#53 Ask Me Anything

Speaker A: Hi everyone. I hope you're having a wonderful week. Um, it's been frankly over a year since we've done a ask Me anything session. And so much has happened in AI and macro and geopolitics, etc. So figured it was, uh, the time had come to answer, uh, all of your questions and every round possible. So without any further ado, uh, let's get, get, uh, this show on the road. Welcome to episode 53, Ask Me Anything. Great. So I've received a lot of questions that you guys submitted ahead of time, uh, which I've decided to go through, I guess one by one. Obviously feel free, uh, to send questions, uh, along the way as the show is, uh, going on along. I guess. First fundamental question, um, that someone asked me was, uh, why does it seem that everyone hates AI right now? Like, why is AI so hated? Um, and I thought long and hard, um, about that. And I think there's um, probably, uh, three different. Whenever new technology appears, um, there's always like, backlash. So let me give you really interesting examples. So back in the day when, um, writing in a way was invented, Socrates was complaining that writing would make people lazy, they would no longer use their memory, et cetera. And now the funny thing and the irony of this is the only reason we know that is because Plato actually wrote down Socrates, uh, sayings. And so had writing not invented in terms of like, preserving knowledge, allowing to build upon the knowledge of other people, um, we wouldn't have that, the knowledge and expertise that we have today. And this has been true through a habit of history. So when, uh, the printing press was invented, people, uh, same thing, worried that somehow when the Bible was printed, you'd like, lose the connection to the church. Uh, uh, when newspapers were invented, the main criticism was, oh my God, you're no longer going to get your news from the pulpit. And that's going to be a big issue. And of course none of us have gotten our news from the pulpit. It's not an issue whatsoever. Um, when the bicycle was invented, people were saying it's going to lead to a crisis of morality because women are going to be able to take their bikes and have affairs versus being stuck in one specific location. Um, and of course all of that was hogwash. It didn't really change anything. Uh, uh, it just made our lives better. Um, and so these concepts of crisis of morality and technology, uh, kept happening. I mean, the tv, television, uh, people thought it was going to create these zombie people in front of the TV that are not using your brain in Any way, shape or form. And the same is true of like the Internet with like Wikipedia. Oh, are the students going to be learning, memorizing, et cetera versus having access to information. And so right now people are worried the same thing about AI. It's going to take all the jobs which has been a concern people have had forever. I'm m going to address that in a different question. Uh, maybe it'll uprise and take over from us as in all the Sobeam movies, et cetera. So number one general concern with new technologies where people are not comfortable with it and come up with all these crazy scary scenarios. Um, so number one, number two, I say AI arrived at a moment in the zeitgeist where VCs and tech founders are no longer respected and they're more frowned upon, criticized, et cetera. So it's not like in the late or early 2000 and tens, um, but right now they feel that they have become the villains right. In the last Superman movie it's like some tech billionaire as the villain. And so the cultural zeitgeist is no longer pro technology, uh, if anything is anti technology. And of course things like social media, both positives and negatives and yes they can be used for promoting fostering democracy, uh, but can also lead to mental health crisis in young women, et cetera. So the, because the world doesn't have the same positive view at a moment where they're afraid of technology, I can see why people are uh, uncomfortable. And then last but not least, as always it's been, it's very easy to imagine the jobs that are going to be lost because of AI. It's always much harder to imagine the jobs that can be created. And so people can foresee a world where maybe the jobs they have or no longer required and there's going to be fundamental change. People are risk averse. Um, you know the, our amygdala has like this fear response. We're hypersensitive to fear because 10,000 years ago, you know, from an evolutionary biology perspective, if you were in the savannah and there was a ruffling of the leaves, um, the people that were really afraid and you know that it might be a tiger that could eat them survived. And so the risk averse people are the ones who survived. So in general we're afraid of change. So I understand why there's this fundamental fear uh, of AI so that was the uh, question from Tom question from uh, um, Emmanuel question. Uh, number two, we live in this moment where A.I. um, and we're seeing an extraordinary productivity, uh, revolution in science, uh, with new discoveries because of AI, often doing a lot of research or doing fine, finding mathematical proofs. We're seeing an explosion in creativity in startups because, uh, of AI, where it's easier to build startups than it's ever been, um, and we're seeing it in finance as well. And yet when we look at our political systems and our political processes, things seem more broken, slower than ever before. The quality of the people there seems to be declining. If anything, uh, why is that? And it's probably one of the biggest philosophical paradoxes of the 21st century. On the one hand, with the best tools, the best people working on changing the world in fundamental ways, and the other side, um, you have political systems that are supposed to be for the public good. They don't seem to be doing a particularly good job. And there's a number of frankly fundamental reasons for that. Um, so first of all, the markets are not great at necessarily allocating and dealing with public services, which is why the public sector has been created. The issue is the reason one works better than the other is as follows. When you're building a startup, for instance, you have a very, it's a meritocracy, um, and if you do something good, you're rewarded for it, and if not, you run out of money. And it's a very quick feedback loop. Very quickly you know if what you're doing is working or not. And the rewards keep accruing, screwing to the winners. And your objective is very clear. Find product, market, fit, uh, create a business model, sustainable, scale your business. And very quickly if things work or not, and it weeds out, uh, the losing ideas and the losing people. Um, the political processes are very different. The feedback loops are very slow. It's very hard to tell if you're a good policymaker or a bad policymaker or if you're a good politician or a bad politician. And so 10 years in, you may still not know the answer to that. And because the systems move reasonably slowly by design, by the way, um, it takes sometimes decades for bad decisions to have, ah, culminated to the point where they lead to bad outcomes. Uh, and because it's much slower and also the objectives are different, right? Like in the venture startup ecosystem is like, uh, you invest at the startup, it works or it doesn't work, you find product or fit, you scale and the other one, your main objectives to be reelected. And uh, the political, uh, cycles are too short. The reality is the things that happen in the world take time to move in the last 50 years, a billion and a half people came out of poverty in China and India. Uh, but that took 40 or 50 years. Nothing happened in two years. And right now in the US you're electing Congress every two years, you're electing presidents or prime ministers in the west every four to five years. In these timelines, very little really happens. So it's actually very hard to tell um, if someone's being effective or ineffective. And so as a result that world moves extremely slowly and I expect will continue to move very slowly. And by the way, as I think through the impact of AI in society, I suspect as with most of these things, people are overestimating the impact in the short term and underestimating the impact of the long term. And the reason they're overestimating the impact in the short term is if you are in tech right now, you're like this is changing everything. It's going to, all the jobs are going to disappear. The world will be fundamentally different two years from now than it is today. But uh, this is not the way the world works, right? Culturally we move slowly. Politically we move slowly. And if you think of where most of GDP is today, it's in public services, it's in large enterprise and these move extraordinarily slowly. Like yeah, when do I think that the DMV will use AI to make the process, uh, um, of getting their driver's license faster? I think it's going to take forever, right? So before I think we're going to see uh, GDP productivity funnily inflected by AI usually need it to sieve into the public services which are 40 to 60% of GDP in most Western countries and in a large enterprise and these are very slow, um, very very slow adopters. So it's going to take a while uh, but ultimately we'll change society in ways we cannot begin a fathom today. Okay so LinkedIn user we are developing first commercialization network with AI agents Jacobian Labs. Does this fall under the FGA Labs thesis? Do you have any thoughts on the commercialization AI prospects? Um, not enough information to answer the question. Uh, maybe I guess is the answer just uh, send us Z. We'll review and let you know but obviously uh, uh, yeah, commercializing AI in some way shape or form makes a lot of sense. Um um, we're developing so Alessandro co founder matching platform calls the founders junction who believes that with AI is reshaping the job market and integral landscape internals will always need a human co founder investors do you agree with this view. Well, first of all, founder dating is a huge deal. Right. Like finding the right co founder, um, matters a lot in terms of building a company and um. And so do I think that with AI you're going to be in a position to help people find better co founders? Absolutely. Right. Like there's not been a very clear process. People take their friends, but the friends may not be the most suited for whatever skill sets uh, they need. People look in the networks around them and so do I think there's a need for foundry dating and finding people that work together. Whatever you're looking for. By the way, um, a CEO may need a COO or a cto. They're, or a CTO may need someone to help them uh, define the business model and fundraise. So I think there's definitely a need for it. Now do I think that most office in the near term will continue to have humans running them? Absolutely. I think your co founder will be a human rather than openclaw. Absolutely. Now do I also think you're going to be using openclaw, uh, as your super smart assistant to do research and help? Absolutely. Maybe not. Open Claw in the near term. In the near term, um, uh, it'll be an open cloud type agent embedded or provided by the core, um, uh, by the core marketplaces, um, sorry, the core AI LLMs like Claude or OpenAI that will offer an open cloud equivalent without any of the security concerns and risks that you're, that you're seeing today. So to answer your question, yes, I think uh, the founders will continue to play an important role in building companies. Most of the founders will be human founders even though you will be using AI. And I do think it makes a lot of sense, um, to actually uh, use AI to find better founders and to improve the co founder dating process. And by the way, I really would do a co founder dating process meaning uh, you should totally, you should totally m, do like projects with them. Like define uh, tasks and see if we work well on them together. You should totally like hang out like uh, meet their friends, meet their girlfriend. Uh, you should go to dinner, like really make sure that this is someone you can see yourself working with on a regular basis for a very long time. Okay, moving on, uh, uh, to the next uh, um, Okay, I remember a question that was related to founders, um, that was actually interesting. Let me uh, go through the list of questions that were pre submitted. Uh, um, okay. In the age of AI, um, how important is a technical co founder and should we focus on finding a Technical co founder versus someone with um, with um, relevant vertical industry. Uh, now the, the answer of course to this question is it depends. Um, as is the answer probably to most questions. If you're building an AI startup with a foundational LLM model, well then yes, you absolutely need a CTO who's absolutely fantastic. Um, if, um, if you're building. A company that is using applied AI truth then probably not that hard to build. In a way makes way more sense to find someone who's going to be, have legitimacy and help you sell into the general contractors and the subcontractors. So the answer is it depends. Uh, but if you're building whatever, if you're an open AI or foundational model, for sure you need extraordinary tech talents. If you're building platform applied AI companies, yes, you need good talent. But in a way the CTO is less key than might have been in the past. In fact, if I think of the marketplaces we build and invest in, the things we care the most about, um, are unit economics. Can you make them work? Do you find product market? So what is your customer acquisition channel? And so in a way understanding how you scale your customer acquisition um, matters a lot more um, and make sure the union economics work than getting the tech because the tech is more commoditized. Uh, and there's more and more things you can do easily with tech today. I mean with Vicodin and cursor or lovable if you're doing something very simple, etc. So but uh, in general there are categories where yes, your tactile matters a lot. Okay, let's go to the next um, batch of questions. Uh, uh, this is a question from Julia. I recently had a conversation with someone super early at OpenAI who basically said he's trying to build a new startup now because IQ will become irrelevant in two years. This is a thought provoking statement. Do you think it bears some element of truth? And if that's true, what do you think are the most vital characteristics skills for entrepreneurs and ambitious professionals to focus focus on? Um, you know it's interesting, you can, I can go both ways on this one. I can make the argument that the very best, smartest people are going to use AI so much more effectively, they'll be even more valuable. So the 10x developer is going to be 100x developer, in which case um, intelligence is not commoditized and actually continues to be uh, a key success factor. But I could also make the case that because now intelligence, ah, and you have the tools that are so intelligent you could be an average developer, an average person and get outcome and that is or products output that is extremely valuable. Um, and as such, um, catches up and intelligence becomes commoditized. I suspect the former feels more true to me or is more true and it feels more true to me than the latter. Uh, right now I'm seeing the very best coders being more valued than ever before. The very best employees using tools in a way to be much more productive. Now will that change at some point and intelligence will be quantitized? Maybe doesn't feel to be that way to me today. That said, the average intelligence seems to be going up dramatically as everyone's improving productivity. Everyone using these tools extremely effectively. And so what would I do if I was thinking like upcoming if I was in college today and I wanted to make sure I'm ready for the workforce? Well, play with all the tools like play with Runway, play with soar, play with mid journey, play with Claude, play with cursor, play with lovable, install, um, your openclaw. Uh, figure out what you can do to create scalable repeatable systems. See where they're good at, test the limits. Um, and there's so much to play with today. So I'd be basically throwing all the spaghetti in the world. Pursuing your creativity and figuring out what resonates and what works for you. Let, um, me see what uh, next question that was sent, uh, ahead of time. Uh, uh, question from Lisa. What type of school or education have you chosen for your son and how did you come about making that decision? So this is interesting because I've been through a few iterations here and actually a few changes over the years. Uh, in my thinking, the first school I took my son to is a school in New York called B Call. And the philosophy of that school, it's a French American school. It's amazing. Um, and the thinking and the theory is you have the rigor of the French system with the public speaking and team building of uh, the American system. And he's been there for two years, man, he likes it. But when I reflect upon in the age of AI, is this the correct way to teach our kids where you have a teacher of variable quality spewing facts, um, at kids of variable quality, typically to the lowest common denominator, where you're repeating the same and teaching the same thing daily for three to four days. It's pretty slow process. And the answer to me is doesn't feel intuitively correct. Right. If I took Socrates from 300 BC and I brought him to the world today or 400 BC, um, he would not recognize the world. We go to space, we have these crazy magical devices. With the sum total of humanities knowledge in our pockets, we fly from one end of the world to the other in ours. And yet, um, when the way we educate our kids hasn't fundamentally changed in 2500 years. And so the idea that you should be using AI to teach the kid exactly at the right level makes a lot of sense to me. So there's this school out of Austin, originally called Alpha School, where they use AI tools to basically get your kid to the very maximum of his potential. So they've realized that you want to teach them to the point where they get 85% of the answers correctly. It's 99% is too easy, if it's 50%, it's too hard. And so in every discipline you want to get them at about 85% and you want to see how far you can get them. And on two hours of curriculum per day, they basically can cover the normal curriculum. And then they use the rest of the free time to lean into the kids natural inclinations to have them do whatever works for them. Now my son is 4 and he's years ahead of math, right? Like for fun, he's doing multiplications, divisions, he understands basic algebra, uh, he loves playing with numbers and ah, he understands negative numbers, et cetera. Uh, but at the same time he's not particularly good socially. And so a school that is more bespoke for him, where they're going to challenge him mathematically and frankly linguistically as well, where he's very, uh, verbose and eloquent, uh, while helping him develop his social skills, which are lacking, I think makes a lot more sense. So starting next fall, I'm, uh, bringing my son to Alpha School in New York, which was created I think this year. So it's the first class right now it's a small school, um, and it's going to be an experiment, it's going to be an Alpha test. And um, if I like it, if he likes it, um, we were going to take Emily there probably as well now. You know, what's interesting is one of their objectives is for the kids to love school. And the most kids don't love school. It's too easy, it's too hard, it's not interesting, etc. And I brought my son, who's a bit shy, uh, to a shadow day where he went to check out the school. I was worried because he doesn't do well in New environments, new people. And so I left him bit insecure and uncertain. I came back to see him and he was like I love the school. Like I want to say, uh, why am I going back to normal school? So I'm excited to see how it plays out. Question from Luis on the stream. From your experience investing in hundreds of marketplaces in today's early stage environment, what ultimately drives investors decision? The most intrinsic strength of the product and the market opportunity are factors like early traction, narrative, et cetera, warm introductions to the ecosystem. In other words you believe there's still real space for investors to cover and back exceptional marketplaces, marketplace ideas purely in their fundamentals before the signal is validated by the crowd. Well uh, if you're backing a very early stage founder the signals are very early right? Like often there is no crowd. The big funds, the Sequoias of the world have raised so much money that they're writing big checks once things are proven and there's an emergent winner. So absolutely there's role for pre seed investors and seed investors to back the right founders and the right ideas um, early uh as they're at the early moments of product market fit and figuring out the distribution channels and union economics and retention and and cohorts um before the crowd uh validates it. Um, the crowd being I guess both a combination of users that scale the business and of VCs with big brand names uh that decide to invest it. So absolutely there's still a big role to be played today um because many people are not investing all that early given the level of capital that they've raised. So today if you're in VC probably you should be in the pre seed seed or you know multi like $100 million fund or multi billion dollar uh funds so you can keep doubling down in like the emerging winners question from a deal. This is an entirely different kind of question because you basically invest in online marketplaces. Can you provide leads for pre seed investors for a non US based pre revenue startup for game changing projects, um, like earthquake protection system. So presuming that those are venture backable businesses, meaning that they can scale to hundreds of millions or billions of dollars of revenues which because there are many ideas that are not venture backable um and so let's think through how you would get funded if you're a pre seed uh founder and the answer actually is there are very few, there are not that many pre seed uh precede VCs to begin with. There are a few and they're usually highly focused. These Days mostly on AI. Um, so non us pre seed. Honestly, what I would probably. And pre revenue, I would probably start with the old adage of fools, friends and family. Um, the good news of the world we live in today is it's cheaper than it's ever been to build startups and to start scaling them and start getting revenues. And so with several hundred thousand dollars in funding, which most people should find a way to be able to get, right? Like our friends went to great schools, maybe working as doctors, bankers, lawyers, right. If you have 20 friends who give you 10k, uh, that's 200k, you should be able to go very far. Um, and so this way you can get some level of traction that should allow you to then go and raise a proper seed ramp for a couple million dollars, given, uh, that there's not that many pre seed founders or pre seed funds. Um, question for Mahesh. Graph neural networks are becoming more and more pertinent to discovering new applications, new pathways. Do you have any relevant thoughts on how this is relevant in marketplaces? Um, the. You can, I suspect that they. So first of all I care about like at the end of the day, um, I like marketplaces because they're what it takes most, they're scalable, they're capital efficient. But I'm not like wedded to marketplaces, right. Like the. What I care more is like can we bring tech to the world to make things cheaper, better, faster? Ah, now can I think of use uh, cases for graph neural networks and marketplaces? Absolutely. There's many marketplaces that don't work without a human because the matching supply and demand is broken, uh, and too complex and there are too many variables that are not clear. And so I can absolutely imagine, uh, a world where in a category where you have all these inputs, all these variables, all these like having an age in the middle that does the matching and the introduction, et cetera, probably makes a lot of sense. So I can imagine it becoming relevant in this category. Uh, but regardless, I think they're reasonably relevant. Nacho on, uh, Twitch. Greetings from Buddha. Catching up with your content? Just watch episode 52. Love the point Resilo being more exposed than Airbnb and Door Dash because low frequency and low management. Lyric. Correct. We're actually building on that exact thesis with Roomix and a native real estate search engine for latam. A month, 150k visits for very good. After 8 months to the realtors in the B2B pipeline, how do you see the Latam opportunity? What does it take to own the category here. So I don't know. Uh, so in Latam there's not an MLS in a way you can um, you can create your own, um, inventory and create value reasonably, um, in a less competed space. Uh, there have been a few companies that have done pretty well in real estate in latam. Right. Like I think of Vivarial in, um, uh, I think of Vivarial, uh, in Brazil. Uh, do I think there's a big opportunity to go after the market with next generation if you want real estate portal using AI? Absolutely. Um, hard to imagine. I mean, not sure if it's Latam in general versus uh, a specific country. Right. Like usually in these categories, uh, um, you need liquidity, you need density, you need the listings. Um, that said, perhaps, uh, to the extent you're a search engine and you have sources that listings, it's easier to fix in the past. So tbd. Uh, I guess. Uh, but do I think there's a big opportunity in going after real estate with next generation tools? Yeah, absolutely. Okay, continuing the questions, um, for another one from Lisa, what are the clearest signs that an AI company is real defensibility rather than temporary velocity? The. It's an interesting question, uh, because what we're seeing right now in the current AI bubble, um, is a lot of companies launching with the exact same product essentially. So you have the Stanford team and the MIT team and the Princeton team and the Harvard team and they all raised 20, 30, 50, 100 million offering variations of the same product. And often doesn't feel particularly defensible. The one week one is ahead, another week another one is ahead. Because there's so much pressure to win. They're all offering their products, um, at a negative gross margin. And you are seeing businesses scale massively. 11 labs or lovable or cursor, um, that in a way we were all incorrect. Not investing in because we're like, what's the defensibility? While they've been scaling, the issue is they get scaled because there's so much capital that's willing to fund the growth at negative margin. So tbd, how uh, this ends up playing out, I worry that a lot of these are gonna die and frankly a lot of these might be taken over by Claude and ChatGPT. I'm sure they're going straight after cursor and after lovable. And yet these seem to be doing well for now. So these feel less defensible. Now. The things that feel more defensible, to answer the question, are if somehow you're built on proprietary data sets that no one else has access to. If you're solving specific, uh, vertical problems that no one else is going after. Um, and so the versus the foundational models, those seem in a way riskier, like I suspect. I mean right now ChatGPT is an 86 trillion market share, but it ebbs and flows. Gemini is going after it, Claude is going after it. The, you know, there are weeks where cloud is better or Gemini is better than weeks where ChatGPT is better. Um, that is a game of kings. I'm a bit skeptical. In fact, someone else asked me a question, it was like, what does the. Actually let me go to that question, uh, that Tatiana ask. Um, see if I have it around here and um, uh, see if I can find it. Um, okay, I didn't put it here, but like what is the massive seed, uh, round. Um, that, that, that was just announced. Right. So we have Yann lecun's company, uh, AMI just raised a billion in seed at 3.5 billion. Like what does it mean about the future of AI and how should investors think about technology versus valuation risk at this stage? And to be clearly the. We are in an AI bubble. Uh, people are willing, uh, to fund because the prize for winning is so high. People are willing to throw essentially infinite money at any price in order to win. Um, but do I think this ends up in tears because most companies are going to fail and many investors who invest at very high prices are not going to see return of their capital. Absolutely. That said, in the meantime is going to lay the foundation for the extraordinary 25 years of productivity improvements and economic growth. We're going to see the same way that the railroad bubble laid the foundations for all the railroad tracks around the US that led to a massive productivity boost in the economy for the decades to come. The same way that the bubble in the late 90s laid all the fiber that led to the Internet revolution. The 2000s, 2010s just took a while for it to happen. So we're in the AI bubble. I hope it keeps inflating, to be honest, because, uh, even if we, even though we've been disciplined, I worry that when it bursts, the companies that are currently having a hard time raising, because they're not AI, are going to have an even harder time raising. And frankly, in the meantime, with all this capital going, think of all this capital going into R and D. A lot of it is like money losing, but it's going to be great for society even though a lot of these companies are going to die. So we're In AI bubble. But it's okay. Okay, um, deal friends and family. It's not a path I can take. Getting, getting the MVP at the stage required VC level kind of investment. So ideal. That doesn't sound like a venture. So there are different types of businesses in the world, right? Like the ones um, that need 10, 20, 30, 50 million to build a large, to, to get off, to turn the lights on are not frankly particularly VC backable. Um, the ones that are VC backable are the ones where a couple hundred K you can get the prototype and get some revenues and then you get your million dollar precede round and you get more revenues and more proof and then you get 3 million. Um, the ones that need 20, 30, 50 million to get off the ground, they either belong in like large enterprise that are in the category or people that have succeeded before that have extra capital but they're not appropriate for normal uh, founders who um. Because that's not the way the VC um treadmill works. Or the VC treadmill is your fool's friends and family for a couple hundred k. Then your million dollar seed, then your sorry pre seed, then your $3 million seed, then your 7 million A, then your 15 million, uh, your 15 million 25 million B. Now in AI you have different numbers in these but these, but that remains the uh, type of numbers for non AI companies uh, that you're seeing. Uh, let's see what other questions came uh, Alessandro very close. Completing our MVP co founder management platform. As these 500 founders on the waitlist understand, you invest in early stage startup, you require proof of revenue. Proof, um, of revenue is not necessary, Alessandro. But definitely proof of product, uh, market fit, that it works, that people like it, that there's retention and the end. You need to know what your business model is going to be. Uh, you need, you need to know how much you're going to charge to whom at least the theoretical unit economics could look like. It can't just be we launch, we'll figure it out later. Uh, that is not the way we invest. There are a lot of people, uh, there are a lot of people that, that do that. It's just not us. Right? It's not the approach we have. Okay, Boris, uh, great initiative. I'm curious about if your investor thesis around Marketplace has evolved since 2022. Become more risk averted precede Marketplace investments shifted more validating AI opportunities inside. Um, so Boris, that was episode 2052, it was my podcast last week which is investing in marketplaces in the age of AI. We continue to Be very bullish on marketplaces. Um and we, we and all the marketplaces use AI. They use AI to translate the listings and to translate the conversations, buyers and sellers so they can be global. So you have pan European startups for the first time. You're using AI to have a one click listing where you take a photo and boom, title description, price category all pre filled for you. Improving productivity. You use AI to do better matching with supply and demand. So we're still investing in marketplaces and they're all using AI more effectively. Um and we're more seed investors than pre seed meaning um we like things to be live and have unit economics. Now the categories uh were more B2B these days than consumer facing but there's fun stuff happening even consumer facing. We're like a live commerce company um uh called Palm street which is like rare plant Marketplace. We're doing uh were investors in a fire uh truck company or fire engine company at like 30k aov uh uh called Garage. I mean so there's a lot of interesting things happening with layers uh of uh services added on it. Uh so still more bread and butter because I don't want to avoid competing in the game of kings with infinite capital and negative gross margin in the AI bubble. I um so we're indirectly exposed to it because while A we have amazing investments in things like figure AI um which is doing very well and B all of our companies use AI um but they're vertical applications of AI versus being foundational AI models themselves. And I actually think that's where a lot of the um uh interesting opportunities lie today in terms of like reasonable, reasonable you can build big businesses with very little capital uh and you don't need like the same super shallow pool of AI engineers. Uni need tips where to find reliable fractional full stack developers AWS angular to help improve an existing SaaS MVP M the Depends how good you need them to be. But there are a lot of like uh places like Toptal uh which allows you to find amazing uh oh no we use a fractional uh probably go to, I would go to Fiverr or go to uh to upwork. The issue is you're going to need to do selection. Um so one of the ways I would do selection on Upwork or Fiverr by the way is you create your spec, you, you, you, you you get like 20, 30, 40 people apply, you look at the best five, you give them the first 10% of the job, you hire five of them and then you see the one that delivers the best that you like working with the best. So you're overpaying for the first 10% 5x. And then you find the one you like and boom, that's the one. So in a way, you don't necessarily even need to interview. You can just validate based on the work they do. And that's the way I've hired a lot of people on Fiverr and on Upwork, uh, over the years. Okay. LinkedIn user Somehow no name showing time no see. Want to find our AGI endeavor. Recent breakthrough ping for a demo. Um, you know, I'm not even sure what if you think of, like, what is AGI exactly right? Like, uh, general intelligence. I mean, currently our GPT can pass the Turing test. Uh, so is that AGI, is that not AGI? I suspect that the way we're going to define intelligence is going to change. Uh, the way it works from my perspective is AI is superhuman in certain capabilities, in terms of ebbing away in math problems, et cetera. And it's way beyond human intelligence. It's significantly better, significantly faster, significantly more patience. By the way human minds work, which is with limited data, we create concepts, which is the opposite of the way, uh, these LLMs work, which are those infinite data. They get patterns. Um, maybe just profoundly different. May just be two different ways of creating thought patterns and processes. So it's not completely obvious to me, um, not completely obvious to me that, like, there's a human. We're going to replicate human thinking. I think we're gonna. We're gonna have profoundly different ways for the AIs to think. Uh, and that's okay. And, and so, yeah, it'll be interesting. But would I. I suspect that whatever your EGI endeavor is, um, it's gonna cost infinite money. So it's. If it's capital efficient, happy to look at it. If you need hundreds of millions, we, sadly, I wish I had more capital. Are not the guys. Um, George, in your experience, how important is choosing the right initial wedge when building a marketplace? What makes the wedge strong enough to expand into a larger ecosystem? So when you launch a marketplace, you have no barrier to entry. Just to be clear, like, anyone at the beginning can build the same thing. Um, your. Your wedge, if you want your bear, your, your. What is going to differentiate you over time is liquidity, right? In these marketplaces, ever more buyers, presumably, are more sellers and more sellers ranks. There are more buyers. Once as a buyer, I go there and I find whatever I'm looking for and as a seller, and it could be of anything, product, service, there's somewhere to buy what I'm selling. That's when you have your wedge. So it takes time to get to build. Day zero, you have zero barrier to entry. But within two, three, four years, your barrier to entry, uh, is actually the liquidity that you have. So find, create early liquidity between your buyers and sellers. And as you get your early liquidity, that creates your barrier to entry over time as it becomes bigger and bigger and bigger. And these things as I mentioned, have a tendency to be winner takes most because uh, ever more buyers earns and more sellers and more sellers brings ever more buys. Continue on the questions, uh, and the presubmitted questions, uh, uh, what metrics matter most when you're evaluating whether AI adoption is actually sticky to marketplaces? Okay, so yeah, I mean so whether it's sticky or not, we look at retention, uh, and that's also we look at retention when it comes to whether or not a um, an AI company is being successful. Right. Like so lovable. So a lot of the AI, uh, companies have massive churn. Um, and so that's one of the things that makes me worry that they have, that they're not very sticky that they have, they don't have permanent, maybe they have product market fit, but they definitely don't have barrier to entry. Um, it used to be that I used Runway for making videos and Now I'm using Sora. So I'm on ChatGPT. It used to be that I was using Midjourney for almost all of the photos and images I was creating for my blog, which itself had replaced stock photography. And Now I'm using ChatGPT more and more and more. So I'm worried, you know, so I would look at cohorts, I would look at retention, um, and not just one month retention but like six month retention, 12 month retention. Like the better products usually have a U shape. You use them, maybe you choose them last, but at some point you come back to them and so uh, cohorts retention curves matter dramatically. Boris. Uh, check out genie. It's Ukrainian chart marketplace, mostly for software developers. Yep, good idea to recommend that uh, for people that are looking for software developers. Okay, continued questions. Um, what founder trade do you value more today than you did a decade ago? Um, honestly the traits that I value haven't changed very much. Uh, I love people that are extremely eloquent and visionary and therefore that can hire a better team, sell better to VCs, talk to press, get better deals, etc. But also know how to execute that, their attention to detail, they, they focus on unit economics, etc. Now the one trait that sadly is not a requirement for success is like being a kind person. Uh, you have a lot of assholes. Uh, and the problem is because some people like, uh, Steve Jobs or Travis got away with being assholes. Um, it encourages, emboldens, or allows people to just not be kind. Um, but life is too short for dealing with assholes and I'm in a position where I don't need to and so I want to work with like kind people. Now that said, or a lot of founders are arrogant. Absolutely. Um, is that bad? You know, you need some level of like delusional self confidence to build a startup. Right. Like the five year survival rate of a startup is like 7%. And so you need to believe the odds do not apply to you. So arrogance, narcissism, I can probably deal with, uh, being an asshole. Definitely not. Uh, but has it changed? Not really. I was kind of ready. Already had that belief system before. Okay, um, question from Jeff. If you were graduating from Princeton and maybe just leaving McKinsey, uh, or consulting in 20, 20, 26, uh, what do you think you would be building right now? And why now? Clearly I'd be building something in AI. Um, this is where the world is and it's changing and it's interesting now. It kind of depends. So if I was 23, depends on the skill set. I'd say there are multiple viable path. Uh, you can join a rocket ship and latch on. So, you know, go work for open AI, um, anthropic, uh, you can build an AI now, building an AI, the thing is, the bigger the game of kings is like, am I going to own humanoid robots? And you have like figure and optimus. Am I going to own the underlying LLMs? You already have like big winners there. Um, and then you have some of the verticals. I suspect I would go for applying AI, um, in categories that are so like old and broken and antiquated, where everything's done by pen and paper and relationships in a category that is of interest to me. Because obviously you as a founder don't work in a vacuum. You have your own set of interests, you have your own set of skills. And so you want to solve a problem that's big enough, that's monetizable, but that you actually care about. Um, and whatever your background is, you know, I would focus on that. And so maybe your parents came from the construction industry, so maybe go and optimize that. Maybe, uh, you Work in the food industry and there's, you know, and you have so many profound problems in terms of like, turnover of employees, uh, sourcing of different materials, etc. So I can think of applying AI to automate processes and bring efficiency to many categories that haven't been addressed before. And I'd probably be working in that now. Which one specifically? I don't know because I haven't been thinking about it because I've been too busy between, uh, uh, my funds, Midas, the kids, et cetera. But, uh, definitely an interesting thought experiment and something I actually intend to allocate time to on a go forward basis in terms of thinking through. Okay, if I wasn't doing FGA labs today, uh, and building Midas, what should I be building? And the answer obviously is something in AI, but what it is, uh, for me today is interesting. I don't know the answer to that, but I definitely. It's a question that warrants asking and I will ask myself, uh, in the coming weeks, month and year, uh, what it could look like. Okay, question from Margot. If we remove from your identity startups, investments, performance, uh, perhaps even financial success, is the person who are you truly? And is this person enough? Um, and it's interesting so in the us people often define themselves by the job they have. And of course the job they have is only a tiny percentage of who they truly are. Like your personality, your needs, your desires, your dreams, your aspirations. Um, now I try to be my true authentic self at all times, and so I think it comes across in the way I speak. But you're still seeing through my blog, through the podcast, you know, the professional version of me. Um, and so to answer the question is the look, look, I think that the meaning of life is to be your true authentic self, whatever that is. And we're all built differently with different predispositions, uh, desires, needs, etc. Um, and honestly, um, at this point, like, actually I'm fully fulfilled by being who I am. Like, I love all the things I love. Like from being a father and a parent, playing with the kids, to play with my friends, to play video games, to reading books, to writing my blog, which is actually these days, not mostly not about business, to interacting with my friends, to, um, kind of actually being, yeah, the patriarch of the family and in the positive sense of the term, uh, to, yeah, playing tennis, playing paddle, et cetera. Yeah, the life I have is extraordinary. I literally think I'm living the best life that's ever been lived. Definitely the best life I can live. Uh, and I'm fully fulfilled. And so if I was not fighting for whatever reason could not be working today's world, I'd be very fulfilled and happy regardless. So uh, I, yes, the, the, the external identity driven by work is nice, but actually uh, and I think it's a source of purpose because I think my purpose is to help harness at least one of my purposes, help harness the deflationary power of tech, um, to solve the world's problems, to make things better, cheaper, faster for the masses, uh, and to try to address the combination of inequality of opportunity, climate change and the global mental and physical well being crisis. But uh, even if I didn't have that, I find extraordinary source of purpose through playing my kids, raising my kids, playing with my friends, etc. Another question from uh, uh, Margot. You give the impression to have a infinite confidence that's super rational and to be very poised. Uh, do you have any insecurities? Um, I'll start actually by answering the question. In the past, in the past growing up I had many insecurities. So because I was really good at being very smart and at getting good grades, I defined myself by that. But I was very insecure socially. Right. Like by virtue of being younger than my peers, uh, by the fact that I never had girlfriends or friends, et cetera. Like I had my first girlfriend at 27. Was it a source of insecurity to not have a girlfriend when I was 26 or never had a girlfriend? The answer is yes. Right. Like uh, today much more comfortable with who I am and so don't have specific insecurities. But do I? So I'd say, I guess the answer is no, no real fears. Uh, but are there things that really graded me that I don't love in life? Absolutely. Like I abhor aging. Like I used to be the youngest at everything I did and now often I'm the oldest. Do I like that? Absolutely not. And so I rage, rage against the dying of the light. Uh, and that's why I work really hard to stay fit, uh, uh, be sharp, uh, and stay, keep my youthful energy hopefully forever, uh, but definitely for as long as possible. So not sure it's an insecurity per se, but definitely something that um, uh, annoys me. And I'm working very hard to fight against uh, father time because uh, yeah, there's so much to do and we live in such extraordinary times and we're so privileged to be it that to have the energy, the health, to be able to live it to the fullest signing. Like I Want to be able to play with my kids in a very meaningful, uh, way. And last question for Margot. Um, if you could not have become a founder, uh, and an entrepreneur, what do you think? What job would you think you would have liked to explore? Uh, that one's hard because I really abhor, uh, traditional structures where like the 9 to 5 job, uh, having a boss. Like I consider myself unemployable. So if tech wasn't a thing, I suspect I'd still be entrepreneurial if possible. And another form of industry category. Now if entrepreneurship itself is not possible, that's way harder because then I'd have to find a job that like, matches more my uh, way of thinking. And I'm not quite sure why that could be, um, interesting experiment for another life that I hope I never have to do because I love what I do and I love the flexibility and the freedom and the creativity. Um, in a way, entrepreneurship is my form of creative expression. Taking something from zero to one and creating something out of nothing. And I'm not sure what else would, uh, be so fulfilling. So no idea, uh, I guess is the honest answer. I mean, could I have been in private equity or consulting or banking? Absolutely. But would I love it day to day, minute by minute? And I think the answer is no. So there are many things I could be very good at. I could be a professor. I'd be a fantastic economics or mathematics professor. But again, would I love it? And the repetition over the years of the same course material. I don't know, it's too slow and uh, not scalable enough. I don't think it would feed my soul. Uh, but yeah, actually professor is probably a, ah, reasonably good one. Um, but not sure it'd be as fulfilling. But for sure it wouldn't be. Wouldn't uh, find it as fulfilling in a way, I scratch my professorial intelligence itch by doing this podcast, by answering the questions of the audience and the users, by thinking through things I want to share. In a way, playing with unicorns has always been about what are all the things I wish I knew when I was 23 and starting as a first time foundry that I now know that I can share with you. And so, and I find that to be more interesting, more scalable, um, than having class. And I used to teach like you know, classes at Columbia Business School or Stanford Business School, et cetera. And yes, you're teaching amazing people, but a small class, not super scalable. And the content didn't change that much. Now it's like whatever crosses my Mind, create the material, poof. Put the podcast and it is as and when there are ideas that are relevant. Okay, George, in early stage marketplaces, what are the clearest signs that a platform is about to break out? And the cold start problem? Rather than remain stuck in low liquidity, um, the if the sell through rate of the items on your site, if you're selling products about 25% or more, you sort of have liquidity. If you're a services marketplace and you start accounting for 25% or more of the revenues of your supply, you start having liquidity. Um, and the way to make sure you get there is don't overflow. I mean I guess it depends on the marketplace. But the biggest mistake marketplace founders can make is having too much supply. If uh, you have too much supply, they're not gonna be engaged, they're not gonna reply, the buyers are gonna be overwhelmed with choice. It's much better. You have the very best supply for whatever category, zip code, et cetera. Find them demand, get them liquidity, then scale a bit more and scale a bit more on the supply, then more demand and keep matching. Uh, a sign that you have product market fit is when you're customer acquisition costs are declining, that's when the users are coming back bringing their friends and your unit economics keep improving. Uh, but early signs of liquidity, typically ah, 20, 25% sell through rate is usually a good sign uh, that in a used good marketplace at least you have liquidity. Okay, going back to the questions from uh, were pre submitted. Okay, uh, Luis Gonzalez, uh, if you're starting global marketplace from scratch today, what would you prioritize most as your core defensibility from day one? Liquidity brand community technology. Uh, especially with AI becoming increasingly accessible, kind of a, I've kind of answered this before but basically day zero, you have no moat, no barrier to entry and your barrier to entry over times becomes liquidity Once you actually start getting the ever. More buyers brings more sellers, more sellers bringing more buyers. So focus on your unit economics, whatever your scalable repeatable strategy is, uh, for scaling supply and demand, keep uh, doing it, keep matching it, keep getting liquidity. So liquidity in marketplaces trumps everything. And in fact imagine that somehow the top of funnel like that the agents would be the ones transacting on behalf of users. They would transact where there is liquidity. So your ultimate defensibility is in liquidity. So liquidity, liquidity. And when in that more liquidity, um, Jean Francois, I see you invested in quits. Uh, can you tell us more about them and what is their ambition in the future. So Quince is one of the fund returners for FJ Labs. They're doing extraordinarily well. They're in affordable luxury, uh, marketplace and direct to consumer brands. The I guess marketplace because they're in an asset light model. Um, the founder Sid is extraordinary. We invested in them since the beginning and uh, I guess the pitch for them, the elevator pitches, it's the quality of a Macy's, the pricing of a Costco and the um, logistics of a Shima Retimo. And they've grown extraordinarily from whatever like 100 million to 300 million a billion in sales to over around 2 billion last year is still growing like crazy. And they just raised at a 10 billion valuation from Iconic. Um, so where did they go from there? So first of all it's extremely rare that a company on this scale like a billion and 24 revenues is still growing 100% year on year. That like never happens. Um, and they're still in the very beginning of their journey. When you think of the categories they're in, when you think of the geographies there, they just launched Canada this year. I think they're going to start launching in Europe. So they're at the beginning of international expansion. They're at the beginning of a category expansion. I can foresee a world where they're in uh, tens of billions of revenues in five to 10 years. And this is a company, you know, don't, don't. You can keep winning. Like the company is already in a dominant position and it can keep winning. There's uh, so I'm hoping that it keeps winning, that it keeps scaling and keeps doing extremely well on a go forward basis. So uh, Quince, uh, is already a fund returner and I'm hoping will continue to be a fund returner in the future and, and ever more so. And one of the biggest winners ever for FJ Labs, Gael, what markets today look boring or unsexy but will produce the next generation billion dollar companies. So everyone right now is focused on the big war in the foundational models. Right? And yes, this is the multi trillion dollar opportunity and the ChatGPT versus Claude, uh, versus Grok, whatever. Um, and this is where all the attention, all the money is going in, right? Like so when we looked in my last uh, podcast, 75% of the venture dollars went to AI and 95% of the YC companies were AI. Uh, foundational model type companies are fighting over the game of kings. What is Completely unsexy right now actually are things like marketplaces. Uh, we have amazing companies in the portfolio that they're growing from 10 million in GMV per year to 30 to 100 or whatever. And because people saw growth of zero to billion or billions very rapidly in the AI space, they're not excited by this anymore. Even though these companies are capital efficient, they need a lot less capital. They have amazing unit economics, they have amazing gross margin. And there are a lot of industries that, where you could use AI to make them more efficient. Um, from public services to construction to retail, et cetera, where I think there's massive, massive opportunities. There are many categories where combination of opaque, fragmented data, uh, um, or needing a lot of people for intermediation. You can imagine worlds where these agents could actually make, improve the economics, make the category larger, etc. So I would say boring old industries that have not yet been touched by technology, where for the first time you could use agents, uh, in order to scale and make the category more interesting and efficient, of which there are essentially infinite, uh, uh, most of the economy has not yet been touched by AI. Um, it's only the super early adopters of tech who think that's the case. What is the biggest blind spot you currently see among venture capitalists? Uh, well, definitely everyone's piling in. All AI, all the time, doesn't matter. The valuation doesn't matter, doesn't matter. Uh, the gross margin structure we need to be in because they win is going to be huge. And it's very bubbly. Um, it feels like 20, 21 all over again. It feels like 2006 real estate, uh, where it only goes up, it never goes down. It feels like 98, 99, 2000 tech bubble. Uh, but uh, at the same time someone is going to win and the rewards are going to be huge. But would I be coming in right now at these insane valuations and anthropic and OpenAI? I guess the answer is no. Uh, could they still grow a lot from where they are and is this the biggest opportunity? They're more possibly. Uh, but if you were early, that's great. If coming in now wouldn't make me feel particularly comfortable. And so I would be the more what we are, the more boring applied AI investors. The way I describe our strategy is the smart way to invest in AI. You invest in companies that use AI super effectively to have IR margin, to have lower customer acquisition costs, to have higher conversion rates. To me that's the correct way to play this. And it's um, yeah, Definitely not what these other VCs are doing. Okay, let's see about the questions that were submitted by email. In the meantime, while you can still keep, uh, posting questions here, uh, uh, let's look at here mayures, which categories subcategories within the AI space. Uh, potential potential, which ones are overcrowded based on the pitches you see and the discussions you have with other super smart investors and VCs. Well, I feel that the foundational model game is super crowded, right? Like uh, the XAI and Mistral and, and also true in the verticals like Runway versus Sora and Mid Journey, et cetera. So that feels extremely crowded to what I suspect will be a winner takes most category. Maybe it'll be two. You know, maybe anthropic wins B2B and chat GPD wins consumer and Gemini keeps its, you know, some market share. But do I see 20 winners in this space? No, it feels 1990s search, uh, engine wars, altavista, uh, versus like us versus yahoo, etc. And then all of a sudden Google comes along. Um, so I would not be funding more foundational models. Uh, and I would be focusing, as I said, on the applying AI to categories that people have, uh, not been using it for right now. But definitely harder to raise in these categories, um, because it's not deemed pure core AI. Um, George, have you seen marketplaces succeed when the value isn't a single transaction, but rather coordinating several services around a larger life event? Um, yes, we are investors in a marketplace around weddings, uh, that is doing pretty well. Um, they have a massive architecture of weddings in Europe. Um, of course the name is going to come back to me at some point soon. Uh, and of course, and the, the way they monetize is helping you find your caterer and your venue and the photographer and the person providing the cake, et cetera, et cetera. So they are coordinating around many services, um, for around one large life event. So wedding is definitely an example of that. Uh, I think it can happen in other large life events. Uh, perhaps we'd have to define what those life events are. Death obviously is a big traction for people like liquidating estates and estate sales, et cetera, um, and you know, like graduating college. Um, I mean the problem, the thing is when you graduate college you need, maybe you need a car, maybe you need, you need a job, maybe you need, ah, a housing. But all these are well done by sites that do that full time. So would I create one, um, site for all these things? I'm not so sure. Um, versus the verticals that are already best in class for each of these categories. Um, same thing on moving cities. So there's a bunch of companies that help you move cities and they're doing okay. No one's done great because again, if I'm moving new city and I need to find apartment. Yeah, Zillow is great. You don't need to go. Uh, so a site specifically for moving. Um, so I think weddings make a lot of sense. Would be death makes a fair amount of sense. What are the other large life events worth thinking about? Okay, continuing on the pre, uh, posed questions, Godfrey, question number one. How has your FJ Labs fundraising matrix changed, especially in recent months, given AI's rapid impact on B2C, B2B market, B2C marketplaces in terms of traction ran size, valuation. So are, um, our valuations going up dramatically at the mean and frankly even median? Yes. Because of AI, you're seeing bigger seed rounds. I mean, we just saw a billion dollar seed round. Billion raised 3.5 billion pre. So clearly the valuations, uh, that people are commending, especially in AI, are a lot higher. Uh, but we are avoiding that AI hype. And so we are still focusing. Like in, in 21, when I was, when everyone was saying, oh, your matrix that I date, it doesn't make sense anymore, etcetera, uh, and of course I was correct. It came back. I was correct meaning it came back with a vengeance and the numbers reset. So if you remove from the equation all the AI hype companies, uh, the matrix is still viable, right? Like, so we still want you to be at, uh, like 500k to 750k a month in GMV with a 15% take rate. When you're raising your series A and you're raising 10 at 30 pre or 7 at 23 pre or something like that, uh, we still want 2.5 to 5 billion GMV per month. That's expecting, by the way, 10, 15% take rate. If you're at a 2, 3, 4% take rate, B2B. We expect much higher GMV when, uh, you're raising your series B of like whatever, 50 million and 53. So the Matrix is still correct, uh, but doesn't apply in AI where people are paying insane prices, um, at seed precede, a B, whatever. Uh, but if you were building a company, I would recommend you to stay close to it because if you raise too much money at too high a price, it will kill you. It's one of the biggest reasons companies fail. They don't grow into the valuations and they fail to raise the next round. If you're a vc, I would recommend it. You just stick close to the matrix, because if you overpay, you're going to have bad returns. And the VC asset class is already not doing very well. So, uh, have good returns. Question number two. Since AI makes building software much easier, how much do early stage VCs value? Technical Co founder. Oh, yeah, I answered that before. Uh, which, as I said was, uh, the answer is, it depends. And it depends on the category you're in. If you're, if you need Technical co founder because what you're doing is extremely hard, then you should have one. If it's, you know, if you're building an open next generation, open AI, have a technical co founder. Okay. Rosa Beluda, what are you missing in life if you're missing anything? Uh, honestly, I'm. I really think I'm living the best life that's ever been loved. I don't think I'm missing anything. Life, uh, I'm healthy life, my family's doing great. Um, I'm doing well. Like, life is extraordinary privilege. And I'm full of gratitude, uh, for the life that I have. So, so don't think I'm missing anything. Uh, maybe. I don't know what I don't know. And there are things I'm missing I don't even realize I'm missing. But, uh, yeah. Uh, next question. Does Palantir have a rival? Uh, there's a French Palantir called Al. Um, not spelled in a funny way, as most tech companies are. But there's a more interesting one called Fundamentals, which is because Palantir, it's hard to tell how much of a tech company is IT versus a services company, right? Like their implementation is like 6 months to 18 months. Most of the revenues they have is coming from the implementation services versus recurring SaaS fees. Uh, and fundamental, they use AI, obviously, and they do integration in two to three days. And most of the revenues are through subscription. So two days. Me, that's the most interesting Palantir competitor. Um, up and coming. Do you have a preferred artist? I'm talking about a painter. Um, not really. Writers, more so. Um, painters. Yeah, no, hardly. I guess not. Not. Or. Look, do I appreciate art and what artists are trying to do? Absolutely. But not sure what. I have an answer to that question. Okay, uh, continuing on the question, pre submitted questions. I recently graduated from master's program, uh, Matteo, and interested in AI startups. If you're graduating in 2026 today and want to build Would you start your career at a large company or an early stage startup? And for someone with a generalist profile is that still a viable path today? And what skills would you prioritize broadly on? Tax, technical and non technical. So in general I, I would, I, I think you learn faster and better in, in startups uh, than you do in large enterprise. The when I graduated from college I went to McKinsey. It was like business school except they pay me. But it would have been just as viable to join a startup um, probably seed A or B, maybe a B sage but not too big. Otherwise you're going to have a world that's very pigeon hold and you're not going to be able to learn as much as you would otherwise. So you want one that has enough product, market fit and funding that is going to continue to do well uh, but not so established that the role is like very cookie cutter and that you can uh, do and prove yourself out and follow your passion and learn as much as you can. Uh, so I would join an early stage startup um, uh, probably an AI probably in the Bay Area and move there by now if I was graduating college and to figure out like what is the best path versus joining a large company. Now again OpenAI maybe is okay uh if you're an engineer. Now if you're a generalist which is your case probably, uh, then the smaller companies make more sense. And do I think there's a path for generalists? Absolutely. I think there's more path today in a way for generalists than ever before because as a generalist you can actually use the tools of AI to, to get tech out of the door very quickly. You can learn to buy code pretty quickly right. Like with cursor you can um, things are much easier for you as a journalist that is smart using the AI tools than they were ever before. So and if you think of like the role of CEO and the founding team in the go forward basis the CEO is the generalist. So Absolutely. Uh, being a journalist is amazing. Now as I said earlier I would play with all the tools. I would, I would you know, create an open claw, play uh, with Claude, play with it with GPT, play with cursor, uh, become super familiar what you can do with them and, and how far did the bleeding edge you can take it. Uh, and you would be shocked at how much you can improve your productivity, how much there is to learn, how much there is to do. Uh, let's see Alessandro. It seems to investors tend to fall into two camps. Those who prefer Warm introductions and hate cold outreach. And those who are open to cold outreach, which camp do you fall into? So first of all, all investors prefer warm introductions, right? So uh, if uh, there's a founder I know or a VC I know or whatever that says hey, you need to talk to this founder who's amazing, obviously I prefer that, but I'm open to cold outreach because not everyone went to Stanford and Harvard and Princeton and is in connected to the social connectivity of the networks that allow you to meet uh, the relevant family founders and VCs. And so some of our best investments came from cold in bands where I've gone any of the big schools or they were instead of, they were in Brazil, but instead of being in Brazil, in Sao Paulo, Rio, they were in Bello Horizonte. Uh, that said the some of the threshold is higher. It's just there's a lot more. We get two to 300 golden bands a week and the percentage that we invest in is a lot lower. So I um, we are open to cold and bad. If you can get a warm intro, much better but we're open to it. Andrew McCain Years since we last met in New York. Your business along selection criteria has changed my life. Ah, glad uh, to hear that project. I'd love to get your feedback on follow up question here regarding services. Do you think there is value following the Palantir model of doing services heavy during scaling, establish customer relationships, a durable moat. The product suite evolves and becomes more autonomous using AI to create true ARR. In other words sources first approach. More of a go to market than is about AI ubiquity. Uh, the answer of course is it depends. It depends on the category, depends on the customer profile and segment. Um, the m. I prefer non services approaches because the main feedback you're going to get from VCs is like are you a services company? How scalable is that versus are you a actual tech company? That's why I like Fundamental more than I like Palantir. It really is a tech company. Um, so to the extent that said, you know, if you're selling to governments often you need to be selling a service. The service layer, the installation, the relationship matters a lot. So I guess the answer is it depends. In general I'd rather invest and have people build tech companies than services companies. Um, and some of the challenges that feedback that these companies face when fundraising because the valuation of a service company is profoundly different from the valuation of a tech company. But if it's a go to market strategy, if it locks in the Customer and then allows you to, to get these MRR AR contracts that are highly valuable. The high margin, then it's okay, right? Uh, at the end of the day, what I care about is what is your go to market strategy? What is your product market fit? What do the unit economics look like? What is your customer acquisition cost versus the net contribution margin per customer? And as long as those work, and if services is the way in, that's fine. But it needs to be explicit that that's the way in and not the end goal. Lisa, a bit of a different question, but I'm curious, what type of school education have you chosen for your son? No, I answered that question earlier, uh, when I talked about office school. Uh, Sonia, what are the kids development games on PC or Nintendo that you use? Um, what's interesting is, um, there's so many educational tools out there. First of all, my son who's 4, is obsessed on YouTube with number blocks. Um, like he's doing multiplications for fun. It's like 8 times 8 is 64. Like whatever, 27 times 2 is 50. It's 54. Uh, 128 times 2 is 256. He does negative numbers, he does basic algebra. Not because I am forcing him to learn math at 4. Uh, you know, when their expectations for him to count at 25 is because it captures his interest. And so he finds educational content on his own that he likes on YouTube and I give him the iPad in the morning when he wakes up and at night before bed and he m basically follows, um, number blocks and learns math. Um, in fact, he's inclined enough that he's asked me to go to Russian math school in New York. So I also sent him to Russia math school. Um, but are there interesting games that you can play with your kids to foster their creativity learning? Absolutely. Um, we just played together on the iPad a game called Lost in Play, which is kind of a adventure game with puzzles where you need to use basically IQ type tests or brain teasers to solve problems to get the story moving forward. And there are a lot of these again, that's appropriate for a 4, 5, 6 year old, um, as you get older. Um, the reason I like building on a combination of Minecraft and Roblox, uh, is the logic patterns of building there. And again as a builder, not as a consumer, uh, is it teaches you coding in a way. It's an interesting way through fun to teach kids coding. Um, so are there more? Yeah, I would again, I don't know the age of your kids. Ksenia uh, but things like Lost in Play or amazing, um, and there are a bunch of kits you can order that are stem where you can, your kids can build robots. I mean there are a lot of things, but I would lean into their interests. I mean, as I said, like I didn't tell Fafa, okay, go learn math. He just decided he loved it and learned it's part of the reason he's so excited about going to, to AI school next year, uh, which is Alpha. Um, next question from Tom. Are you worried about job losses? Uh, created by AI? So this is the perennial question. Uh, AI is going to take over all the jobs. There's uh, going to be 95% unemployment, it's the end of the world, et cetera. Uh, and this is a fear that is universal and has been universal for hundreds of years. Right? The, the Luddites were against the electronic loom in the early days, even though it made the life of people that were weaving, uh, a significantly better. And this has been true throughout history. Uh, and people have worried about like all the job losses. But let's say I take you back 26 years to 2000. Um, and I told you and we were now like uh, March 2000. Like look, in 2026 I've come back and the top four job categories of 22,000 have disappeared. Uh, there are no more travel agents, there are no more bank tellers. A trillion of local retail has disappeared because of online commerce. All of car manufacturing has been automated. And these are the top four job categories in the US right now. Please now describe the economic conditions in 2026. And people would tell you, oh my God, mass unemployment, Great depression, et cetera. And yet today we have lower unemployment, higher employment and 2x GDP per capita than we did back then, despite all these job categories disappearing. Um, now of course I'm hearing right now, but this time it's different. Uh, it's happening faster than ever before. AI is replacing all these jobs. And so first of all, it's not happening that much faster than ever before. Um, in 2011, 2012 when the first self driving cars came to the fore, people were like, oh, the top job category in the US with 4.6 million jobs is truck driver. Um, and all these jobs are due to the spear. They're gonna be no more truck drivers. What are all these people going to do? They're gonna be automated, uh, away. And we are now. So this was like 2011, 2012 between you know, literally 15 years ago. We're now 15 years later, not a Single job of a truck driver has yet been automated, uh, by a self driving truck. And we're at the very beginning still of the self driving AI revolution. Now do I have any doubt in my mind that at some point in the future, 10, 20, 30 years, 1 ah, hundred percent of vehicles on the road will be self driving? No doubt whatsoever for sure, it makes sense. And they'll also all be electric. But um, it's going to take time. Like the first ones that get automated are the most expensive because the technology costs a lot of money. Uh, and culturally it takes time. A lot of people, first time they get a self driving car, they're scared shitless that uh, it's going to kill them. Even though singularly safer than traditional cars. So culture moves slower than technology. Technology moves very quickly. But governments will take a long time to adopt AI. Large enterprise will take a long time to adopt AI. These changes happen a lot slower than you think. So number one doesn't move as fast as people think. Number two, especially people in tech, because we're at the forefront of tech. Number two, people don't understand how many jobs are really going to be created or lost by AI because they don't understand where the elasticity of demand for a product or service is. So right now one of the big thesis people have is, oh, programmers are going to become obsolete. You will no longer know the AI will code itself. You will no longer need programmers. It's a possible outcome, but it's far from guaranteed that that's the most likely outcome. Um, in the 1980s there was a job where people were called the spreadsheet. And the spreadsheets were done by humans. Highly paid, highly skilled humans were built a spreadsheet before something called Symphony, which now I guess would be cool and be Excel, came to the fore. And Excel did lead to the destruction of all the jobs of spreadsheets. But you know what? It created the jobs of millions and millions of millions of financial analysts who now had the tools to do financial modeling, financial analysis. And so a couple thousand jobs disappeared. Millions of jobs were created. So uh, when it comes to software engineering, for instance, you could make the case that as the cost of software development becomes very low, demand for it explodes. And companies that historically did not hire software developers like SMBs or governments or large enterprise at large scale would start doing it. And so I can actually make a case, I'm not guarantee that this is going to happen, that as it becomes so much cheaper to build software, demand for software will increase so much that actually employment Increases. And that's not including the fact that there's so many new job categories that are going to be created. Right. Like the. In 2000 people could not imagine what the role of a social media manager would be. Uh, or a twitch gamer, caster or whatever. So so many new jobs are being built ah. And created that people have a hard time imagining. So am I worried about the job apocalypse? No. Are jobs going to change? Yes. Will there be losers and who will need to be retrained and helped uh, to adapt because the winner isn't losers. In, in as the job market evolves are often different. Absolutely. Um, but am I worried about 95 unemployment rate and the Great Depression and we're all out of a job and, and it happens overnight? Absolutely not. Um, it goes against economics, against everything that's ever happened, against culture and the speed at which people are willing to adjust and adopt technology and the inertia built into our political systems to our economic systems, et cetera. So no, I do not think this time is different. But yes, I do think that as per usual, this technology will profoundly transform humanity and the way we live our life though it will take a lot longer than people think. So we're yet again overestimating the short term impact of AI technology. Underestimating the long term impact. Okay. Jorge. Building uh, decision intelligence infrastructure for the TMAC USMA industrial corridor. Okay. I guess that means Mexico. U.S. probably in Mexico. Um, B2B to B model targeting customer brokers, environment consultants and accounting firms, distribution channel. Do you see value in Latin America or industrial verticals in the market to fragment to build venture scale from there? Well, I'll take a step back. Uh, do I, do I think you can build venture scalable businesses in Latin America? Absolutely. Um, think of like new bank in Brazil or Plata which is a Neobank where investors in Mexico do I think, you know, they make out of libre, etc. So first of all there the Latin American market is large, growing ever more sophisticated, is starting to have its own uh, VCs, you know from Kazakh to Monashees, et cetera. So you can totally build successful venture backed startups in Latin America. Uh now specifically in your sector, I don't know enough about the total addressable market size, economics, etc. Uh, but my, to the extent we're talking like 10 billion plus dollar market where there's probably enough margin structure, I suspect and the answer is yes. Uh, so yeah, reasonably positive. Okay. LinkedIn user not sure why names are not always showing and sometimes they do. Oy, Fabrice, I don't know if you remember me from earlier episodes, been a marketplace in the Netherlands and provided advice during several earlier episodes. Sold the marketplace, used the money to now build an insurance company. Heavily integrating AI. Great use AI ready for customer service fraud, pricing, claims processing, marketplace advice area. Well, you're more than welcome. Uh, and I think what you're doing in terms of using AI to do, improving in everything customer service fraud, pricing, claims processing makes a lot of sense. Um, we're investors in a company in Europe called Ace Waves. Ace Waves is a customer care company for marketplaces, uh, where they integrate and they, they automate. The AI replaces a big chunk of your customer care team on average, allows you to lower your customer care costs by like 50% while improving your NPS, improving customer satisfaction, et cetera. So the. Yeah, definitely use AI for customer service for all those things and every startup out there should be using the tools to their fullest extent possible. Uh, Georgia, I'm probably butchering your name. Thank you for answering my question. I push you record a platform at Jacobian Labs bringing GNNs. I'm uh, not sure what that is necessarily commercialization and one. But you said your AI said pass. Is it possible to send a pitch deck or demo to you directly? Um, yeah, send me a LinkedIn in mail, uh with the deck, et cetera. Um, still working on my AI. By the way, the pitch Fabrice is just trying to give you feedback, et cetera. I, I'm going to try to make it more nuanced in terms of like what it likes with. It's unlike what it would. What would it need to see that's different for us to want to invest. So don't take the AI pass as a um, end all be all. By the way, I review and the team reviews all the the pitches, uh, to February pitch Febreze on my AI on februaryscript dot com. Uh, um, I haven't done that yet, but it's on the to do lists of the last batch of pitch, uh, February. So yeah, send me an in mail. Uh, we'll review it. Mention um, that you mentioned, mentioned this conversation from this episode, uh, for reference and yeah, we'll take a look now. Yeah, I don't know how much traction you have. We uh, typically are post launch, post revenue, post post product market fit, but early, early but post all those things. So not sure exactly where you're at, but we will look at it. Um, let me see if any other questions have come in the last few minutes and if not, if you don't have uh, any final questions. Uh, uh, we will bring this to a close. Let me go check. People have sent questions uh, on WhatsApp. Um, okay. I think no, I think um, I think we're good. I think we've covered every question that's been asked uh, uh, so far. So thank you for tuning in as usual. I will uh, post this, the transcript and the summary of this episode uh, uh, on uh, my blog next Tuesday and not sure what the next episode will be and when it will be just yet. Uh, um, perhaps one of the questions people were asking earlier um, in terms of like what AI companies I should be building if I was building it today. Um, actually wait a few more last minute questions are popping in. George, your experience what separates marketplaces become truly massive platforms for those who remain niche um, or services businesses. You know the thing is it's hard to tell in the early days, you know like Uber originally was a black car service. So it was very high end, it felt very niche and that's why um, the uh, I was saying the other founder chose uh to do stumble upon instead of choosing to do Uber. He thought Uber was smaller and it's just when UberX came to the market became bigger. Think of Airbnb. Airbnb originally was inflatable mattresses and people living rooms felt like a very niche product and of course became a much larger category. So find you know follow market fed and see how big the category ends um up being. And sometimes you can create ginormous category. Just so happens that housing is a enormous category and monetizing underutilized housing is a ginormous category. So had it been pitched like that would have been obvious. It was big from the get go. Just wasn't pitched that way to in the beginning. Um, so how would you know how big it is? You know often even if something feels small you can actually go to coin drawn category, add other verticals, increase the temp, what the limit is, you know that often the sky is the limit. Things can end up being a lot bigger than you think. Uh, LinkedIn user in the current phase of AI, how far would you allow decision making be done by AI in the level of human supervision? I would absolutely. Well depends what you're doing. Right. Like if you a use common sense of. When I ask AI to do research which I do on a regular basis, definitely, definitely cross reference the results. Also ask AI uh to give you the counterfactual. So if it argues for something, say if you were opposing, if you were arguing the Opposite view. What would you think? Also, ah, ChatGPT is a huge sycophant. It tells you how amazing you are on a permanent basis. Ask for honest, realistic, no holes, wide feedback, very explicitly, otherwise you're going to get a rosy tinted uh, ah, answer as to, as to what you're doing. But in terms of like fundamental human decision, uh, fundamental important decisions, I would totally have human supervision right now, um, for most tasks. Um, now are there things that can be automated like customer care for, oh, what's the tracking number of my order, uh, or I didn't arrive or whatever? Like yes, absolutely. That you can have AI do it but like mission critical things, use human supervision for now. Uh, hallucinations, errors, biases. But it's interesting these are biases because it wants to please you and so it ignores the downside, it tells you how amazing you are, et cetera. And so you need to be very careful in the type of questions you ask and how you diligence it. In fact use multiple LLMs, um, to test concepts and ideas to make sure that you're getting uh, a better perspective. Um, quick questions. We're in B2C. We're evaluating various age startups. What matters more to you? Early traction. Strong insight into a mass problem that incumbents have ignored. Uh, B2C is hard, um, because you have inventory, there's competition, et cetera. So I care about early traction and unit economics. So for me it's actually more than early traction is unit economics. Uh, but obviously does it need to be a problem that's big enough that it Warren's going after. Absolutely. But for sure in B2C, how do you market it? Uh, and how do you scale marketing? The issue is the customer. Acquisition costs are going up and so it's hard to make the margins often work. So making sure that you can find your economics working to me and scaling and repeatable is probably the m the most key supervisor AI. They constantly ask information, information from all of our operational AIs we allow do light decision making. Yeah, that makes sense and more than light impact. Supervisor human. Yeah, that's rightly the proper way to use agents and the way I would use my agents. So. So for instance, uh, if I have my open claw go and looked in LinkedIn to see potential LPs for the funds, uh, and like buy who could write 250k to find checks and different geos and think through when we could do a meeting. So I can. Great. Do I let the open claw then? Do I ask it to draft emails? I Could send. Yes. Do I automatically let it send the email without me reviewing it? Absolutely not. And is the. And. And maybe it'll do it for the long tail, but would I let it do it for, you know, I don't know if I'm pitching a hundred billion dollar pension fund that could write a $20 million check on the fund. Absolutely not. Like, yes, advise, draft, et cetera. And even then, like, I love, I don't love AI writing. Uh, I love my own writing. I guess I was biased, uh, when I wrote my huge big thesis on the meaning of life this summer, which was a like 10,000, uh, word piece, uh, on my perspective and the meaning of life. Um, after I was done writing it, I uploaded it in AI, uh, and ChatGPT. It was like, okay, give me feedback. Um, and except for the obvious mistakes of spelling mistakes, grammatical mistakes, et cetera, which I fixed using AI, I ignored all the advice. It's like, oh, your title is way too generic. The Meaning of Life. You know, you need a punchy action thing. The thing is way too long. You need to break it down in like, whatever, 27 pieces. Your, uh, examples are too opaque. And like, I basically is like, you know what? I love my own writing. I think the way you write is like, too flowery and cumbersome and I hate the EM dashes or whatever. Like, yeah, uh, thank you for the advice, but no thanks. Uh, I do my own writing. Um, that said, I do like getting feedback from AI so, for instance, yeah, I asked for like, ideas of things to write about, etc. I just like to do my own writing. Um, and by the way, a lot of them m. It did identify mistakes and repetitions, et cetera, that did lead to fundamental improvements. Um, but yeah, I think the way you're using AI makes a lot of sense. It's also the way I use it. But look, I'm AI super user. Like, I talk to AI on a regular basis about everything. I test everything. I create everything from videos to images to testing business models and finding real estate. I mean, you name it, I use AI for it. So. So use, uh, it. It'll make you more productive. Okay, I think we've reached, uh, the end of the stream. Uh, thank you all for joining in. This was interactive, uh, and fun. And, um, I'll see you in the next one, whatever the next one is, whatever the topic may be in few weeks, few months. We shall see. Have a fantastic. Sam.