So Kamila, you started at Meta where you were a top AI engineer, and now you run Perceptive Ventures, one of the top agentic AI seed funds in the world. Tell me about how your experience from Meta informs your day-to-day as a venture capitalist. It's pretty critical. And before joining Meta, my company was required, so I was a startup founder and CEO. And both of those experiences are really critical to how I invest today. Having been a founder, I know how fast one can move and how nimble one can be. But having also been a big tech operator, I understand which large spaces big tech finds attractive and wants to move into. And the key here as an investor is making sure that we're not investing in spaces that big tech is going to dominate or be really interested in. And by the way, when I say big tech, I also mean OpenAI and Anthropic because at this point they have sort of like a neo-incumbent power in AI. How do you know whether Big Tech, whether Meta, Facebook or Anthropic, OpenAI is going to go after a space or not? Understanding scale. You know, I ran a $10 billion product suite at Meta, which is, you know, sounds large, but in the grand scheme of Meta was actually not that big. And so there are $10 billion businesses that these large companies don't really have an interest in entering or pursuing because it doesn't really move the needle when you're a multi-trillion dollar company. That's too small for them. But a $10 billion startup is a very interesting outcome for a venture investor like myself. If there's not top engineers on Meta that are going to go after a problem, you think that's a safer place to build a startup and to build something that could be dominant there versus having to compete every day against the problem? these large LMs. The big problem with incumbents is that they have distribution power. So no matter how innovative your product may be as a startup and how forward-thinking it is or well-executed it is, if you don't have the distribution power of these behemoths, it's quite dangerous to compete against them. So when you started Perceptive early on in your genesis, you made a big bet that the future of AI would be agentic. Why is that? A lot of AI outsiders, I think, were convinced that artificial intelligence was about building tools to help knowledge workers. But the reality is that artificial intelligence is really centrally concerned with replacing human decision-making. And that has three components at its core, prediction, judgment, and action. And these three components combined replace human decision-making, which is the entire point of AI. So when you put them all together, it creates a completely agentic system. And the clearest example of that today for laymen is Waymo. When you get into Waymo, the system is performing all three functions. It predicts where the cars are, other cars are going, where it is going, how objects in the environment, such as pedestrians and bikes are behaving, and that applies judgment to those predictions. It says like we should do X or Y. And then it takes action by actually moving the car in the necessary direction at the required speed based on those predictions and judgments. That's a fully agentic system. And that's exactly what's happening with software. Software is becoming agentic, which means it's not only eating software, but it's actually able to eat entire human workflows. So do you fall in the camp where you believe AI will destruct human labor? Or do you think it's going to make things so efficient that more people will transact and there'll be more opportunities for business? I think it will disrupt and destroy a lot of industries for sure. I think it's also going to create a lot of new opportunities. And there's a lot of jobs that are also very difficult for AI to replace. We're always going to need restaurants. We're always going to need hotels. We're always going to need plumbers and electricians. We're going to need people to service the millions and millions of robots that are going to exist in our world. So it's going to create new jobs, but it will certainly disrupt and replace a lot of human knowledge work, human labor. Being on the inside and seeing all the disruption that's down the pipeline, what's your framework for figuring out what AI disrupts in the near term future and over long term? In the near term, it is easier to disrupt things that are less regulated. And so the areas that will be slower to change are the ones that are more regulated. Spaces like the law or health care, where there are merchant guilds that protect those industries and accredit and license the individuals that work in those industries. working in concert with government to license those individuals. Those things are going to be a lot slower to change, but they will eventually, as safety is proven not to be better with AI, as efficacy is proven not to be better with AI, but it's just going to be a lot slower. Last time we chatted, you said that there's a couple of players in the market that saw this agentic future years ago, and they have a head start. Tell me about these companies. Working on AI internally at Meta, we knew where things were going. That's actually what led me to leave and start Perceptive. We saw that future coming because we were part of the group building it. Our vision at the time, even if we were to pull people internally at the company, though, would have seemed crazy. People probably in the company might have thought that was pretty futuristic. But those of us working on these topics realized it wasn't that crazy because the models were getting there. So there is a head start that some of these big incumbents have, but it doesn't mean that this is the end all and be all. We are in the early innings of LLMs and we don't fully know if LLMs are the right architecture for developing AGI or superintelligence. So it's still a question mark if even this is the right path long-term. It could be some other new company comes about and develops a new architecture that it's actually more efficient and better for developing the GI-TPD. But certainly when it comes to the LLM landscape and the big platform models, there is certainly a head start that these big companies have. Seed stage venture capitalists in general have a difficult job of predicting the future 10, 12, 14 years from now. Today, that's even more difficult with the pace of AI. How do you create a framework investing 2026 for 2036 and beyond? One of the hardest things of investing is seeing what's shifting before everyone else does. 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The best part, these proprietary channel checks integrate directly into Alpha Sense's research platform, trusted by 75% of the world's top hedge funds, with access to over 500 million premium sources. From company filings and brokerage research, to news, trade journals, and more than 240,000 expert call transcripts. That context turns raw signal into conviction. The first to see wins, the rest follow. Check it out for yourself at alpha-sense.com slash how I invest. We try to think a lot about what the world is going to look like and specific industries are going to look like and invest towards that vision of the future. That's, we have a very thesis driven. And so we steer away from what seem like near-term improvements and innovation. So we've historically never invested in co-pilots and things like that because we didn't believe that co-pilots were the end goal. And so we try to think about like, well, what is an agentic future for healthcare look like? What does agentic future for legal look like? What does agentic future look like for construction, et cetera, et cetera, et cetera. And work our way backwards from that in order to say like this, this company fits that mold. But more specifically, this founder fits that mold because we have to see that that founder gets that future. A lot of founders let say most founders are optimizing for the next three to five years in whatever industry they in And that how far out they think And they you know they pitch you like hey I going to get to Series A I don care how you get to Series A I concerned about how you going to build a billion company How do you marry those two things, which is I need to be pragmatic enough to attract the next round of funding while also not being leapfrogged by the next generation of technology? I would say it's a little controversial to say out loud, but I would say that the tier one investors in venture across stages, you know, whether it's Seed, Series A, BC, are very forward-thinking. They are investing in very disruptive innovation, whether it's Kozla or Founders Fund or Sequoia, that's how they think. And so there is an element of just being de-risked because we're aligned in how we think with some of those bigger players. And these investors are investing at the Series A pre-revenue. Basically, they realize that gap between the future and the current state, and they're willing to subsidize, even from a revenue basis. They're looking for something fundamentally different in terms of milestones. Yes, it does. It depends on the industry, right? So in B2B, we've historically seen, or in the last couple of years, that it is very easy and quick for AI companies to get to revenue quickly. So by the time they get to series A, they're doing substantial amounts of revenue. So from that perspective, they're de-risked. But also, you can look at Kozla being the only venture investor at OpenAI back in 2017, 2018, something like that. When OpenAI, it was pre-revenue then and it certainly still leads cash today. So there is their nominative, being that visionary willing to back pre-revenue, but also there's a lot of companies that are getting revenue very quickly these days based on just AI. You're on the bleeding edge of Agentec AI as an investor. How much do you build a thesis around different parts of the market and how much do you let your founders draw you into what they see as the future? A mix of both. Sometimes there are industries that we haven't sat down and thought about and fleshed out in terms of what we think that future looks like. And so we can chat with the founder about what they think is going to happen. And then we try to sit down and say, all right, does that make sense to us based on what we see happening in other industries as well. But it is often that we have already come to a place of understanding or having a general rough sketch of what we think the future is going to be for that space. It's interesting as a former founder, you're just stuck in the weeds pretty often and so it's often hard to see the bigger picture. So rare is the founder that really understands what the bigger picture looks like and how they're going to get there. A lot of people have trouble conceptualizing an agentic AI future, how does that work? Let's say I'm a business owner. Do I just go in, grab my coffee, press play, and then leave and come back at the end of the day? You know, what's crazy is there's a world where AI is the business owner. You know, I've talked to really visionary founders who are working on this. You know, what is a world where AI owns property, where AI has legal rights? And if so, then they are the business owner. They they can spin up businesses, which is pretty wild. Until we get to that sort of regulatory regime. Like, yes, I do think there is a world where, and I think it's even here now already where you see, you know, small business owners that can, you know, press a few buttons and run a large operation because they've automated so much of it. It's pretty awesome to see. The question again becomes like, at what point do they become replaced by an AI that owns the business? And I subscribe to this agentic AI feature. I think it's more or less obvious if you think from first principles. What's not clear to me is a second order effects. So if I'm an investor, I'm running an endowment. How should I think about investing into other asset classes, assuming that an AI-agentic future is imminent? Every asset class is going to be touched by AI private equity. There's been some large titans of private equity who were anti-AI a year ago now, but they're publicly trying to defend their portfolios because they're scared that the companies they've invested in are not going to survive the AI revolution. Every asset class is being touched by this. Think about what might not be, maybe commodities, but even then commodities, there's a lot of the AI boom has driven a need for certain kinds of commodities. So it's even impacting that space in different ways. And I think the job of allocators of LPs is going to change because the Yale model, the Yale endowment model of investing, even that could be automated. Assessing different industries, assessing different managers in different sectors can be automated. So it's really going to touch absolutely everything, even when we think it's not. How do you think about AI enabled businesses versus AI first businesses in the non-venture space? It's hard to say, then anything is not going to be touched by AI. So even think like you mentioned widgets. So I like to think about industrial, like legacy industry kind of businesses, petrochemicals, you name it, like really old school stuff that requires machinery to operate. That's also getting automated. We see, we get pitched ideas in those really obscure industrial areas that you would think of. PE just buys that, makes the widgets go faster, go, you know, buying with less people, the whole operation with less people. All of that is also getting automated. So even if you're a lower middle market PE firm that does that, and we've actually started to see this, is some of those PE firms are starting to hire AI engineers or AI technologists to look at their portfolio and say, like, all right, how is AI going to disrupt these companies? That's the thing that people forget is you think that just because you're not doing it's not going to happen. But the reality is that someone else is going to try it. And if they're successful, they're going to beat you. So that's how we see it and we see what's happening. And by some accounts, emerging managers in VC, there's an extinction level event happening where anywhere from 50 to 75, some predict up to 90% of emerging managers are on their last fund and just won't be able to raise any more funds. How are you surviving this extinction level event? and how you're preparing yourself for the next era of VC? One of the reasons it's occurring is because too many venture managers came out of the pandemic high when anyone with a pulse in a deck could raise a fund, frankly. And it wasn't necessarily people who should have, to be honest. There's a lot of skills required in order to raise a fund, build a firm. And you made that distinction. A lot of funds don't know the difference between running a fund and running a firm. How are you building your firm? And what lessons have you learned from building a firm? A firm is a brand. And most people don't realize that you're, to be a successful venture manager, you have to be consistently marketing that brand to founders and to LPs, founders and LPs constantly. They think that it's just a function of having deal flow and making the investment. And it's not. The only reason your firm exists is because you have been able to bring LPs into your capital base and stewarded that capital well, and then continue to market your performance and your ability to continue doing that over and over and over again. Venture, if you look at the studies about successful venture firms and starting all the way back, Sequoia, et cetera, they are successful today because of the success they had in the past. So they've continued marketing of that success. And a lot of venture managers don't like marketing and they don't like fundraising and they don't like investor relations, but that's the key to building a successful firm. You have some enviable LPs, especially earlier on in your firm building. How are you able to secure those LPs and what are some best practices for other emerging managers that want to bring in blue chip LPs? I think the key to being a successful venture manager is having a very strong network. And people think that that just means a founder network. I think that's half of it. And the other half is having a strong LP network. Again, if you don't have the money, you're not an investor. So you have to have a strong LP network to begin with. It just happened in terms of how my life came together, my career that I did know a lot of LPs and I had raised money as a founder so I already knew how to do that So I already had the network built in to go out tap it and start my firm And from there word spreads LPs are a very insular talkative group of people They like to share their deal flow in terms of venture managers that they're finding. And that's how my LP base was able to grow is through that word of mouth with these investors. Talk to me about these AI tools. What AI are you using internally that gives you an edge over your competitors? I believe that you can encode and build models of what a successful founder looks like in B2B startups and then also in consumer startups, because I think they're actually different. And so that psychographic model, I think, is key. And I think it's something that's repeatable and scalable. If you look at some of the character traits that really define the best founders of the history of technology from Bill Gates, Steve Jobs, Mark Zuckerberg, et cetera, et cetera, they'll share common things. And so I think that you can actually model this and use that model just like any other AI model to say this is the right founder to bet on versus using just gut instinct, which is what a lot of precedency venture investing is a lot of gut instinct. But gut instinct is just data. It's just accumulated data in your mind and body that I think can be actually modeled. It goes without saying AI is a hyper-competitive seed market. How do you compete against other firms? And also, how do you compete? You mentioned Kostla. the Kostla, Sequoia Founders Fund, how do you compete against these multi-stage platforms as well? We are of the size where we don't have to compete with the big boys. We can collaborate with them, given our check size. And so we're in deals with a lot of the big guys, Founders Fund, Kostla, et cetera. So this is due to size. Where we do compete is the other pre-seed and seed firms. And where we win is because we are exited AI founders. We've been down the road as founders before, and in particular in AI. And so it's a very, I don't want to say it's easy, but it's a pretty straightforward argument to make to any founder, like we've just been there before, what can help you with the challenges you're facing today and will face tomorrow from inception all the way through exit. And so that's what really been the key for winning for us because most VCs are run by career investors who've never built anything before. And then the firms that do have some level of operators, they tend to be operators, they're not founders. Very few firms have actually been built by former founders. Founders Fund is certainly one and Dries and Horowitz is another, but there's actually very few when you think about it. Tell me about some of the biggest misses you made as a VC. And what were the learnings from those mistakes? The most consistent logical fallacy or mistake that I see from smart VCs, and this is like a very predictable at this point, is that they really like the founder and they really hate the business and they don't invest. And they're right about both, but their decision not to invest is wrong. Right. And what happens when you do make that decision to invest or not invest is you're saying like there has to be a pivot. and I'm investing with the hopes that this team will pivot. Sometimes you feel so strongly about a team that you say, I'm going to invest and they're going to figure it out. And I don't believe in this thing that they're doing right now, but they're going to figure it out. That's how we got our first check. When I was a founder and CEO, we got our first check and our investor told us, we have no idea what you're doing or where this is going, but we really like you as a team. So here's a check. And that's the kind of bold investing you need to do. And then we've done, we've invested pre-idea. Like I met a founder who had amazing two or three exits after his belt. And he was like, I don't know what I'm going to do next. And I was like, take my money. I don't know what you're going to do either, but you're smart enough to figure it out. So sometimes you just get to get better. Would you rather invest pre-idea or in the wrong business model? Both are fine. I don't think there's an either or. Again, if it's the right team, it's the right team. You have to believe that they're willing to move quickly. Because sometimes you can have a really smart team, but they don't iterate fast enough. They get caught up in sunk costs and say, oh, we've already built all of this. Do we really want to pit it to something else? You need to invest in someone who's willing to let all that go and be ruthless with their time. Talked about AGI earlier. Do you lose sleep on this doomsday AI situation where there's an extinction-level event, not in the venture ecosystem, but humanity in general? I don't lose sleep over, but I do think it's real. I think we have to think about it, And it's unfortunately true that we have to balance it with national security concerns. So there's often this tension in the U.S. at least of building for safety and building for speed. You can, you know, dumb it down and say it's probably versus open AI. But the reality is, is that we don't build it. China will. So I even think about it. The decision is we have to move forward. There is that tension. Right. What's a key philosophy that you've changed over the last 12 months that you now that leads you to make different actions? One of the key things I've come to accept is that some of the best founders in the world are not necessarily always the best people to work for or to work with. There is an element of ruthlessness that's required in building generational companies to transform humanity. It's a sacrifice they are making personally, but it's a sacrifice they ask their employees to make as well and a sacrifice they ask investors to make as well. And so there there's often a desire to do business with people you like, right? Like it's a common maximum in the business. And the reality in venture is that sometimes you want to do business with people you don't like because they are the best, the most extraordinary, impactful people in history. Reminds me of a story you told me when we were having dinner a couple of months ago. Tell me about that. Yes. So we, it's an interesting story. So we were early in a company and the founder did behave in a certain way that was me you know not very agreeable and i'm trying to be careful how much i say here he's not very agreeable and when we talked about it and i see you know one of my partners said hey like do we want to work with this guy you know he seems like an he's doing kind of things and i said actually i want to work with him even more now because he can be an to me if despite all the things i've done for him that makes me realize like this guy is going to do whatever it takes to build this this company. And that was a wake up call for me and for our team in terms of what it takes to build a generational business and how we look for those people and back them and the compromises you have to make. How would you explain that? Because there's obviously the opposite is also an axiom, compounding relationships, compounding reputation. But here specifically, it's almost a zero sum mentality to relationships that was a superpower. How would you explain the mechanics around that? There's at the core, a level of humility you have to have because when someone's being disagreeable or an asshole, there's an element of like, I'm offended. It's my ego that's saying like, I'm hurt. I don't want to be hurt. I don't want to continue interacting with someone who's hurting me. So it takes a stepping out of that and saying that doesn't matter. What matters here is as a venture manager, I'm here to make money for my LPs. And is this the right person to make money for my LPs, period. So it's taking yourself out of the framework that you often are in in terms of being led by ego and about pain and whatever and hurt and saying like what actually matters. Is that a specific case where you had to just burn through all your relationships in two three years because there's a short window or is there some general wisdom there for highly disruptive startup founders? At the end of the day the best founders in the world have all the leverage you know they can they can choose their investors and so they will have leverage in that dynamic always you know once you come in they still will have leverage over you even if no no matter how big your position is in the company, because they can always raise more from someone else. So I don't think from a founder perspective, you just have to be conscious of that that the dynamic now And that okay I not here to be in the spotlight I here to support founders I like how Vendor Kozla says he not a VC He a Venture Assistant He helps founders He assists them and a service provider. That is the role. And so you have to own that and let this ego of the VC push that aside. And it doesn't mean that your relationships are fraught. It just means that you have to be careful with those people. And people who worked, I'm fortunate to know people who worked with Steve Jobs or were on board with Steve Jobs, and they all knew you got to be careful with him doesn't mean that you can't have a relationship with him. It doesn't mean that he's not extraordinary. It just means you just have to be careful. Yeah. Would that be the case if you were a customer of that entrepreneur? Clearly that would be counterproductive to scaling, but it's, it's really your seat, your commodity to that entrepreneur. So he didn't find the need to use niceties and waste time with you as a commodity versus if he was trying to secure a large product or a large, large contract, that would be a necessary condition for him to succeed. Yeah. And again, these founders, it's not that they're perma assholes. They are quite charismatic, very friendly people when the moment is right. And so they know how to turn on the charm when it comes to sales, when it comes to customers, clients, et cetera. And that's their magic is that they can be both. now when I look at my portfolio and we look at our top companies, top founders, unicorn founders we've backed, they'll have that ability to from one second go ruthless to the next second be like the nicest guy in the world. And so they know that they, in order to build a massive company, they're going to have to be the nicest guy in the world where they're outselling, where they're outpitching. But when push comes to shove and there is a moment that requires decisiveness, they're not afraid to pull out the ruthless side of them. Yeah. If you think about your energy and being nice as being highly energy consuming, they have an efficient use of their energy when it comes to different parts of the value chain. Of course, that sounds like a psychopathic, but when you take away the moral frame on it and you look at what's going to lead to, if you're trying to create an entrepreneur from scratch, that's going to execute at the highest speed with the fewest amount of resources. That's almost like the perfect equation. Yep, exactly. And I think we like to judge, you know, even using the word psychopathic, it's like, oh man, do we want psychopathic founders? But what if that's just simply what it takes to build transformational global companies? It's the level of psychopathy. You could be 100% psychopathic and provide massive value to society. I'm not going to name any founders. Psychopathy is a clinical definition of not caring, having low empathy and all these things. You could literally be clinically psychopathic. And if you have the right incentives, they could end up actually carrying society forward. And you could say that's wrong, that's bad. But on a net basis, they're actually very positive for society. We need them. Exactly. Yeah. Last time we chatted, you said that whoever controls the computing platform controls the future. What form factor do you expect the future of compute to take form? Let's talk about what today's interface model looks like in these computing platforms. So we primarily use two interfaces. There's the computer, which we're chatting on a computer right now. Most knowledge workers sit at a desk looking at a monitor or a laptop. And this is interface model number one, let's call it. The second interface model is the phone. And I actually argue this is probably the most important one because most people on the planet have a smartphone, but most people on the planet do not have a desktop. And the GUI, the graphical user interface, that we use on laptops and monitors and phones, it's been around for 40 years and it's entirely text-based. Even though it's visual, I still have to read the written word on my calendar, on my emails, websites. Reading is actually not that fast. Like, it's not necessarily the most efficient way to process information. And part of the reason for this is that we developed the spoken word long before the written word. We're wired for speaking, which is why we're having this conversation by talking instead of writing back and forth to one another. So that's a fundamental principle behind these interaction models. And again, the phone follows that logic, but I think the phone is going to be the first one that breaks because it's an even more inefficient interface. People often check their email on their phone and then wait to respond on their computer because typing on a phone is so cumbersome. And we're already seeing early signs of that, that audio is faster and preferable. You see people using the dictation function to write emails and SMS on their phone. That's audio. That's a spoken word. So the input is becoming more and more audio based. So I think that's what we're going to see break first. And that's going to be the platform shift that matters the most. we've already started to see it with Humane, which came and went, but now OpenAI is going to release its own audio first advice. And while it may have a visual component, again, it's going to be primarily an audio interface. What is one piece of advice you could go back to 2006 when you had just graduated Princeton? One timeless piece of advice that would have either helped you accelerate your career or helped you avoid causing mistakes? One thing that I wish I had done was actually work at a big tech company earlier in my career, before I was a founder. When you're a founder and never worked anywhere before in tech. You're really flying blind, but when you work at a high talent density place like Google or Meta, you understand what the bar is across a variety of functions. So it wasn't until I got to Meta that I really understood what world-class design looks like, world-class product, world-class engineering. I thought I knew as a founder, but it really wasn't until I got there that I understood the processes and systems that the best engineers in the world, the best designers in the world, the best product people in the world use to get the job done. And so if I was going back and talking to the younger version of myself, I would have said, go learn there, go learn from them and then go out and build a company. So you're not making a lot of mistakes. And I've only worked for three months in my life for somebody else. I worked at Jeffries for a summer. So I'm similar to you, very entrepreneurial. And when I think about these meta engineers and these Google engineers, are they the same level of talent at the high end as the top founders? And they just have a different risk appetite or are founders just a different class of engineers, designers? and etc. I think it's just a risk appetite question and going back to the psychopathy you know a conversation there's a different you know profile there but in terms of they care too much about being liked how do you care too much about being liked there's yeah they're not that they're not the extreme of that psychographic profile that are found not enough trauma not enough trauma necessarily yeah yeah so I think those which I think are the frankly the key factors because there are tons and tons of intelligent brilliant people in the the world, but how many of them have the right, let's call it the right trauma, the right wiring, the right psychopathy, the right, et cetera, et cetera, et cetera, to be a generational founder that transforms the world. To play devil's advocate on you wish you would have went to meta or Google earlier. You never know how that plays out. You could have been a lifer there. And I also, I started my career as an entrepreneur and it's embarrassing how ignorant I was at the time, but yet I developed the skillset of being an entrepreneur in an unknown environment that But if I had to pick, I'd go with that skill set versus the hard skill set. The skill set of a founder doesn't translate very well to corporate America is what I found. When I got to Meta, one of the first things I told my manager was, here's a list of a dozen people I think we should fire. And she just laughed at me. Was that day two? This was in the first week. Day one. I quickly could tell who was pulling their weight and whatnot. And she just laughed at me and she said, hey, this is not how things work in corporate land. We're going to have to work with these people, even if they're not great to work with in terms of their efficacy. And so I have a strong bias for fashion as a founder, and that doesn't always translate very well to corporate land where there's systems and processes that slow you down and you can't just fire and hire the team that you want. So I think it really depends on what you're optimizing for. Camilo, this has been an absolute masterclass. Thanks so much for jumping on the podcast. Thanks for having me. That's it for today's episode of How to Invest. If this conversation gave you new insights or ideas, do me a quick favor. Share with one person in your network who'd find it valuable or leave a short review wherever you listen. This helps more investors discover the show and keeps us bringing you these conversations week after week. Thank you for your continued support.
