00:22:01 · Luca Ferrari, Anish Acharya
But again, any project that could be huge would probably require a decade plus to get there and rule number one to win and you know be be that huge success is not having failed in the meantime and so I think often it's better to take two three years longer but take no or very limited risk than than speeding up and then crashing and burning. [00:22:24] S1: I mean, think these are great rules of thumb, know, perhaps encouraging a bit more ambition in product and the size of the swings and a bit more caution in credit and debt. We've seen many situations where founders tend to underestimate the probability of things going sideways with debt? [00:22:40] S2: Particularly if you rely on one segment, market, one product, one revenue stream because boundary conditions can change quite abruptly. You're still not fully insulated if you have a diversified portfolio because diversification is a complex concept and it depends on whether you're diversified or not. It depends on against what particular phenomenon and you could you know your... But your different... Supposedly diversified assets could be highly correlated when it comes to the response to that particular phenomenon. But so again, with care. It's tricky, but if done properly, it's a massive boon. I mean, there's plenty of companies who have used that consistently in history, you know, Broadcom, TransDigm and have done incredibly well for many decades. And they wouldn't have done nearly as well had they not used that. So...
00:22:40 · Luca Ferrari, Anish Acharya
[00:22:40] S2: Particularly if you rely on one segment, market, one product, one revenue stream because boundary conditions can change quite abruptly. You're still not fully insulated if you have a diversified portfolio because diversification is a complex concept and it depends on whether you're diversified or not. It depends on against what particular phenomenon and you could you know your... But your different... Supposedly diversified assets could be highly correlated when it comes to the response to that particular phenomenon. But so again, with care. It's tricky, but if done properly, it's a massive boon. I mean, there's plenty of companies who have used that consistently in history, you know, Broadcom, TransDigm and have done incredibly well for many decades. And they wouldn't have done nearly as well had they not used that. So... [00:23:32] S1: Yeah. Yeah. Interesting. My theory is that everything is correlated, but that's a subject for a different talk. [00:23:38] S2: Well, I tend to agree. I mean... But not necessarily to the to the same extent. Yeah. Exactly. That's right.
00:23:38 · Luca Ferrari, Anish Acharya
[00:23:38] S2: Well, I tend to agree. I mean... But not necessarily to the to the same extent. Yeah. Exactly. That's right. [00:23:43] S1: That's right. Okay. Let's quickly talk about durability and moats as a favorite topic in Silicon Valley right now. You know, a year ago was SaaSpocalypse around Opus four five four six. All those names traded down 40% in backup, so I don't know what folks accomplished with the SaaSpocalypse. It seems like it was a little overblown, but it has brought about this discussion of where durability lies in a world where you can trivially create software with AI. How do you think about it?
00:24:08 · Luca Ferrari
[00:24:08] S2: I never fully... So I think the valuations for SaaS historically were for the most part absurdly high, but not because AI was not a risk, because they didn't make any sense from at least from the perspective of someone going back to what we were talking about earlier, someone who values assets based on reasonable expectations of free cash flows in the long run. In most cases, I think you could only justify those valuations based on the speculation that you'd be able to sell them to someone for, say, the same multiple down the line, but in the meantime you've grown 50% or something. Right? Because they were based often on assuming that the current 12% organic growth would last for fifteen years. And it's like, sure, but you know, the world changes so quickly, that's insane. Right? Organic growth almost never goes up, by the way. I mean, very rarely. Again, going back to Mark's. It typically goes down and so those assumptions made no sense. Now what I think AI gave people an excuse to go back to their models and say maybe I don't fully believe in those assumptions, let me be more cautious, and the reset valuations were, I think broadly speaking, reasonable. I mean you could always argue plus minus 20%, but they were more in the range of reasonable in my view. Now I never really bought too much into the risk of now writing software is cheaper, therefore these companies are screwed. I do buy in the idea of it's gonna be much cheaper, therefore they'll suffer on the margin, but now they're screwed. The reason is I think writing software has been reasonably cheap for a long time and most of the companies that matter, you know, companies worth at least, I don't know, a billion dollars, the cost of replicating their product technically Yes. Was negligible relative to the value of being a, you know, a winner or significant gaining significant market share in that market even five or ten years ago. Like, yeah, maybe you needed 20 good engineers, but it's not like replicating Salesforce is not rocket science, you know. We own WeTransfer. If you had 10, you know, five great new graduates who wanna spend three months in a garage, they could probably build a product that's 80% as good, you know, and in fact, guess what? A 100 teams have done that. There's plenty of clones, right?
00:26:22 · Luca Ferrari
So mostly software or digital products do not succeed because it's very expensive to replicate them. They're now SpaceX. They mostly succeed because of other factors. First mover advantage, sometimes you start, you build a brand simply because people know you and nothing else. And then there is a lot of habits people don't, you know, the actual switching costs but just also just psychological switching costs people don't want to bother switching if it means you know our company making a billion in revenue you're saving $3,000 for that such who wants to even bother taking the time and risk and it's rational not to do so. Two, it could be network effects. We own Eventbrite. People don't go to Eventbrite because you know nobody among all homo sapiens has managed to replicate a ticketing platform but it's because on Eventbrite you have 90,000,000 people who go monthly look tickets, and so you sell more basically, you know, right? And so AI can replicate that a million times, but they don't have the audience. And people go there because everybody posts events there, right? Or something like Komoot, you have proprietary data. With Komoot because of the history with all these users, we know that that particular path is muddy and you know it rained and there is a dog barking like and we have photos of those corners and trees and whatnot and turns that are not available, they're not available on satellite, they're nowhere to be found. And so again, it's not... It's actually... Komoot is quite sophisticated actually the routing, but still, know, smart people can build that over time, but they don't have the data or scale advantages, you know, Airtable, our most recent acquisition. Most customers pay Airtable less than $20,000 a year. Mostly there are large enterprises. Even if you get to a point where you can ask your agent by AI agent to press a button and it replicates the code for air table pretty much perfectly, which we're very far from. But we'll get there I think, you know, soon enough probably within the next few years. Supposedly, you'll still want to have someone at the company who's responsible to making sure that that code seems legit, that if something breaks goes to the agent and asks the agent to fix it and whatnot.
00:28:33 · Luca Ferrari, Anish Acharya
I think there's a far future where AIs run our lives and companies nobody works any longer, which is interesting, but you know, it's not... I think most people would agree it's not in the next five That's right. As long as you have someone being responsible for things, even just a 0.2 FTE of a software engineer would still cost you more than paying air table for the same thing. So, sure it's an interesting philosophical point but ultimately you're not gonna do it rationally. It's dumb. So there are all sorts of reasons why I think most not all but most digital products are reasonably well protected. Again they will suffer on the margin new customers you know maybe people search for products through their agents and agents are have a different set of criteria they follow to choose and so before they people tended to choose product A now it's more product B that will certainly hurt product A not to the point that they melt away overnight, you know, because of this. [00:29:29] S1: And those are natural market evolutions, right? Like web to mobile and preferences change, maybe it's agents instead of humans that are searching, but, you know, our data shows that the enterprise spends eight to 10% of total spend on software. So as you think about where you wanna point your AI and your token budget, it's probably not in replicating payroll. It just seems like a high downside, low upside proposition. [00:29:51] S2: I... Sounds so great.