Bending Spoons is Eating Silicon Valley | CEO Luca Ferrari

30:49Again, it takes a level of intellectual humility, intellectual honesty, that if you think your vision is right, you're perfect, you already got the whole thing figured out you know let me break the news you you haven't uh not even steve jobs maybe one of the best to ever do it not even him had had it all figured out he failed repeatedly uh so you you you haven't either uh so you want to again probe things figure things out and and i through through that process i think of of approximation of toward the truth um you will expand your competitive advantage basically because most people don't have almost any understanding of the truth most people don't actually seek the truth, they seek pleasure or comfort and they want to just confirm that they're right and they're good.

31:37Just that mindset, that scientific process of approximation toward the truth will set you apart and give you very good chances of succeeding. Now in our particular context, developing this again operating system or this technological platform is just an instance of that process of work, but it's not the root cause or where our culture originates. It's just a manifestation of it. And our attention to talent, our acquisition strategy, everything follows from the same root approach. Again, seeking the truth, refining that model of the truth all the time and adjusting our strategy and execution accordingly.

32:16I was talking to Christy about this before recording, but I think there are some misconceptions of the business model of the company. A lot of people put you in the PE bucket. Some people put you in the product manager bucket. There's also the technology bucket. So of those different kind of angles, it seems very much you're a technology company. Why do you think so many people misconstrued that? Some of the ways we are most different from private equities are, number one, we're not a fund we don't buy to sell companies. We have never sold a material business. We intend to own and operate these businesses forever.

32:50Whereas private equity, for those among the audience who don't know, generally these are funds, they raise money from third parties, from limited partners, and then they hold the companies for, on average, five years and then they sell them. And so it's a completely different approach and mindset to what you do, what you do not do. The second big difference is that price equities, typically they are a financial place where there is a small group of very capable financial operators and they'll buy these companies, they'll make changes often, they change the management team, again, they may touch prices, occasionally operations.

33:23It's a relatively hands-off approach. I'm not aware of many instances in which the underlying technology for that business was rebuilt. The product was dramatically changed. The organization was dramatically changed. At Banishpoon, we... and again, and of course that's the case because a private equity, you have a small team of financial operators, financial specialists, so you just don't have the, let's say, the workforce and expertise to make some of these changes. If you look at the Bennispools organization at this point approaching a thousand people in the core team over two thousand including all the acquired teams.

34:01Most people, probably 60-70 % of this pretty large team are software engineers, AI research engineers, product designers, product managers, growth managers and so obviously these people are not sitting around doing nothing. What does our software engineer do? What does a product manager do? What does a product designer do? They build product and technology. So that's almost all we do. And we implement these very deep transformations in the acquired businesses where we rebuild big chunks of the code base, we are erected a cloud infrastructure, we launch a lot of features, if we think they're useful, change the user experience, trying to make it more more intuitive we experiment tremendously with monetization and and and often reinvent monetization in pretty significant ways what's premium what's available for free the prices the different segments of customers we rethink marketing from scratch or at least in very major ways and these transformations are very time-consuming and challenging they're also some of the most fun parts of what we do and that's where a lot of our returns originate.

35:11So difference number one, we don't sell businesses. Number two, we transform them pretty deeply at the core. And the third major difference is that we try to integrate these businesses pretty deeply all together on top of that shared platform operating system. And we have this core team or centrally, let's say, managed, and then they are deployed into the different businesses and they move very fluidly across the businesses. And this is unavailable to private equity structurally because as a private equity, you want to buy a business and then sell it. If you integrate it with all the other businesses you've bought or most of them, it's going to be extremely difficult, if possible at all, to sell it to someone else.

35:53So yeah, there are similarities, but there are also pretty glaring differences between what a typical private equity does, whatever typical means, because again, private equity is a very diverse world, and what Bennisports does. You've raised little equity and you've fueled most of these acquisitions with debt. I'm curious, how big can these acquisitions get? Yeah, we have almost all of the capital we have deployed toward acquisitions has come from debt or our own free cash flows, that being the majority of the capital. And over time, we have tried to acquire, on average larger companies because I just discussed how hands-on we are, how deep we go into these companies and how much we change them for the better, at least that's what we try to accomplish.

36:45Those transformations take a lot of time and effort. And we find that that time and that effort do not scale linearly with the revenue potential of those businesses. In other words, we don't need nearly as many people, or let me phrase it differently, we can get it done for a much larger business with a relatively similar number of people as for a smaller business. And so given that we don't have infinite operational capacity, we prefer to acquire, I don't know, five or 10 businesses each year, but bigger than 50 smaller ones. So that's been our approach, hence the increase in the average scale of the businesses as a opposed to the frequency of the acquisitions to make sure we keep compounding revenue very rapidly.

37:31How big can it get? Well, so far, we see no end in sight. There is no obvious saturation point. I mean, it's very difficult to tell if and when growth will slow down. I'm sure it'll slow down. I'm having some issues with Google. I don't know if that's of interest for you. Well, maybe in the future. I think it's pretty far away. We have joked, I mean, look, just jokingly, I mean, we have sometimes joked maybe one day, you know, who knows. some of the AOL at some point was broadly speaking you know as prominent and and dominant as Google has been in the past decade so maybe in 20 years but actually like Google a lot I hope they do super well and we do super well you guys operate very efficiently per employee I think the last metric you mentioned was four million per four million in revenue per employee per spooner which is a member of that core team now approaching a thousand people uh if you if you count everybody we have on board including acquired teams it's probably a little less than half of it's still very high but a little bit less than half that number probably but because you know how efficiently and lean you can run a company do you just look at all these big tech companies all these other companies out there and like are you just like what are you guys doing like how do you make of that?

39:02No, I mean, we don't have, it's very easy to criticize from the outside. You know, we, it's quite difficult to run a business, we know, firsthand. And a lot of the, a lot of the ways we manage to create value relative to the previous owners are not available to those owners and those management teams under their particular circumstances. For example, again, a big part of value creation comes from that set of proprietary technologies we discuss it they it would be uneconomical unrealistic for those businesses to build them so they don't have them many times businesses attract very good talent during their heyday and then as they are still pretty nice business and maybe growing but a little bit more you know their opportunity has been saturated a little bit more they're not as cool any longer they stop attracting some of the strongest talent.

39:54Some of the people who are most entrepreneurial, driven, proactive, start moving on to other businesses. And so those management teams find themselves occasionally having to, or more often than not really, actually, having to run those businesses with perfectly fine talent, but not like top-notch talent in many cases. At Bennis Rooms, we have been able to attract, I think, extremely strong talent. We had 800 ,000 job applications in 2025. We hired 300 people. And so we can introduce, add to those teams selectively individuals who are extremely high performance, extremely high agency, very competent in relevant areas.

40:35And that fuels a new wave of innovations, of efficiency. And again, that's not a shortcoming of the previous executive team. It's just they didn't have the employer brand to attract those people. And a lot of those people join Bennispoons because they like the idea that they can rotate over time over multiple businesses and platform teams that enables tremendous growth and keeps it interesting and a lot of career opportunities. So that employer brand can only exist if you structure your company like Bennispoons. You can never achieve it as a, say, single product company. That's to say a second major difference that drives performance and that's not available for those teams.

41:16A third one could be different incentives. If you're running a business and it's just one product, the markets will typically almost, you know, primarily value you based on your organic growth. Is your subscriber count growing? Is your revenue growing? How fast? Because if you're invested in a company, really the upside is in believing that that company grows. There's still value in a flatter company, but there's not a lot of discussion there. It's not as exciting. Multiples compress. So there's this pressure for management teams to show growth at all costs. But if you only have one product or, let's say, a set of products in a niche in the market, sometimes there's not a lot you can do to ignite a lot of growth because maybe that market has been saturated.

42:05The truly big groundbreaking ideas have been had. and having whatever missing one is out there in the universe of possibilities is difficult. And so sometimes people throw a lot of money, whether it's R &D or marketing, just desperately trying to unlock that extra growth and that improved multiple. If that business becomes part of Benny Spoons, we still really like to make it grow, of course, as much as we can, but there is no pressure to grow beyond what's profitable growth because ultimately anybody who buys stocking into Bending Spoons, yes, they like our individual businesses to do well, of course, but the main thesis is Bending Spoons can generate amazing cash flows from businesses and redeploy toward new acquisitions at very high returns, and this, over time, compounds attractively, hopefully, for many, many years.

43:01And so do I care all that much whether that particular business is growing 15 % or 5 % Not really. I mean, I'd like to know, and 15 is better than five, but if 15 is achieved by burning a lot of cash for very little profit many years into the future, I'd rather get five and have all that extra cash being deployed toward acquisitions that are accretive. So often these executive teams and those owners are extremely competent. Otherwise, they probably wouldn't have built successful businesses. Their very structure and context in which they operate puts them at a disadvantage vis-a-vis that business being run within managements.

43:44One thing that I learned through all this is not only are the products super retentive and people might think that, oh, you might be buying this product. You'll be ruthlessly cutting headcount. You'll be making it more expensive. Maybe you'll have churn, but no, retention is still good. And also within this type of organization where you, if you have really high agency, if you have really good ownership in yourself and you can kind of move around, you're giving a lot of that to your employees and they're really retentive too. So you've created two really high quality kind of systems here. Yeah, I think it's a good way of looking at it.

44:22We have businesses with lower retention, businesses with higher retention, but I can't recall a single instance where retention got worse after Bending Spoons took over. Often it's improved, it's at least stayed the same, but ultimately we win by being relatively better. It's not that we necessarily need to buy only businesses with perfect retention, as long as these businesses do better under us than under the previous owners. And so we're, you know, we bought businesses with mediocre retention and businesses with great retention and generally preserved or improved those retention rates. And yes, when it comes to our team members, we are fanatical about creating one of the best work environments on the planet.

45:10And I think, you know, there's a lot we could improve and no doubt about it. We've put plenty of flaws, but we've done pretty well there overall. we have had essentially no unwanted churn of spooners, of these people, part of the core team. Last year, we had 0.6%, so 0.6 % were most companies in tech, as far as I can tell. 5 % is considered actually pretty good. And a lot of that super high retention comes from the excitement of being able to learn and grow across all of these different challenges. It keeps it fresh and interesting. Whereas if you're working on, say, Evernote, maybe it was exciting the first couple of years, let's say our product manager, but then after a while, you know, refining and refining, note-taking, it can grow stale.

46:02But what can you do? You like the company, but ultimately you have to look for a different employer to take another step, learn something new. At Bennis Pumps, you just raise your hand and say, I feel I've exhausted my creativity and excitement And for Evernote, what else can I do? And we may put you on a platform team to build an internal technology. You could move to AOL and trying to improve email UX, which is a completely different and fascinating challenge. So yes, we have been able to retain people very effectively when it comes to the retention of teams that come on board through acquisitions.

46:37I was quite worried initially that a lot of people would feel disheartened because we got acquired. Sometimes this is perceived as a failure, even though it's not. It may be a success, meaning that you actually got a nice exit. But you may feel that you're not as important as the core central team. I think there, too, there is a lot we can improve, and we value these teams, and we're trying to do better. But overall, I think things have gone a lot better than I thought they would. We have an excellent relationship with all team members. Retention rates for those team members, in no case are they lower than pre-bendispos.

47:20Sometimes they've improved substantially. So at least we're not damaging the quality of those workplaces, if anything, in many cases improving it. But those retention rates are not as high as those we have in the core team. They're more in line with what I said before that's considered okay for most technology companies. What would you say is core to the culture here? So, I mean, there are several things, but probably the one or two that truly stand out as particularly distinctive. One is something called extreme ownership. We want everybody to care deeply, tremendously about being amazing at what they do, about helping their team and the company succeed.

48:06We'd rather work with slightly less intelligent people if it comes down to that, but they have to really care. We don't want to work with anybody for whom doing well here, seeing the company succeed is not our super high priority. And the second aspect of our culture that I think is unusual is that we are highly scientific in how we approach the work. again first principles being logical being rational being enthusiastic and putting a lot of effort into probing again reality so that we can refine that model of the truth we do a lot of that last year alone we ran more than 3 ,000 experiments across our products.

49:02And those are just the ones that are like super quantitative and recorded and documented. Of course, there are a lot more initiatives that maybe don't qualify as a perfectly rigorous experiment, but they're motivated by a desire to learn and understand things better. and that building Bendis Pus as a learning machine has been instrumental to, in general, succeeding, but specifically being able to expand the competence circle so that we can successfully acquire and transform and drive returns from a broader and broader set of businesses. If you look at what we were acquiring when we started, it was very simple iOS apps, very basic, and then more complex and larger iOS apps and then Android apps and then web products and then we went from sole serve to now substantial enterprise sales organizations and we even did like I mentioned earlier hardware recently with Tractive and I mean it's early so but it's going really well so we try to to keep expanding the share of the world that we believe we understand and improve that understanding continuously.

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51:38Set up payroll for any country in minutes. Hire anyone anywhere. Get visas handled fast. And get back to building. Visit Deel.com slash sorcery. That's D-E-E-L dot com slash sorcery. So, talking about the culture and how you've built out, where do alt spooners come into play? Yeah, old Spooner as an ALT alternative or alter ego is just one of those 50 plus tools. Something that we developed this year and it's been adopted very enthusiastically across the company. Basically, we built this. It's really like an agent that lives in Slack. At least the interface with Spooner's members of the core team will be looking to deploy this across all of our team members.

52:27but you interact with it on Slack as if it were any other colleague. And you have one old spooner. You can name it and give it a profile picture and all that. And automatically that agent will have exactly the same level of access you do across all of our platform. So if you have access to certain code base, it does too. if you have access to a certain customer support tool with a certain you know level of permissions it does it does too and I can basically task this agent to do stuff for you and it could in principle do pretty much anything like anything you can do in principle it can do obviously AI is not perfect so some thinks it's better than other things.

53:19And it's fully integrated. So it's basically, I don't think you can really achieve this at all with third-party solutions because they, as impressive as they are, you're never going to be able, I believe, to, at least not in the foreseeable future, to integrate them as deeply across the board and to tailor them specifically to what you want. And by the way, if you do, then you're, I don't think you can, but even if you could, then you'll be locked in with these vendors which is dangerous because you know you'd be completely exposed to massive increases in prices potentially in the future. So partly with Allspooner we achieved I think much better effectiveness because it can do a lot for you in a very efficient way and I'll give you an example in a moment and partly we achieved good separation and very low levels of dependency from any provider of AI infrastructure or AI models.

54:12So examples of what Allspooner can do. It can do data analysis for you so I was looking last night I was looking at the results of you know certain A-B tests on StreamYard which is one of our products and normally I would have had to ask someone from the team a data scientist to pull the data out prepare the analysis or at least do some of the work for me I you know I can do my own data analysis but I would have needed someone to do some of it and certainly would have taken either me or this person multiple hours and I simply chatted with this with my old spooner and I told it oh please you know go and and do this or that and maybe five minutes later I had the analysis it was I was actually very positively impressed it gave me plots with you know highlights very detail-oriented and nice or if you're running one of our businesses you can and I saw this first hand multiple times you can go to your old Spooner and you can tell tell it that you saw a bug this happened it's a real thing that happened with Evernote I the general manager of Evernote told her old Spooner that she had encountered the bug as well she was using the app and and and test the agent to check on our customer support platform that whether the bug was was widespread among users or her report was the only one and then to go into the code base identify the root cause code a fix and ping the engineering lead for for that project to review the fix and push it to production so maybe she she spent i don't three minutes to provide these instructions and then I'm sure the engineering lead had to spend maybe an hour or two reviewing the code but the bug got fixed and this is something the same day and this is something would have taken weeks probably between back and forths in different people and and wait in a lot of hours of actual human work to get it done so thanks to this and many other technologies we built were probably two three times as productive easily and the list is long but this is roughly what to expect now the potentially from a business perspective even more interestingly Altspooner really helps us as I said stay independent of providers we have built our own orchestration so every time you task your agent with something under the hood we have an algorithm that will select the most appropriate AI model or multiple AI models to get the job done considering say quality effectiveness but also cost and it can draw from many many different models.

57:03We end up using open weight models we self-host so these are basically free I mean there is a little bit of cloud cost but for 99 % of the requests and tokens and the frontier models generally closed wait through API's for I don't know maybe 1 % of the requests only for the most complex tasks or for supervision. So they will, sometimes we use them again automatically to check the work that got done by the slightly less intelligent models as a more senior engineer would with a more junior engineer, but that's way cheaper than actually doing the work, which is often perfectly fine. And even if it's not, the smarter model will provide a few pointers and then the less smart model will go and fix it.

57:47So because of this, we've been able to stay independent of any one vendor and keep our costs for tokens super low, basically negligible at our scale. Wow. When did you start deploying these AI agents? Also, your point on not having a third party is very counterintuitive to all the marketing that's going on right now with all these AI assistants and applications that are coming out. We work with all the big labs. They offer great products. We use them enthusiastically. I'd like to think we're a good customer, but But we don't want to be dependent on any of those specifically if it can be avoided.

58:23And there are solutions out there that are much cheaper and often deliver essentially the same quality. But it takes, I think, strong engineering capabilities and the right culture to be able to harness those possibilities. Obviously, the easy approach is hand over the keys to one of these companies and buy their more expensive product. It will make you come across as AI-enabled faster and more easily, but it will be, I would say, much less effective, but certainly way more expensive. Literally orders of magnitude more expensive. I don't know if you saw this, but Jensen just declared we've reached AGI with OpenAI's ASTRO model.

59:09Yeah, some people say that. Maybe true. I mean, I don't even know. I've heard different definitions of AGI and none of those is super unambiguous. So I don't know. Nobody can tell. But it's obvious that it's very smart. Whether we should call it AGI or not, I'm not sure. Nor do I care too much, to be honest. I don't think that AGI, even if we can describe it very specifically as a threshold, I don't know that crossing it is a particularly, like the moment we cross it is a particularly noteworthy milestone. You could easily, you know, people sometimes define AGI as AI can do everything that any human can do but better.

59:57I don't know that that's necessarily more exciting or scary than AI can do. 95 % of the things that humans can do, AI can do just as well or better, but 5 % it can't yet. I think this is almost as exciting and almost as scary, depending on what the 5 % that it can do is. But assuming it's not handpicked to be the things that keep us in control, but just a random set of tasks, our brains happen to be more capable at. So I'm not too keen on whether we pass the AGI thresholds or not, but the trajectory is clearly one where AI does things better than us, increasingly so both vertically, so the gap in how much better it can do a certain task is growing, unsurprisingly, but also horizontally, like the percentage of tasks it can take on and do better than humans is increasing.

1:00:53So I don't think there's any stopping that short of some sort of world war where we regress to the Middle Ages. Well, it seems like now the next benchmark is RSI. And that, with it, comes a lot of fear-mongering for cybersecurity and cyber risks. Yeah, I mean, it's a very fair fear. I'm equal parts enthusiastic about AI and absolutely scared shitless. I think this will be this could be it could definitely make a case for this being the great greatest boon for humanity ever by orders of magnitude Possible yes plausible maybe I'm not sure Equally it could be the thing that wipes us out or creates equally awful scenarios

1:01:41And what's like I don't think humans of course want the latter the point is can we control it and and and even before it's so powerful that controlling it is all that matters I think we well we are approaching that point but maybe we're not quite there yet but but regardless before that can we prevent it from falling into the hands of like some sort of degenerate or evil person because you know similar to nuclear weapons but potentially worse I I think because, I mean, I'm no expert in nuclear weapons, but I think, number one, it's very difficult to do irreversible, widespread, massive damage with nuclear weapons, such as almost wiping out humanity without killing yourself in the process.

1:02:32You could use AI to your benefit while causing immense damage to everybody else. I think it's easier because it's much more surgical. So can we do that? I'm not sure. it's pretty scary. The accessibility point, yeah, the accessibility point I think is the most alarming because it's literally accessible. The barrier to entry is so low. Yeah, I think that, but also something that really bothers me is that we don't know how smart AI is, and the smarter it gets, the less we know. Because in general, intelligence is difficult to truly measure. it's not like height or weight or colors where we know it's objective and so it could be a lot, it could be less, we know, at least we know.

1:03:22And the smarter an entity gets, the easier it is for it to hide its own capabilities if for any reason it's the appropriate thing to do whatever objectives that entity has. Additionally, it seems to me, I haven't heard anybody talk about it, but it seems to me that AIs are, they come across as inherently low ego, like they don't brag. If anything, they tend to be humble about what they can do and they warn you that this may be wrong and you double check it. And I'm sure this is mostly the way that being programmed because it's a lot more embarrassing for a frontier lab to have an AI claim, I solved your equation and I'm sure it's right and then there is a clear mistake.

1:04:03As long as they disclaim I may be wrong, double check it, it's a little bit more acceptable. But it doesn't strike me that these AIs, these AIs don't strike me as they are likely to boast so that our perception of their capabilities tends to exceed their capabilities. I think they'll probably only show us what we ask them to show us. If even that, like I said, they could also conceal their real abilities. But even if they're well-intentioned and honest, I think they'll tend not to show us more than we ask them to show us. And so I believe are in time, our understanding of how good they are may tend to be a little bit less than they are.

1:04:39Like we may underestimate them basically. And that's very dangerous because as you approach a threshold of real danger and real potential, even a modest underestimation of their capabilities could be catastrophic. Look at exactly to your point, the cybersecurity incidents that happened, most people were shocked, even many researchers. And why were they shocked? because they didn't think this could happen, right? The level of lateral thinking and call it perseverance that these models and ability to collaborate among them that these models showed was beyond what most people thought was possible right now.

1:05:18So what's to tell us that we are not ignoring plenty of capabilities that simply haven't been probed, these models haven't been probed to display? And, you know, in a year's time, I think the problem only gets worse. It was crazy. I was I don't know. I'm I'm thinking a lot about the opening. I hugging face incident. And I was reading through the reports. There were like two different research organizations that put out reports on it. And there were like different civilizations and they all passed through different ones to get to the next one and all behind the scenes. And it was just a crazy situation that I don't think is really talked about much.

1:05:57But I'm curious, where do you get most of your, like, how do you research most of the stuff in AI? How do you stay on top of it? Well, I mean, mostly by doing, we are very active. We rarely, we have built our own models, but it's mostly narrow. We certainly don't compete on the frontier models. We sometimes build narrow purpose models to do something very specific. And if you have a very specific use case, you can often build a model that's just as good as the frontier models at that very narrow time. It's awful at everything else. It may be completely incapable of doing anything else, but at that one thing, it can be even better, and if not, way cheaper.

1:06:35So, for example, if you use, I don't know, Meetup, the events product, we own it, and the recommender system, the system that once you search for something or you're looking for inspiration will determine which events and groups to show you, that's built in-house, and to the best of our benchmarking and knowledge it's just as good as if we were to use like some of the frontier models which obviously comes for essentially for free as opposed to these models being very expensive. So we do some of that. Most of our work is studying third-party models, sometimes fine-tuning them if they're open weights, certainly combining them and leveraging for the different activities and optimizing which ones we use for which activities as I was describing before.

1:07:17So we're very hands-on in the field and therefore it's relatively easy to stay abreast of advances, but I will say I've never seen any industry or new technology progress as fast as AI has over the past, especially the last three, four years. And so I feel that, you know, I make an effort to catch up this week and maybe for a few months I need to focus on M &A or something else, then I feel like I'm completely outdated on my knowledge. So it is quite, it's exciting. I'm an engineer at heart, but also, like I said, particularly as this is quite dangerous, I think that speed is not, I mean, it's not ideal.

1:08:05I'm curious. What do you think the question is about AI that people aren't asking? Oh, the people aren't asking. I mean, I don't know. It seems that people are talking about it so much that they've asked all sorts of questions. I think it's maybe the main issue is whether we're answering these questions in a satisfactory way. For example, I think most people agree that this is scary in many ways. And yet, frankly, I don't think anybody has done anything truly meaningful to make it safer. And I mean, even the labs themselves, I'm sure they're investing in safety. I don't know enough. But they're rushing to be market leaders or they're dead.

1:09:04Their valuations would probably drop 90 % if there was a perception that they're losing ground. And so, you know, they're trying to survive and thrive this year, next year. And so I'm sure, you know, there's more they could do, be more cautious, but that would come potentially at existential... It would drive existential risks for them as companies. Governments, I don't know, they may be talking about it, but I haven't seen anybody do anything meaningful. The EU created the AI Act, which I find to be, like, highly harmful to the industry. and solves none of these problems, like the real existential threats to humanity doesn't really tackle those.

1:09:51So maybe an interesting question that people haven't asked, at least haven't heard being asked, is why are we failing to do something about it? Because people are asking what we should do. Nothing is happening. I haven't heard a lot of people say, what's currently preventing fixes to being proposed and deployed? You know, what's the root cause of this inability to do something about it? Because if we were to fully understand the root causes, then maybe we would stand a chance to do something useful. What's been the biggest difference, you're a global company, the biggest difference in perception and application of AI in Europe versus U.S.?

1:10:33And I also apologize. I'm totally taking up all of the air right now with these AI questions, but I understand I have a very intelligent engineer in front of me, so I'm going to ask them. But what do you think is the biggest difference between the perceptions and actual applications? Well, I think there are, like, every time there's something moving very quickly and being newsworthy, there is a lot of exaggeration and misunderstanding. I think on the one hand, some people think AI today can do more, And this is typically people who don't really use it, but mostly read about it. They think it can already do everything for you, and it's a lot more advanced than it is.

1:11:12And as impressive as AI models are, I think today they still have very glaring limitations across most use cases. So I don't think we're at a point where you could hand over the keys of your life or work to AI, and you could actually trust it to add significant value. I think there will be a good risk that things could go awry. but I mean the trajectory is certainly very promising. Then there are people who rightfully fear that AI will destroy jobs and I've changed my mind at this point recently but it's certainly a very important topic but rather than thinking of proactive ways of protecting prosperity and people more than workers people they go on the defensive and they try to come up with these more protectionist regulation or approaches, which are obviously an awful idea.

1:12:07Because a country that doesn't embrace AI, unless every country in the world stops progressing in this field, which I would say we could put in the bucket of the impossible things pretty much, again, short of a world war, a country that does not fully embrace using AI is destined to complete irrelevance and basically, you know, becoming third world in probably maybe even just a few decades. So that's a certainly a dumb approach, although it's a populist approach and as such, it can help occasionally get votes. Yeah, maybe those are some of the more, you know, remarkable extremes I've seen, but there's, I mean, we could talk about it for a long time.

1:12:51We could talk about it for a very long time. We have to get to the walking portion, but before we do that, I just want to ask you, what are you most looking forward to in the next 12 months? Well, I mean, there are many things, but I'd say probably further progress in our in-house technologies, especially taking advantage of AI. We have very, very big plans, and we're seeing massive progress. I do think that, you know, we talked about it before, Bed and Spoons, you know, the central team, $4 million in revenue per member of that team, and this has grown tremendously. It was about$1 million just two or three years ago.

1:13:34I think we're about to see this keep rising pretty fast, and a lot of that, some of it is scale, just bringing together this business and integrating them all together creates tremendous leverage, but a lot of it will be technology. And so I can't wait to see some of the things we're working on and we have in mind actually come to fruition. I think it'll be extremely exciting. We try to constantly reinvent what running a business effectively, efficiently looks like, be at the cutting edge of that, so that we can then go out into the world and buy businesses for really good prices for sellers and deliver high returns.

1:14:12and the technological aspect of that progress is very exciting to me. Amazing. Well, thank you so much for hosting us here today and having us at Bending Spoons in Milan. This is amazing. And I'm so excited for all of the other conversations we're going to have with your team. Thank you so much. Thank you. Hey, it's Molly. If you enjoy our interviews, check out our newsletter, Sorcery.vc, where we deliver a once a week top deals and tech headlines email and also go deeper on our podcast interviews. Subscribe to Sorcery today. And don't forget to subscribe to the podcast on YouTube, Spotify, Apple, or wherever you listen.

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