This EU Firm Made Billions Buying Up Forgotten Tech

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What do you do with a software company that was once a household name but has fallen on hard times? Our next guest has built a business around answering that question. His company acquires struggling businesses like Vimeo, like AOL, AirTable, and Eventbrite with the goal of overhauling how they operate cutting costs and making them profitable again. And over the summer, this company went public on the NASDAQ at evaluation of more than $18 billion with the stock jumping 40% on its first day of trader. That IPO turned what was once a relatively obscure Italian company into a public market story that investors around the world were suddenly paying attention to. We wanted to understand how this model actually works, what the company does to turn struggling software businesses around, and what it's like to take the strategy from a private company to a public one. This is my conversation with Luca Ferrari, the co-founder and CEO of Bending Spoons. Luca, thank you so much for joining us on this episode of the ProfG Markets Founder Series. I'd like to start at the very beginning in 2013, where you're not actually in Italy, you're actually in Copenhagen, you're in Denmark, and that's where Bending Spoons begins. Tell us the origin story of this company. Very few people know this, but with my co-founder, almost the same people, we launched startup in 2010, also in Copenhagen. We were using AI clearly too early to automatically write diaries for people. We did that for three years, raised a million dollars and failed miserably, I couldn't make it scale. Although I'm pretty proud of the product we built, but sometimes that's not enough. So in the ashes of that company, we were left with about $40,000, the B.C., who had given us the money, basically sold their shares back to us for a nominal $1, and they apparently appreciated it with work hard and being honest. They didn't want to go through the liquidation process, and we ended up liquidating the company ourselves and basically got those $40,000 out of it almost completely. And I was a seed capital for Bending Spoons, so that's 2013, again, Copenhagen, moved the company to Italy about a year later, but that's where we were at the time. And the strategy we're still running these days, and the key in size behind it, for the most part, had originated from that failure. Obviously you get smarter in time, but most of it was in place like that. So you had a tech company, you say an AI company, I would assume that they're calling it machine learning back there, and I assume that there was not a lot of hype around that sector, that's obviously changed. It doesn't work, then you have $40,000 leftover, which you take out of that to start this other company called Bending Spoons, what actually was the idea behind Bending Spoons, and also I think people will probably want to know what's with this name, Bending Spoons. Over those first three years of that failed startup, we saw our skills in engineering, marketing, product design, improved tremendously. Obviously we didn't feel we were anywhere near world class, but certainly much better. And so we thought, okay, if we work on this skill set and other relevant skills and build our own tools, we should be we should be able to get to world class levels at some point. And at the same time, we saw that finding product market fit going from zero to one, so to say, seemed to require a lot of stars to online, because we met so many startup teams, where people work really hard, and we thought they were brilliant and still couldn't make it work. And sometimes in other cases, it did work. And so we should be able to find people who are maybe tired of running a business or maybe they don't have the skills to go from one to 10, who will, you know, will sell to us. And if you're really, really good at doing this, we should be able to pay a price that's appealing to them and still be able to create enough value to generate stronger returns and be able to compound capital efficiency. So do those were the relatively simplistic ideas we had back then, and because we knew we were going to grow a vast or fully vast portfolio diversified portfolio different products, we had to find the name for the company that wasn't related to the particular product. And so one of my co-founders Matteo is a big fan of the movie The Matrix, and I think he had watched it the night prior or something, and in the morning it came all excited and said, we should call the company bending spoons inspired by there is this scene in the movie of a little guy bending spoon with his mind supposedly. And we liked it because it reminds us of, you know, the mind is powerful if you set your mind to something you, you know, maybe you can do the seemingly impossible. So we just found it kind of inspirational. We like the idea of making a little bit of fun of poking a bit of fun of ourselves, you know, and not taking ourselves too seriously. So that was also a cool name in our view and it's stuck. So we'll get to what you guys do today, which is you are essentially buying a lot of these different software companies and we'll get to that. But in the early days, my understanding is you guys are building tools, you're building software products, you're kind of like an app studio in the early days. Tell us a little bit about how what you were actually building back then and how it eventually led to this seemingly slightly different business model where you're actually going out and buying companies with money that, you know, now you have. But back then, I assume $40,000 is not much you can buy with that with always a quiet company is the first acquisition happened. Very quickly, I think so we started bench from the summer of 2013, the first acquisition was in 2014, I don't think. From that point onward, there's ever been one year where less than 90% of our revenue came from businesses we had acquired. So I'm not sure where the studio thing comes from, but I think it's just that the first acquisition we did that people recognized was ever known in 2023 so people just us feeling that what we were doing before was launched from scratch, but nearly all we have done over the past 13 years was acquire existing businesses and I'd like to think make them better, more successful. We have launched occasionally we have launched products from scratch, more so in the early days because we had no money and so, you know, it was both the only thing we could do, but also it was more likely to move the needle at this point, you know, we're at a brown rate in terms of revenue of almost $4 billion. It's more difficult to launch something that can, you know, reasonably move the needle, but the first acquisition happened like I said very early and we paid $10,000 for it. So very small, but, you know, the power of compounding is such that it turned 10 into 20 and then 20 into 40 fast forward 13 years, we are where we are. We actually had very modest injections of equity mostly, you know, other than the IPO a few months ago, we had a significant injection of equity, about a quarter of a billion dollars in the end of toward the end of 2025. So really up to that point in time, most of the growth was through the investment or free cash flows and then that which we have used for almost 10 years at this point. So tell us a little bit about that first acquisition, how did you identify this company that was worth $10,000, same amount of money that a lot of people would pay for a call and what did you do with this company to turn it around, what were you bringing to the table? That one was a lot easier than things today because it wasn't even a company really this was a mobile app for iOS, I still remember quite distinctly that it was an app to personalize your iPhone's keyboard. I don't even know if such apps exist these days, but in 2014, I think around that time Apple launched opened up APIs to be able to do that and a bunch of apps came out and we saw this one and we thought it had a bunch of users. And we thought it could be both the product was not that good, maybe had users because it was a first mover and had achieved a good positioning on the app store. We could believe we could improve the user experience, monetization was almost nonexistent. And so we bought it, we rewrote the software completely redesigned the UI and introduced monetization. And it was built, the app had been developed by an individual like a single developer, so kind of an amateurish. Operation obviously these days we buy sizable companies with professional management teams and institutional investors But the key principles trying to be Superior at the key functional expertise necessary to run that business Superior relative to whoever is selling it to you stood Obviously the bar to be stronger today is much higher But the the idea is pretty much the same. So this gets to the heart of what bending spoons actually is And I think there's a lot of confusion as to what this company is because on the one hand There's this software element where you guys are using AI you have this software background You kind of come from this Not silicon valley culture, but certainly a stalled up culture But at the same time you're doing what many other asset management firms and private equity firms have done for decades Which is your finding companies? You're buying them. You're acquiring them. You're taking up large positions I mean, you're taking up a strategic stake in the company and then turning those companies around This is what investors have been doing for decades. This is This exists. This is an entire industry Which I think I would call it private equity. So in your mind what actually is Bending spoons because to me, it seems like it is at the end of the day. It's an asset management firm The the sitting investment part of what we do is it's absolutely important clearly we grow primarily through acquisitions for a serial acquire the part that would distinguish us from any private equity I've seen I would say there are three very important differences And one is that we are not a fund. We don't buy to sell. We've never sold a material business So we buy to hold and operate forever The second perhaps more important difference is that when we acquire a company This deep private equity is I'm aware of or or I've seen operate they they do intervene. Obviously, they you know They may cut cost maybe intervene on monetization. They may change the executive team But the interventions are relatively relatively superficial and you can you can tell By looking at the the team at private equity firms. It's mostly small teams of financial professionals Bending spoons takes a different route. We do those things as well, but but we we take a different route on in that we We rebuild the org often completely or in large part. We May re-architect the cloud infrastructure completely rewrite big chunks of the code base accelerate priority development Re-imagined monetization from the ground up marketing. So they say much much deeper transformation to the point that sometimes we it's almost like we buy Brand customer base user base and try to overhaul everything else very deeply and that I mean that's represented in the in the team We have which is even if you look just to the core team Forget for a second the acquired teams. That's roughly 800 people and overwhelmingly their software engineers It's a scientist product managers product designers. So naturally, you know, most of the work we do is that sort of we also have our we have our own Team of financial professionals because we need that too, but there's this additional piece and the end of third big difference is that while Pretty much all private equity is by businesses and they keep them separate to sell them down the line sometimes they put a couple of Senior gst businesses together, but that's the extent to which they they put things together We we integrate everything super deeply onto the same platform. I an investor some time ago told me that after due diligence in Ben is supposed that they They found that we all it's almost like we buy companies and then we they get stripped down through a product installed on a shared operating system I think it's it's a bit of a simplistic metaphor, but there's truth to it. So if you look at how we do things we Generally within a few months from the the moment the acquisition closes we swap out to the entire The state technological foundation we've built dozens of proprietary technologies, whether it's AI orchestration data processing AB testing recruiting payment management credentials management like basically every component of running a digital business with built-in hours natively integrated and and that's swapped out for whatever third-party vendor things the business is using We have this core centralized team for R&D GNA marketing Who we redeploy very fluidly across all of our businesses to go after our R&D opportunities and up on their exhaust that we we throw them so we keep cost efficient It's so to the point that it would be almost impossible to sell one of our businesses even if we wanted to so that's a downside of our model So there are similarities with private equities First and foremost the focus on acquisitions, but I think the the the day-to-day operational approach is in integration and transformation is is quite it's quite different So it's a bit of a hybrid that's a one of the cliches, but it's also true about the private equity strategy is that you buy a company and then you dramatically cut the costs of the company which usually comes in the form of layoffs And that is something that you guys have demonstrated as well. This is a pattern that is pretty consistent across the companies that you acquire It's also something I think that people some people criticize you guys for rightly or wrongly, but When you look at some of the the strategic decisions you've made like we transfer staff for example two months after you bought it 75% of the of the employees had been cut. I mean house central is headcount reduction to the strategy And what do you make of one the fact that that does sound very also very similar to the private equity model and to the criticisms that people might have that Well, you're cutting headcount If it's a moral moral judgment if if someone thinks that Trying to make a business as successful as possible is bad. I don't have any defense against like say completely Valley point of view. I disagree obviously or I wouldn't do it. I think in general Uh, the world tends to work better the economic pie tends to grow larger if businesses are run at excellent level Uh, but uh, you know, it's a perfectly I respect the fact that someone would disagree with me on that point We definitely we have done it almost every single time. So it's definitely been a pattern. Um, I would say that in general cost efficiencies have been approximately 50% of our value creation of role Uh, and within that 50% probably the Org part it's probably roughly a little over half. So maybe I would say of the of 100% of of our value creation. I'd say maybe 30 35% has been about optimizing organizations one thing we do that's uh, I believe misunderstood is people tend to think that we End up reducing headcount Simply because we want to cut costs and while optimizing cost is obviously a significant driver We actually try I'd say just as important for us is that we make that or far better position to kick ass for a long time Uh the in my view flawed assumption some people have is that The number of people you have in a company is Almost, you know, definitively got the terming whether the company produces great product innovates quickly We are of the opinion that if there is a correlation between headcount and say innovation or or or or the ability to optimize customer experience monetization that's a weak correlation at best And that what drives those Virtuous outcomes for the most part is talent density whether people use powerful tools whether the culture is one of you know Rationality high performance whether whether or not you have a lot of red tape or you actually give people playing a space So what we try to do is Bring these companies back to what I would call startup mode small teams of supremely talented people We'd get out of the way and give them plenty of you know very wide mandate very powerful technologies I mentioned them quickly earlier Um, and what we see consistently is that magic happens despite going down in headcount maybe 80% sometimes more uh demonstrably and we we publish a lot of this stuff on the various blogs or brands The masterbly the rate of which we fix bugs reduce say technical incidents or Launched new features goes up sometimes dramatically um, so yes, we we have absolutely consistently got Uh headcount no doubt about it sometimes dramatically. So uh, we do so also No doubt about it for for cost efficiency, but equally we have been able through the same Means to make these businesses a lot more competitive from the point of view of product quality and and a pace of innovation So for us, it's really a win-win But I understand that it's painful for those involved. We try to mitigate the unavoidable. I think Pain of being laid off which sucks. I mean, it's a very tough thing to go through By being transparent by offering top-of-market separation packages By being empathetic and flexible, but that doesn't make uh that transition painless It makes it a little bit less painful and we if we could do what we do without that uh Objectively bad element we will certainly be very happy to avoid it None of us enjoys that part of our job structure My understanding is also that you are you are specifically finding companies that are struggling struggling on basically every metric struggling With their profitability struggling with their business model and these are companies that otherwise would have been Stagnating and probably perhaps would have done the layoffs anyway Um, I guess this gets to the the next question which is How do you identify What company is the right company for? for your business model, for integration with your software products and your software team, what makes the company acquirable? I think you're right in many ways. I would say a big percentage of our acquisitions have been struggling companies. Not only have acquired several companies that were growing nicely and thinking commute air table recently. We shared the growth rate, but yes, we have a bigger percentage of companies in our acquisition portfolio. That were struggling then to say most acquires. I think it broadly speaking, a valid characterization, and sometimes, yes, the exact teams themselves tell us that, look, if I say I need to take difficult decisions in a way, let's, I'd rather you do it. It's happened. I wouldn't say it's happened often, but sometimes it's happened. What we look for is, on a qualitative level, three things we like to acquire large businesses relative to our current size. The reason is, I described how we conduct is extremely deep transformations and integrations. Those take a massive amount of time and effort. The good news is we found that we don't need the number of people, the amount of time we need to complete those transformations does not seem to scale really, at least not linearly with the scale of the business and so we're better off acquiring fewer companies and deploying those resources toward transformations than move the needle as opposed to acquiring a hundred companies, but not having the time to do anything really well. We like to buy, say, five companies a year give or take that are large. The second thing is we want to feel confident. We can predict their performance at least five or six years out with confidence. That's an entire whole discussion of science, but on a high level, that's the answer we need before we decide to pull the trigger. The third big criterion is we need to believe we can greatly improve those businesses or fully the product that detect the org when it's this remarketing, ultimately, revenue and cost. It's an earnings game at the end of the day. Those are the three big criteria than how we get to those answers that's a lot of many steps and it's got complex, but other than the scale, the scale is very obvious. And once those are three checks, then it boils down to the math of returns. Among the companies that check all three boxes, then we look for investments that will yield the highest returns so we can compile as fast as we can. We'll be right back. Support for the show comes from engine. The company's winning right now aren't cutting travel. They're booking smarter. Here's the reality. The average business travelersman's 45 minutes booking a single trip on a legacy platform. With engine, that booking time drops to as little as two and a half minutes. And it's AI powered personalization gets faster the more you use it. Multiply that across your team every trip every year. That's not a perk. That's a competitive advantage. Last year, engine customers saved more than $300 million on travel. And with the engine X card, get up to 10% back on any hotel booking. 33,000 businesses have joined. Now it's your turn. $500 in your business signs up and start traveling at engine.com/founders. Engine X visa commercial cards are issued by fifth third bank and a member FDIC. Earned up to 10% back and points on eligible engine travel purchases. Actual rewards are it's vary by purchase category and may change points of no cash value and are redeemable for rewards through our program. See full rewards terms for details at engine.com/ax/rewards-terms. We're back with Lucifer Ari. When we look at some of the names of the companies you've acquired, especially like AOL and Vimeo, these are sort of once great companies or once companies that were previously known to everyone sort of dollings of the tech industry that have gone out of fashion, I would say. Is that part of the strategy is taking these once big name brands and transitioning them or is that just a coincidence? I think it's mostly a buy product. We don't actually have internally guidelines for our M&A team, look for brands from a buy gone era or anything like that. It's more than I think, at least historically, maybe at least in the last five or ten years, maybe the future will be for us. We found that the market tended to undervalue the unsexy things. In our view, overvalue, the new and sexy sometimes to a fold in a major way. We try to be rational operators. You can never prove it. I'd like to think we have been rational capital allocators and operators. While we're comparing, after having done the qualitative screening and done the math, we're comparing the returns we would get from the AOLs of the world, or I'm not going on a name name, but let's say, fleshier, newer, sexier things, we found that the latter would consistently give us much worse returns and we saw no reason to do it simply because people liked it. AOL is actually a very good business. It's not I and it's not obviously not going places, but 30 million people use it. For many of these, as their main email and they use it all the time and these are perfectly, they're not less valuable as human beings or as customers as people using the small, fleshy, new email clients simply because they like AOL. We're happy to serve those people just as we'd be happy to serve the cooler, early adopter. It seems that many investors prefer to go toward cool and sexy and we're happy to take the less sexy things. This is one of the reasons I'm fascinated by your business. It's a big theme on our show, which is that the best investments are the unsexy investments. You want to capitalize whenever one has for various stupid reasons, written some company or some stock or some investment off. It seems like you are capitalizing on that dynamic. That is a very investment-minded strategy and you are someone who comes from you are building companies, you are building software products. What is your background in investment, in financial valuation, because it does seem like a very, in a lot of ways. It's what classic value investors have done and you seem to be in that camp. What got you to this point, given the fact that you kind of had more of a software background? A funder and I studied very similar things, engineering, physics. I think that's really our background and maybe driving passion is technology and science. We just felt that applying that to business would be fascinating because it actually business offers a lot of challenging intellectual problems. It's also rewarding financially. We decided to go down that route, but we have, I believe, retained that engineering and scientist, engineer and scientist mindset and try to embed it as much as possible in the organization and everything we do, even talent. The way we recruit is completely scientific at this point. I'd like to think we are curious people, we have studied the other explaining. I think it's more difficult, let me put that way, it's more difficult to learn quantum physics than how to calculate an IRR. I think it's better to have studied STEM and that's generally tests your intellectual capacity and gives you better problem solving tools. You can then learn other things if you put in the effort, so there's plenty of books on finance and economics and where big fans, people like Warren Buffett or Tom Murphy or Harry Singleton, Benjamin Graham, there's plenty you can read, it's not rocket science. If you try to learn from people who are smart and have done it before, and then, of course, try not to copy paste blindly, but understand the boundary conditions they had and the boundary conditions that apply to you, there's a lot you cannot, a lot of mistakes you cannot avoid. Yes, we try to value, value, I'm just telling the way that it has to be again a business that's beyond, beyond as past is prime necessarily, for us, it's math, it just happens that the market values the in their prime businesses so highly that we end up buying more of the past their prime businesses, but ultimately we just try to compound the efficiently that's all we're trying to do. You mentioned Warren Buffett and that's exactly who I was going to bring out because there seemed to be a lot of parallels here. You talk about, you're not flipping companies, you're not trading companies, you're buying companies and the plan is to hold them forever and I have to say, I mean, the first company that comes to mind when I think about this business model is Berkshire Hathaway and I look at what Warren Buffett did, starting with very, very small companies, sounds like I think he took a less strategic position in a lot of those companies, but he still took some strategic positions as well. But it sounds like that's quite similar to what you're doing, but you're doing it in a tech and software enabled world. Is that kind of the vision for bending spoons or do you think that is an apt comparison? I'm a big fan of Buffett and his colleagues, Dad Washler, I think they're amazing. I think you'll just want to be careful with comparing because we're talking. It's almost like you're asking an aspiring parent and Michael Jordan. Exactly. It's like, sure, obviously, yes, it'd be great, but at the same time, we need to stay humble and acknowledge that we're doing it. We have done 1% of what they did. But broadly speaking, I think it's an app comparison that for our ownership mindset, rational investing, trying not to let the trends of the moment sway you unless there's a good reason for it. I think a huge difference would be that Berkshire has historically being a more passive acquire, like they try to be very good at selecting the right companies and then letting them operate, doing more of the same. We're on that particular dimension. We're almost at the exact opposite end of the spectrum where we like companies where our ability to make big changes and the very integration into our technological and people platform will make a difference, but yes, it would be a dream to be able to build a company that's almost an institution of that scale. We'll see. We're certainly here to try. So you start in Copenhagen, then you move to Milan. You are in Italy. I think that this IPO put Italy on the map in terms of business news. We rarely hear about Italian companies unless we're talking about luxury cars or storied brand names. To what extent does being in Europe play a role in your business? There are a lot of European companies that have decided we're going to move to the US because there's more opportunity here. I had like the CEO of Salonis on recently who tried to move a lot of his operations to America. Tell us a little bit about operating in Europe and the extent that it has impacted your business and your strategy. For example, currently, yes, we're at the port of Milan, Italy, but most of our people and actually more than 50% of our team is in the US and 60% of our revenue. And most of the businesses that we're acquiring are in the US or definitely very international with a huge US footprint, but we continue to be a European company, let's say at least formally and certainly a big chunk of our R&D and our headquarters. We decided to build a company in Italy specifically quite consciously. Our startups, in my experience, are built out of inertia like we happen to graduate here. Let's launch a startup. That's what we did with the failed AI startup or machine learning or whatever on a call. Once we decided to start brand names for us in Copenhagen, we put some thought into where we should be building a company and chose Milan, Italy quite consciously. For two reasons. One was just, let's say, commercial selfish reason. And that was Italy, 60 million people. Good education, actually. Lots of people are cheap on their shoulder to prove that we're not less intelligent or less capable without weak end, but very few great job opportunities. We thought we could find a lot of capable talent and it would be a win-win for them to join an ambitious project that hopefully would be a huge company one day. And for us, we'd be able to surround ourselves and create people, create strong teams and hopefully have better chances of succeeding. So that was one reason. The other reason was we just had this idea that and I still have it, the world is a better place if knowledge, opportunity, wealth is better distributed. I think it's totally fine that you have one or two hubs where those are off the charts, you know, Silicon Valley. You'll never gonna have a uniform distribution. That's okay. But I think if you have a just a gigantic gap and a growing gap, I don't think that's a stable world. The world will ultimately, anybody wins. And we want to improve it. You could build a company of global caliber and absolutely kind of key cast company in technology, which was our passion. From, with roots in an unlikely place, like Italy, but it could have been Portugal or Greece. It just happened to be Italian. It was easier for us. Plus the other thing I just told you. So we moved there and built it there. And I think it's being good and bad. Look, the good part is the common part. I just described the bad part is Euroke has truly incredibly high levels of oppressing regulation. I'm a big fan of a, I'm not a libertarian. I think that I want to be clear. I'm actually a fan of an extremely generous, supportive, welfare state, a society that helps people. I just don't think that a good way to do it is by imposing massive encampuses on companies. I would say, you know, have us pay lots of taxes and help people, but don't make getting a permit for building something impossible, getting, you know, being able to fire a team member because you can hire some higher performance in possible. So I make it easy to deploy to launch projects and allocate resources efficiently and then use taxes to provide a generous safety net for those who are left behind. I'm actually in favor of being wealth taxes and more taxes for rich people. I just think we're doing it the wrong way, but Europe is good, but it could be a lot better if I think changed in this regard. - I was gonna ask you what you think the gap is between US entrepreneurship and European entrepreneurship and there is a gigantic gap. And there is a gigantic gap in productivity and GDP and overall wealth creation. I assume you believe it is a result of overly budding some regulation in Europe or is there anything else? - No, there's more, that would be reductive. I think that's a very big reason. One of the main reasons, I'd say another big reason is culture. I think Europe has historically, and this changes by country. Europe is quite, people who have traveled Europe and spend a lot of time in Europe. It's quite a heterogeneous country. Like the people can be quite different, but I think on average, compared to my understanding of the US, which I think I know visionably well at this point, there is a greater tendency to fear and criticize failure. People can be stigmatized for failing. And when they succeed, they're often criticized for being too ambitious and maybe there is a sort of, the default is to be suspicious. Maybe someone helped them too much or they got lucky, or which obviously doesn't breed. You can still be a successful entrepreneur, but it doesn't help. And then the, I think that another factor is the market is especially historically being more fragmented, whereas the US has done a fantastic job at basically unifying the market. And so the winners got bigger, faster, and in a global world, that's a huge advantage. None of these things is huge in and of itself. They're all marginal frictions. But the way, in my opinion, the economy works is that when I certain location in these cases, even 20% more appealing resources start trickling from the less appealing location to the other location, whether it's human resources, capital resources, and over time, that builds an advantage in the more appealing location that can be massive. And I think the US today, in my estimation, if I look at the 1000 of the best Broadway from Italian universities every year, are actually, let's actually take the top 100. Let's really go at the top of the best of the best or really the people who tend to have breakthrough, breakthroughs in R&D or launch, successful companies. My estimation is that probably a good three out of four end up in the US. And early, often even before graduating, and that's difficult to capture in the statistics, but down the line, five or 10 years, that compounds to a major disadvantage to Italy or Europe. And that's being going on for decades at this point. So how do you deal with that issue if the talent in Italy and in Europe is being sucked out of Europe and they're all going sent over to the US and they're working at AI companies in Silicon Valley in San Francisco? I mean, how do you deal with that? Is that a problem for your business? - Not so much for us, 'cause we, I mean, first of all, we attract, we bring people back quite a bit. There are a lot of people who are originally European and they like the US, but maybe their family, their dear ones are in Europe and they've been looking forward to coming back and they haven't had that many opportunities. So they see benefits as a great opportunity, not to be able to come back and yet not give up that level of ambition, high compensation and fast career growth and whatnot. Also, we happen to be, generally, we hire people who are graduating or when their students would have gone abroad and they stay and they have a fantastic career and we'll be opening offices in the States next year. So it's not really a management's problem per se, but it's a massive problem for society here in Europe, I think. Out of solvite, frankly, I don't know. I don't have a silver bullet, I think. You need fundamental reform, certainly massive intervention on regulation, but frankly, if you did that, it wouldn't solve it overnight. It's something that would have to build up over a long period of time. I don't know that you can reverse the compounding that's going on for decades to be honest, not in any reasonable timeframe. It is quite worrisome, in my view. Even, frankly, in many ways, even for the US themselves, 'cause again, a world where people in the US are 10 times richer than everybody else, I don't know that's a stable world. A world where people can travel safely and be generally happy and go, I think we need a level. You can have a country that's dominant and substantially better off, but if the gap becomes, and it's not today's situation, but with AI potentially accelerating the divide, if the divide becomes just massive, it's a difficult Earth to inhabit, I think, for all, really. Even the ultra-rich and ultra-successful, in my view, at least. We'll be right back. Here's the reality. The average business traveler spends 45 minutes booking a single trip on a legacy platform. With Engine, that booking time drops for as little as two and a half minutes. And it's AI-powered personalization. gets faster the more you use it. That's not a perk. Now it's your turn. Get $500 on your business signs up and start traveling at engine.com/founders. Engine X visa commercial cards are issued by 5th third bank and a member FDIC. Earn up to 10% back on points on eligible engine travel purchases. Actual rewards are it's vary by purchase category and make change points of no cash value and are redeemable for rewards through our program. See full rewards terms for details. Go to engine.com/ax/rewards-terms. We're back with Luca Ferrari. You were able to not let this affect your business. I think this is one of the big questions for founders or the big problems to solve is how do I recruit talented people to my business. And especially it's difficult if you're starting from scratch. What did you learn about how to build an excellent brand that world-class students and engineers want to come to and want to come to work for? Because to me, I think that when you're building a business, the people are almost everything and you need to convince them that they're going to succeed and that they going to win. How did you do that? A lot of people in my experience tell you that they believe people are important, but then they don't walk the talk. So they actually don't put in the time or effort into that as those words would warrant. At Bennichael's, we try to remind ourselves that the jobs we offer are our most important product. More important, any customer-facing product we have. So we try to make those jobs as great as possible, then word of mouth will help you a lot. You hear two people, they are absolutely happy and satisfied and they will tell their other friends from university. It's actually fantastic here as you join. We have heard so many people that way. So we can discuss how we try to make jobs here amazing. It's actually not that difficult if you stop. For a second, remember that you are in a as a founder, CEO, you are in an unusual position and in an awful vantage point, actually trying to stand in the shoes of team members. It's not that difficult to find what the type of person you want to hire would appreciate. Of course, good pay, but then autonomy, trust, respect. A lot of times management teams are a little bit arrogant in expecting that people should love it to work with them simply because they want it to be that way. So you try to work hard to make it a great product and then you need to put in an effort to promote that product. When we were 50 people at Bennichael's, we already have something like three or four people doing recruiting alone. I can master investment just going to you know, recruiting events, posting job ads, calling people, emailing people. At the beginning, you need to persuade people. I spent so much time persuading people to join us and there a good founder needs to to provide a vision that's credible and the energy and passion that would convince the those who are, you know, invincible. So you punch above your weight. Basically, you hire slightly better people than you should be able to. And then if you do that right, hopefully a virtue cycle is is ignited where you offer better and better jobs. You can pay more and more as the company becomes more successful. And the track record speaks for itself at the beginning. It's more like you have to believe me. But now, you know, go, you know, read on glass door or go talk to 50 people work here. You can establish the truth pretty easy. So that's, you know, a lot of effort. And then, you know, you want to to select well among anyone who applies. And we believe that's a question of science. And we have tried to make it that we would data scientists and AI researchers would put in a lot of effort to detect signals and sound loss application that predict performance and we keep iterating and improving. Not unlike, I think, a quantitative trader would algorithm trying to find signals in the market to tell them which stock is like to go up and would start to go down. We try to do the same thing with people and find people who are will be amazing if provided with enough opportunity and coaching. What does that look like that, that sort of more scientific approach to hiring? We need to first establish an objective function. What you want to optimize for we found that in our case at this stage, that's a performance as rated by once colleagues after 12 months on the job. The more people you hire, the more the deeper you can go into the funnel while still retaining statistical significance, we are currently hiring several hundred people a year so we can go fairly deep one year. Which tends to be pretty good. And then we, so that's the your objective function. And then what you do is you need to identify as many signals as you can in someone's profile even beyond the pure application. And then you just, you rigorously track them and see how combinations of signals best predict that outcome at the objective function level. And that's a, that's not a difficult problem that's pretty well established in statistics or the problem is of course, capturing that ultimate one year and you know, way that's reliable, always in the same way, pre-structured. And those signals, the signals are really the key. Some are pretty obvious, for example, GPA. It's not perfect predictor. It's only a mild predictor, but it's, if someone has done really well in university, they're more likely than not to do well, at least at least once. Most people will believe that helps. If someone has gone to a more competitive selective university, that's a, it's a predictor too, a weak one, surprisingly. People think, oh, someone to MIT, they must be a genius. Actually, it's much less predictive than you would think, but it is predictive a little bit. Some other are quite amusing and yet quite predictive. For example, we found that if someone was politically active during, when they were a teenager, but stopped being politically active when they were like in their 20s, as a very good predictor of drive of agency entrepreneurship, which you, at least we definitely want to bend his phones, it would have never occurred to me. We spotted it through, it would AI basically. But then you can rationalize it by saying, if someone is 16 and they're not content enough with being a good student, they're looking for ways to change the world around them. That's a good sign of, again, productivity agency, a healthy level of dissatisfaction. If they're still doing it, when they're 24, it's great, but it's probably more of a life mission and their job is probably, you know, takes a backseat to it. And so they're likely to do super well relative to people prioritized their job. So hundreds of signals like that, we keep finding nuance. Many we generate through tests, we have people go through practical tests, but we try to, we look at, you know, what people write in their emails, what tone they use, how do they interact with people who are not in a position of power? We found that how people email our, let's say, our support agents who help them just with the logistics of their application, and clearly are not the person deciding whether they get hired is a very good predictor of whether they are a collaborative humble team member as opposed to because they're always nice to people late in the funnel when they know that the offer depends on that interview. But those who are assholes in life, they will show up as assholes more often than not, when people who are not perceived to be in a position of power. So hundreds of those none is very predictive, but when you put them all together, we're pretty predictive at this point. It sounds quite similar to the strategy that Ray Daly has used at Bridgewater for many years, where there was a lot of, he wanted to track everything. He wanted to track every meeting, every interaction, sort of put everyone on a social graph, which I think in a lot of ways probably worked, but also he got a lot of criticism for it, and a lot of people did not like it because it feels like, felt like to a lot of the work is in that culture that they were being surveilled, and that every interaction was a test. And it sounds like in a lot of ways with the level of tracking that you find that you're employing, that you might run into potentially similar issues. I guess, how do you think about that issue, and do you think about it? Do you think of it as a potential issue? I didn't work at Bridgewater. I've read a few things about it, so I'm just kind of familiar with it. What I just tried only applies before you get hired on the job, we actually don't do any, there's a just a review at the end of the year, which is based on input from your colleagues. We don't do any tracking of working hours of anything really. So precisely for what you mentioned, we are staunch believers in the fact that most people react really well to being trusted. And so we try to hire people who believe we believe our amazing, or can be amazing, given enough time. And then we give them uncomfortably high levels of trust and freedom. To the point that sometimes we've been criticized for the opposite, because sometimes we have had these situations where we acquired a business, and then we established as a general manager, someone was like 27 years old, and sometimes [BLANK_AUDIO] our team members tell us, are you crazy like, you know, this person, how can you trust she can do the job? And historically, she has, by the way, but, but I think if we were to, to monitor and surveil people, that would, that would really destroy that, that trust that's such a motivating factor for people to come to work and do their best. I guess it makes sense. It's like, you're extremely discerning before they're hired and extremely trusting once they're hired, which I think is makes a lot of sense. It's probably the right strategy. Over time, you assess people's outcomes over a range of scenarios. You don't need to, to surveil how they got there. If someone is consistently delivering, delivering quickly, high quality work, I don't, I don't care to know really how you got it done, you know, like, if you use it, I didn't use that, I did it work later, you didn't like, ultimately, we want to work with people who are effective. And so we can just measure how we contribute to projects over time. And I don't think surveilling people would add in very much if anything to be honest. But pre higher, you don't have, like, pre higher, you need to, you don't have any information to look at in every niche and cranny to be able to figure out what are extending an offer makes sense. One of the big themes with your business is sort of using AI and using modern computer science and infusing it into these businesses. What does that look like? What does it look like to take a company like Eventbrite and then give it whatever the AI bending spoons magic actually is? What are you attaching onto these businesses? So I think we try to use AI broadly speaking for two things. One is there are some times features you can build for customers that are only possible today. Thanks to AI that were maybe not possible in the past. You mentioned Eventbrite, I think. We haven't done it yet, it's very early, but I think one of the ways AI could help make Eventbrite better is by greatly enhancing the recommended systems. When you go to Eventbrite, there's roughly 80 million people who go there monthly to find interesting events near them. What you show them as a recommendation makes a huge difference in what they are satisfied and what are organized yourself tickets. So it's really like a win-win. And that's a difficult problem, especially because you don't have the data that metadase. You have very limited data clearly because the people only go there for the events. So AI, we believe, could be quite helpful in making that better and even marginal improvements in that recommended system can be quite valuable for both parties of the marketplace and the other big ways. That's completely bespoke to the product, obviously. Then there is something much more to say, general purpose that applies to almost any business that's using AI and technology more generally cutting edge technology to be operationally much more effective and efficient. For instance, again, I told you we have dozens of proprietary technologies. Most of these are based in the AI, especially these days where, if you don't use AI, are probably giving a lot of value on the table. But some are really AI-centric. For instance, we've got something called Alternative Spooner, old ALT Spooner. Each one of us, and Spooners, by the way, are basically the members of this core team, highly selected recruiting process and people will move around their businesses. We're working now to extend this technology, by the way, to ALT members. It takes a little bit more work. But you have this personal assistant that lives in Slack. We use Slack for communication and automatically, as exactly the same level of access you do across all of our toolkit. And you just talk to this agent and you ask you to do pretty much anything. For example, you could say, I actually saw this live as I was in a channel on Slack where we post feedback on every note, ideas to improve the product. I was there to, I was just writing about a bug I found. And I saw our general manager for every note. She wrote that she had experienced the bug and asked her Alternative Spooner to, first of all, investigated by going to this tool to build, to collect and categorize customer support tickets and check whether that bug was prevalent among customers, which is something she was a corner case and then go into the code base, identify the root codes, code a fix, and then message the technical lead for that project, Marco, so that it could review the pool request and find basically prove it so that that fix would go and benefit all customers. And she did that in, I don't know, like, five, less than five minutes. And the agent went off and did it. The bug was six today after because Marco apparently didn't have time to review it the same day. But it probably took, I don't know, 30 minutes of a person's time to do something that would have taken optimistically 10 hours, even just two years ago. And, but actually, we would probably never have solved that bug because it would never probably have reached a level of priority that we would go after it with the cost. So this is just one example. And interestingly, that technology, you don't even get to choose the model that's used, that's being used. So there is a gateway that the harness is built in house of open source components. And then the gateway is also built in house. So then when a task comes in, we have a algorithm that will determine the best model to or combination of models to implement the task, to try to optimize for quality and cost. So we have, of course, access to the APIs for the frontier models, but also we have self hosted over 15 or something different open weight models and combinations thereof. And for 99% of the tasks, we actually go open weight, spend almost nothing, we were currently, like I said, close to $4 billion in run rate revenue. We are, as far as I can tell, one of the most aggressive users of AI of any company, writing 94% of our code with AI, almost all of our data analysis, almost all of our design. And on a run rate annualized basis, we're spending 15, 1, 5 million dollars in all AI related spend, because it's almost all done with super efficient open weight stuff. And the frontier models are used only for supervision, which is super cheap. It's like if you have a senior engineer just overseeing 10 junior engineers taking a look, but not doing the work themselves, that's way cheaper. And then for some super critical task, but those are quite rare. So when you bring this to an acquired team, it can make a massive difference in the efficiency with which things get done. And it's not just, you cut costs, but also you just launch more features, you can run more experiments in monetization. And it's all a virtuous cycle of compounding over time, which is quite powerful, especially if you can deploy it across new acquisitions, because then you can invest more in building these tools, because you're amortized across it growing diesel revenue. It is a really good endorsement of how AI can make businesses more efficient, also an endorsement of the value of the open source models, which is that they're cheaper and you're not losing that much. So long as you're strategic about when and how to use them, which I think is going to be a huge shift in the AI landscape over the next few years. But also, is kind of an endorsement of the AI will take your job story, because you're using AI, it's making the business more efficient, and you're also reducing headcount pretty dramatically in a lot of cases. And it seems like AI is doing a lot of the business work that humans would have been doing in a, yes, less efficient system. But I think if I were worried about AI taking my job, I would point to bending spoons as an example. Are you concerned about that? What do you think about this issue? Yeah, very much so. I agree. We watch your saying. I also think that I don't believe the answer is telling companies, well, try to be worse than you could be, because I think ultimately that's not a lasting solution. But I think, societally, this could be a big problem. Up until a few months ago, I was quite pessimistic about this. I really thought I couldn't see a way for people to be employed, even in 10 years, at least the bulk of the population. I guess I've gotten a little bit more positive about it, as I read an article by an economist, I forget his name now, but we made a, and so I'm putting people who, or everybody I've heard say, don't worry, AI will create more jobs. Their claim was, ultimately, I cannot do everything humans can, better than you must can. And I think that's a dumb argument. I think it's true today, but who are brains are ultimately molecules and electromagnetic signals. Look, we're going to get there, maybe next year, maybe in 20 years. It's a difficult but definitely not instrumentable technological problem. And the upside for whoever sold it is so massive that someone is going to solve it. Maybe it's not LLMs. Maybe we need some breakthroughs, architecturally that we will gather. So I think that's a dumb argument. But this economy is made an argument that I think is brilliant. And it's like the concept of comparative advantage, or opportunity cost, or what you will, you are probably, you know, you are anyone at companies, probably much better at a range of tasks than some colleagues who are doing those very tasks, but your time is limited. And so it's ultimately more efficient for you to focus on certain things, other things you're better at, or they're more value-adding, and other people will do the other things. And ultimately, although the capacity it can have can be ordered some magnitude greater than that of a human, ultimately it's limited by something, whether it's energy or chips or, you know, it's never going to be infinite. And so there will be things that AI cannot do because it would be stupid to use those limited resources for AI to do those things. And you must very likely be the next best option. And in a world where the economy has grown massively because of productivity gains through AI, maybe we get paid so much more for those things simply because there's so much more money to go around that whoever is enjoying part of that share of that. the AI pie. So to say, he's willing to pay a 100 times more than their pain hurt today. And I think nurses are paid a lot more today than they were paid 100 years ago for very similar reasons. So I've got more optimistic. But there's this this scenario, which could be almost, you know, having on her in some ways and maybe having on her to even need to work because we found a way to distribute that wealth and we can all pursue our hobbies and whatever. But this is a same I say my heaven on her. I quite like it. But I also got pretty worried that if the point AI is so powerful and there's this limiting factor or say energy, it's a slippery slope where if we lose control of AI, then why are we feeding humans? You know, because that's taking away energy that could be fed to give an AI that extra 0.1% to do even more. Like if if if we're pushing that limit, what prevents those are controlling it or AI itself from from turning this into a massive dystopia, a bit like the paper clip typical dystop. So I got more optimistic, but also this scenario, I think opens up even more concerns on some truly extraordinary bad scenarios. A lot worse than people are unemployed kind of scenarios. So I'm I'm excited about AI because I'm ultimately a technologist and I think it's fascinating, but I'm also extremely scared about some of the implications it could bring to society. It seems so much rests on the transition period. How do we transition into that future and what decisions do we need to make? And it seems like we do need to make some pretty important decisions. We are out of time. I want to just wrap up with final question for you. You have found yourself in extremely successful position. You are working in AI. You're also working in investment. You've you've seen a lot of things. As a founder, what advice would you give to anyone who's listening to this podcast who's interested in being entrepreneurial, maybe thinking about living in a more AI enabled world and how to succeed in that world? What advice would you give? Try to look for for ways to be valuable, create value where a few people are looking. I think if you if you're building the, you know, harness number 28, simply because someone like a VC was not being able to finance the bigger brands as well into the $5 million. I think you're probably with your time. So try to find a place that's a little bit concealed, unseen, on sexy. And, and by all means, ask yourself a question what AI could do to make it better or more successful. But don't look where everybody is looking because especially if you're looking for me to give you the answer, you're probably not Elon Musk. And so you have no chance of winning. I think where everybody else is already pouring billions and trying hard. That's one thing. And, you know, but then go for it. I guess there is, I've heard very few people. It's a bit like having children. I've almost everybody chooses to have children does not regret it. Sometimes people who choose not to later regret it with entrepreneurs, if I'm similar, I've rarely found them entrepreneurs later. Like, oh, I wish I'd never tried. Even if they fail, they almost all cherish the experience. So, you know, give it a shot. Don't be stubborn. If you fail, time and again, at some point, get a job, but give it, give it, give it a shot. Luca Ferrari is the co-founder and CEO of Bending Spoons. Luca, we really appreciate it. Thank you for joining us and to our audience. Thank you for tuning in live. We will see you next time. Thank you for having me. This episode was produced by Alison Weiss and engineered by Benjamin Spencer. Our research associates are Dan Shalon and Christian O'Donohue and our senior producer is Claire Miller. Thank you for listening to the Profty Markets founder series. We'll see you next month with another founder's story. Support for the show comes from an engine. Here's the reality. But the company's winning right now aren't cutting travel. And its AI-powered personalization gets faster the more you use it. That's not a perk. 37,000 businesses have joined engine. Now it's your turn. Get $500 from your business signs up and start traveling at engine.com/founders.