together, playing a little cards, talking, chewing the fat. He said, you look great. You know, how'd you do it? And I said, glp. Oh, you know we're doing GLPs. I said, that's great. I have just started speaking about it publicly. I said, hey, I got an idea for you. Serena Williams and Charles Barkley are becoming spokespersons for the GLP movement. I said, that's great. Congratulations. What a great idea. He said, would you be a spokesperson with us? And I said, you know what, I've never done the spokesperson thing except for Athena. Athena wow.com to get yourself a, an assistant and get a great discount on it. It's a crossover here. Sure. And I talked to my wife about it and I said, hey, I think this would be like a noble thing for me to do. Just chit chat about my weight loss and be honest about it. I sleep better, I ski better, but just feel better about myself. So if you are sad, embarrassed about being a fat bastard or you just want to lose the extra 10, I'm not telling you this is going to work or not, but I am telling you it worked for me. I am telling you that Road Co is a place you can explore it with a great team. I trust them. There you go.

Alex (71:06)

Road Co. That is the first time I think someone has ever successfully nested a promo inside of a promo. Ladies and gentlemen, promo ception.

Jason Calacanis (71:15)

Well, you know, it's it's a good thing too because we just had to run payroll on gusto.com Jason. And I'm so focused because of my Athena assistants taking all this, like, stuff off my to do list. And I'm. I got such great sleep last night because I'm not snoring and I don't need a CCAP machine because I'm so fat. All of these things work in a, in a positive cycle going forward.

Alex (71:36)

Yeah. This is the, the Jason stack, if you will. This is how to go. How to go full Jason.

Jason Calacanis (71:41)

Speaking of the stack, I should probably do something for Whoop. I. I'm actually, you know, I stopped wearing my Apple watch because I got into Whoop and then I've been doing my labs like function, health and superpowers. WHOOP now has labs in it. And then there's another place over here, a local place that everybody goes to to get labs. So that's the next thing I'm going to start talking about is labs, blood work, well, self directed healthcare.

Alex (72:03)

The thing that we're going to talk about next on the show, however, is what startups should build in the realm of AI. I have a question for you based on a little bit of data. So first of all, Jason, do you recall we had Ramp on the show just the other day?

Jason Calacanis (72:16)

Yeah.

Alex (72:16)

Mr. Eric Gliman on.

Jason Calacanis (72:17)

He was great.

Alex (72:18)

Oh, one of the best guests.

Jason Calacanis (72:19)

We've got to have him back on for sure.

Alex (72:24)

Okay. There, just found it. Sorry. I've got three screens and I lost a window.

Jason Calacanis (72:27)

Yeah.

Alex (72:28)

So, Jason, I found this really interesting bit of data from the Ramp team. And what this chart shows is different retention levels. Over.

Jason Calacanis (72:36)

Here we go. Content marketing. They get the free ads all the time. This is the last one. Go ahead. You know, this content marketing strategy, it just kills me. It's like Card is trying to do this all the time. They're like, we don't want to buy ads on the program, but we do want you to talk about all this Card a day. I'm just like, enough already. No more carded data. Enough. Okay, well, we'll sneak this one in. I'm going to just do one more of these. All right.

Alex (73:05)

This shows different retention levels for AI products in the enterprise. And this is interesting. Thank you. Back in 2022, retention was roughly 50% by the end of the year. That improved to 63% in 2023 and then 2024 up to about 80% by the end of the year. And then this year it's tracking even better than that. So we could see much less churn in the enterprise. And I think ramp is big enough in the startup realm that they have enough companies using them to make this be reasonably directional data. I'm not trying to say that it's perfect or that it should all go use ramp, but this, to me really spoke to an improvement in the ability for startups building enterprise AI products to actually retain customers long term. This contrasts with some information we've seen from Deutsche bank about how ChatGPT, the leading consumer consumer AI product in the world, has seen its growth rate essentially flatline in Europe. And so I'm curious, from your perspective, talking to founders as you do, if you recommend that they're going to be building in the realm of AI, they should focus more on the consumer side of things or more on the enterprise side of things. Six months ago, I would have said consumer, but now I'm not so sure.

Jason Calacanis (74:20)

There'S going to be a market for both. What you're seeing here is two phenomenons. One, there's less sampling going on and more product market fit happening. Stronger product market fit. So when new products come out, people get promiscuous. When you first got your iPhone, you went into the App Store. When the App Store launched, I think in the second or third version, and people were frisky. They're going, buy this for a dollar, buy that for $2. But then things became subscriptions, things became $60 a year, and you kind of lock into, hey, I really like Financial Times, the Economist, Wall Street Journal, whatever your bag is. I really like com.com, oh, I use Fit Bond, you know, for my fitness stuff, whatever it happens to be. Or I got a subscription to Whoop. I got a subscription to Function Health, I got a subscription to Fitbit. You kind of lock into your peloton, whatever it is. So that's pretty natural over time. And that's what you see in the retention chart. Now, in terms of Europe, that's a weird place. So there could be cultural things going on here, but putting it aside, there's also a natural audience for paid products. And when you hit, it can be very hard to go above that natural audience. And you have to do new things to expand the audience. Netflix, perfect example. Netflix added games. Remember, they put like a strip of games on there. Then they started doing live, and they started doing, like, boxing matches, UFC matches. They're doing all kinds of interesting live stuff. And then yesterday, the ringer did a deal to bring the ringer podcasts, which are really shows that are video they're just shows that are like, the video, like here is like maybe half of broadcast quality or 80% of broadcast, but nobody cares because it's about the content and the freshness of it and the uniqueness of it and the depth of the experience of the hosts. So when you hit your natural lights, you try to do new things, and sometimes they work, sometimes they don't. And so that's what we're doing generally seeing here in these, in this data. And I've just made a new policy. Here's the policy.

Alex (76:22)

New policy.

Jason Calacanis (76:24)

We're going to use all this great data. We're going to use ramps, we're going to use carters, we're going to use Zillow. But going forward, we're going to clip out who the data is from and then we're just going to say a leading SaaS company released some data. Here it is. Because I know what they're all doing. They're all hacking advertising. It's infuriating. It's enough already.

Alex (76:50)

Let me, let me, let me steel, man, that for you in the other direction, one of the hardest things to get in the private markets is information about what's going on. And companies that I think take the time to hire economists, as companies like Ramp and Carta have, and do actual rigorous analysis on a large enough data set, I think can at times put out useful data. And we've, we've talked about Carta before and you'll note that we haven't had Carta data on the show in a while because you were opposed to it. But I do think occasionally there is a chart that shows something so interesting, even with a slightly biased source, because I know they're, they want.

Jason Calacanis (77:25)

All right, I'll cut the difference. Okay, I'll split the difference with you. You're a mensch. I'm a business guy. I get it. You got, you're, you know, I was a journalist. Now, like, I'm more like the publisher. So you're like the, the editor, the writer. I'm like the publisher is like, we need to make money and monotonous. Here's what we're going to do.

Alex (77:48)

Okay.

Jason Calacanis (77:49)

We're going to take the logos off. If it's absolutely great, I might, might say revealed who gave us the data. We're going to hack them back. I'm hacking. It's a hack back.

Alex (78:02)

You do know they're going to text me, not you, right?

Jason Calacanis (78:04)

Absolutely. And they should, they should text Alex at.

Alex (78:07)

Yes.

Jason Calacanis (78:07)

415-555-1212, please. All right, everybody in the show.

Alex (78:15)

Come on, wrap.