Why Being a Generalist VC Is a Competitive Advantage (Aydin Senkut, Founder & Managing Partner at Felicis Ventures)

Speaker A: The history of Felicis suggests that even in these hot markets, when other folks have leaned in and gotten burned, you've managed to be strong enough on the selection that those vintages still look good. Speaker B: There has been many instances where we picked the company just right and we were off by a 10x on the entry valuation. So everybody looked at only that side and said there is no way it's going to work. But what they missed is the revenue growth that materialized after was 30x, 50x, 100x. So while we were 10x wrong on the entry price, we were absolutely absolutely underestimating the revenue growth by even a much, much larger factor.

Speaker A: One of the investments that you've made is in Skilled AI. How have you thought about the way AI begins to enter the physical world more? Speaker B: We're going to have a ton more robots in the next 10 to 20 years. I doubt it's going to take jobs away. It's just going to do jobs that people are not meant to do, but they're doing it because there is no other way of doing it. I do think it's going to be happy coexistence. We're going to have a lot of robots and they're going to take more drudgery out of our lives.

Speaker A: When Aydin Sengkut started as a solo GP in 2006, most LPs rejected him, giving him little chance of succeeding as an investor. Speaker C: Nearly two decades later, and Aydin has transformed Felicis into a Silicon Valley franchise, now on its 10th fund, a $900 million vehicle. While many VCs insist on the importance of specialization, Aydin has kept Felicis genuinely generalist. From Shopify to Adyen to Canva to Crusoe, the firm has found billion-dollar outcomes across nearly every imaginable category, including in companies that many others overlooked. Speaker A: In today's episode, Aydin and I discuss how he scaled Felicis from a one-man operation into a well-oiled machine, his framework for evaluating opportunities across wildly different sectors, and why he's betting aggressively on AI despite the sky-high valuations.

Speaker C: We also cover his approach to portfolio construction and what he learned from working with Google founders Larry Page and Sergey Brin. I'm Mario, and this is The Generalist. Every revolution in AI creates one question that never changes: can you trust the output? AI for work is incredible, but without trust, it's just leading to faster mistakes. The challenge isn't building an AI that can answer questions, it's making sure those answers are right. That's where Guru comes in. It's the AI source of truth that connects everything your company knows. So every insight, every answer, every recommendation is grounded in verified knowledge, not outdated information or hallucinations.

When your teams and your AIs share one trusted foundation, Everything moves faster with fewer redos, fewer blind spots, and more confidence in every decision. Because in the age of AI, truth isn't just power, it's protection. See what Guru is doing for thousands of companies like Spotify, DHL, and Stripe at com. That's com. Speaker A: Well, Aydin, I'm super excited to have you here. I've admired your career for a long time and I remember the last conversation we had very, very well and really enjoyed it. So lots to get into today.

Speaker A: Well, Aydin, I'm super excited to have you here. I've admired your career for a long time and I remember the last conversation we had very, very well and really enjoyed it. So lots to get into today. Speaker B: Looking forward to it. Speaker A: I'd love to start a little bit with your origins because, you know, you started Felicis as a solo capitalist. The language of that term hadn't come to the fore yet, but you were a solo GP running a strategy that, you know, really was your own.

Um, and that has evolved into a real franchise over the past 16 years such that, you know, you guys recently announced, uh, a 10th fund, $900 million. Uh, and so I'd love to sort of begin this conversation maybe by closing the gap between where you are today and, and how you started out. Uh, how did, uh, a boy from Istanbul wind up in Silicon Valley? Speaker B: I kind of feel like, uh, I, I lived in 5, 6 different lives. You know, when I was a kid, I couldn't be farther from the truth of today here, but it was really interesting.

My dream as a kid when I was 7, 8 years old was always to travel around the world, meet people, do something, and whatever it is, it's to learn languages, to learn other cultures, to discover other countries. I was very lucky that I was able to get into actually a German school in Turkey. And that allowed me to then use the language afterwards. I came to the US for college and then ended up working in countries like Morocco, Switzerland, Germany, Brazil, and then came back to the US for grad school.

And all of those things, I think, just gave me like a little different flavor, which then allowed me to make the jump to Silicon Valley. And that was a crazy story too because I was not really an engineer, so I had to really push to get my first chance as an intern. And I ended up coming here about 30 years ago. And the languages and the experience of having lived abroad has always served me well. It's actually what differentiated me at Google and allowed me my first product job there. And then I did international sales.

And that allowed me to get this ability to wherever I am, relate to people. And I think this is interesting because it's one of the most underrated aspects of venture capital. Everybody thinks about the numbers, but it's really about people. And what's really interesting is even today, one of the things that makes Felicis different is a lot of our most successful companies tend to be global and international. So in some ways, I am living the dream, the crazy imagination I had as a little kid. And that's what I feel like.

I'm, I'm working and loving what I do and, you know, I have that enthusiasm, enthusiasm of an 8-year-old. Speaker A: Hmm. Amazing. Well, uh, I think we're gonna go, you know, go into a lot of those different, uh, pieces of the story. But, you know, one of the things that struck me when I was researching you a little bit was that your parents were entrepreneurs. Uh, so you, you, you must have grown up with, you know, seeing what it really took from a, from a very early age. Speaker B: Yes, indeed.

I'm an only child. Both my parents were entrepreneurs, different paths and different learnings. Uh, my mom started as a VP of, uh, HR, and that was really interesting because whenever I went to visit her at work, I was fascinated by, um, how she did what she did. You know, she had this elaborate system of like really getting to know people and what made them tick. And what was really great about what she did is it was very much skill-based. And then later on she joined a recruiter and then she just wanted to do it in her own way.

And then she had her own recruiting firm. And what was really cool is she worked until she was 81. Wow. And foreign firms employed her all the way from Denmark to Israel to Bulgaria and like crazy countries where she had no background. And they're like, look, you're so good at what you do. We want you to go to these countries and still do what you do in Turkey for us. And she would take my dad with her. My dad, on the other hand, I came in, they met in college, they were college sweethearts.

I came pretty early, so he had to kind of pick something very quickly. And our family business was textiles, which was a big industry in Turkey. And the big difference there is that was good as it lasted. but it was a commodity business. And as long, or as soon as kind of cheaper textiles came to Turkey from Asia, his business was pretty much done. And so it was a very important lesson that stayed with me that it wasn't just important to be an entrepreneur, but what you did really mattered. And I kind of realized that strategically, you know, like being in a line like I am now, it's very much like skill and capital based.

it's very asset light. Also, it's kind of like very much adapting to the times. In fact, it's ahead of times. So the likelihood to get disrupted is a lot lower versus if you're in a traditional industry, you know, you have a factory, you have like a whole team of people, you know, like you have very like thin margin for error and you're at the mercy of what's happening in the markets in the world. So that's something that really stayed with me. On the other hand, I also have to say, that for those that are brave enough and lucky enough to be an entrepreneur, I think this is the best thing in the world.

You know, like some people have the personality, they're not really made to be employees. They're made to be like, you know, like do crazy things, like take some chances and risk, do original things. And sometimes the best way to do that is as an entrepreneur, as a founder, which I'm sure you would appreciate. Speaker A: Yes, definitely. You were employee, I think, 63 at Google. And I imagine that was a very special group of people at the time. That you joined, I imagine the talent density must have been pretty remarkable.

I wonder what you remember of those early people and that early company. Speaker B: I remember a lot of stuff, and here's a crazy story. The reason why it was 63 and not 30, actually my offer came in when there were 30 employees, but it took over 3 months for my H-1B to transfer. Um, and I still have these nightmares that I think if we were in today's climate, I don't even know if I would have made it. So I'm very grateful for those early days. Coming back to Google, look, the one thing that starkly stood out for me is how smart the people were.

Everybody around me, I felt, were super smart. Not only were they super smart, they were super talented. And one thing that stood out for me is how unique and individual each one of them were and how a different take they had on everything. If you were to ask me one thing that stayed with me from my Google days, where I was for 6 years, through its IPO is that whenever we faced a big problem or whenever we had something big to do, we never took a standard way to do it.

We never went the orthodox way. We were always very creative. We always did something very unique and unusual and something that I never thought would work, or I'm like, oh my God, this is crazy. Wow, this is a totally different way of tackling it. And lo and behold, not only did we do it, but it also turned out to be Wow, that's a great way or best way to do it. And I think that training was really important because in essence what we do, if you're like, hey, what is the venture capital business?

It's a business about outliers. The only way you can be successful is to be an outlier yourself, to identify other outliers and appreciate them before it's obvious. Hopefully have a chance to partner to invest with them. And so the best way to train for that is to be at an outlier company, see how it operates, how it does things, just to kind of get that DNA. And I thought it was fantastic training in that way. Speaker A: To, to what extent did, you know, seeing Larry and Sergey and, and Eric Schmidt sort of operate that business and, and, you know, the extreme level of growth that that company went through sort of impact what you started to look for in entrepreneurs?

Like, did you find yourself almost trying to pattern match against, you know, these, these three very remarkable people? Was it perhaps, you know, uh, more abstract than that? Speaker B: No, I mean, definitely whatever you learn and your experiences really stay with you. And it wasn't just the three of them. Like we, we had a person who ran like data centers and infrastructure for Google. We used to joke that he was like Darth Vader. He would negotiate with data centers and like, I don't know, a couple of them went bankrupt after that.

And like, I never ever wanna negotiate against that guy. But everybody that did something, like the person who did the web spider was only 18 years old, and he was really special, and he's still a dear friend. Everybody was unique and individual and super strong in some way and super smart. But some things really stuck with me at the end. For instance, everything that I did with Larry, every single thing he asked, nothing less than 10x would be acceptable to him. So every time he asked us to do something, it had to be 10x better, 10x faster, or 10x cheaper.

And his concept was very simple. If somebody just asks you to do something better, say 20% better, 30% better, on surface it looks like, yeah, it's great. But the thing is, you can do that with a marginal improvement. But if somebody asks you a 10x change, you have to completely change the way you think. You have to completely rethink the way you do things. So that really stayed with me. The other interesting thing was, for instance, like Larry basically said no all the time. I mean, I think like his vocabulary was no 99% of time, and then maybe like yes every now and then, and then some other words.

And I mean, I'm dramatizing a little bit, but the whole point of that is he was very razor-sharp focused and very much of the mind that do very, very few things well. But make sure that those things are things that matter. The other thing that I observe, especially like Sergey, it was so fun to work with him. Even though both Larry and Sergey were only PhD students, they were never in a corporation or worked a single day in their lives, they had an amazing business instinct as well. So they were special that there are a lot of people that are academically smart, but to combine that with a commercial instinct is pretty rare.

And when Eric Schmidt joined, all he did was kind of button things up. It was really funny. We were 500 people and he's like, what? Like you guys are still running this on QuickBooks? We made a NetSuite implementation and so on and so forth. So it was a really great combination and a really great kind of distillation of duties. And the other interesting thing was they were really committed. This was not just a job. I mean, I used to see Larry at 9:00 PM, 10:00 PM at night when his day job was over, he would go to his office and basically configure or create servers.

And he's like, I'm like, Larry, why are you doing that? Can we not buy servers? He's like, why would we buy servers? Like, they're not really done for the way that we want them to work. And CPUs are so cheap, storage is so cheap. I would be pretty good at configuring it myself. And not only will it be cheaper, but it will be the exact machines as we need. Like, he could have easily taken an easy way out and say, why am I doing this at 10 PM We can just buy servers, but even there, like every single thing he did was very much perfectionist.

It's very much down to the smallest details. Speaker A: Gosh, I love stories like this so much to, to just to really see what obsessiveness and perfectionism looks like in action. And also that extreme focus. I mean, uh, it's funny, it rhymes so directly with one of those famous Steve Jobs quotes about, you know, focus isn't saying no to things that aren't a good idea. It's saying no to something that you, you know, is a great idea, but, but doing it anyway because there's something even more important. When did the idea of investing sort of come into your mind as something that you were interested in and that you, you maybe thought you would be good at?

Speaker B: Honestly, it also started when I was a kid. You know, I don't think about it as much, but again, when I was 7, 8 years old, I, I joke like only Turks and Brazilians, we were two countries that had 100% inflation for 20 years. And what ended up happening is when I was 7, 8 years old, you know, families have different dinner conversations. Our dinner conversation every night. Are we going to buy German marks, French francs, Swiss francs? Are we going to buy real estate? Because you couldn't keep it in the local currency.

I mean, 100% means every year, whatever you have, like, essentially lost most of its value, or at least half of its value. So that meant that from a very early age, regardless of math, regardless of finance, everything I was doing was around how can I think about, like, compounding returns and where would money appreciate the most. So it kind of became second nature. It was great training. The other thing was I used to read all my parents' Fortune and Businessweek magazines, and I used to see these incredible companies and CEOs and the stocks, and I'm like, wow, it would be amazing to be able to buy and sell this or maybe become a CEO one day.

And you have to start with a dream. And little did I know that there was this really interesting part of finance called venture capital. Um, and when I left Google and I wanted to tackle this, I went through a bunch of other ideas, but realized that those sounded great as hobbies, but as a business, again, I went back to my parents' beginnings and I didn't want to tackle anything where there was anything that could be disrupted by the markets or was not asset light and all of that. And when it came to the idea of venture capital, I'm like, this is great because honestly, like, all you need is capital, a great strategy, and execution.

So from an entrepreneurship point of view, it felt like the best opportunity. But the other scary thing about it is I've never done it. I didn't have a network. I didn't have a team. All I had was some capital and a crazy idea. But that's what the founders and entrepreneurs need sometimes and go all in. So I did, and I went all in. Speaker A: Had you made a few angel investments during your time at Google that had sort of given you a flavor of it? Speaker B: I did not.

I did not. Speaker A: Wow. Speaker B: It was complete cold turkey, cold start. And what was really interesting is the beginning was even crazier. I actually was a little bit afraid in the beginning. I'm like, wow, like, you know, maybe, you know, I should really be more conservative. It was also crazy in the sense that I was expecting my first child. My first son was on the way. And when you're expecting a child, the dads become very conservative as well. So my initial reaction is maybe this is really crazy.

I'm going to fail my wife, my family. Let me go get a job, maybe learn the ropes before I tackle this crazy thing. But the people that I interviewed basically said I wasn't an engineer. I wasn't senior enough at Google. I mean, I told this story many times, but the reality is, look, everybody goes through setbacks and disappointments and what seemed like initial failure or something like that. And to me, everything that happened in my life, like every single good thing happened on the back of some disappointment or failure. And this was similar in the sense that those rejections became rocket fuel.

And we always talk about starting a company and why did you do that? But I think the motivation and the fire and the impetus to succeed is equally important, if not more important. So for me, that was really like the big catalyst is not that just I wanted to do it, but I also really now needed to do it and not only do it, but be so good at it to prove all the naysayers wrong that said like I could not do this thing. I was not fit to be a VC.

That's it. I mean, honestly, this is one of the reasons why I relate to our founders that we work with so much, because a lot of them early on are told the idea is terrible, it won't work, you know, like What they are thinking about is crazy, or they, they're thinking about it the wrong way. I've been in their shoes and there is nothing like being in someone's shoes to feel like you are one of them and they feel like they're one of you. It all worked out. It all worked out, but it was a crazy beginning.

Speaker A: When you fast or you, you rewind to that, to that, uh, first fund, which I, I think it ended up being a $41 million fund if I'm remembering correctly. Speaker B: Yeah. Speaker A: What was the sort of strategy that you were going into it with? Like, you know, did you have really specific ideas about You know, this is the number of positions I really care about, and these are the, you know, the, the parts of the ecosystem where I think I can be most effective. I think, you know, about a lot of the newer solo capitalists now and being able to sort of understand how someone who's, you know, really grown from that position so much, sort of seeing where it starts is so, is so valuable.

Speaker B: I mean, look, there was a lot of strategy and design. Surprisingly, nothing was really left to chance. Honestly, one of the great things about getting the opportunity to do this for 4 years with my own capital as a solo GP is that I made 100 investments. It was one of the best times to invest. Even in 4 years, I already had 12 exits. Speaker A: Wow. Speaker B: By the time we were doing our first fundraise. So I think it's a little bit different than today. Uh, there are a lot of great people on the scene, but not as many that can say, hey, not only did I have one, but I had a dozen exits.

It's a really great validation that the strategy is working. The other interesting thing was, look, venture fundraising is much more difficult and different than people think. Limited partners have a very traditional way of thinking about things, and they want you to do what traditionally worked. So if you have an idea that's really different, it's very, very difficult to get limited partners to buy in. On the other hand, it was also interesting that you're basically telling them this is an original. If you were to follow the other ideas, you're gonna keep investing in the exact same funds.

Then what's the impetus to invest in a new fund? And so for me, it was really simple. I did quite a bit of benchmarking and analysis and realized that there were 2 or 3 things that was very difficult for the incumbent VC firms in Silicon Valley to do. Number 1, they had this sense that if you're gonna do venture, it needs to be local. Because you need to keep a close eye on the companies. Also, they wanted to have control of the company in case something wrong, you know, you replace the founder.

So they were very inflexible and wanted to have high ownership. And they also had this attitude that in order to do venture capital investing, you need to be expert in an area, which meant that as an investor you would always be in a narrow field. Yes. And I know one of the topics we're going to chat a little bit later on is to be a generalist. I had a completely different strategy. I thought, listen, if I try to be very good at those things that the other firms are already excellent at, that is not a very high probability way of making my way to the top.

Yeah. So I had to do something completely different. Not only would I be really good at that, but that also had to be something where the existing firms would be very hard pressed to do well. So I basically said, you do not need to have offices internationally and you do not need to be next to the companies you invest. Not coincidentally, a lot of our great successes have been international because I lived in these countries, I knew the cultures. That's where my inherent advantage was, right? So I did not feel like I need to go to that country, have an office.

Um, the other thing is, look, I felt that if you were intellectually curious, you did not need to be a subject expert. If you understand what's really important about an area, you can still make the investment. Like I can make a biotech investment. I don't need to be a doctor or a VP at Genentech to be able to make good investments. In fact, in some crazy way, it's better that you're not an expert because if a crazy founder comes and say, you know what, we're going to do some things in a very different way, you're the expert, your first reaction is, I've been doing this for [redacted address] to do that is the standard way.

And this probably has less chance of succeeding. In some ways, the only way you can be like more imaginative, a little bit bolder, is to be in this situation where like, wow, you know, like just maybe this can work. And then the last thing, uh, is so much of traditional venture was concentrated capital, few number of companies, and that never really made sense to me. I mean, I had a different thinking on it. And, and this is where again, my, you know, 4 years of solo investing, 100 companies, I felt that at then, like the traditional venture model is about 20 companies per fund.

And I always felt like 50 to 100 companies, roughly 50 to 70 companies per fund is the right size. And what I basically like found, and maybe one day I'll, I will be able to bring a mathematical model in front of you, the odds of improving the returns and reducing the risk drastically goes up until about you have 50 to 70 companies in a fund. How do I know this? Because we have 10 funds and we had situations where we had about 80 companies per fund, and my first fund had 100 companies.

So I could totally see how the end made a huge contribution in terms of how many more unexpected winners the portfolio had. And because the portfolio size was really small, small ownership did not matter as much, right? So like there's all these things that everybody is like, well, that's never gonna work. That's never gonna work. But in some ways it's a little bit lazy because they're also not trying to understand your reasoning. Like they're not saying like, well, maybe it could work. Can you help explain to me? I'm like, Yes, it actually works.

If it's $5 million of investment and you own 1% of the company, for that to be a fund driver is not a huge, like, push in probability, right? Like, even at $41 million. And then we did crazy things with the first fund. Like, our first major investment was in Angry Birds, and the whole round was bigger than our fund. And what people didn't understand why we did that is because I realized that all my peers were going to continue investing in the exact same seed companies, continue to go to Demo Day and all of that.

And I'm like, I'm going to do something that nobody probably is going to do or nobody even expects. What was really great is the international background and the comfort of having lived in 4 continents and having been in 50 countries. I felt like I could be home anywhere and come up to speed in an instant and convince those founders that we would be a great partner for them. Speaker A: Wow. So interesting. So many threads there that I'm excited to dig into. One that I hadn't fully appreciated and I really should have is, is the way in which your international background does map to so many of these winners.

I mean, Angry Birds, the company's Rovio, maybe, uh, you'll have to— Yep. Speaker B: That's it. Speaker A: The Scandinavian company. That's, that's the one. Speaker B: Um, it is Finnish company. Speaker A: Finnish company, right? Adyen, Netherlands. Canva, Australia. Uh, you know, Shopify, I guess Canada. Uh, but, uh, but so many of these really do map in that way. I wonder which other ones maybe come to mind. In mind for you that you think it only because I'm sort of a man of the world, uh, was I able to catch this before, you know, the folks that were still on Sand Hill Road?

Speaker B: 100%. I mean, even some of the more recent investments like N8N in Berlin, Germany, or Tynes in Dublin, Ireland— Dublin, Ireland. Again, the funny thing is we did not invest in those companies because of the country they were located in. Speaker A: Sure. Speaker B: We just were enamored with those founders and we were enamored with the markets they were in. And it just so happened that they were not in Silicon Valley. So I think the adage was Silicon Valley is so strong and has such incredible talent density.

Don't get me wrong, we have a lot of amazing companies ourselves in Silicon Valley. That's where we're based. But I always had this sense that, hey, there is all this incredible talent around the world, and just because they're not in Silicon Valley doesn't mean that they can't build and scale a company the likes of which that we've seen in Silicon Valley. It's a lot more common here, but that doesn't mean that it can't happen anywhere else. And lo and behold, like, we kept doing that company after company, country after country.

And, and again, it's just one of those really cool things because one of the things that people don't appreciate as much about venture is not only do you have to be right, but you have to be right before it's obvious to anybody else. So this is something that I think we truly owned. In terms of, hey, talent is truly global, opportunity is truly global. And I'm really happy that we kind of were the vanguard. And now if you look at some of the traditional VCs, like Sequoia has many more offices and is much more international.

And even many funds that said they would never invest internationally or would require a local office or would not invest across sectors have now started doing that. And I'd like to think that we were there first and we were the original And kind of like essentially like shown people that that idea can work. Speaker A: Hmm. The other piece that I really wanted to dig into was, you know, the extent of the diversification that, that you practiced, because I'm a much, much, much earlier investor in my career, have, you know, much less successful than you have, uh, than the track record you've pulled together.

But I've always felt that, uh, it must be so hard to create the level of outlier returns with such a diffuse portfolio. At scale, like maybe you can do it on an earlier fund, but from what you were saying, it sounds like you're, you've managed to still with quite large portfolio size, you know, maintain that level of performance. Am I sort of understanding that right? That you're still having sort of 70 companies per, per vintage? Speaker B: Look, I think we have about 35 to 60 companies per vintage. Maybe, maybe for ease, let's just say that if the traditional size is 20, 25, Yep.

We have doubled it. Let, let's call it 50, right? Because we have some funds where we had a little bit less, some funds we had a little bit more. The reality is the following: when you have too small of a fund size, what ends up happening is first of all, you don't have enough n, right? Like the chances that you're gonna have great winners from 20 companies versus 50, there's a statistical difference that 30 more shots on goal definitely makes a big difference. The second thing is when you have a small portfolio and all of them are high ownership and something goes wrong, now like it essentially jeopardizes the rest of the portfolio.

What was really great about having at least like about 50 companies is that we did not put the same size check and own the same in every company. It was always a little bit asymmetric in the sense that, I mean, this is the thing about venture capital. Sometimes like not only is everything so obvious and clear, you can back up the truck. And sometimes it's like, wow, like, I must be literally insane to be doing this. And you just do not want to, like, write a big check. And so the way that we have managed risk is to never treat everything as binary, like yes or no.

We kind of treat it as a spectrum. So all of these things helped us. And then the other thing that I was obsessed with, the concept is a little bit talked in this book called Antifragile by Nicholas Nassim Taleb. Speaker A: Yep. Speaker B: But you know, I'm, I'm a very, uh, deep student of finance. I was obsessed with investing. And one of the things that I really wanted to show is this business is all about risk and LPs and like, you know, venture capitalists like, well, like we have this one fund that's 10x, but then sometimes there are bad vintages.

And to me that was not acceptable. I wanted every fund, every one of our funds to be successful. And one of the ways I wanted to balance risk with the returns is I thought if you have a higher N, and let's say that you have a view of the world that you kind of have a feeling that there are maybe 5 or 10 areas where there are going to be great companies. Instead of only choosing one, if you did all of them, and we can talk more about this in generalist versus specialist battle, but I thought, hey, wouldn't it be great if we had a portfolio size and a strategy that allowed us to be in all of the sectors that we believed in?

So then what's really great is a lot of these sectors are not correlated to each other. So depending on what happens in the world, maybe not all of them will succeed, but they will succeed in different ways. In, in which case, like some of the great ones, you know, can make up for the other ones that did not work out really well versus in a much more concentrated portfolio, in a much narrower focus. If something goes wrong or if the world changes, now you're stuck with a strategy that's completely out of fashion.

It's useless. Similarly, like the portfolio has too much exposure to one area and there is nothing else to make up for it. So again, having grown up with a lot of risk and having seen a lot of like crises or companies that went out, I wanted to have a strategy that was just not great for returns, but also equally resilient. And I thought this strategy can really work. And luckily for us, it really did work in this way. Speaker A: And so you have that diversification for the resilience, but it sounds like you're sizing the initial checks very differently based on how much conviction you have in the company to start with, and then probably concentrating very aggressively in the ones as they grow that you feel like have the most upside.

Is that sort of the way the, the pieces come together? Speaker B: That's absolutely the concept. And I think I also need to be humble is that, look, we've done really well with company picking. And concentration of capital is not easy. And that's one of the reasons why we went from $41 million fund to like $925 million fund today. Not to mention like the real inflation. Like, I feel like we've gone at least 4x. You look at the price of gold, you know, like $900 million of today is like $225 million of 10, 15 years ago.

Um, but you know, like the company is also like need a lot more money today. And so you kind of need a fund size to not just be able to make enough bets, but to have enough capital in reserve that you still have some capital left over to concentrate into the winners. Speaker A: Yep. That totally makes sense. Uh, thanks for walking me through that. We did talk a little bit about this, this sort of generalist approach and, you know, for very obvious reasons, I, I love that this is the way that you see the world and, uh, it makes instinctive sense to me.

Uh, why do you think it's —still so common in Silicon Valley that so many people find it hard to imagine that someone could be effective across so many sectors? Speaker B: It is probably one of the hardest things to do in venture. Honestly, if you ask me, the one thing that I'm most proud of is that we have literally touched virtually every area of technology and we have succeeded even though we have zero background. Like we've done— well, consumer, you can argue I was at Google, so I did have a little bit of a background, but the companies we invested were maybe not related to what Google was doing.

So whether it's consumer or e-commerce or fintech, later on AI, security, infrastructure, developer tools, I mean, we tackled areas like hardware, literally we had no background in. And so I think I want to come back to this generalist approach versus specialist approach. The way that I think about them is a very first principles way. So I think most people misunderstand generalists. Generalists is not about, hey, we have this big area, we're going to spray and pray and we get lucky. And after we get lucky, we can say, well, of course we were right.

That is not the point. I think the way that I see generalists is different. The way that I think about it is generalists, you start from a much larger universe. So imagine you and I are both investors and there are two different ways we can go about the world, which is Hey, here's the universe of all great companies. The generalist approach says we're going to start with all of them. And then based on what we think like has the highest potential of growth and what's happening in the markets, we're going to hone in on the ones that are best, you know, risk reward.

I think what people misunderstand about generalists is because you're starting with the top of funnel that is so large does not mean you're trying to boil the ocean. It means that you have a much larger universe to pick from. And the conventional wisdom says, well, you are not qualified to pick the best ones from a large universe because you're not specialist. And I think that wisdom is not right. And we have practiced it now, like we're on our 10th fund. And I think we have great data to show that you do not have to be an expert to make good picks.

The specialist instead says, hey, you know what? The specialist approach will save you because you know the sector so well that you're gonna pick the best companies. I think a nuance that it misses, it means that now you're starting with a very small group to begin with, right? Like let's say that, hey, it's only like enterprise, it's only this. Well, in a large universe of companies, that's a small percentage. So first of all, you're starting with a much smaller base, right? And then on top of it, you're looking for outlier companies.

Well, in the general universe, you're going to have tons more outliers. In a specialist area, mostly what's going to happen is, well, we kind of ran out of outliers, but we basically said we are going to specialize. Now you're going to find more and more niches that go into smaller and smaller parts of the market. And so like instead of investing in all number ones, now you're investing— well, we need to invest in number 7 because we told the world, you know, we're a fintech firm. Like, why would you like— I want to invest in Stripe or Adyen.

I don't want to invest in Stripe or Adyen of Indonesia or Malaysia. That is not what gets me up in the morning. Like, I want to find like companies that completely dominate the sectors around the world. So that's the concept behind generalist versus specialist. The other like interesting thing that most people never talk about or think about is that it's also very risky to be specialist, right? Like imagine if you were a consumer person, there was quite a long time where consumer produced a few good companies, but the rest of the companies did not do well.

Or enterprise was really, really hot. I mean, 10 years ago, SaaS, it was all about SaaS. Today, I mean, it's kind of like a death sentence to be in SaaS. AI is disrupting every area of SaaS. And if you basically stuck to that and you were a SaaS fund, you're going to have a very hard time. So this is the curse of being a very narrow specialist, that not only does it limit your options, but it is also always at the mercy of the markets. And if something happens, it does not give you a lot of options.

So now you have to go back to your LPs like, actually, I was wrong to be a specialist in this. Now I'm gonna go to this new area. And they're like, how are you gonna do— go do this new area? Yeah. Do you see how it works? Versus we always said we're a generalist, so we were always true to our world. Yes. We always said we're going to pick from a large universe. But if you look at all of our 10 funds, the mix on each, every single one of them is different.

And we perfectly picked all the interesting markets that we thought were poised for great growth, basically 5 to 10 years before that growth actually happened. Speaker B: It is probably one of the hardest things to do in venture. Honestly, if you ask me, the one thing that I'm most proud of is that we have literally touched virtually every area of technology and we have succeeded even though we have zero background. Like we've done— well, consumer, you can argue I was at Google, so I did have a little bit of a background, but the companies we invested were maybe not related to what Google was doing.

So whether it's consumer or e-commerce or fintech, later on AI, security, infrastructure, developer tools, I mean, we tackled areas like hardware, literally we had no background in. And so I think I want to come back to this generalist approach versus specialist approach. The way that I think about them is a very first principles way. So I think most people misunderstand generalists. Generalists is not about, hey, we have this big area, we're going to spray and pray and we get lucky. And after we get lucky, we can say, well, of course we were right.

That is not the point. I think the way that I see generalists is different. The way that I think about it is generalists, you start from a much larger universe. So imagine you and I are both investors and there are two different ways we can go about the world, which is Hey, here's the universe of all great companies. The generalist approach says we're going to start with all of them. And then based on what we think like has the highest potential of growth and what's happening in the markets, we're going to hone in on the ones that are best, you know, risk reward.

I think what people misunderstand about generalists is because you're starting with the top of funnel that is so large does not mean you're trying to boil the ocean. It means that you have a much larger universe to pick from. And the conventional wisdom says, well, you are not qualified to pick the best ones from a large universe because you're not specialist. And I think that wisdom is not right. And we have practiced it now, like we're on our 10th fund. And I think we have great data to show that you do not have to be an expert to make good picks.

The specialist instead says, hey, you know what? The specialist approach will save you because you know the sector so well that you're gonna pick the best companies. I think a nuance that it misses, it means that now you're starting with a very small group to begin with, right? Like let's say that, hey, it's only like enterprise, it's only this. Well, in a large universe of companies, that's a small percentage. So first of all, you're starting with a much smaller base, right? And then on top of it, you're looking for outlier companies.

Well, in the general universe, you're going to have tons more outliers. In a specialist area, mostly what's going to happen is, well, we kind of ran out of outliers, but we basically said we are going to specialize. Now you're going to find more and more niches that go into smaller and smaller parts of the market. And so like instead of investing in all number ones, now you're investing— well, we need to invest in number 7 because we told the world, you know, we're a fintech firm. Like, why would you like— I want to invest in Stripe or Adyen.

I don't want to invest in Stripe or Adyen of Indonesia or Malaysia. That is not what gets me up in the morning. Like, I want to find like companies that completely dominate the sectors around the world. So that's the concept behind generalist versus specialist. The other like interesting thing that most people never talk about or think about is that it's also very risky to be specialist, right? Like imagine if you were a consumer person, there was quite a long time where consumer produced a few good companies, but the rest of the companies did not do well.

Or enterprise was really, really hot. I mean, 10 years ago, SaaS, it was all about SaaS. Today, I mean, it's kind of like a death sentence to be in SaaS. AI is disrupting every area of SaaS. And if you basically stuck to that and you were a SaaS fund, you're going to have a very hard time. So this is the curse of being a very narrow specialist, that not only does it limit your options, but it is also always at the mercy of the markets. And if something happens, it does not give you a lot of options.

So now you have to go back to your LPs like, actually, I was wrong to be a specialist in this. Now I'm gonna go to this new area. And they're like, how are you gonna do— go do this new area? Yeah. Do you see how it works? Versus we always said we're a generalist, so we were always true to our world. Yes. We always said we're going to pick from a large universe. But if you look at all of our 10 funds, the mix on each, every single one of them is different.

And we perfectly picked all the interesting markets that we thought were poised for great growth, basically 5 to 10 years before that growth actually happened. Speaker A: Yes. The, the, the specialist is able to do what is locally the best deal versus the generalist can do what is absolutely the best deal. Perhaps there's a trade-off in some level of precision between the two, you could argue, but, but I'm not even convinced that's always the case. I wonder what this approach sort of says about your investing lens as you might define it?

Do you find yourself, you know, much more founder-driven than your peers, for example? Because I think that's one of the ways that generalist strategies can work is if you're able to almost, you know, pierce through the really thorny and complex details of a certain sector, which, you know, it's impossible for you to gain the, the amount of industry knowledge as someone who spent 20 years in you know, 2 hours with a founder. But if you're able to analyze this person in a certain way, uh, maybe it doesn't matter as much.

And so I'm, I, yeah, I wonder how you sort of find those, those shortcuts or, you know, those efficiencies. Speaker B: Look, my personal take on that is people are lazy, so they just want to look at success and say, oh, all the success, it was because of this one factor. It's so much easier to say it was all, only the founders. Now, having said that, Let me tell you that the most important ingredient in all of that is the founders. In fact, going back to what you asked me about Larry and Sergey is that the other cool thing about Larry and Sergey were not just that they spent tens of thousands of hours and they were really good at what they did, but they could explain to you the most complex things in less than a minute and make you feel smart.

What, what I wanna say is, look, let's just put something to rest. I think without exceptional founders, it's very, very difficult to succeed. So founders definitely is the foundation that we look for, but I'm gonna say yes, but, and add that even some of the very best founders, sometimes when they face a very difficult market or at a really bad time, things have not worked out really well, right? I mean, we can always find a few things where like, oh yeah, but like the best founders pivot and find a way.

Yes, but statistically speaking, you're looking at 1% or 5% or 10% of the cases. Nobody ever talks about the 90% of the cases where the pivot didn't work. Now, we're always here to make it happen and to support the founders. All I'm going to say is that it's kind of like you look at a championship team and yeah, it was all the quarterback or it was only the coach. The reality is, yes, it was the quarterback, it was the coach, it's the 100,000 hours that they train. It's the fact that they pick different strategies.

It's the fact that they took the right risk at like 15 different games. We really wanna simplify things and say, okay, that's it. Like we found the secret. The reality is there is like 20 secrets. There is so much more nuance that goes into it. And again, like not to take it away from the founders. I mean, I have so many great examples of founders where like when there is nothing, they will something. To existence, and it's just incredible how they're able to do that. A good example of that is Scott Morton at Revel.

I mean, he was the top engineer at SpaceX, wrote all the software for Falcon rockets, and then one day he's like, you know what? There is no definitive infrastructure company for critical hardware, including space and other industries like utilities, dams, all of that. And literally there is nothing that exists. He just says, I'm going to do it. And all of a sudden, like, he's able to attract incredible talent. And next thing we know, in like 12 to 18 months, he has his first prototypes already working. I mean, I've never seen a founder like be able to do that.

It's a little bit of the equivalent of like Moses went to Egypt and parted the sea. We literally are working with founders like that today, and I will never take that away from them. But what market they tackle and at what time they tackle is also equally important. For instance, I think we are essentially in the beginning years of a huge space age. We're gonna have tons more satellites, we're gonna have a lot more things happening in space. So this is actually very timely because SpaceX had to do everything they did from scratch.

And interestingly, like at Google, we did a lot of things custom for which there is like now platforms today. We, for instance, build our own thing which Amazon with AWS turned into a huge cloud business. We literally had our internal AWS cloud 25 years ago. We build it, we build everything from scratch. Now you don't have to do everything from scratch. So it's just to say that yes, everything starts with amazing founders, but there is also a lot more nuance to it. Speaker A: Yes, absolutely. To push on that question maybe a little more, have you ever seen a situation in which you felt it was a truly top basis point founder, who didn't find a way to succeed, maybe not even that company, but the next one.

My feeling is that if you find someone that good, ultimately they almost always figure it out somewhere along the line. Speaker B: I think one of the things is, yes, they do figure it out and I will not take it away from them. And I think what some of the things that happens is like, look, I mean, everybody's dream is like, we're going to be great and take the company public. But the reality is sometimes, you know, you're part of an acquisition. And your product is still serving, you know, hundreds of millions, if not billions of people.

So you have succeeded. Maybe the company didn't go public, but it still succeeded in the way you originally dreamed of. So I guess the thing is, look, the very best founders do figure it out and do make it work, but it might not be in the way that people have expected. Speaker A: Yes. Yes. Uh, I imagine you've had to reinvent Felicis a lot over the years, you know, as, as the founder of it. As you look back on, you know, the, the decade and a half plus now, what have been the different sort of form factors and, and maybe what have been the hardest transition points along that journey?

I, you know, frankly imagine that one of the first transition points of going from, you know, a solo GP to entrusting other people to make investments and to, you know, share this sort of mental space with you must have been, you know, a really significant one. Speaker B: Definitely. It was a very steep and also very gratifying learning experience, but I think that, that needs to take us back to our origins. And what was really interesting is you and I just talked a little while ago about strategy and how we try to be different than standard VCs.

So now I'm going to go to the heart of it. And it is, I looked at all the other VCs and I really tried to think like, what is one thing that all of these incredible VCs that came before my time not good at, and what is one single thing that could be my true north and define our franchise for decades to come? And what I basically ended up at is traditional VC. At the moment they succeed, they become very rigid and stagnant. All of them had some kind of a turning point.

All of them started with a dream, and then they have some really great bets, like incredible returns. And right at that point, they're like, don't change anything. You know what? I was walking my dog and whatever. It was the morning and we were based in— and then, OK, great. This works, so absolutely keep it. Don't change anything. LPs really like it because clearly something worked. And what people don't understand and what I observe at Google with super high growth is that that's actually when you're most vulnerable. Actually, that's the point at which you should be willing to question everything and figure out like anything that can be improved and changed.

Because if you don't do that, somebody else will and you will get disrupted. So that's both the blessing and the curse of Silicon Valley and technology, is that it's always like crazy. It's always a battlefield. You think you won the battle and then somebody braver and somebody crazier comes along. And if you haven't adapted, like all of a sudden you're a dinosaur and then you get crushed or killed in the battlefield. So I basically said, I can fail at everything, but one thing that will define this franchise that we will never ever fail or cannot fail is learning and adapting rapidly.

I literally said, that's our constitution. If our firm is a constitution, that is our constitution. But by the way, this means that learning and adapting rapidly doesn't mean that your strategy changes all the time. It doesn't mean that you are flailing and spraying and praying. It just means that it's the same strategy, but you can apply it in different ways. And do you see how it's perfect with the generalist approach? Because that essentially gave us the flexibility of when we saw opportunities in the market. And I'll give you an interesting example where there was a really interesting turning point in the history of Felicis where we did an analysis of all the successes and realized we had nothing in AI or very few things in AI and security and infrastructure.

So we made a hard pivot into those areas. I feel like the defining aspect of what we do is our strategies always remain the same. Our differentiator of being the trusted brand by founders and doing right by founders always stayed the same and we scaled it, but all other aspects we learned and adapted, right? We started as a solo firm, then we were 3 people, now we have research. We're doing 20 different things that I would've never even imagined that we would be doing today. Yes, same strategy, same generalist approach, but the practice and application and what sector we choose today versus 10 years ago, it's so different.

The team is very different. What I love about that is the thing that kills civilizations and cultures is the inability to adapt. Like, why did the Roman Empire die? Like, why did all of these great civilizations, like, go become extinct? Is because they could not keep up with the time. And so that to me was the thing that If we are the fastest adapting, fastest learning, you know, team culture in venture, we will always have a place in the upper echelon of venture as long as we are able to make it there.

Speaker A: Amazing. I love that, uh, theory, this willingness to, to rethink things and sort of prevent against that stagnation that, as you say, success, uh, often breeds. On the, on the subject of, uh, you know, avoiding stagnation, you guys have been, I think, very aggressive in investing in AI, uh, and doing it, you know, at, you know, almost every altitude it feels like, you know, you have Crusoe at the energy layer, you have, you know, sort of some orchestration plays with N8N and, you know, infrastructure, Supabase, and some of these sort of bespoke model companies.

How, how have you thought about the right way for Felicis to be involved in this? And why have you been willing to sort of lean in so aggressively? Such that, you know, it seems like a lot— that is, I would imagine, the majority of the firm's activity at this point. 100%. Speaker B: This is a really great thread because I think about it a lot. And I was just talking to a VC club at a really well-known university, and I told the students the following: venture business is very simple. There is only one thing you need to do, which is you need to find companies that have hockey stick revenue inflection curves and be in these companies before the steep part of the inflection happens.

That's it. That's venture. I did it in less than a minute. You do that right and consistently, no matter what you do, you're going to succeed. Notice I did not talk anything about sectors. I did not say anything about stages. I did not say anything about the economy or markets, nothing else. I did not say anything about valuations. All of these things are excuses like Sometimes it's a great analogy in F1. They complain, you know what, oh, it's terrible, it's rain. And the best drivers win whether it's dry, whether it's rain, whether it's a challenging circuit, whether it's night, whether it's day, whether it's street, whether it's whatever.

This is the thing that comes to my mind is that people complain about the markets. Oh, AI is a bubble. No, valuations were really high. And we can find companies not only across all the sectors and all the geos, But also when the markets are up, when the markets are down, when it's really expensive, when people think there is a bubble, because what they're not doing is they're basically looking at things that they can't control, but that has no impact in how they choose companies. The only thing that matters for the companies is whether you can find that hockey stick curve.

So now how does this translate into AI? In my 20 years of doing this, AI age is the first one where I have seen these growth curves, the hockey stick growth curves. Happen at the most insane velocity and the sharpest steepness, right? Like, to give you an example, even like the Google age, Google went public in 6 years. Shopify went public in 6 years. I need to look up the exact time, but like, these companies got to $100 million of revenues, let's say, between 4 and 8 years. 10, 20 years ago, getting to $100 million of revenues in 4 to 8 years was considered exceptional.

Today you have not one but multiple companies, maybe soon to be dozens, that are rocketing from $0 to $100 million in revenue in 12 months or less. Not only are they doing that, they are doing that with probably about 10% or less of the people that traditional companies did. Because one of the great things about AI, like, you would've hired in so many different roles and like, I don't need to hire in that many different roles. Like, there are some like edge things that I can like rely on AI and Instead of like a team of 100, I can do this with a team of 10.

Now you can move a lot faster. You don't have to hire a lot of middle management. So it's not just a steep revenue growth, but also you can probably do that more profitably. And this is what I want to get to, is that people again are very lazy and they're only looking at one aspect and drawing conclusions. Oh, AI, it certainly must be a bubble. You know, that's not going to work. And yes, it's true, there are companies that do not have a durable technical advantage. But there are very few companies that not only do they have the durable technical advantage, not only do they have growth, but they're also going to be able to get to profitability.

And if they do, they're going to become invincible and it's not going to be bubble. And this is the reason why, for instance, you know, like 2021, people can't stop talking about it. You know, we made some of our best investments in 2021 when the market was at its peak. And everybody thought we were crazy. That's going to be a horrible vintage. Those companies are going to be like— I cannot tell you how many LP meetings I had to take to explain to them, but no, we can pick companies even in that environment.

And we did. I actually had to look back just to make sure whether it's N8N or Supabase, those were some of the most expensive investments we've ever made, highest valuation. And conventional wisdom is that certainly is not gonna work out. And it worked out. Not only did it work out, it worked out exceptionally well. Despite the fact that we paid maybe 10x what people thought we would pay, the companies grew their revenues by 100 to 500x. And so that means that what on surface looked like a terrible move ended up being a genius move because everybody else were like cold on their tracks.

We were aggressively pursuing those companies. And those founders are like, you know what? Nobody had the courage or the insight or the imagination to see what we see, but you did. And that's basically our brand today, right? Like when founders look at our brand, at our firm, what I want them to see is that these people have been brave enough, even when things were tough, even when valuations were crazy, even when markets were really crazy, they still go to their founders and have this incredible conviction and partner with them even in those most difficult situations.

Speaker A: Okay. So interesting. I wanna make sure I'm sort of following the way this hangs together because it strikes me as on the one hand, it's, it's, you know, there are parts of it that are on trend, but I think there's also a depth behind it that is maybe built on some contrarian principles. So, uh, I think one of the things you're saying is that yes, maybe there are these companies that are getting done at 200-300x revenue. But as long as you can pick the ones that are actually likely to have a durable technical moat, you're happy to pay even a few years, let's say, in advance of, of where they're, you know, let's say reasonable valuation or, or, you know, durable multiple might settle at because you think they might really be sort of game-changing, world-changing companies.

And the history of Felicis suggests that even in these hot markets when other folks have leaned in and gotten burned, you've managed to be strong enough on the selection that those vintages still look good. Is that right? Speaker B: 100%. And the best way to summarize it is follows, just so that the math makes sense. Um, I'm gonna simplify it a little bit. Let's just call it VC 101. And here's the interesting thing. There has been many instances where we picked the company just right. And we were off by a 10x on the entry valuation.

So everybody looked at only that side and said, there is no way it's going to work. But what they missed is the revenue growth that materialized after was 30x, 50x, 100x. So while we were 10x wrong on the entry price, we were absolutely like underestimating the revenue growth by even a much, much larger factor. And so that's the thing, like, to be successful, it's not only that, like, you need to be right on the valuation side. In fact, it's the opposite, because if you're basically a cheapo and say, wow, like, I'm basically gonna think that's too expensive, I'm gonna go for the cheaper companies, you're forgetting the most important part, which is the revenue growth never materializes.

So you will only be successful if the revenue growth materializes. It does not matter that you were, like, paying a much higher price. But you have to be in those companies where the revenue growth is like 50x, 100x, 1000x, because without that, we're never going to get to the point that we want to get to anyway. So that's the part that people don't talk about, to be able to like understand what are the dynamics, what are the ingredients to be able to like look at a company when none of this is done, when all of this is like in air and uncertain and say, you know what, we have the imagination, we have spent so much time trying to understand the space and these founders, we think that this company and these founders are the most likely to be able to produce that growth.

And that's the thing, like, that's what we're really good at. And it happened literally over and over again across all the different markets, all the different geos, all the different state, you know, stages of investment. And that's why I tell our LPs, like, if I showed you the time we invested and the growth that ensued— 20 investments, every single one of them looks like seed, only 10% were seed. Some of them were Series B, some of them were Series C, some of them were Series A. This is why, like, I'm like throwing twitches when people talk about markets or stages.

It's just like, go back to the essence. That's the essence of venture capital, to be able to find companies that are these extreme growth companies. Speaker A: And it's because these companies are the ones that matter so much that, you know, if you have to pay up for the access to the number one versus, you know, getting a, a steal of a deal for the number 10 in a market, you know, there's no real value in, in, in that scenario where you're getting a, a better valuation because, you know, the, the, the number 1 business is gonna run away with it over a period of time.

And so that, then that makes me wonder if you even need to care in a way about whether this is an AI bubble or not, because in some respect it doesn't matter, right? If you're always just gonna believe that you pick the biggest winner. It all should work out in the bull case, right? Speaker B: Not only that, but let me go back to the point that I made. People are looking at it again very simplistically. Oh, it's an AI bubble. What they're not paying attention is that there are 7 different markets or 10 different markets that are coupled to that.

So it's not just AI. What is the raw material of AI? It's data. Who manipulates data? Companies like N8N, which is data translation. Companies like Supabase, which actually store the data and make it actionable. We are talking about AI way while everybody's looking at the chip, while the processing actually happens in data centers. You know, 100 years ago when the greatest wealth was created, it was all about oil, and the people that made the most money were the refineries. That's the data centers of today. Then you look at what is the most important resource for data centers is energy.

We actually do not have a scarcity of chips. We do have a huge scarcity of energy, right? So like, the energy is going to benefit from that. Basically where I'm going with this is people are looking at it too simplistically because some of these things are such high numbers and it is not what people expected. They're thinking that, oh, like, some of it must be wrong. And don't get me wrong, some of it is wrong, right? Like, just like everything, like internet wave, like People basically like thought a lot of these like websites on the web that sold things didn't amount to anything.

But Google that was built then became a trillion-dollar company, right? Like every one of these eras where people thought, oh, this is really bad, some companies really, really got it right. And not only did they get it right, but they got it right 10,000 times more than what people expected. Yes. How can I say that? Because I was one of those early people that said, Oh God, please let Google be a billion-dollar company. It became a $4 trillion company. Wow. Yeah. I was off by not one, not two, three zeros, three orders of magnitude, right?

Like it not only became a multi-billion-dollar company, it became a multi-trillion-dollar company. Yes. Speaker A: One of the investments that you've made, uh, is in Skilled AI, which is in, which is in the sort of robotics space, obviously an important part of the AI ecosystem, but in many ways it still feels a little bit like the, the younger sibling that, you know, gets attention every once in a while, but maybe not as much as some of the flashier applications. How have you thought about the way AI begins to enter the physical world more?

And, and why was Skilled one of the companies that you were sort of most interested in? Speaker B: One of our most favorite companies. I mean, so many like interesting things. Let me start by like some really cool anecdotes before we made the Skilled investment. We made 6 robotics investments and virtually all of them failed. And not just failed, but failed miserably, like absolute abject failure. So any other traditional VC would've said, you know what, 6 failures are enough. Do not make this mistake again. But this is the reason why our culture is learning and adapting rapidly.

So your initial reaction would've been, oh, like it's AI boom, why robotics? Here's like a couple secrets. The reason why it's different now, why Skilled was really interesting, is that all the other robotics companies were trying to make the robots do one simple thing, and the programming was all about making the robot do one thing over and over again. It literally took them years. Like, people don't learn to walk like that. I mean, babies just like go fumble and do stupid things sometimes, like fall out. And like, I'm like, sometimes like, God, you know, my two sons Only if you knew like the moments where they came really close to doing something really crazy when they were like toddlers.

But that's how we learn. And then after that, you never think about like, oh, like you're walking, like, oh, I'm just stepping here, whatever. So you're inherently understanding movement, right? And so the reason why I got excited about Skilled is unlike all other areas of AI, this concept of how will robots generally learn skills, and that's why the company is Skilled, the data for that did not exist. So the company had to master synthetic data. They were one of the first to master reinforcement learning. So they got many, many different things right.

It's because the founders, the two founders, have been doing this for well over a decade. They were the best experts in this field. Like whether it's Meta, Google, like a lot of the things they did were based on the papers that these founders wrote. You know, this is really interesting because it looks like Essentially, it reminds me of Microsoft. When the PC wave happened, Microsoft said, "We're not going to build the PCs. We're just going to be the operating system for all the PCs." Yes. So I think that's the second thing that I learned from robotics is that if you're trying to do both software and hardware, it is very, very difficult.

And also building hardware is really costly. I'm not saying that Skilled will never build hardware. I just love the fact that they really focused on software first. And they said, "Our software not only has to be very good, So good, in fact, that you can take the cheapest robots that are literally 100 times less precise and make them more precise than the robots that cost 100 times as much, just because the software is so good in managing them. This is literally what Microsoft did with PCs. They were competing with these elegant workstations, and software made the PCs shine.

And then the last thing is, look, um, a lot of times when these investments are made, This is like a really good insight. So I thought about, hey, you know what, let me think about it. Let's say that we're using our imagination. If robotics works, well, what could be the kind of positive impact? And then I did this simple calculation. If you take US, Western Europe, and Japan, there are 190 million low-skilled jobs. And if you basically say like $25,000 a year, which Skill can easily offer, and if you can charge like multiples of that, but I'm like, wow, like you don't even have to replace all of them.

0.001 would be a $10 to $50 billion company. Yeah. Not value, revenue. Yeah. $10 to $50 billion at a 10x multiple. That, that, that is almost on its way to become a trillion dollar company. And it's 0.001% of the market. The reason why I'm telling you this, the margin of error is so great. Like even if they captured a tiny piece of the market, not even 1, but 1/1000 of a percent. It's gonna be a huge company, right? And so that's the thing, like, people are like, oh, like, robotics is crazy, it never work, like, it's not gonna scale, whatever.

No, it actually will work. We're gonna have a ton more robots in the next 10 to 20 years, and they're gonna do a lot of things. And I doubt it's gonna take, like, jobs away. It's just gonna do jobs that people are not meant to do or not should not be doing, but they're doing it because there is no other way of doing it. And like, there are so many jobs that are unsafe, it's risky. People are getting killed, getting injured. People are doing the job at night because you know what, they need to do something.

And I just feel like we're gonna use people for different things where hopefully it'll be like better value-add jobs. So I don't think it's like one or the other, like, oh, robots will come, none of us will have jobs. I do think it's gonna be like this kind of happy coexistence. We're gonna have a lot of robots and they're gonna take more drudgery out of our lives, and then hopefully we can do more a higher value, higher order of things as humans. Speaker A: I think I'm right in saying that Felicis hasn't invested in one of the sort of large general purpose labs like, you know, an OpenAI, Anthropic, even, you know, the European sort of, uh, offerings like Mistral.

Has that been a concerted strategy or more just a consequence of sort of when your own AI strategy came to the fore and, and, you know, the, the opportunities that came in front of you. I'm curious maybe that what that says about how you see this sector. Speaker B: Yeah, I mean, look, first I need to start by being very humble. I have to say that I think I drastically underestimated Anthropic and OpenAI. And this is the thing, I think human beings, you look at large numbers, I look at the valuations, man, I look at what these companies were doing and I think I underestimated the value they can capture.

So I think the right thing to do here is to say we've done really well in many areas of AI. I think we should have taken Anthropic and OpenAI a lot more seriously. The growth that they've been able to capture, the value they've been able to capture. If you basically say, hey, what's your biggest regret? I'm going to go back to 2008 and talk about Airbnb, but what is your biggest regret in the age of AI? I feel that we should have taken this much more seriously. Taking a bet in one of the large model companies, whether it's Anthropic, OpenAI.

You can make pros and cons for each one of them differently. I'm not really sure I would put Mistral in this bucket, but I will certainly say Anthropic and OpenAI are special companies, each in their different way. And I will be the first to admit and own— and this is part of the learning and adapting fast culture— is that you have to be very honest with yourself. You know what? That was a miss. Yep. That was a big miss. We way underestimated that because the cool thing about that is we are talking about growth, but there is yet another angle to it.

We have not talked about growth at scale. These companies have been able to grow at scale. Like, I don't know, like we talk about 0 to 100 million, but I don't know how many companies could go from 30 million to 3 billion in as record of a time, right? Like when cars, it's always like 0 to 60. But the harder thing to nail is like, I don't know, like 60 to 200. It becomes exponentially more difficult to go from 60 miles per hour to 200 miles per hour. So I am just acknowledging that I think those two companies have really done something special.

And I just look at the valuation numbers and I choke, but we are very aware of it. We got some other things. I mean, we still made foundational model bets, whereas Runway or Poolside or Skilled, Yes. Uh, they're just not building generalist models. They're building specialist models. But again, nothing takes away from the fact that I think Anthropic and OpenAI are gonna be huge companies. Speaker A: Well, I, I'm sorry to bring it up in that case, but, um, nature of the game, as you know very well. Speaker B: Nature of the game.

All good. Speaker A: All good. You, you mentioned, uh, Airbnb, and that's one that I feel like a lot of folks look back on as, you know, maybe their big miss. What, what was it that that didn't work for you at the time or that you missed? Well, let me be very specific. Speaker B: I have an email still from 2008 directly from Brian Chesky. This is even before YC invested, by the way. He's like, Aydan, we really enjoyed our meeting with you. We really feel you should invest in our company and you still have a chance to do that at $2.5 million valuation.

For a $60 billion or $100 billion company, One of the biggest lessons I learned, and this is why, again, I'm gonna keep going back over and over to this, is that this is why I want learning and adapting rapidly to be our core values. That while the decision was academically correct, it was practically very wrong. Essentially what happened is I thought it's what a wonderful idea, but the reputational risk of something going wrong can kill the company early on, right? Like if you are Airbnb and something bad happens in one of the houses, like I don't know, something like really bad or illegal.

Yes, that would kill the brand. Speaker A: Yeah. Speaker B: But what happened, what ended up happening is the community was so strong that the community basically self-policed itself and something bad did not happen. Where am I going with this? Not only was it a miss, and it is a very visceral miss, but basically what happened is— this is the thing about venture that is so like tough, is that your biggest misses are not the companies You know, you're like, you're saying yes, it's just the ones that you're saying no that end up being great companies.

Because if you're not in those best companies, your returns will not be as good as the very best ones. But just to kind of like put an example of how you can turn, take lemons and turn them into lemonade. One of the reasons I ended up finding Adyen and investing in it, I also missed and underestimated Uber. I'm a very avid driver and I'm like, why would people want their own drivers? I had to eat my words on that one as well. But what ended up happening is after missing out on Airbnb and Uber, it basically like dawned on me that it was like an era where even Google and Facebook were having difficulty with international payments.

I'm like, look, there might be yet one more chance to play this. Yes, maybe we cannot invest in Airbnb and Uber anymore, but if the international growth is going to be staggering for them, there will be an international payments company that's going to capture this. and that ended up being Adyen. So the only thing that I'd like to get a tiny little bit of credit is it was a big failure and setback. And instead of saying, okay, like it doesn't matter, I have big ego, like we will find great ones.

I said, no, I'm not gonna let this rest. I'm gonna go find yet another company and turn that lemon into lemonade. And Adyen became like one of our biggest exits ever. And it was very interesting because when Adyen first got announced in the US, It was the only company I literally remember calling Wall Street Journal and they're like, actually, we don't even know what this company is. We don't even have it in our database. That's how under the radar it was. And this is where every VC in the US was investing in Stripe, right?

So like, again, like going back to that, like not only do you have to be right, but you have to be right and in minority. Like you can't be right with 100, 500 other people. You have to be right and kind of be in like this small minority where like it's not obvious to everybody else. Speaker A: That's a great story. To finish, I always like to ask a, a more sort of abstract philosophical question or two. One of them is, if you had unlimited resources and no operational constraints, what is an experiment you would like to run?

Speaker B: It would require a little bit of, uh, design, but I think one of the things we're obsessed with is like truly understanding what makes outlier founders. And I don't know if like a huge longitudinal study has ever been done. In fact, I did a little bit of a Google search. I think one of the largest studies ever done was only 1,000 people. And I think the only large-scale human study was COVID because everybody was going through it. But if we had unlimited resources, again, privacy safe, opt-in, or however is statistically designed to be relevant, but again, respecting people's privacy, I would love to do some kind of very detailed study of founders and what are the elements and, you know, personality aspects or like whatever, like what in their backgrounds really spiked, you know, because I feel like all these founders are very talented.

But this is the thing, like, it's not just as simple, like, so many of them are brilliant, so many of them are brave, all of them are very brave. But then what determines the ones that spiked the highest and the ones that ended up doing okay, just not great? So that would be an awesome thing to do. Speaker A: What's a tradition or practice from another culture or time period that you think we should adopt today? I'm going to mention something from my heritage. Speaker A: What's a tradition or practice from another culture or time period that you think we should adopt today?

I'm going to mention something from my heritage. Speaker B: As you know, a Turkish-born American, we have this concept in Turkey called misafir pervarlik. It's just about hospitality. And it's not just hospitality as in, hey, like you're nice to strangers, but you literally, if you have a guest, the guest is basically treated as if it's the most important member of your family. You literally truly make them feel at home and you care for them. And the reason why I'm mentioning that is honestly the essence of everything we do for the founders at Felicis, putting them first.

That literally is that culture. I always like to think of my grandmothers. I didn't get a chance to meet my grandfathers, but my grandmothers were the epitome of that. In some ways, like we have these cute little traditions, like everybody that comes to our office, we always give them a chocolate or something sweet as they leave. It's just this sense that everybody should feel special when they're interacting with us, especially founders. So it's a little bit of a cultural touch. And in a world that's so polarized and stressed and grumpy, we want to add a little bit more happiness and a little bit more kindness.

Hopefully we're doing our part and we can scale it. Speaker A: I love that. Final question. If you had the power to assign a book to everyone on Earth to read and understand, what would you like to assign? Speaker B: I'm going to pick one of the latest books that I've read that, you know, was really impactful for me. It's a book called Clear Thinking by Shane Parrish. He was a Canadian intelligence operative. And the reason why the book is really interesting is every time, like, I read a book, oh, this is a great story, or it's like Talked about this one thing.

The, the interesting aspect of this book is all about decision making and how we normally make decisions where we're kind of defaulting to things that are not obvious to us, and it really impacts our decision making. And when you think about it, if you could get one thing right that could scale throughout your whole life, I think that would be making better decisions. You would have a better family, you would have a better career, you would have a better personal life. And so what I liked about this book is it broke down and said, this is 4 different ways, whether we realize it or not, we default to these different things.

And we think that we're making conscious decisions, but they're really like reactions and we kind of programmed. So it essentially says like the way to like unwind that or break that like kind of futile process is like take a little bit longer or whenever you're about to make like a reactionary decision, like put things so that you can't move as fast or is more difficult so you don't basically like make a decision in a rush that you later regret. So I love the book. It's not a very long book. It's an easy read.

So I would highly recommend it. Clear Thinking by Shane Parrish. Speaker A: I love that. Final question. If you had the power to assign a book to everyone on Earth to read and understand, what would you like to assign? Speaker B: I'm going to pick one of the latest books that I've read that, you know, was really impactful for me. It's a book called Clear Thinking by Shane Parrish. He was a Canadian intelligence operative. And the reason why the book is really interesting is every time, like, I read a book, oh, this is a great story, or it's like Talked about this one thing.

The, the interesting aspect of this book is all about decision making and how we normally make decisions where we're kind of defaulting to things that are not obvious to us, and it really impacts our decision making. And when you think about it, if you could get one thing right that could scale throughout your whole life, I think that would be making better decisions. You would have a better family, you would have a better career, you would have a better personal life. And so what I liked about this book is it broke down and said, this is 4 different ways, whether we realize it or not, we default to these different things.

And we think that we're making conscious decisions, but they're really like reactions and we kind of programmed. So it essentially says like the way to like unwind that or break that like kind of futile process is like take a little bit longer or whenever you're about to make like a reactionary decision, like put things so that you can't move as fast or is more difficult so you don't basically like make a decision in a rush that you later regret. So I love the book. It's not a very long book. It's an easy read.

So I would highly recommend it. Clear Thinking by Shane Parrish. Speaker A: Amazing. He's also the author and founder, I think, of a great website called Farnam Street that I would also recommend folks check out. I'm sure you're familiar with it. Speaker B: Very familiar. I, I, it's one of the few like daily newsletters that I love. It's very inspiring, very positive. Highly recommend it. Farnam Street. Speaker A: Amazing. Well, Aydan, it has been so lovely to chat with you and, uh, I really appreciate you opening up, uh, about your craft and, and the way you see the world right now.

Speaker B: Thanks Mario. I really appreciate the opportunity. Great talking to you. That's it. Speaker C: Thank you for listening to this episode of The Generalist Podcast. Please subscribe on Apple Podcasts, Spotify, or your preferred podcast app. Ratings and reviews help others discover these discussions, so if you enjoyed the conversation, I'd be grateful if you could take a moment to leave one. For all past episodes and more, visit us at com. See you next time as we continue to explore the future.