Inside CVC: The Moat Is Dead: Yariv Adan on Data, Defensibility, and Life After Google

Yariv Adan spent 17 years at Google leading Google Assistant, Google Lens, and the commercialization of Cloud AI's conversational and generative AI products before becoming a venture capitalist. He joins Philipp and Steve to argue that the old AI moat, being fast and owning proprietary code, is gone, and that proprietary data is now the only defensibility left. He explains why he looks for founders who have already proven they can hire, fire, raise, and scale, not just build, and why roughly 60 percent of his portfolio are repeat founders. He makes the case for corporate venture capital as a distribution advantage rather than a speed advantage, and pushes back hard on founders who mistake a successful pilot for a signed contract. He also explains why disability-driven AI products can be a real, large market and still be the wrong business for venture capital to fund. A direct read on what actually holds up once the code stops being the advantage.

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Introduction

Welcome to Inside CVC, the podcast that brings together leaders in innovation and capital investment to explore the trends shaping the business of corporate venture capital. I'm your host, Steve Schmith, and together with co-host Phillipp Willigmann, we're speaking to corporate investors, entrepreneurs and ecosystem builders driving the future of innovation. Inside CVC is brought to you by u-path Advisors, helping corporations and startups unlock sustainable growth through strategic partnerships. To learn more, visit u-path.com. That's the letter u dash path dot com. And to catch up on all of our episodes, search Inside CVC wherever you find your podcasts. 

In this episode, we sit down with Yariv Adin, general partner at Ellipsis Ventures. Yariv spent seventeen years at Google leading Google Assistant, Google Lens, and the commercialization of cloud AI's conversational and generative AI products before becoming a venture capitalist. In this conversation, we talk about why proprietary data is what holds up. Once coding stops being the advantage, why he backs founders who already hired, fired, raised and scaled, why corporate venture is a distribution advantage, and why a successful pilot is not a signed contract. We close on the biggest mistake investors make when they think that they have found a strategic, defensible moat. Here's our conversation with Yariv Aydin. 

Interview

Yariv, thank you for joining us on inside CVC today. How are you? Good. Thank you for having me. Yeah. Looking forward for the conversation. It's going to be a wonderful conversation really around topics that we talk a lot about on our weekly show. Let's start a little bit with your background. Seventeen years at Google, Google Assistant, Google Lens, all under your leadership and management. What was the moment that made you walk away from those exciting areas and get into venture capital and actually writing checks? Um, so I actually knew for a long time when I worked at Google that, um, if I ever work again after Google, which was a question for itself, um, it will not be in another company. Um, I just felt that when you work at Google, especially in relatively senior positions, you work at a scale that is often qualitatively different than, than anything else. And that scale changes, you know, when you work at large scale. None of the textbook solutions work. All the edge cases actually materialize and more. And you constantly are pushing the the front on what's possible. And I just found that like, okay, going, even if it's my own, going to something that is smaller or smaller scope would not be as interesting, especially after thirty years of building software and deploying software in different positions. And I always knew that actually this is I was looking, okay, what kind of alternatives allow me to do that scale and to do the things I love with that scale, like think about hard problems, continue my learning curve and learn very, very quickly. So actually VC has that, right? So, you know, we're dealing with many companies, different founders, different leaders, always at a very high strategic way. But also we were very hands on in helping hire, helping on the product stuff, helping deal with problems. And then we, we touch all possible industries. We're doing robotics, we're doing biotech, we're doing AI, infra medtech. So you need to learn a lot to understand very quickly. So so to me, it's, it's a progression and it's almost like a natural progression. A lot of the things that I learned how to do at Google and across from building and leading organizations to, to identifying an outlier talent to building AI to commercializing AI, um, is very handy and very, very useful. So it was very natural. And, and I love doing something different. You know, I'm definitely learning and I'm still a toddler in the VC world and it's fun to, to learn and start over. So what is that vantage point sort of give you in terms of identifying real innovation from hype? You write the dual view of being inside the lab and now being in the investor. What sort of view does that give you of the ecosystem of the landscape? So I think it gives a bunch of things. First, everyone talks about that. The most important thing when you invest in the early stage teams is the team. But if you never worked with the top zero point zero zero one percent and you know, and worked closely and learned that there is a lot of flavors over there, right? Like then do you really know what outlier talent is? Right? Like many times I see it a lot. You know, people are saying, oh, you should look at these companies are like from DeepMind. And I know like DeepMind was like, you know, tens of thousands of organizations at the moment, eighty percent or more. Google wouldn't make even as a team leader because they lack the necessary skills that are maybe amazing researchers or engineers, but they're not. Team leader. Would you invest in someone like that as a company leader? Not necessarily. Um, so really knowing what is outlier talent, identifying outlier talent and knowing how to work with them, because I've actually, I've seen like, sometimes these people are not easy. Sometimes, you know, people are talking about that in AI. Intelligence is kind of a, you know, very jargon, right? People intelligence as well. Some people are very, very good geniuses in some areas and are complete like a three roles in other areas. So how do you work with someone like that? Whole area of identifying talent, working with talent, mentoring talent, having managed them for for twenty years is a, is a huge advantage. Yeah, it's a pleasure to have you on the show. Thank you for your time. I want to dive into this a little bit further. In last year at the CVC summit, you brought it up already. And I think, um, you said it in a recent interview that code and speed is, is no longer the real mode in AI and that everything is really about data and what you call the expertise mode. So can you walk us through that, what it actually means, um, when you back companies in that space. Yeah, right. Like we've seen it happen to muscles, right? Like, you know, the moment we switch to machines and to cars, how strong you are, how fast you can run, less of a difference, right? So, um, when you are depending more and more on, on a, when factory AI plays more and more factor in how quick you can move. And basically the field leverages. And it's not that you don't need any engineers at all, but you need many, many less engineers and you need it before, right? So it's not about you cannot move as quick, depending on how many great engineers you can hire, right? So you have many more that are like at the forefront of weakness, right? So being quick is not as defining, right? Like that peak is now like a table mountain that I think is getting wider and wider. So in the past, two things were very critical. One is because moving quickly, you know, it wasn't like the speed of light, right? Like if you had a six month advantage, it was hard to close that gap. And the second thing, things were extremely sticky and complex. And I think two things changed. One is you don't have now any more six month gap because we're seeing that very complex thing. Devin, when it came out, seemed like science fiction. People were sure that they were, you know, twenty four, forty eight hours open. Devin. They came after us and others as well. Right? So actually being quick is not enough. Not that it's not, you know, it's necessary. If you're not quick, you will die. But it's not like, you know, a huge advantage. And, and the second thing is the AI stack is much less sticky than the Sarsstock. So actually moving stuff out, replacing harnesses, replacing models, replacing agents. You know, companies themselves are actually rebuilding themselves every time. And the funny thing is, when we see founders speak, they are saying, hey, you know, we're two people. And within six weeks we have this. So many times I'm saying, yes, but what you're saying is that someone else can do the same. Like, how are you? What is unique in you? Right? Like so that advantage. So, so, so I think like, in that sense that that moat went down. So you ask yourself, um, what, what would you know, you have a solution somewhere. What would prevent someone from replacing you or at least forcing you to, to compete on price? Right? Because my other point is if you're building something that is not very defensible and differentiated, eventually you will compete on price. I think one thing why we haven't seen it so far is I think because procurement is still mostly done by humans, and I think it's a very inefficient and erroneous process where people are making decisions where to buy based on very uninformed decisions. And also a person can make only out of two three their ability to find and assess who else builds that around the world and who is better is very limited. I think that very soon we will see a genetic procurement of software and a lot of it transactional. And then basically it kind of, you know, I want to to do X and you will start seeing just by the model, the model in a way is already a small marketplace. You are asking it and telling it, here's what I want and do it right. Like actually it can delegate some stuff there. Maybe the model will itself will price it differently. But I think once you do that, if you are not doing something unique and you are in an open marketplace, you will compete on price. So either it's easy to replace you or you're competing on price. So the question is, okay, in such a world, what is defensible to allow you to do margin something that not everyone else can do or it will take time, or maybe a smaller amount of teams can do it. So there is a place to margin. I think that it boils down to two things. One is data. If the problem, not the solution. If the problem requires unique proprietary data that not the model and not anyone on the planet can easily generate simulate whatever you know that data. Then you have a mode because you're doing something that others can't. Or if someone comes and switches you, there is a switching cost because quality degrades or the ability to do degrades. And this is why also like, you know, many times it's not about from the beginning, you have a that data mode, but if you have a foot in the door and there is a very clear path to some data flywheel, so that when I look at your product thereafter, it's very clear to see that it's better. And if someone comes, there is a very tangible switching cost. That that's a good moat. And it's very hard to do it because at the end, the customer owns their own data. And in the past, you know, building and running data pipelines and stuff was very hard today, again, using AI, it is easier. So even though it took you a year to, to build up data and improve, if I can run it now in a batch in a week or two, that's something, you know, a competitor, a competitor can do it. And I think over time, with enough pressure that that happens. So, so really, it needs to be okay that you actually added something and you actually train the model or did something non-trivial that you own, not the customer. Right. So this is a kind of things that we look for. So if we kind of talk about competition for a moment and you know, you you're in Europe obviously worked for a US company, and we have a lot of guests on the show. We're talking about, you know, the competitiveness of Europe versus Asia and the US. So if you look at this in Europe, what what opportunities do you see for European founders and startups? Is it the data richness we have here in some corporations and family businesses they can leverage? Or what do you think is kind of like the opportunity for Europe to build out a leading position in the AI space. So. So I would look at it a little bit. I think it's easier to talk a little bit on Israel as a model. You know, Israeli founders, they don't have any advantage of being in Israel. Now there is a little bit of a enough unicorns and stuff that you can actually find friends and whatnot. But like, you know, until five, five, you know, so they were like, they were just global, very strong entrepreneurs that happened to live in Israel. And these are the kind of people, honestly, that we are looking for in Europe. So we are not looking for people that are actually trying to build a product for Europe, in Europe. We are looking for people that are looking to build a global leader, and they just happen to be in Europe. And the advantage in that sense is that Europe has some outstanding universities. So, you know, there is a lot definitely in the deep tech and whatnot. You know, there is talent that is coming out of it. And there are also some very good companies here and some, you know, good startups here that, that were that actually you can also get some good experience. So, so, so, so I look at this like local talent that is supposed to be building global products. And. I generally don't like companies that come and say, we build for that and whatnot. Like I think, I think it's very hard to start from a regional product and become a global leader. We've seen many times the opposite direction where global leaders actually push out local players. And so so that's the type of things saying that, you know, there are definitely a great automotive and other companies like, you know, yeah, there are great customers here and it's fine if you are like working with them, especially the global players. And, and that's completely fine. There is a lot of industries where there are global leaders still in Europe. And but yeah, we are looking for is the best talent in Europe that can be built. The top companies in the world. Yeah. And that you can find them. On that note, we've had a couple of conversations lately about that sort of talent coming to Europe, maybe even born and educated in Europe. But then they leave. How do you keep them to stay? Well, there is a multiple questions. And again, you know, going to Israel as a model, I think it's fine actually. And I think it's actually good for Europe, for founders to build strong companies, go out to the world winning the world. Some of them we lose, but actually many come back, you know, definitely Europe, quality of life, culture. You know, a lot of people want to come back and a lot of people that are successful want to give back to the university, to the community and whatnot. We see it everywhere in the world that even even if people leave often, you know, they invest or they do something. So, so I wouldn't worry. I think strategically we should worry about how do we build more global leaders from Europe and work less? You know, we shouldn't worry. How do we keep them when we don't have them? Let's create many of them. Let's open that funnel. Then look at the funnel of what happens when the money comes back, where investors. But that's like a secondary problem. I think the key problem today is how do we have, you know, the ambition and the experience? And, you know, for example, I see it very clearly. I know that the Zurich ecosystem quite well. Everyone is talking. It's a very hot ecosystem in Europe at the moment. And the good thing is that ETH is an amazing university with some amazing programs. Google brought here a very large number of like five thousand or six thousand engineers. And many of the startups and the VCs in Zurich actually have at least one one Googler or whatnot. So but you still see the, the immaturity of the startup ecosystem in, in Zurich and especially since, you know, I actually grew in Israel, I had a startup in nineteen ninety eight. And then I saw that ecosystem grow. And I see parallels to the early days. And first, the ambition, right? Like success in Zurich is to sell your startup for three hundred or four hundred million dollars, right? You know, very few actually are kind of I want to create a company for generation or IPO or whatnot, or even unicorns, right? Like still selling for three hundred, four hundred is considered a success. We're seeing a, that companies are living for too long. You know, there is somewhere I saw even someone very proud that the average life of a company in Zurich is ten years. And I'm like, yeah, but this company should have died after a year and a half. There's just not too much stupid money that keeps them alive and people are afraid to fail. The investors are afraid to fail. So instead of actually, they should have been now at round three of their third company, they would be much, much better rather than tenth year of something that should have died. We're seeing a lot of companies that come out of academia without anyone from the industry. So it's kind of a PhD idea. Looking for a problem. And these are all kind of great substance, but lacking maturity. And so I think like, for me, and I don't think that that's unique to, to Zurich, I see it a lot, you know, in the two other ecosystems that are relatively young. And I think like in Europe, we should really think, how do we mature, move quickly, make sure that we generate more large, ambitious players that are not looking at that, looking globally, knowing how to build it. Combine science and expertise and technical expertise with commercial expertise. How do we have, you know, sophisticated local money invested in them? And then we should worry if we do that and we see that afterwards, everyone goes away. Okay, that's a good problem to have where I'm still waiting for that problem. Yeah. It's just such an interesting point of view and take on that on that topic. Thank you. Um, let's turn a little bit about or let's turn back to corporate venture capital. That is largely what the core of this show is. You talked earlier about keeping your eye on edge cases from where you sit. Do you believe that corporate venture capitals are really a source for edge cases in early AI startups? So so we work with some corporates. So most of the corporate VCs that I'm in contact with don't invest as early as us. Uh. And I think, uh, so I wouldn't generalize, right. So, so I think that, that, that's like one question. And I think like, it depends a lot how much they're independent versus non-independent. Often it has to do how well is the corporate doing? Right? Like when everyone is rich and happy, there is a lot of freedom and openness and creativity. And when there is less so it's becoming a more strict. I think it's a very interesting and important source of capital. I think there is like very clear pros and cons. I think the connection to the industry, uh, is critical at the end. You know, most startups commit suicide and then the others die and go to market, right? Like, so actually, uh, if you are a corporate venture that actually helps them go to market, that's a huge advantage. Um, clearly there are different from people like us that are completely independent, you know, and the tools we use and the decision making, right? Like speed and whatnot. So I think like a. To take a founder perspective, I think you should understand that that not all VCs are the same VCs and you should choose smartly, which this is a, you should talk with one optimized for conversion. So basically look for a VC that already invested in your space and your kind because you're not going to be the first company they will do. So I think that that's one. And then think if you are looking for additional added value, like connection to a certain sector, then, you know, corporate VC is a huge advantage. I would also always speak to startups that that VC invested into here really. Everyone said they will help you and whatnot. Some do, some don't, and not just in corporate venture. So yeah, so like, you know, as a founder, I would say, do your homework, understand the differences between different VCs and understand the difference between boutique VCs to the very large multi stage VCs to corporate VCs. I think they all have a place. And yeah, so I think there are good and bad in every category. Yeah. You mentioned founders in your portfolio, I understand is roughly about sixty percent of repeat founders. I'm curious. What do you find that's different between people that have gone through the process before versus founders, first time founders that might be in all other ways. And I think like the clear downside of experienced founders is like, you know, the biggest question, how hungry they are, right? That's one thing that like, you know, do they really have it to put it all in? And we're like, you know, when shit hits the fan, it's like super hard. Will they stay? You know? Is that something burning in them or is it like, you know, kind of a nice way? And I have learned that the, the biggest difference between amazing people and great people and good people is often not in how good they are the first time, but how good they are the second and third time. Like the really good people, like, you know, they've learned and now they are amazing. And other people are like, you know, they've learned nothing, or they learned all the negative stuff or God knows, you know. So so it's not like blindly, but but I think that if you go to someone that first show that they can do it, right? Like one of the biggest questions that you have when you see a set of founders is like, can they really build and scale a company? Can they hire, can they fire? Can they raise, can they build a organization? Can they talk to like, if you have someone that actually demonstrated that they can do it, you know, that that goes away. They also know what they are against. You know, so very rarely you see stuff like burnout or fights amongst the founders and so forth. You know, they have many times the networks, right? So often it's not just repeat founders, but founders in an area related to what they've already done. So they have the credibility because, you know, many problems of startups is credibility and distribution. And if you are a repeat founders, often you know that that's another advantage. Um, so yeah, so basically we know they can do it. They've done it before and learned and improved and, and they bring some assets. This is a, some of the advantages that we see and yeah. And I think, yeah, sure. Of course there is also. And we have some of the companies that where we, we saw like, okay, super amazing young people that we think they demonstrated outlier already early on. And then yeah, it's a, it's a different risk. Yeah. So, um, we talk a lot about, you know, AI startups and doing great pilots, uh, with, with, with their customers where you sit today. Like what, what do you think really needs to happen to move from a lot of these pilots to use AI to create real value? Um, especially, you know, within the organizations and moving beyond just pilots, what do you see as like the biggest, The biggest, the biggest wall we are running into right now. So, so many. And there's two different things, right? Like if you were a someone from a corporate and asking me, how do I move from, I would tell you, don't worry about that. Develop your muscle like a new world is coming. You know, you used to be in the desert. You are going to, to live in a, in the ocean. Start growing your fins and whatever fish parts you can grow. Don't worry. How, how much does it cost and whatnot? You're going to die. Otherwise the threat is not the wasted money in the process. The threat is that when the water comes, you're not ready and you don't have it. So so from I think that from a corporate wasting stuff, you know, wasting, you know, there is always a learning curve. You know, you go to university, no one is talking. Why am I paying for eight years in PhD so much money? Where is my ROI? Wait, the ROI will come, right? So so so I think the ROI for corporates in learning, developing the muscles in the systems data. There is at least two or three years for a company to be AI ready, and they cannot read about it. They need to do it. They need to do the mistakes. They need to hire people. They need to change leadership. Now, on the startup side, um, yeah, you want to make sure you are not there. So the first thing that I would tell you, and that applies for pilots or very long sales cycles, I learned that products come in three flavors, painkillers, vitamins and viagra. And, and viagra is great. You know, you can be, you can do amazing things. You haven't done that. No one has a budget for viagra. So like the first thing you should ask yourself is, am I a painkiller for this? Because especially in a world where everyone is willing to try and pilot, that's like so seductive, but no, am I actually solving a pain that they were looking for a solution for it? Because if not, anything beyond the small pilot is going to be super hard. Second thing is, and this is like, you know, kind of go to market one hundred and one, who is the champion of this deal? Does that champion has a say on spend? Does that champion has a budget? Is he signing the check? Right. AM I actually talking to selling. You know, what do they care about right. Like, you know, am I selling the right thing to the right person? Because it's so easy to find people that have either, you know, pilot money and or whatever. There is no actually executive support. This is a local. And when the person moves or loses interest, there is no champion in the organization. Right? So you need to make sure, especially as you go to a large corporate, who is the VP or above. How important is this pain compared to other stuff? Was budget allocated? When is budget allocated? Right. I kind of of hygiene to understand whether you're even on a path. The third thing is also to, to have a deeper understanding of, of budget. You know, if you come and are saying there is an existing budget that is currently spent on this problem, and I come either with a solution that comes and said, I can do the same thing for less budget, or I can do a much better for the same budget. That's usually an easy sell. If you're coming and saying, oh, you guys now need to find new budget for this thing, but over time it's going to to do this and that and that that, again, that's very hard to convert in the consumer world. I've learned that in order to get adoption, you need three things. The value needs to be immediate, personal, and guaranteed. If you tell me I'm doing something, you know, do this and in the future something will happen or do this, and overall the product improves or do this. And then sometimes it improves, sometimes it doesn't. Nobody does it. I think the same thing applies in some other flavor to enterprises. It needs to be the value needs to be very close, either to bottom line or top line. You need to show me how am I making money or saving money without complex voodoo calculations in the middle? Or how am I doing something that is tied to a KPI that I care deeply about and I is a decision maker? Because like, if you tell me I'm saving you thirty percent of the time of people or I'm saving you time or reducing its very hard, then you start using it. And then when you get to the person that needs to make a decision, do I put money in this and that? If there isn't a clear needle that moved, they will not invest. So I think like a lot of the reasons is like for this very basic reasons and people are so locally optimizing, oh, I got myself into a pilot and they didn't do their homework. So like it has nothing doesn't matter if the product works or doesn't, right? Like, you know, you, you can try to sell hamburgers for free. Vegetarians will not buy, right? So if there is no budget, it doesn't matter how great it is, if it's great, but not moving the right KPIs, no one will make money. Someone at the end. No one has a lot of money. It's a trade off. You need to win the trade off. And I'm surprised how. And especially going to a repeat time. Founders know that. Or no doubt more. I think like first time founders, they just like especially people that never worked in corporate. They just don't understand this work. They think that everyone in the corporate that get excited somehow can buy their product. It's like very naive in my opinion. I want to move the conversation, um, in a personal, in a personal, uh, direction. And we spoke quite a bit about it. Um, and it's kind of like investing in innovation, which, which solves for humans with disability and chronic illnesses. Um, I think we, you know, we both spoke about it a lot and we had, uh, you know, several guests on the show who talk about the importance from a moral imperative, but also that it's generally underrated to invest in the investment in this space. You've lived this from the inside since your accident. And also one of our guests who got recently diagnosed with ALS. He built an AI model to support voice conversations. And I would love to hear your perspective and share with our audience. Do you see disability driven problems as a real category of opportunity when it comes to AI, or is it still treated as a niche? So. So I would separate between. Is this like a category, an important and useful. And you can make a good business versus is this VC investable? I think that generally, because what I said before, a lot of the things that used to be VC investable are no longer VC investable. For something to be VC investable, you need to have a path, a clear path to one hundred million, because, you know, this is one out of twenty. You know, you need to find the outliers and so forth. And I, I am not sure. I think that thanks to AI, you can relatively easily build amazing products for people with disability. You know, definitely, you know, voice, vision, ability to understand data recommendations, dealing with loneliness, support. You know, there is so many things that used to be hard or impossible that are currently doable. And, and, and you can build really amazing experiences and unlock and deliver amazing value. I think a lot of it is about just building good products with stuff on the shelf. I don't think I don't think there are data or expertise here, honestly. So I think like, and by the way, the market is very big, right? Like, you know, definitely everyone. The biggest disability condition is a is aging disability. But you know, some kind of limitation, at least at the moment everyone ages, right? Like, you know, then there is like, you know, eye and hearing. There are so many neurological and other, you know, stuff, right? The market is very, very, very big. And, and preventive health applies also to so, so stuff that you do for people with disabilities actually many times applies to the broader population and preventive health. So I don't know if it is a business, I think like that actually great. But generally, you know, I wrote this article donkeys, not unicorns. I think that like building good businesses, building good products now is so much easier, cheaper and faster than it was before. But I don't think it's a good business and I don't think you want VC, you know, VC, nothing comes for free. I would like either bootstrap it or get some angel money or some strategic partners money or even like, you know, a loan, you know, God forbid and and build an amazing product and grow organically. The need is there, the value is there, the technology is there. And I think defensibility is tricky. And the and the frontier models are very strong competition. I think you can build a decent business. I'm not sure it will grow to value for the business versus basically dividends, right? Like you can make money, people will pay for it. And so, so that's, that's my feeling on a lot of the B2C stuff, uh, in general. And that's my general recommendation for entrepreneurs. I think the bar for becoming a unicorn and a VC investable company, I think like actually was increased. I think the main rule of you need defensible, you need defensible, uh, some, some defensible mode to be a successful startup for, for VC. I think that's fixed. What counts as defensible went off the roof because of the the commoditized models, but how hard it is to actually build a good product and distribute it. I think that actually went very down for the same reason. So my recommendation for people, yes, this is a very clear market, very clear need. It's a niche but not niche in size. A and I strongly encourage people to, to build stuff. Yeah. And so yeah, I, I built a, yeah, I built a, if you experience, I had my own startup in that space. And it's very gratifying to have a company where, I don't know, the goal is to reduce pain in the world or help a blind people or, you know, yeah, it's a, it's a very gratifying experience. Why don't we close this out for corporate venture investors that are listening? You've clearly shared a lot of expertise in your point of view in this conversation as well. What is the biggest mistake you see them making when they think they've found this mote that they can defend. Yeah. Cognitive dissonance. Right. Like, you know, when you're in I think that's the biggest the most human thing is cognitive dissonance. Like we cannot stand it. Right. If you are invested up here with companies, with SaaS, companies that demotes are things that are clearly eroding, it's very hard for you to to realize it. I think that's the challenge. I think that the laws underpinning how we build software from scarce resources engineer to a model that everyone can buy for twenty dollars, stickiness, from high stickiness to no stickiness, procurement from people on trust, to completely open marketplaces with agents that don't know each other and prove to each other that they can do something or not. Um, from marketplaces, an asset to a peer to peer when an agent can communicate to it, right? Like these are like, you know, the very basic rules. The same thing that kind of happened with Einstein and Quantum, I think is like, you know, that compared to until today, you know, we struggle to grapple it because suddenly it's not about understanding physics, it's just accepting math. I think here as well, it suddenly, you know, all of these things, you know, first mover advantage, brand, a marketing, all of these things are no longer relevant. Um, that's my opinion. People are still sticking to it and refusing to, to accept it. We've been saying it for three years and three years ago, I think it was fine to to call us crazy. I think at the moment, like the right thing. 

Conclusion

That's it for this week's episode of Inside CVC. As always, thanks for listening. You can find Inside CVC wherever you find your podcasts, make sure to follow, subscribe and like. We'll see you next time.