From the early days of Facebook and learning from Zuck to building a $2B+ VC franchise w/South Park Commons

25:22And as the market got crowded by 2018, it was getting pretty crowded in terms of the number of different seed firms that were out there. And I know they're decidedly different. But one question that always comes up is, OK, as you're moving into this, you have to raise money from LPs, right? which is a very different motion than raising from as a company to traditional venture investors. And there's different type of LPs, right? There's family offices, there's individuals, there's institutions, all those things. And I go back and want a question that we always ask, and I think most LPs that are sophisticated ask is the right to exist question.

25:58And it usually boils down to three things of if I'm investing in a fund one, the idea if you're an institution, because I want to back you for a very long time, fund after fund. So I really want to see the same traits that you look for in founders in you. Do you have intellectual capacity, depth? Do you have the work ethic? Do you have something that really gives you the right to exist? If you look back at that first fundraise, when those questions were coming up, why does this need to exist? Why you? And then ultimately, What about it are you addressing that does not exist? Because I think back in whether it's YC or Techstars, and this is not an accelerator, but there's some parallels to those things.

26:40Take us back into those conversations. And more importantly, what were some of the areas of pushback that made you the most, really made you internalize things the most, and maybe even doubt a little bit? Yeah. So I think you're totally right, Samir, that the first fund, And in some ways, like you don't have a track record, right? We are just, you kind of mentioned the Wall Street Journal story. We just finished up our fund forays, which is ending up at, it's a much larger fund now. It's like 575 million. We have 2 billion in AUM. But if you go back to fund one, that was a$55 million fund, right?

27:15And we've been able to raise subsequent funds based on performance. But in fund one, we didn't have that. The big thing, when you go and ask our LPs, who have kind of been with us from day one, in every single fund. I think that they would highlight a few things. I think they would highlight, at every first fund is based on, it is based on kind of like the individuals raising the fund, right? Like, are they, to your point, do they embody the values that they're looking for? Are they, do they demonstrate depth? Do they work hard? Do they have clarity of thinking, right? Are they creative? Are they magnetic?

27:48And I think Ruchi and I scored highly on all of those fronts. The one thing that has been, that has always worked in our favor is that our positioning is unique. I think that to this day, there are not that many, I would say minus one to zero, as we call it, kind of communities full of really smart engineering kind of technical people who are all essentially tinkering and trying to build something big. And that was a thesis that our initial sort of LPs got. And in some ways, it's only gotten magnified as our scale and our, I would say, our success stories have kind of gotten out there. So that's been really nice.

28:27Like we have a fairly unique and differentiated mechanism. Like I would actually go so far as to say that we position this, like if you read our blog post that just came out, I kind of say that we are the anti-accelerator, right? I think there are lots of accelerators out there and they're all fantastic. I hold them in super high regard. But I think that if I started a company, I'd be less worried about like sprinting really hard because I know I can sprint. Like I've done this my whole life. I'm in good shape. I can sprint if I need to, right? Right. The question is, there are 360 degrees around me.

28:59How do I know I'm sprinting towards the right thing? Right. So for me, a lot of the questions that I'm really passionate about helping founders understand is, are you pointed in the right direction? Right. Like if this is a like and the reality is that startups weirdly are both sprints and marathons. Right. So it's not like they're just marathons where you can kind of settle into a steady pace. You have to be sprinting really hard for a long time. So how do you know, like, this is something that will give you enough juice in the tank, like at mile 20, right? Or whether it's like mile 10. So I think that this framing that you come to SPC, not just to like run really hard at something, which by the way, again, there are other people out there, but to take a little bit of time to make sure that you are actually like running towards the right goal, that's unique.

29:45There are not that many people doing it. And I think it's kind of been cool to see us both define that space. And then now, I think you have multiple people kind of like in the same ecosystem. But I do think that we are the ones who really pioneered, I would say, this methodology. And that's kind of been, that has worked well for us to kind of be a differentiated thesis in what is a sea of early state funds. I think that as you kind of built, there's a lot of parallels to running a firm and then running a company. And I think about, you know, Fundforge is closed. You had the benefit of a track record, eight years of experience backing companies, showing the execution model working.

30:21But fun two wasn't really like that. It was just, you know, really a sense of what did you do the things that you were going to say you did? Or you said, did you do the things that you say you were going to do? Has it been working? Are there any things that now suggest that you're ready to turn over enough cards to raise a bigger fun and bigger fun? No different than a C to a series A to series B to series C. It gets easier. You risk over time. The big challenge, though, is fun one to fun two. One of the questions people have asked you is, what mistakes did you make in Fund 1 that then informed Fund 2?

30:51And there's always mistakes. We all make mistakes, things that we look back and could have done differently. What was the big thing that you adopted from, like, what was the big learning that you adopted from Fund 1 to Fund 2? Obviously, the model was the same, but were there micro decisions or methodologies that totally changed from those two funds? Yeah. I mean, first to kind of pause there for a second, you're totally right that, like, Fund 2 and Fund 3 are the tricky ones, right? Because by Fund 4, why did we, if you kind of think about it, in 2000 and not even, at the end of 2020 or early 2021, we had maybe like 70 million in AUM, right?

31:30And today, like at July 2026 or August 2026, like we are at 2 million, right? And so we have to, but then why is Fund 4, 5, like almost 600? And the reason for that is because Fund 4 is being raised on our track record, right? Like we have like all these decacords and these companies that we've been first checked into. So in some ways, you're right. As your track record builds up, if you've done a good job, then it becomes in some ways easier to raise because people can judge you not just in your thesis, but your results. But fund two and three are tricky because especially if you're first checked in, all of that stuff is still so early, right?

32:07Like how do you demonstrate that something like your thesis is actually working? Looking back now, I think that we made, we had two big learnings. in the course of fund one that we actually executed upon that I think that the LPs were like, oh, you have learned from these two things. And that's a really good iteration of it. So the first one was that when we started fund one, we were a classic like$55 million spray and pray fund, like write a 200k check there, like write a 400k check, 2 % ownership, 3 % ownership, right? And we quickly realized as we did some insane modeling, actually, and then also like learning about the ecosystem, that there might be some funds that are good at spray and pray, right?

32:49There are some iconic ones that like have done really well. We are much better as high conviction investors, right? So we very quickly moved to a world where we were like, if we don't get seven or eight percent ownership, that was our fund one target, we will not be investing, right? And that ended up like actually being a really good motion for us that aligned well with like the depth that we go into with our members. The second big change that we made, and this also worked really well for us, was that we realized early on, and SPC is this weird thing. Early on in the beginning, you had to join us.

33:23If you wanted to join us, you had to join us full-time. So you could not be employed anywhere, right? And also you had to be unemployed, right? Basically. So you had to join us essentially like full-time unemployed to explore. And we didn't pay anyone. Like there was no money on the way in. So really what happened was that we were, and we weren't funding anybody on the way in. So what happened is that we had really, I would say, in some ways, artificially limited the set of people that we could serve in Fund One to being a small subset of potentially great entrepreneurs. So towards the end of Fund One, what we realized is that, wow, there are a lot of people who actually want to enter the minus one exploration phase, but for whatever reason, they don't have personal runway.

34:05Maybe they have to take care of their parents. Maybe they have a mortgage. So we introduced a new program whereby you could take a very small amount of capital on the way into SPC. This is basically what we call the founder fellowship, right? And this was given to people who are pre-idea. They were just given to super talented individuals or teams who just needed some time, who needed some money to explore. And so I think what LP saw was that, frankly, if I have to use it in company terms, our time just grew a lot bigger, right? So we were able to kind of unlock like this, essentially this mechanism or we added a product that made our TAM grow a lot bigger.

34:40So I think the combination of those two, nailing down our investment ownership kind of like mechanism, and then also like expanding our TAM is what really allowed us to land Fund2. And that was a much less, it went from 55 to 150, but without your point, a ton of like track record. So I think we had to demonstrate how, what the evolution had been in the two and a half years after raising Fund2. Yeah. During this time, in eight years, it doesn't seem very long from the life of a venture capital firm. You have firms that have been around 20, 30, 40, 50 years, and over time, it's around durability of a firm, building that brand.

35:16But you have gone through a lot of change in terms of fund size. The model itself is the same, but four years ago, there was a new introduction to the public of ChatGPT. So that completely changed the ground underneath us in terms of how companies are built, the speed, all of these things compressed. The round size is obviously much larger. In some cases, if you look at someone like an Anthropik that's only been around for a few years now is the most valuable private company in the entire world. How did that shift your own internal mental model of size of fund, anything that you had to adopt differently or change in the way you either assessed or you deployed capital?

35:55Wow, that's a great question. So one of the things that, Samir, I did not realize this when we started the fund was that SPC is actually much closer to a frontier tech fund than I realized. And looking backwards, it's somewhat obvious, right? We invite really talented technologists to come and tinker with us, right? The ethos at SVC is that you should be thinking about what is happening at the frontier and kind of the things that are not that popular today and potentially hopefully are kind of like popular or understood like two or three years from now. Right. So looking back, I have found it really interesting that all of the areas or all of the sectors that we have large concentration in terms of like our bets, whether it be AI, right.

36:48AI is all of our industry, but whether it be AI models, AI semiconductors, AI serving, AI applications, we were about 18 to 24 months ahead of the curve in terms of like when we made those investments, right? And so what I find really interesting is that, I mean, if you're ahead by 18 or 24 months, that means that even as a smaller fund, you can hope to really give capital in a reasonable way to these founders and also get sufficient ownership for it. If you are competing on the open market for the thing that is, I would say, hot right now, I think it is actually quite hard for even like a fund of our size for fund four to compete because you are right.

37:31right? Like if you're out there competing with everyone and all the big firms want to come down, so they, you know, if you're a big firm with 5 billion kind of like as your latest fund size, it doesn't matter to you like what the valuation is like for your first slug in, right? So what I find interesting is that our model allows us, I like to think it allows us to see the future early, right? And that also means that it is like good from an investing perspective. But that also means we take risk. Like we invest in things before they become the current thing. Like we have a fantastic robotics portfolio, a drone portfolio.

38:05And but all of this was done before it became physically I became the only thing that people wanted to invest in. Right. So I think that the question that we are often asking ourselves is not what is everybody like, what is the next thing? Right. This is why like the ethos of SPC is bring in really smart engineers, and then let us all explore the frontier together, right? As opposed to let us figure out the best startup idea to work on. And there's a subtle difference, I think, right? Because I think the best startup idea right now tends to often gravitate towards the set of things that are allowed in the ecosystem, as opposed to like, what are the set of things that not enough people know about, that kind of like are unpopular today, but hopefully if we do our things right, we'll be kind of like hot in like two years, right?

38:52So it ends up being a little bit more of a frontier tech fund, which had its own sort of risks, but also like, I think really good pricing kind of like opportunities. Yeah, if you have a certain worldview of where things are going to go, and you end up being right, this is the whole thing, which is you invest in things that are either not apparent, or against the crowd. And you're right, those are usually the best outcomes. In times like this, you can be a little bit consensus, and the big funds are a consensus. That's okay. They can put a lot of money, the multiple that they need on the entirety of the check they write is much smaller because if I put a billion dollars into a company and Dreesen just wrote a billion dollar check into Adams, for example, which I think is one of the biggest, if not biggest checks they've ever wrote.

39:31You get a 2x on that. That's 2 billion back. That's amazing, right? It doesn't work if you're investing 700 ,000 or a million dollars and getting it. I mean, we literally I mean, like our like this is the question that we ask ourselves before we make any single investment. Will this one investment, does it have the capability to return the fund? If we don't believe that, for whatever reason, the market isn't there, the technology isn't differentiated, it's too competitive, like the founder might be missing. We are just not going to invest, right? Like our underwriting philosophy is that every single company at the point of investment, we strongly believe that it can return the fund if things go out in the right way.

40:12And then there's also a second part, right, Samir, which is that I have told, I don't know if I'm allowed to say this in the podcast, but I tell all my LPs this. I think I told you this. Like, I have early stage venture is a both a very, I would say, job that gives me a lot of happiness. But it's also hard. You work really damn hard, right? Like, you are out there kind of like in the trenches with your founders. So I tell people that like there are easier ways to have more kind of like guaranteed returns. The reason why we should be building SPC, like in terms of like returns for us, is if I can give 5x net every single fund, right?

40:48Like that is my goal. We will hit it with fund one, we'll hit it with fund two, fund three is early, we're only two years in. But that is my goal. And if I ever see a world where like, our thesis, our investing motion doesn't allow us to do that, then we have to take a pretty hard look as to like, does this model like how, like, what do we need to change in order to like make sure that happens? Yeah, even in the time, and I think it's a great way to think of the, does this particular investment have the potential to return the fund? Because if you look back 20 years and you look at the track record of every single fund out there, and you don't have to look at all funds, but the top performing funds always had one company that ended up being ultimately trans slammed that returned the fund or sometimes multiples of the fund.

41:32And that's gone back in time. I mean, Excel was an investor in Facebook, did really well. Their investment in Facebook. And we've seen that with SpaceX and some of these large companies. Now, the art of possible seems to be fundamentally different. And I think about when you and I started our careers. I mean, I was in the dot-com and then, of course, mobile and cloud. Now you have AI, which appears to be the biggest super cycle. And I'm very techno-optimist about how this is going to change productivity. Now, how are you underwriting to the size of these companies? because what you might have modeled out in 2018 was based on past heuristics.

42:06Now you see companies, a trillion dollars. What do you think is, if you separated fact from fiction, yes, we are in a frothy market. There's no question about it. But how do you think about the ultimate return that you now believe these companies can reach to get you? And how does that affect ownership? It's a good question, right? If you just kind of do the math, right like we it's a 600 million dollar fund so we basically want to invest a slug that you know after dilution and so on will return us at least 600 million to kind of return at least one ton of the fund right so if you do the math like if a company is worth 10 billion right and we let's say owned 10 percent at entry diluted down 40 let's say 40 percent right then like that kind of gets you down to like 6 % ownership at whatever outcome that returns you.

42:57So my take is that maybe we actually do this, can I see a$10 billion outcome? Now, I think you have you make a really good point. Can like stuff that I thought 10 billion was I like today might actually be 100, maybe even like 500. Like I look at one of our companies based in and the kind of the kind of trajectory they are on in terms of what they're building, their go to market and kind of the traction, like they could end up being a lot bigger than kind of like even kind of like the 10 billion outcome. But I think that I tend to be and this is odd for me because I'm such a I'm a huge techno optimist myself.

43:32But I think that honestly, it is quite hard if somebody tells you that my thesis for underwriting into a company is because I think that this could become like a half a trillion dollar company. I'm like, come on, man. Like that's that is I mean, I hope it happens. But that is still we don't have enough proof points of that. So I think, but I think you should be able to make a case that like, if they build this, like, how will it, how will they become a$10 billion company? A lot of that is like, how will they get to have a billion dollars in, you know, ARR or revenue with like pretty high kind of like, I would say like good unit economics, good margins.

44:02That's it. That could be a$10 billion company, right? And if you cannot make like a thought experiment case for that, you have a real problem. Yeah. One of the things I struggle with, and maybe you do, and I think a lot of people probably do but don't admit is there's like this level of cognitive dissonance right now where I from a technology standpoint from a curve standpoint this is the biggest innovation we've ever seen and we're very early whether it's AI in the physical world AI in our day-to-day how enterprises work and we're just at the forefront of those things and you've seen the model improvements over the last few years both on open weight and then the closed frontier models and I get very excited about what the next 5, 10, 15, 20 years are going to look like from an innovation standpoint.

44:44That said, there's the capital market side of me that has gone through many cycles. The dot-com bubble, of course, 2008, 2009, and even 2021 going into 2022. That part of me swallows the red pill more than it swallows that blue pill. Trying to make sense of it, if you were to look at, And it's very easy to pattern match today's environment with past environments. And it's like, this looks like this, so this is going to be true. And I think about 2000 and 2021, we had massive run-ups in terms of capital being deployed into startups. And then you had a precipitous drop-off when it was very clear many of these companies didn't have durability.

45:27There wasn't enough. There was too much cash, too high valuations. How should we think about it? what truly rhymes versus what are the nuances that we need to consider to maybe break away from the mold of just using past heuristics? Probably like a few different angles to it. I think that the first one is at least the last 15 years or so, software, the cost of running any software thing has really been zero marginal cost, which people, that's a good thing for the software providers, but it's kind of weird because it also meant that there was nothing you could innovate on below the software layer, right?

46:05Because there wasn't enough value to be captured. But the fact that today, there is actually like a big, essentially, it's more like an industrial kind of like supply chain. You need the minerals to build the chips, to build the GPU clusters, to build like the data centers, right? So there is kind of, I think this, I think part of the reason why this feels like an even bigger super cycle is because it involves not just software. Like this particular innovation that we have requires like in some ways, capital markets all the way down, right? Which we haven't really thought, I view that as a good thing.

46:40I actually view this as like a, this is not just like a small podunk software part of the world. Like this is actually kind of like requiring, if you kind of look at in some ways, the entire growth of the economy of America right now, it's kind of driven by kind of this new technology called AI, but you can call it railroads. It's the same thing, right? Like it is a fundamentally enabling technology, but that kind of like requires like, you know, basically innovation literally from the ground up, right? Like from the time you actually get those rare earth minerals and so on. The second thing I find interesting is that its applicability is also not frankly just limited to high value knowledge workers, right?

47:21I think that's interesting. Like we're kind of building out like for all of the high value knowledge work, coding, marketing, finance, they're all getting accelerated, but it's also going into domains that I don't think at least in my 15 years in Silicon Valley, like how many founders have I met in the last 15 years talking about putting nuclear onto like a cargo ship, right? Or yesterday, actually literally talking to a founder that I just, you know, I just found we just funded, which was, hey, I have a gun that is the world's biggest gun that can shoot things into space because rockets are expensive.

47:52It's called long short space, right? And so it feels as though that the scope of, and again, perhaps it's unfair to call it just Silicon Valley right now. Call it like Silicon Shenzen, I don't know. But it feels as though the scope of what people are building is also much broader, which makes it hard to reason about. And then thirdly, I probably have the same intuitive sense of this is a great technology. It makes me so much better on all these kind of like dimensions. but man it also sucks in all these different ways and it's kind of like dumb right but despite that I see my dad using it all the time I see my son using it all the time I see my six-year-old daughter using it so maybe this is one of those technologies where the floor is so high in terms of what it is able to allow you to do whether it be to be more productive to entertain yourself to do something that people get it people see it right yeah and that's actually been shown I mean If you look at the adoption rates of PC, Internet, AI, AI is so much faster.

48:56To get to a million users versus Facebook, very different in terms of the time frame. And I'm with you in terms of I do think we're in this. And your analogy of the railroads, I think, is the apt one. I think this is the biggest innovation since the railroad in terms of what it's going to enable. At the same time, my belief from a capital market standpoint is we are putting a lot of money into these. Well, I think there's a lot of rational reasons to do so because the reality is the companies of today that do make it and do become the top 5 % to 10 % are going to be degrees of magnitude bigger than anything we've seen.

49:28No question about it. The key is like where are those gaps where you can still invest in valuations where the risk return still makes sense because you still have to hold a microscope while you look at the telescope of where these companies can be. And it'll be interesting to see. I mean, this is probably one of the most interesting times in my 27 years working in venture capital. It's interesting. The best way to find that out, and I'm not saying this simply as a plug, the best way to find out is actually come roam the halls of SPC. And part of, I think, what some of our LPs really love doing is actually coming to a lot of our like fireside chats or coming in for our roundtables, our learning forums, our paper reading groups, because it is a sneak peek into the future.

50:06Right. and that's the most fun part of my job right like being able to interact with these founders because they will have ideas that i would not have thought was possible that they will kind of blow my mind about yeah you know what i tell people the same thing because when they i hear a lot of people especially outside of silicon valley and in different parts of the country and some of it's the distaste of ai just more in the press cycles and media in terms of what it is and what it isn't but i always tell people that are skeptics just come to silicon valley for a day we'll take around. And they always walk away with a very different feel because they see the people that are actually building these things.

50:39And you see these things that are real life applications. I didn't know this could exist. And I think that's what you and I get really excited about. If I may add one more thing to that, right? Like, everybody's obviously freaking out about the CapEx kind of like rollout and so on. But man, like, when was the last time, like, there was a piece of technology that if my son wants to spend 60 bucks a day on, and he's nine, But he's writing a bunch of code. He's generating a bunch of videos. I'm like, this is so good for him. He's being generative, right? He's not passively consuming random content on the internet.

51:09He's actually like learning how to make and build along with like this enabling. So I think that I really do think that the amount of compute and electricity that we will want like five years from now, we're still only at 2 % capacity, right? So, but you're right. It is cognitive dissonance. It's kind of, it's scary because I'm just like, my God, you're going to put a lot of money. And I sure hope there's not any hiccups because it is a hiccups for like the hyperscalers that's going to boil down into our ecosystem, right? Nobody's immune to it, right? So yeah. Yeah, it's going to be very interesting to watch.

51:41But I like you share a lot of optimism for what the future holds. Maybe just to wrap this up, one question that I'd love to ask you, because you did move from being within a company, being an operator in your own company, is the biggest thing you've had to unlearn from being an operator to now investor? Oh, that's a good question. I think as an operator, yeah, that's a good question. So the way I would answer it is that an operator, kind of your reason to operate, right? Like the reason why you kind of show up, you exist is because you want to bring predictability. You want to figure out how to take X and make 10X, right?

52:14And you want to, in some ways, like reduce the variables and you want to like make stuff more understandable. And I have found that as an investor, anytime that I try to do that exercise of reducing dimensionality, or in some ways, overly reducing a problem, I end up in some ways, making bad investment decisions. The reality is that startups are messy, like an especially early startup investing is super messy. And in some ways, what you want to invest in is the high alpha founders who have a lot of potential. And you're not trying to early on kind of in some ways do this reductive exercise that like, Oh, I don't know exactly what they'll build, how they'll sell it, how they'll like those those questions will actually end up leading you to say no, right?

53:00Whereas an operator, your whole job is to be like, Oh, that's an unknown thing. Let me go drive like as much like, like certainty around it as I can. And so sometimes I think a lot of it is like just learning to kind of like let go and instead focus on the one or two things that matter to you as an investor. If you're really cared that this person is highly charismatic and magnetic and kind of like make sure you get good signal on that but then also don't let the smart part of your brain and i'm a smart guy right try to like over intellectualize and almost like reduce variables in the part that you should actually learn to let go yeah you can talk yourself out of any deal if you go deep enough oh absolutely yeah i mean i tell people there's a thousand reasons to say no to every startup they haven't built much yet right like there's a thousand reasons but it's probably one or two to say yes and it's your job to feel really good about this one of the reasons if you want to invest.

53:53100 % agree. Well, this has been a lot of fun. I again, congratulations on what you've built throughout your career, but also with the last eight years at SBC. Getting to this fundraise is great validation of everything you've built. Thank you for your support. I really it really means a lot. Yeah, and we really appreciate you being on. So thanks again. Thanks for listening to another episode of Venture Unlocked. I hope you really enjoyed this conversation with Aditya. If you'd like to get Venture Unlocked content straight to your inbox, go to ventureunlocked.substack.com and sign up or head over to Apple Podcasts or Spotify and subscribe.

54:26Thanks again for listening.