Why AI Moats Still Matter (And How They've Changed)

1. 0:00 – 1:12

   Intro

   1. DHDavid Haber0:00

      The thing that is fundamentally different about this product cycle is that the software itself can actually do the work, and therefore the market opportunity for software today is no longer just IT spend, it's largely labor.

   2. ARAlex Rampell0:10

      It's not like all the jobs will go away. I actually think that's not gonna happen at all. There are a lot of things where if I could hire somebody for a dollar to do this task, I would a hundred percent do that. I've never been able to hire somebody for a dollar. Now I can hire software for a dollar.

   3. DHDavid Haber0:25

      While it is important to understand model capabilities and what's happening in the frontier, you still need to figure out how to apply that technology.

   4. ARAlex Rampell0:31

      I think moats matter just as much as they did before. The one change is that in the supply-demand equation, there's conceptually more supply of software on the cup because the barrier to creating this stuff has gone down dramatically.

   5. DHDavid Haber0:43

      I think AI is an incredible tool for differentiation. The idea that a voice agent can speak in fifty languages fully compliantly, twenty-four seven, highly differentiated, you know, certainly versus the human. The AI-ness of that capability, in my opinion, is not a source of defensibility.

   6. ARAlex Rampell0:58

      It is just so consensus. Like cloud was not consensus, mobile was not consensus, and that's why the incumbents kinda screwed up.

2. 1:12 – 2:42

   Do moats still matter?

   1. ETErik Torenberg1:13

      We've spent a lot of time talking about moats and how moats have evolved, and are there still even moats in, in this new era? And so why don't you r-reflect and share some of the conversations we've been having or some of your, your perspectives on this broader, broader moat question. May-maybe David, we'll, we'll start with you.

   2. DHDavid Haber1:28

      Maybe just to jump right into it with, with a hot take, I think moats still matter, and I think a lot of the moats, um-

   3. ETErik Torenberg1:33

      Moats still matter.

   4. DHDavid Haber1:35

      Still matter, exactly. Um, and I think they're largely the same, right? I think, you know, I often think about this between, uh, sort of differentiation and defensibility. I think AI is an incredible tool for differentiation, right? The idea that, you know, a voice agent can speak in fifty languages fully compliantly, twenty-four seven, highly differentiated, you know, certainly versus the human. Um, but the source, the AI-ness of that capability, in my opinion, is not a source of defensibility. It, it's largely differentiation. The defensibility of a software product resides, in my opinion, you know, from owning the end-to-end workflow, you know, from the context in which that it's a- it's applied. You know, becoming the system of record, having a network effect, you know, deeply embedding yourself within your customer. And I think these were the heuristics that were always, you know, things that we would always look for when evaluating software companies. I think the thing that is fundamentally different about this product cycle is that the software itself can actually do the work, right? And therefore, the market opportunity for, for software today is no longer just IT spend, it's, it's largely labor.

   5. ARAlex Rampell2:36

      The challenge often has been that everybody can build something

3. 2:42 – 5:01

   Data network effects only work at mega scale

   1. ARAlex Rampell2:42

      at small scale, and a lot of the... They kind of... I wouldn't call them network effects, but some of the defensibility moats only become, uh, apparent at large, large scale. So like a lot of people talk about like, okay, when you take an example from like the, the long, long time ago, pre- pre-AI era, um, if I am building an anti-fraud company, and I've seen lots of people, right? Am I going to do a better job than a net new anti-fraud company that's seen a few people? And the reason why this would be called a data network effect, although, um, there's another podcast that Martine and I did a long time ago debating whether or not data network effects are real, but it's something that really... It's almost like gravity. Gravity actually, like one atom actually has, exerts gravity on you, but you only really see it at like very, very large scale. Like the Earth, you notice the gravity. The Sun, you, you notice the gravity. Jupiter, you notice the gravity. You don't notice it for like that glass. And it's the same thing for a lot of these data network effects where at very, very small scale, when you have twenty companies that are all saying, "I'm going to stop fraud," like, all right, they're all building the same things. They all have the same algorithms. But when you've seen four billion people and you know, like, these people are bad, now you can sell each incremental customer, each customer of your anti-fraud technology, to, to use this example, because you've seen more customers, and you can get actually better results. But the challenge is that a lot of these, these moats only really are evident at mega, mega, mega scale, and the same argument would apply. It's like, oh, like I've seen four customers. David's seen three. I've seen four. He's seen three. Pick, pick my software. But it's like you've seen four customers. That means there are eight billion customers you haven't seen. There are eight billion customers he hasn't seen. Like, what's the difference? Whereas, um, at mega scale, it's like, all right, I've seen four billion customers. He's seen one billion customers. Well, it's actually kinda easy to see that the results of my product will be better, but that's at scale. Um, and a lot of the question is like on the zero to one phase, it's hard to make the argument that like I have better... Like if it's fraud, I have better fraud underwriting. If it's, you know, AI do the work, like I've done more phone calls to a particular type of customer, and therefore I do a better job. It's hard to make that argument at sub-scale. So, and this is often the challenge, is that it's kinda self-evident that if you become the biggest company in the world, then you have a moat. But how do you get to the

4. 5:01 – 5:48

   The ankle biter problem

   1. ARAlex Rampell5:01

      scale where you actually could show that the... You can't get to that scale if you have nine million ankle biters, um, and you are yourself an ankle biter of just we are trying to get to scale, and nobody can because it's so easy to actually produce software. And that's kind of the, that's the double-edged sword of AI, is that it's very, very easy to produce software. Um, everybody can go do something that is a very obvious idea because it's obvious everybody's gonna go build it. But can you get to the type of scale where you actually could show a moat? And that, that has gotten, you know, arguably harder because you have a larger end count of potential cust- or sorry, uh, comp- uh, potential competitors. Um, but if you get to mega scale, then you could show the moat, and that, that's kinda the zero to one versus one to n.

   2. ETErik Torenberg5:46

      And may, maybe talk about what's

5. 5:48 – 7:14

   Are incumbents more or less defensible?

   1. ETErik Torenberg5:48

      different about defensibility for even the, the bigger players today in the AI era than it was in, let's say, the Web2 era. Are the companies today m-more defensible, less defensible, or how should we think about sort of the strength?

   2. ARAlex Rampell5:58

      I don't know. I, I think the, the less defensible part... I mean, th-this is, this is why a lot of enterprise software has gotten beaten up in the public markets. It's kind of two reasons. Number one is that if you're doing per seat pricingLike, how do you come up with a pricing model that people feel is fair? And a lot of it is just psychology. And for whatever reason, for the last 20 years, it's like per seat per month with like, uh, you know, you've, you've heard my joke, the, the tall grande venti model of like software, uh, charging. It's like somehow that felt fair. And whether that is fair or not, like, I don't know. But like people are like, "Oh yeah, it's like $85 a seat, you know, per month. Yeah, okay, that sounds reasonable." Whereas if you, if you proposed that pricing 40 years ago, you would've been laughed out of town. So this just became the norm. Um, and the reason why, you know, as I was saying, public software companies have been beaten up a little bit is like, uh-oh, maybe you won't sell as many seats. Like, is Adobe gonna sell as many seats if now you don't have to hire as many graphics designers? Or is Zendesk going to sell as many seats if the software just answers all the queries? Like, the answer is no. It doesn't mean that the companies are toast. They might actually quintuple their revenue because now they charge per outcomes as opposed to charging per seats, but that's kind of part one. Part two is, wait a minute, now everybody can vibe code up a Zendesk competitor.

6. 7:14 – 8:48

   Will companies vibe code their own Zendesk?

   1. ARAlex Rampell7:14

      So maybe companies will just start... They'll stop buying software. This one I don't think we've seen at all, um, but I think there is the, like the, these two-sided, um, these two risks. But to answer your question, does defensibility change? Well, if you now are able to code your own software, like why am I paying-- Like, your margin is my opportunity. Well, look at the margin of software companies. Like Salesforce has like an 80% gross margin, like they should have a 1% gross margin or, you know, nobody should use Salesforce anymore. That, that would be the pro case of moats really starting to disintegrate, but I don't think we've seen that happen at all, um, because it turns out people, um... On, on the one hand, two things are actually happening. One is that this is kind of like Clay Christensen theory. It's like the incumbents overshoot the market. So the amount of features in Salesforce or Zendesk or NetSuite, it way exceeds the feature set that you need, that any individual customer needs, because it's meant to encompass, it's like all of these weird edge cases, and you kind of see this if you use Microsoft Word. When was the last time you wrote a book? When? Never, right?

   2. DHDavid Haber8:19

      [laughs]

   3. ARAlex Rampell8:20

      I've never written a book.

   4. DHDavid Haber8:21

      Never.

   5. ARAlex Rampell8:21

      It has all of these things. They probably have-

   6. DHDavid Haber8:22

      Well, wait a minute.

   7. ARAlex Rampell8:22

      ... 50 software engineers. Yeah. Make, make... But, but if you do write a book, guess what? Microsoft Word has all these features just for book authors to like make a table of contents or something. It's like, I don't use that. So they, they keep bundling more stuff in there, so they overshoot the market. And theoretically, it's gonna make it easier for somebody. But, you know, so that... But, but, uh, k- kinda going back to what I, where, where I started with this topic, um, like it turns out that this concept

7. 8:48 – 10:09

   Why you won't vibe code Microsoft

   1. ARAlex Rampell8:48

      of I'm just gonna vibe code Microsoft Word, it's like there are all of these, there, there are these edge cases that you just don't know about. So it, it's actually, you know, why don't you grow your own food or weld your own aluminum or build your own house? It's just, it's kinda easier to use this concept of comparative advantage, um, and just say, "I'm going to buy something off the shelf." So anyway, so I think moats matter just as much as they did before. The, the one change is that in the supply-demand equation, there's conceptually more supply of software on the come, um, because the, the barrier to creating this stuff has gone down dramatically.

   2. DHDavid Haber9:22

      I, I think the flip side to that too is that, um, while, while there will be more software and, and again, the, the kind of marginal cost of producing software is, you know, declining asymptotically towards zero, um, the way that these companies are getting more deeply entrenched within their customers has, has differed. Because, again, the software's doing the work, and therefore, in many cases, it's actually replacing labor. And so if you've transitioned a team out that has now become, you know, your software, like you're now much more dependent on that product to run your business. Um, you know, and again, it, you know, h- is it more difficult to, to replace that software with another piece of software or to rehire that team? I think it's an open question. But again, the software is, is doing more of the work and therefore, I think getting more deeply embedded within their customers.

   3. ARAlex Rampell10:04

      Well, pa- part of it is just like the Goldilocks zone of pricing. So, um,

8. 10:09 – 11:21

   The Goldilocks zone of pricing

   1. ARAlex Rampell10:09

      and I w- I wrote some tweet or whatever it's called, X thread about this a long time ago. I call it the janitorial services problem. Because if I went to you, you're the CEO of a giant company where you write your books-

   2. DHDavid Haber10:18

      [laughs]

   3. ARAlex Rampell10:19

      ... um, in the future. So you have a 300,000-person company. I find you. It's like, "Eric, I can get your toilets 9% cleaner and save you 1% on your toiletry spend or your, your janitorial services spend." Not only do you not care, you don't even care enough. You don't, you won't even like exercise the mental energy to find the person in the company who does care, right? And that means that your janitorial services spend will never change. And the problem is it's hard to get in. The good news is that it's hard to get out. Um, whereas for something that's like 90% of my profits go to like you, the jan-- or to, to... I'm now 90% of your profits as the CEO of GE. They're going to me. Your number one priority is like getting the hell off of me, right, and like doing RFPs left and right. So part of it is also just like how relevant this is, and there are some companies that operate in this Goldilocks zone of irrelevance, like these janitorial services, where even if you have nine million competitors, like y- they're just not gonna go anywhere. Which is why like a lot of the strategy that we talk about internally is greenfield, right? It's like those

9. 11:21 – 13:32

   Greenfield strategy

   1. ARAlex Rampell11:21

      companies are... They're, they're stuck for good. Um, is there an, a high rate of new company creation that will not use the crappy old janitorial services company but will actually res-- Like your pitch of like, "I will get your toilets cleaner, and I will charge you less money," that really resonates, but that's, that's not gonna resonate to the people that are using the old-fashioned stuff.

   2. DHDavid Haber11:43

      What, what are examples of, of, of company or space in the Goldilocks zone, and what, what is an example of a co- co- companies or spaces in the greenfield zone?

   3. ARAlex Rampell11:50

      Well, like payroll companies, right? Like, um, ADP and Paychex. I mean, these are companies that are collectively worth hundreds of billions of dollars, um, very, very profitable. And how does pay-- Like, you could do your own payroll. Actually, it, it's kind of a good metaphor for software in general. Like, why is it that you have to... Like, why can't I just pay you? You're my employee. Why can't I just, like, cut you a check? Well, because I have to withhold taxes. Well, how much tax do I have to withhold? Well, it depends, right? And there is this, like, super complicated lookup table. It's like, well, you live in this county, but you spend this many days in New York, and this, that, and the other thing. Oh, and you, you, you, you owe, like, child support, and the IRS is garnishing your wages. Like, all of these things that are very complicated. So it turns out it's just cheaper to go to ADP, and ADP just charges you, like, I don't know, like fifty bucks a month per person that you might be paying a hundred th- It's a, it's a paltry sum compared to the overall amount of payroll. So nobody really switches their payroll companies. Like, that would be an example of one. On the other side, um, I had a lot of companies, uh, coming out of 2022 where the market really went through a downturn, and they're like, "Wait a minute, I'm spending four... I, I had a thousand employees. Uh, I downsized to two hundred employees. I had a thousand licenses for Salesforce," right? What's a thousand times a hundred dollars a month times twelve? That's one point two million dollars a year. Wow. Like, that's a lot of money because I only have two hundred employees, and I only have six months of cash. Like, I gotta save that. And they didn't do that for their payroll spend. So y-you see it, um, uh, like a lot of companies do wanna rationalize their overall software cost, especially for these things where they recognize in aggregate, like most people aren't actually using the seats. Um, so I'd say like, you know, Salesforce type stuff,

10. 13:32 – 16:22

    Which software gets cut first

    1. ARAlex Rampell13:32

       um, you know, some of the creative tools, like if you... Like A-Adobe is very expensive, and you might just do like a wall-to-wall license saying, "Why not?" But then you look at if you're like, "How do I save five million dollars? Nobody's using this." Well, it's five million dollars. Whereas for things where inextricably the delivery and the payment are linked, right, which is very, very different than per seat, uh, pricing for software, um, like payroll, like obviously I'm not gonna pay for payroll services unless you are employed here. Whereas I might... Like, we have six hundred people that work at our firm. I think we have six hundred licenses from Microsoft Office 365. Like, we probably-- I bet there are a lot of people here who have not opened Microsoft Excel in a year. So why are we paying for that? And that would be the idea of kind of rationalizing software spend. Um, so it, it, it kinda depends, but I think per seat pricing, where it's like it's just easier to pay for the entire thing wall to wall, you know, your, in your entire organization, those are often the first to go versus things that are, again, inextricably linked to the actual usage.

    2. ETErik Torenberg14:34

       Yeah. So you mentioned earlier that we've seen, you know, basically you mentioned, uh, there was this concern that maybe instead of Zendesk, people, you know, or companies will vi- you know, there'll be a vibe coded version of it, but we've seen none of that so, so far. Is your mental model is we'll, we'll see it to the ex- in, in examples where the, the cost is significantly high or in which there's sort of greenfield, uh, in op-opportunities? Or what is sort of your mental model for the types of software that we'll replace?

    3. ARAlex Rampell14:59

       Yeah, I mean, I think the greenfield one is always true, but when you look at greenfield opportunities, you need two things to be true. You need the entrepreneur to be very, very patient and say, "I'm not going to try to sell to everybody who's... If I'm, if I'm starting a net new payroll company, I'm not going to try to sell to GE because I recognize that they are, they, they are hostages to ADP, and that's never gonna change." So one is that patience of entrepreneur, and the other one is you just need a, a high enough rate of new company creation to really make it work, which is why, um, like to pick on one space of electronic health records or electronic medical records, how many new hospital systems are created every day? I mean, it rounds to zero. So if I'm trying to go build a new EHR system to go compete with Epic or Cerner, I can do that. Um, there are a lot of edge cases there, but it's like, and I might have patience as an entrepreneur, but wait a minute, like I need to sell five million dollar deals to big hospital systems. Every single hospital on earth is currently using an EHR system, gonna be really, really hard to make that work. So I think, I think both of those need to be true, like the right type of entrepreneur who's willing to be patient because it, it's, it's often a very lonely game of it's like, "I built this great product. Wait a minute, I don't have any customers yet," and you wanna see high traction because you're seeing in the rest of the market, like some companies are just going like this, and my company's not, and I'm in Silicon Valley, and I need to recruit the best people. It's like they wanna work at the company that has the graph like this, but you need this... Greenfield

11. 16:22 – 17:44

    Steel man: Brand and velocity as moats

    1. ARAlex Rampell16:22

       requires patience.

    2. ETErik Torenberg16:24

       Yeah. The-- So we're s-talking about how moats still matter, and in, in many ways they, they look pretty similar. Let, let's steel man the other side for a second. W-w-where, you know, where are we even having this conversation where some people say, "Hey, you know, brand is the, is, is, is more shipping velocity or b-because this era is different." What are the, what, what's the steel man of the, of the argument?

    3. DHDavid Haber16:45

       Look, I, I think this market is noisier than ever, right? And so I think finding ways to sort of, you know, stand out from the crowd probably matters more today than it has, you know, in the past, I would argue. I think the other thing is that the, the underlying technology is changing so quickly. And so, you know, as a founder, you wanna be living on the frontier and understanding kinda what model capabilities look like because it can dramatically change the, the efficacy or the, the, um, you know, the capability of your underlying product. Um, and so I think, you know, um, you know, one of the things that's changed, I think that's been in- really interesting in this sort of, um, you know, current wave of especially vertical applications that we've seen is, is the type of founder. You know, I think founders today are often younger and more technical than we've seen in, in prior generations. Um, you know, and, and, and so they're less often native to the particular industry, but they're fluent in the tool set, right? And I think that's really important because, you know, to the same point, you, you gotta, you gotta stay on the frontier and understand what's coming. At the same time, you know, I wrote this piece that

12. 17:44 – 19:58

    "Context is King"

    1. DHDavid Haber17:44

       I call Context is King. You know, while it is important to understand, you know, model capabilities and, and what's happening in the frontierYou still need to figure out how to apply that technology. And so while the founders themselves are maybe less native to the particular industry, they're still hiring for context in a very early in a company's life cycle. A good example of this that I, I sit on the board of is a company called Eve. You know, the two founders of Eve were the earliest employees at Rubrik, which is, you know, now a public infrastructure company. Um, you know, they built a legal AI company in the plaintiff law space. Neither of them had any particular background in, in employment law or, or personal injury, but they deeply understood, you know, how to apply, you know, document extraction technology and, and sort of, you know, voice and LLMs more broadly to this very particular work, you know, uh, workflow. And they've hired plaintiff attorneys actually on staff. So anytime a new model is released, you know, they're understanding, you know, from people in industry the impact that it's having on, on drafting, on, you know, their ability to, you know, to reason through a case, you know, or a matter. Um, and so again, it's sort of this tension of like, you know, building the brand, having momentum, you know, understanding what's happening on the frontier, and yet, you know, figuring out ways to apply that technology in the context, you know, of your specific p- customer. Because again, I, I, I deeply believe that that is where a lot of the sources of defensibility reside. You know, I'm-- I'd love to find other examples of businesses is, um, where the technology, like, reinforces their business model. It doesn't compete with it, meaning-

    2. ARAlex Rampell19:14

       Yeah

    3. DHDavid Haber19:14

       ... in lots of areas of legal, um, if you make your employee fifty times more efficient, you're eroding your billable hour. In their business, they operate at a contingency basis, meaning, you know, they only get paid if they make... if they win. So there's no sort of limit to the amount of AI that they want to adopt. Uh, and if you can become five X more efficient, you can take on five X more clients. Um, anyway, these are sort of characteristics that I think, you know, I'd love to find more of, and hopefully that can be kind of a bat signal too.

    4. ARAlex Rampell19:42

       I think the other steel man is if you believe that brand matters, which it almost tautologically does, because what do I buy? I buy the thing that I've heard of, right? So there's an advantage there. And if you believe that for a lot of

13. 19:58 – 21:47

    Feature vs. product vs. company

    1. ARAlex Rampell19:58

       companies and products, somehow having scale is effective, right? So not a network effect, but a scale effect. So if I'm Honey Nut Cheerios and I know that people are gonna buy lots of my Cheerios, I can, I can build a big factory and not, you know, hand crank out each Cheerio. I'm, I'm going to have these compounding advantages just in terms of economies of scale, right? Like Amazon, is that... Does that really have a network effect? No. It's like, it's kinda nice that everything that I buy will show up the next day or in two days, and how can they do that at low cost? Because so many people are buying things. So there are some things that have scale, and those things also benefit from brand. So if you can move the fastest, right? So if you can agglomerate capital and labor, so it's like I raise the most money. It's a very, very generic idea. But somehow, like most other things on planet Earth, if it's the biggest and, like, really, really big kinda gravitational scale, then it's just gonna work better. So can I get there the most quickly? But there are twenty companies that are doing the exact same thing. And at that point, I wouldn't say that momentum is a moat per se, but momentum has the highest chance of getting you to gravitational scale where you do have a moat. And if you don't do that, by contrast, you're just gonna get eaten alive because you can't hand crank out the Cheerios. You, you have to get to the scale where you're able to build a factory, and with the f- you have the biggest factory, you can crank out the most things at the lowest cost. So what is the trajectory? What is the slope of you versus all of your competition? And if you have not a good slope, um, you're, you're just not gonna win that game.

    2. DHDavid Haber21:29

       No.

    3. ARAlex Rampell21:30

       W- [clears throat]

    4. DHDavid Haber21:31

       One of the questions for defensibility in, in Web2 companies was, "Hey, would Google, you know, would those... will they some-someday build this or, or Facebook or name your incumbent?" Um, in, in the AI era, it's will OpenAI or will, will some other, you know, major company... H-how should companies... How should we think

14. 21:47 – 24:04

    Will OpenAI build everything?

    1. DHDavid Haber21:47

       about that, that framework in the AI era? You know, it, I mean, it's funny. I, I feel like eighteen months ago, this, uh, you know, GP- GPT wrapper was on everybody's lips, and I think it was, it was largely used as a pejorative. You know, it was like... And I, I think, you know, to some degree, I think there are some spaces where, like, the model capability and the application capability are... If they're very overlapping, I think you're in a, in a risky spot, you know. Um, but the reality is that there's so many-- I think one of the remarkable things that's happened is there's so many markets that were never particularly interesting to sell software into that are now radically interesting spaces to build companies in. Again, in large part because, you know, the market is now labor, not just IT spend.

    2. ARAlex Rampell22:28

       Yeah.

    3. DHDavid Haber22:28

       Plaintiff law being an example. You know, uh, you know, Alex has... We have a company called Salient in, uh, applying voice agents to auto loan servicing. F-five, six years ago, would we be back to software company selling to, you know, non-bank auto lenders? Probably not. The company's doing incredibly well, again, in large part because, you know, the capability of being able to, you know, uh, speak in fifty languages, you know, fully compliantly, you know, with, with customers in fifty states working twenty-four/seven, um, you know, is just so differentiated, you know, uh, versus the individual. And they're finding that their ability to collect is meaningfully higher, you know, than, than that labor, that the, th-that the kinda cost-benefit trade-off is so dramatic. The company is getting a lot of, you know, revenue from those customers who may not have had, um, you know, millions of dollars of, of IT budget historically and are now very willing to pay for a product like that, you know, given the impact on the business.

    4. ARAlex Rampell23:19

       And, and the way that we used to talk about this a long time ago is, uh, and th-this almost had a pejorative slant to it, but it's like, are you building a feature, a product, or a company? And what's the difference between the three? Well, a feature is like there's an existing product and you tweak that product to make it marginally better.A product is, you know, n-not that. It's like some hopefully system of record or something that keeps track of something. And then, uh, a company is probably the most defensible of those three, where you have a product and, you know, maybe you own a platform. Like the platforms tend to be the most valuable companies. But, you know, a feature is like I've built a Chrome plugin, and that doesn't mean... And there, there, by the way, there are a lot of Chrome plugins, like Honey was a Chrome plugin that got bought by four,

15. 24:04 – 27:05

    Steve Jobs told Drew Houston Dropbox was a feature

    1. ARAlex Rampell24:04

       for, for four billion dollars. Like, I wish I had done that, right? That's, that's a good feature. But that was a feature. You know, a product would be like, "Ooh, I built my own browser." And a company is like, "All right, well, like my own browser company actually makes money." Like you don't actually have a company, even if you have 10 products, if you don't have a sustainable path to have that company be around in 10 or 20 years. Um, and I think kind of another way of thinking about what David just said is that now the features like, you know, the feature was the most pejorative and seemingly small of all of those three, almost obviously. Some of the features can be incredibly profitable because it's like, wait a minute, like this... It feels like a feature, um, because it could get added to Salesforce, right? Or it could get added to one of these other things. But the amount of money that I can charge for my feature is like orders of magnitude more because it's like, "Hey, I'm going to be the front office receptionist for your, you know, orthodontic clinic. Like, that's my job. Like, that's my... So that's, that's, that's the feature." And it sits on top of whatever software you currently use, but the feature I can now charge $20,000 a year for because it is doing the job of laborer. But uh-oh, will the existing product that my feature is riding on top of, will they go build those, those pieces of functionality and/or will another company show up that just says, "Hey, we're gonna sell the greenfield with the new product that kind of has this feature set embedded"? And, you know, feature product company, it still is out there, but, um, I've just never seen a world where the features, if you will, can, can get to revenue scale as quickly. And by the way, you, you kind of often have to start with the feature because a, a customer isn't... Like think of it from the customer's perspective, the customer being the business buyer of software. It's like, "I know. I wanna be locked into a piece of shit, uh, software company for 20 years. That's what I'm looking for as a buyer." No, it's like, "Ooh, I have a problem to solve. My problem is I can't hire a front office receptionist for my orthodontic clinic," or, "I can't call people in Mandarin or Cantonese to go like repay their auto loans. Like, what do I do? Oh, something shows up and it offers that functionality. Boom, I'm a buyer." And then that functionality has to... That, that feature has to backfill product, backfill company as quickly as possible. So that's still true today as it was 10 or 20 or 30 years ago. Um, but the difference again is that the feature... The, the revenue for the feature is just so high, and the demand for it is so high because, again, in many cases, you're just responding to help wanted ads effectively.

    2. DHDavid Haber26:28

       Yeah. And so I think the effect of that is that there, there's been sort of like a Cambrian explosion of interesting markets to go after. You know, I think it's unrealistic to believe that like OpenAI is gonna go build, you know, the, the, the, you know, front office assistant for the, you know, the dental clinic, like as their core, you know, kind of business. They're not gonna do that across every single market. I think the other dynamic is that for many of these companies, part of the product value is actually orchestrating the work across lots of different model companies. And so I think having one, you know, uh, you know, foundation model business, you know, going kind of up the stack, I think limits the actual impact of the actual, of the application p- you know, potentially as well.

    3. ARAlex Rampell27:04

       Well, I think that, you know,

16. 27:05 – 30:06

    Platform risk: Will they compete or tax you?

    1. ARAlex Rampell27:05

       if you kind of think about this versus other platform companies, um, so Facebook was the preeminent platform company of, of Web 2.0, so call it from two... When-whenever they opened up Facebook platform, which I think was like 2007, um, people built their businesses on top of Facebook. Facebook would never do those particular things. Like, so Facebook is never gonna show up and say, "Hey, you know what? We should build a farming game." Like, they were like, "No, we're gonna have a platform that allows companies like Zynga to build these farming games." But what the platform normally does, if they don't actually go compete with the, the underlying products, is they say, "I'm going to tax it, but I'm going to tax it in ways that are kind of at my fancy. So this week it's 10% taxes. That's my promise. Oh, wait, I changed my mind. Now it's gonna be 40% taxes." So that's why it's always dangerous to build on somebody else's platform. So I think the two things to look at are, number one is, will the platform owner compete with what I'm doing? Um, and that's also another Goldilocks zone question, right? Because why is it... I, I published this graph of VisiCalc versus Lotus 1-2-3 versus Excel. So VisiCalc invented the spreadsheet in 1979, had 100% of the market because they were the only player in town. Lotus built a better version of that. Uh, Lotus got to, like, I think 70% market share by 1985, which was when Microsoft released Excel for, uh, a Mac. Um, and then by 2000, uh, Microsoft had 96% market share. And why is it? Because they owned Windows. Like, the, the platform owner normally wins. So s- but that's because it was just such a hu- Like, why do I buy a computer in 1997? Because I wanna use a spreadsheet. Like, it was just so intrinsically linked. Like, that was one of the main use cases for computers in business use, right? It's like using spreadsheets. So that was like violator of Goldilocks zone, whereas other things where it's like all you have to worry about from the platform owner is that they're going to tax you, but they might tax you in very, very bizarre ways. But, uh, part of what David was saying in terms of, like, there are multiple model companies, which is great. Like, the problem with Windows was that it was like 95% of the market. Like 95% of your customers used Windows, so if I'm gonna go build a competing spreadsheet, I'm just toast because the platform owner is just gonna drown me. Um, now there are five model companies or, you know, more, like when you include all the Chinese models and whatnot, open source. Like, I don't have to worry about that, but I do have to worry about them saying, "Wow, this is so relevant." Like, why is it that OpenAI got a public company CEO to quit her job and just to become the CEO of a- of applications at OpenAI? Maybe because they have a huge application opportunity. But this is the nice thing, is that a lot of these things are so obscure, but they're still big.But I don't think OpenAI is gonna go do them because it's like, are they going to do like dental care management? Like, they, they could, but if they've done that, then I would be short OpenAI because it's like they've run out of good stuff to do.

    2. ETErik Torenberg29:57

       Mm-hmm.

    3. ARAlex Rampell29:57

       Um, that's something that they should do in 2029. And then this is... I think I told you this, this story before. This is I, I, I-- Th-this changed my outlook on life when

17. 30:06 – 33:38

    The "gold bricks" conversation with Dan Rose

    1. ARAlex Rampell30:06

       I pitched this guy Dan Rose at Facebook, who was running business development there. I'm like, "This is a huge opportunity. You should use us for payments. We're gonna do this. We can make so much money for Facebook." And he was so patient and nice, and I, I love this guy. I'm on a board with him to this day. He was like, "Alex, that's such a great idea." I was like, "All right. I got the deal. Yes, he said it's a great idea." "But we're not gonna do it because you're pitching me a go-- like, we have gold bricks all around us." Like, and he was right. I mean, like Facebook in 2010, I mean, how much mon- Facebook has grown their revenue pro-- They, they have more profit every quarter today than they had revenue per year in 2010. It's just such an incredible company. And he's like, "You're pitching me a gold brick that's like 100 feet away, and it's real. Like, I love that gold brick, but we have like hundreds of gold bricks where I just have to like stoop down at my feet and pick them up, so I'm just not gonna do that one right there." And that's how these big companies think. Um, but the nice thing is that these are gold brick... Th-these gold bricks are bigger than they've ever been because you have software that can do the job of labor.

    2. ETErik Torenberg31:02

       Yeah. Um, which is o-on that note, if, if you were, uh, r-running OpenAI and you were thinking about whi-which gold bricks or how to even... what mental model to think about, sort of what, what are the things that you should be doing first versus things that, hey, maybe let, let other people do, h-how would you be thinking about that question?

    3. ARAlex Rampell31:16

       I mean, I think a lot of it is where... Well, it's, it's two things. Number one is we want to be the backend for everybody. Like, the platform... I, I think it's two things. Number one is can we be the platform for pretty much everybody who's building anything? So we're not going to go in these, into these obscure spaces like, you know, orthodontic care, uh, at least not until, you know, 2045. So let's make sure that every single developer is using us. Um, and this is part of why Microsoft crushed Apple in the 1980s, because Apple made it really hard to develop software. Um, and a-and what's actually kinda interesting is that both Apple and Microsoft, um, ha- Like, Microsoft started off as a compiler company. Like, their very, very first products, they were not Microsoft Office. It was not DOS. They built a Basic interpreter, um, for the programming language Basic, and they had a big business. Their, their biggest competitor was Borland, um, which only made compilers, and like the early rallying cry, if you talk to any early Microsoft employee, was "Beat Philippe." Philippe Kahn was the CEO of Borland. So Microsoft was focused on that, um, made a lot of money on that, and Apple was like, "We should make money on that too." And they had a product, it was called MPW, uh, Macintosh Programmer's Workshop. I remember I, I used to use it in the 1980s. And, uh, it was like $2,000, I think, in 1980s money to buy this, you know, IDE or, you know, programming, uh, thing, and, uh, it's like, how do you afford that? So like... But it was like, "We have to make money on that. Microsoft's making money on this." And then lo and behold, there were like 10,000 times more, you know, uh, DOS and Windows software products than there were Macintosh software products. And of course, Apple corrected that mistake when the iPhone came out, when... They d- now, like Xcode, which is the way that you build products for, um, for Mac products or Macintosh and, and iPhone, iOS, it's free. So like, they, they kinda corrected that mistake. Um, but I'd say two things to answer your question. Number one is can we be the biggest consumer brand in the world? So ChatGPT has 800 million weekly active users, like get that to 5 billion, right? Like, 'cause even if Gem- Gemini 3 came out today, it might be five times better, but are people that are using ChatGPT just as consumers, are they going to switch? Like, m-maybe, but it's unlikely just because they kinda make that their, their default, and then be the backend for everybody who's building anything, and that way it's like kinda all the gold bricks kinda come to you.

    4. ETErik Torenberg33:31

       Yeah.

    5. DHDavid Haber33:32

       I think the other, uh, thing that we should anticipate, we're already b-beginning to see from some of these big model companies are like

18. 33:38 – 35:26

    What OpenAI should prioritize

    1. DHDavid Haber33:38

       what are the big horizontal applications that they can li-likely sell to every, you know, large enterprise? And I think, you know, you saw today with, you know, Google's, uh, Antigravity launch, like the IDE is gonna be one of those things. I think like that, you know, if there's like product market fit for, for LMs, like, you know, c-coding is definitely, you know, o-one of the top categories. Um, so I think that, you know, thinking about what are the big horizontal kind of applications in the enterprise. I think there's also, to some degree, and, you know, we'll s- I think this has been earlier to sort of play out, it's sort of the Palantir opportunity. I think we're still very early in, in sort of the proliferation of this technology into large enterprise. Um, at the same time, you know, unlike prior product cycles, you know, you know, like the cloud, if I'm the CEO of a large public company and I'm, and I'm asking myself, "Do I need to be in the cloud?" It was sort of an esoteric idea. You know, today I can plug a, you know, prompt into any one of these models and intuitively understand the impact that it could have on my business, right? The, the efficiency gains in my customer support organization, in my engineering organization, in all of my back office functions. At the same time, many of them don't know where to start. And so I think you will see sort of this consultative, sort of forward deployed, Palantir-esque sort of sale into very large enterprise from some of these, you know, big model companies. Again, I think we're early in that, but you've, you've heard inklings of this with, um, you know, with Anthropic talking about wanting to build into financial services and, and other markets. So, you know, I agree. I think the biggest opportunities are the one that Alex is describing, but I think you will see them selectively, you know, try to build kind of applications that cut, cut across every one of those, and then they'll probably choose, you know, a few sort of like lighthouse customers to build, you know, l-largely bespoke kind of custom integrations into these, you know, bigger enterprises, but where the ACBs-

    2. ETErik Torenberg35:21

       Yeah

    3. DHDavid Haber35:21

       ... you know, just really make sense.

    4. ETErik Torenberg35:23

       In, in, in Web2, there was a lot

19. 35:26 – 39:16

    Will AI consolidate to winner-take-most?

    1. ETErik Torenberg35:26

       of w-winner take most. Um, you were talking about one of the benefits in AI is that there, there's multiple winners. To, to what extent is, is consolidation in-in-inevitable? Or, or how do you think sort of this, this pl-plays out?

    2. ARAlex Rampell35:38

       Well, I, I think if you have 20 companies that are all doing the same thing, um, what has historically happenedIs that, uh, it's a bad market if there are 20 companies doing it, but then, I don't know, the bottom 15 just go bankrupt. Um, and then maybe there's some consolidation where number one buys number two, number two buys number three, and assuming that we have a functional FTC and whatnot, it's like all of this is approved because it's not like you're taking... This is like orthodontic clinic answering software or something. Um, so and then what was a bad market becomes a good market. Um, and this kind of goes back to like why momentum is important because if you have 20 companies that are all at the exact same scale, um, then it's actually great for the customer, which is like the, the prices go to zero, um, or they converge on the price of electricity. Whereas if you... This is not saying you want to go build a monopoly in orthodontic answering software or something, but rather you can charge more if you get to a certain scale because whatever the, the, the quality of the product that you're delivering at the end of the day is just higher. Um, and you have to get to the critical scale to get there, and sometimes you just need these markets to, to work themselves out. I mean, like when I was running my company, TrialPay, we had, I don't know, 20 competitors, and it was tough because it's like, you know, um, everybody would be pricing their product at a loss. You know, this, this loss leader only works if you end up leading with... Like, you have to make money at the end, and nobody really had a plan for that because the venture capital dollars were really subsidizing everything, and that does not get a good market. What does become a good market at the end, and sometimes this is what, you know, Vista, the private equity firm, would do, is like, "We're going to buy one as our anchor. We're gonna go lowball, um, and put the other five out of their misery," and now we end up with actually, actually a pretty good product at the end or a pretty good business at the end, pretty good company at the end. So I think that will probably play out the same way here because you just can't have a market where you have everybody loss leading, um, and nobody's big enough to get any kind of scale effects. Um, is there gonna be a, a world where the, the 19th player survives? I mean, Jack Welch, uh, would always say, "You have to be number one or number two, and there's no value to being number three through 100." I don't think that's changed.

    3. ETErik Torenberg37:52

       Right.

    4. ARAlex Rampell37:52

       Right?

    5. ETErik Torenberg37:53

       Even in the model provider example? Uh, uh, and I'm also curious if prices go down materially.

    6. ARAlex Rampell37:57

       Yeah, I, I, I don't, I don't see how... Like there actually are... I mean, people know xAI, Anthropic, OpenAI, Gemini, like they, they know, or Quinn. Um, they, they know the big ones, but there are actually, there's a long tail of things that people haven't heard of, um, where it's like they've raised lots of money. It's just like not... It, it's, and it works fine, but how can you sur- Like the model company is the most cutthroat because, like, unless you're state... If you're state-of-the-art minus, minus, minus and you're trying to earn a living, it's just like that, that's just not gonna work. So that game is super cutthroat.

    7. DHDavid Haber38:31

       I think, I think the one area where that, um, may have diverged, and Martine talks about this a lot, is like, um, you know, when, when markets are growing so quickly, you, you end up having specialization. And so I think in other kind of modalities, you know, in, in some of the creative tools or, you know, people have specialized to like serve, you know, the upmarket. You know, like I'm, I'm producing, you know, movies. Okay, I'm, I wanna create sort of like social, you know, quality content. Like these are different, you know, markets that, that, that the models can kinda specialize in. Time will tell, you know, how sort of, uh, you know, defensible those become over time. But, um, maybe that's the optimistic take that like, you know, early on everything looks, you know, overlapping and competitive, but we're still so... You know, the market is growing that everything can kind of expand and people can kind of specialize over time.

    8. ETErik Torenberg39:15

       Earlier when you, we were talking about

20. 39:16 – 43:48

    Why Dropbox survived anyway

    1. ETErik Torenberg39:16

       the feature versus product, uh, it, it... Didn't Steve Jobs once tell Drew Houston that Dropbox was, was just a feature? [chuckles]

    2. ARAlex Rampell39:22

       Yeah, I mean, that, that's why it's, it's always been this pejorative thing, but that's, that's kind of the point that I was getting to is that nobody wants to like, "Oh, I need this company." No, it's like, "I need this feature." Um, every now and then you see a product that is not a feature because it's just like so far out of left field. Like nobody was anticipating ChatGPT dominating their daily workflow in 2022, in October. Um, but then once it came out, it was this like, "Holy crap, I... Th- this is incredible." And that's not a feature. You could argue it's a feature on top of your iPhone, but no, the iPhone is the delivery mechanism. That's a, that's a product. Um, and they've, they've obviously turned that into a company. Whereas other things, it kind of is like, you know, why is there antivirus software? That almost doesn't make any sense. Like shouldn't the operating system stop you from getting viruses? Like why do you need a third-party tool to do synchronization between devices? But it turns out, like the reason why Dropbox has survived and thrived since Steve Jobs made that comment is like it's really hard to do well. Um, and there's a lot of other things, like once you've built that feature, you can backfill with all sorts of other product, which is what Dropbox has done a pretty good job of. But it, it is hard because this is the, the danger of building on somebody else's platform is that, you know, I'm gonna build this thing that they should have had, right, if they had the foresight. Um, and if it doesn't operate in the Goldilocks zone, right, it's like, wow, this is so... This will like triple Apple's profits. Let's just say that Dropbox would have tripled Apple's profits. Would they have dropped everyth- Would, would they have focused on building that versus the iPad or something, whatever like Steve's last, uh, gizmo was? Like sure. But if it's kind of in this like Goldilocks zone of irrelevance, like janitorial services, it's like, yeah, they should do that. But, you know, platform owners get lazy. Um, this is why like, you know, half the things on my iPhone don't really work if they're built by Apple. Um, try... Like any, any parent that's listening to this, if they've tried Screen Time, it's just like an embarrassment upon humanity. And because they don't have to go sell as a... It's like they don't have to compete on feature. They compete on the fact... They don't even compete. They just like, they're the platform. They roll it out, it's gonna be bad, and that does create an opportunity for somebody to come up with a feature and actually out-compete the, um, the, the platform. But like you have to be careful because it's like obviously the platform owner is gonna go compete with you. And that's why often what I find very compelling about entrepreneurs when they know this, like they've studied how is it that from every single platform shift from like, you know, we were talking about AC versus DC current, like there, there have always been these battles for like who's gonna be the underlying, you know, layer. Um-The best entrepreneurs have studied this and they have a plan. They're like, "I know I have a feature." Like Drew knew this. He's like, "I know that like there's this stupid comment on Hacker News." It's like, "Oh, this is just like our sync with this, that, and the other thing." It's like, yeah, of course Drew knows that, but he built this into a $10 billion company because like he had a plan. And the best entrepreneurs, they often like, okay, I know it's not this naivete of like, "Oh, I'm gonna build this." There's no way that they're gonna build it because they're too dumb and stupid. It's like, no, they're not. Like these companies, if they get their act together, they will marshal a lot of resources to go compete with you. It might take them five years, but they will 100% do it. You have to backfill your feature with a product, and you have to have a moat for that product as opposed to like, oh yeah, like the big company will never figure this out. It's like that's not true.

    3. DHDavid Haber42:40

       I, I think what's u- also unique, I, I wrote this piece a, a while ago called The Messy Inbox Problem, and it was sort of a wedge strategy that we've been observing across lots of d- different industries, and it's just this idea that, um, you hook into a bunch of your different unstructured data sources, could be email, could be fax, could be phone. Um, you know, Tenor, as an example, has trained a model to be able to extract all the relevant patient information from those data sources to plug it downstream into some system of record, in their case, an EHR. But this exists in a CRM, an ERP, um, what have you, and I think that, that wedge for that feature is interesting in large part because it lives up funnel from software, right? You're replacing the h- kinda human level judgment of the individual, like often that admin... You know, the secretary sort of like collecting the physical facts and then plugging it into the HR. And so now a bunch of AI companies can kind of, you know, wedge in and then eat away at all the downstream workflows that might have been, uh, their point solution software companies. And so, you know, Tenor is no longer just doing, you know, the messy inbox. They're now doing scheduling and prior, you know, uh, prior auth and eligibility and benefits, um, and they've used that wedge to try to become, you know, kind of the end-to-end platform. Eventually,

21. 43:48 – 44:06

    The messy inbox wedge strategy

    1. DHDavid Haber43:48

       maybe they become the system of record. Um, but again, because you can kind of replace the human labor now with software, um, I think it's creating opportunities for these, you know, features to actually become products and, you know, in, in their case, I think become, you know, whole companies.

    2. ARAlex Rampell44:02

       Well, I think, I think this is the thing that in my mind is very dramatically different

22. 44:06 – 48:18

    Why AI is different: It's consensus

    1. ARAlex Rampell44:06

       than every other platform shift is that the, the, it is just so consensus. Like cloud was not consensus. Mobile was not consensus, and that's why the incumbents kind of screwed up, where it's like... And then sometimes it was just like completely, um, I'll, I'll use the, the, the Silicon Valley term orthogonal to their, to their business model because it's like I sell $5 million a year products, and wait a minute, I'm gonna charge $100,000 a month. Like that's just hard. Like how do I pay my salespeople? How do I make my quarterly numbers? So that's why like, you know, Workday beat PeopleSoft. Um, or that's why, you know, Salesforce beat Siebel. Um, so all of these things played out, but behind it was this concept of it's like that new thing, that iPhone is stupid. Um, like there's no version of the s- the famous Steve Ballmer clip of like him saying this, "Nobody's gonna buy an $800 phone with no keyboard." Um, there's no version of that for AI. It's like how do you find a big CEO or even a small CEO who's like, "Nobody will use that tool that makes you 100 times more productive." It's of, of, of course, and this is why it's, it's kind of a bonanza for most of the incumbents as well because anybody who has a system of record will add a button or a feature, to use our parlance, that will make them more money. Um, so like they're just kinda gold bricks everywhere, and the challenge though is that there isn't this, this kind of white space to occupy in the same way that there was for cloud or for mobile or for a lot of the Web 2.0 things where it's like you just... Like the incumbents screwed up. They weren't paying attention. They scoff at this new technology. Like nobody's scoffing at this new technology. Like everybody's just trying to embrace it. But, you know, the opportunity often exists where a, a lot of the areas that just seem too small that don't have an incumbent at all, like those actually might turn out to be like, you know, trillions of dollars of value, and that's kinda what makes it much more exciting than like last gen where it's like, oh, I'm just gonna copy everything that was on-prem and make it, you know, recurring billing cloud, and I'm gonna do that at a time when like the big guys say that's stupid and I don't get it.

    2. DHDavid Haber46:10

       So some argue that, you know, mobile was, was ultimately sustaining in that although there were, you know, n- net new companies and use cases that were, you know, $100 billion like Uber and Airbnb e- et cetera, that, uh, you know, the incumbents, you know, some of them became trillion dollar companies, you know, h- hogtied by mobile. When we look at the, you know, business impact of, of the AI era, um, what's your mental model for thinking about sort of the incumbent versus startup or, or kinda net new company in terms of va- you know, value capture?

    3. ARAlex Rampell46:36

       I, I, I think a lot of it is the same. Like u- unless you really screw up the, the pricing model or like, you know, you're all per seat pricing, it's very, very hard to just get the market to adopt something that is just violently different and you're operating in the public eye and your technology team is bad. There, there are a lot of ands that need to happen. I have a hard time believing that incumbents will really suffer. Um, I mean, there probably are some things. Like, you know, ta- take like one example of... And this kinda goes back to distribution versus technology. Like all of these business process outsourcing companies, these BPOs, they're the largest employers on the planet, so like Tata, Wipro, Infosys. So if I'm JP Morgan and I say, "I need a call center, and this call center needs to have access to like customer records, and it needs to be safe, and everybody needs to be trained. Like, and I need to have like 100,000 people that can answer the phone," you know who can do that for you? Infosys.Right? Or Tata. Um, Tata has already done the integration with JP Morgan in this case. They might just add AI, and now they don't need 100,000 people, and they maintain that JP Morgan contract, and they operate in the, the area of the Goldilocks zone, where it's like they're gonna make like 100 times more money. That, that's one case. That's the bull case for Tata. The bear case is like JP Morgan's like, "Wait a minute, like we should partner with a startup to do this," or, "We should do this ourselves." And now, like Tata loses that relationship altogether. And it could go either direction. Like, you know, I, I think a lot of these things are really up for grabs. But I, I think the, the default is that the incumbents probably will do well, but you can pick a lot of these cases. I mean, this is why you see the public markets kinda don't know what to do.

    4. ETErik Torenberg48:13

       Mm-hmm.

    5. ARAlex Rampell48:13

       Where there is a case that is very, very bad for a lot of software companies,

23. 48:18 – 49:30

    Jobs won't disappear—$1 tasks will explode

    1. ARAlex Rampell48:18

       but there is a- an alternative case, which is like if you operate in the right Goldilocks zone, um, and you're, you know, you, you have the right momentum to actually build these things and embrace these new technologies, like you'll maintain all of your customer relationships, um, and you're just gonna have a more profitable business. And it's not that you're gonna do this... Like the, the most compelling thing I think about AI that almost everybody gets wrong is like, "Oh, it's gonna destroy all the jobs." Like our, our beloved representative, uh, from Silicon Valley is like trying to like eliminate AI. It's just so crazy that our elected representative wants to turn us back to farmers of, uh, of tangerines and whatnot in, in Silicon Valley. But, um, [chuckles] which, which again, I, I think is crazy. But, uh, it's not like all the jobs will go away. I actually think that's not gonna happen at all. What's going to happen is there are a lot of things where it's like if I could hire somebody for a dollar to do this task, I would 100% do that. I cannot hire somebody for a dollar. I've never been able to hire somebody for a dollar. Now I can hire software for a dollar. So a lot of these tasks, like, you know, look at how many people took taxis post-Uber, right? And it's like, did you hear people say every-- Like you, you probably took an Uber to get here today, right? Would you have taken a taxi 20 years ago? Like no way,

24. 49:30 – 50:35

    The Uber/taxi lesson for AI

    1. ARAlex Rampell49:30

       right? Because it's like where would you find the taxi? How would you arrange the ta- It's just like way too complicated. Whereas once you make it very, very abundant and less expensive, like everybody's gonna use this. And I think that's the, that's what Ro Khanna and, and his ilk are missing, which is it's not like, "Oh, I'm gonna go and say I'm going to like eliminate all the jobs." Like think of it in that JP Morgan example that I just mentioned. It's like wouldn't it be cool if every single customer of JPMorgan Chase could have their own personal friend that they could talk to every single day there that would help them with every single element of their financial life? Or it's like, "I'm stuck downloading the app. I can't figure out how to get it set up." "Oh, talk to somebody in real time that will help you about that." Why don't they do that? It's just like the cost is known, it's high, and then the value is probably low. And as soon as you can bring the cost down to zero, now you're gonna start hiring AI in all of these different areas that you just would never bother hiring a human for because it's just like you can't train the human, you can't find the human, and the human's too expensive.

    2. ETErik Torenberg50:26

       I think that's a good place to wrap. Guys, thanks for coming to the podcast. Moats still matter.

    3. SPSpeaker50:30

       Good to have you.

    4. ARAlex Rampell50:30

       Yeah. [upbeat music]

Episode duration: 50:45