Uncapped #1 | Shaun Maguire from Sequoia

26:16But I got fully manipulated in 2016 to be very candid, like where it came from is I was too trusting of the US intelligence community. And I had worked in and with the US I see. And I think there's many unbelievably great people, some of the greatest heroes in America and the world are in that community. But I was raised like a lot of people, my family were in the military, and I was just like extremely trusting of that community. And my route vulnerability in 2016 and 2016 to 2020 was a deeply trusted that community. And so things like, you know, when people in the IC said that Trump has ties to Russia in 2016, like that, for me, worst possible scenario if you would have a Manchurian candidate, president that's owned by Russia and somehow skates through.

27:07And then in 2020, I wrote about this a bunch, But I still didn't vote for Trump there even though I had really like just policies in 20 this first term right two weeks before the election 51 intel officials five former CIA directors came out and you know said that the hundred by and laptop was Russian discrimination and that so did enough doubt in my mind that wow maybe if Russia wants this guy to win, then like I want whoever Russia doesn't want to win to win. And that really worked on me. I think everyone had different vulnerabilities, different things that they, you know, data sources that they waited.

27:50But for me, two things coincided, which were one I had learned that I had just been deeply manipulated and that was infuriating to me. And the second thing was Silicon Valley starting around 2016 or so, the Trump administration. And I think that became such a so much animosity and people got more political and more vocal against Trump. Coinsided with like the DI movement, James DeMorat, Google, Me Too movement, cancel culture. I think a lot of people in tech simultaneously got so frustrated by like cancel culture in the valley at the same time where people were realizing that they'd been manipulated for a long time.

28:37And those two things came together and it was just like, fuck it, I'm pissed. Like, you know, I'm gonna start speaking my mind and once some people started to speak up, it's just like every time one person says something, it gets easier for the next person, the next person. So, Balzen, that is something like, from in information theory perspective, you can codify. and that was something that was, I was actually going through my mind was like that you can trigger an information cascade with like small, small change in bits. Yeah, it goes back to sort of the, the prisoner's dilemma thing where once you see other behaviors like that, it just gets much, much safer.

29:13I also really like the root vulnerability concept. I think that is like, I haven't heard it quite like that, but I think that's something that like, all positions have that and understanding your own weakness and where you can get trapped is probably really essential. As techs politics have kind of flipped from the left to the right, what's interesting is I think we historically weren't that deeply embedded in the government and now we actually are in what looks like a much more obvious way to me. And you see a bunch of players inside of tech having much more influence with the government, the government seems to care about tech in a way that it never did people get invited to the White House or it seems like they've got a voice in all of these places.

29:51Is ironic that this happened with Republicans not Democrats for what it's for? It's crazy. And it seems like that was like a real fumble from the Democrats. And it seems like they like had that at their disposal this whole time. But you know, here we are. And one of the things I'm wondering about is, well, this drastically changed the types of companies that become important. And so I'm thinking about the types of companies that, you know, maybe this got most, like, accurately, momentically captured by like Andrewsons, you know, American Dynamism Fund, And there's all these companies that require the government to do government scale things.

30:25And you see this with Andrew and SpaceX and OpenAI and like many others of what are kind of like the biggest, most important companies at the moment, who is going to have these big government relationships. And so I'm curious will this sort of tech government hybrid, will this change companies, or will this just make it a little easier to navigate? Like what's the impact for tech here? There's a lot of directions to take this one initial quick thing. In some sense, it's challenging and risky to have tech be closer to Washington. Whenever you take a side, your more at risk if something goes wrong, the conflicts of interest are more acute.

31:08I think that we should have a deeper relationship between tech and Washington and Washington should be funding more ambitious tech projects. And I think a lot of times, like the government investments into tech or loans, whatever have been, I think treated unfairly. There's seen as a conflict of interest, whereas oftentimes these programs were, you know, there's a broad agency announcement and a lot of people bid on it and a tech company happened to win it or the loan was given to 10 companies, nine wearing combs, one is a tech company, but the media focuses on the tech company. So look, I think we should be doing a lot more and I hope we don't jeopardize that.

31:51But the even bigger thing to me and I haven't said this too much publicly. I wrote a manifesto for Sequoia a few years ago, I think of three years ago. So hardware manifesto. I've been obsessed with hardware my entire life. if you know, I have a PC and physics, I'm literally was obsessed with semiconductor as a kid, I completely obsessed obsessed with the chemicals industry and I know I was also obsessed with early Silicon Valley. And if you look at Sequoia, Sequoia made almost all of its money the first 25 years on hardware investments. You know, one of the first investors in Apple and Cisco and linear and many other things.

32:35many, many other companies and video, first investor and video. The last 25 years, the boys made almost all of its money in software. And kind of a question I asked myself was, like is hardware dead, long live hardware? Or is this kind of a secular trend, secular, you know, in a finance perspective, especially like Wall Street oftentimes means like, longer trends than just one economic cycle. And so I wrote this manifesto three years ago. And now it's obvious to everyone, but literally in my manifesto, I had two stocks. One was NVIDIA, one was Tesla. And I really strongly believe we were just in a secular period where it was all about software and not about hardware and some of my realizations, there's a bunch of things.

33:26But one that I think is not fully appreciated, almost by definition to like every software revolution is preceded by a hardware revolution. You can't have some new software platform if you don't have the hardware to run it. And for example, you can't have Uber and DoorDash if you don't have the iPhone. You need to have the App Store and the App Store needs to have the iPhone and the iPhone required 20 years of development with Qualcomm, Broadcom, fiber, cat -back, all sorts of that Cisco. But there was 20 years of hardware before that. To have deep learning, you needed to have the GPU, to have the cloud, you needed 20 plus years of CPUs getting really cheap.

34:19The whole point of the cloud is that we got to a point where hardware got cheap enough that you can put a ton of relative to commodity hardware in one place and operate and you get an economic advantage to do it that way. Anyways, you can name any software of Lucian history and is preceded by a hardware of Lucian. Something like VR today, part of why we don't have great VR software is a hardware is not good enough and is getting better very quickly. And the input to VR hardware, like a lot of it, it's by a lot of what's been happening with the iPhone. I think sensors in general are one of the most underrated technologies in the world.

35:02My estimate is about a trillion dollars of market cap of companies that are basically sensor companies or selling sensors. A lot of the market cap of Honeywell or Raytheon or from sensors. There's many other companies. Keyens is a $100 billion market cap company. Anyway, it's like, is hardware dead or are we missing something? And I really think we've been missing something. I think that thing is that basically the way Moore's law happened, hardware matured in a bunch of different areas all around the same time, which led to a bunch of software ecosystems all catching on. And now a lot of those have run out.

35:39The app store is very few new interesting apps getting created. VR is not quite here because the hardware has to get better. In my opinion, AI is still hardware limited. You see it with the AI Data Center buildouts, but it's not just going to be Nvidia that benefits. There's going to be a bunch of other companies on the hardware level that benefit. We're seeing the beginning of autonomous vehicles, like just on and on and on. I think we're at the beginning of a new hardware revolution. Silicon Electronics are starting to become silicon photonics. We've just kind of gone the first commercial applications of silicon botanics that are actually economically viable.

36:15And anyways, I think we're entering a new era where the next 25 years through robotics, NAI, and space, and then some of the later platforms like VR and then bring computer interfaces and medical technology all these things. I think we're entering another golden era and obviously defense technology to a massive extent. I think we're entering another era where that's gonna be like a very money -making opportunity. And that requires government partnership, or at least it's enhanced. If we want to compete with China. Because it's such big dollars or something else. Because it's big dollars also because of the biggest driver historically as an early adopter of hardware has been the defense department.

37:01I don't think that's something that should be ignored. And I think one of the other biggest trends in the world right now is like, literally one of the biggest macro trends is for 25 years we were outsourcing manufacturing to China. Now we're bringing it back and that re -enshoreing, just an insane driver also of like hardware development in America. So like if you think about this, you know, as it applies to investors, Sequoia did all this, you know, investing in these crazy companies a long time ago, you know, over the last 20 years software, you know, not to do another. or Andreessen thing that's offered you in the world, that's obviously what dominates.

37:34It's offered? Andreessen amazing at marketing, obviously. Very good. And that was right. And that's kind of what's played out. And I think outside of a couple of names, which are incredibly important asterisks, like Andral and SpaceX and some other companies that are very hard, hard tech problems in companies. I think most investors who invested in hard tech over the last 15 years maybe, let's say, Like, just, it like mostly didn't go well. I don't know what the overall return is. If you, you know, if you, if you include these like outlier companies, I don't know, like maybe actually with the long tail, it's actually very good.

38:12Still, but my question is, was it, was it a bad time and now it's a good time? Or is your mental model that hardware companies are even more of a power lot than software companies? And so as a result, it is very good to invest in this kind of stuff. If you are capable of doing it, but if you're bad at it, you are like more likely to lose your money, then average, you know, like another way to say this would be, I think the sort of prevailing wisdom, which you might agree with, you might disagree with, but you know, would be like a smart enough reasonable in the mix San Francisco investor, who runs around making investments in a lot of sort of good, you know, what we would think of as, you know, sort of classic AI software companies right now will probably get a hit.

38:53They will probably do fine, but you know, going and investing in hardware companies, like unless you hit big one, you're going to like, you might get zeros all around. So like, how do you think about, is it about the time, or is it about not everybody's equipped to do this type of investing? I think all of the things you just said are true. I think it was a bad time to be investing in hardware. On average, the last 25 years, and you know, with the caveat that I think some of the best investments simultaneously, some of the best investments of the last 20 years were hardware companies. SpaceX Tesla.

39:24I'm of the camp that intervals going to be an absolute giant company. Me too. But I think on a relative basis, I think like the amount of market cap that will have been created retroactively by hardware companies in the last 25 years will be very little compared to what it was for the 25 years before and what I think it will be the next 25 years. I believe it was a bad time. I also think that most VCs were not equipped to invest in hardware. But that's okay. It's like the industry evolved for that because it was a bad, like just bad macro time. Are you saying that VCs were not in that moment or do you think even in a good moment for hardware, most VCs are not equipped to invest?

40:00I think a lot of the VCs that were good the last 25 years are not equipped to invest into a hardware era. It seems like a really different mindset because to your point, hardware comes first and then the software comes. And so you have to think way differently. For sure. Versus when you see this thing's working, now I can just bet on some application of it. Earlier today, I was reading the story of how Kleiner incubated Genentech. And I mean, they literally incubated the company. I can't remember the name of the partner that really did the work, but basically this person had been following some of the top biowork out of, you know, in the Bay Area.

40:39And there was faculty member, Stanford faculty member, UCSF, where he'd been following their work. They basically approached them to try to commercialize the work and Kleiner convinced them to start a company, Brooke Byers, my friend Blake Byers' dad, was one of the people that was kind of on this team, but it was three people from Kleiner that basically approached them and convinced them to start the company. The idea of like you have a VC that's reading the scientific literature and finds these two professors and thinks they can create a new platform in biotech and then goes and starts to come in with them and then you build a company for decades.

41:15That's just not how most VCs have been doing the job. The last few decades. And granted, I think it's still how a lot of people in life science VC have been doing it. But I actually, I don't think that's where the biggest hard -ropped opportunities are going to be the next 20 years. And so just to use that as a thought experiment, that's just not how VC has been done. The last few decades. But I think there's also something very important you said, which is, look, I do think the power law curve of hardware is steeper. One of my insights around, I think, why? I think there's a fundamental difference between software companies and hardware companies.

41:51There's many, many, many. But one is, with software company, if you have a successful first product, the probability that you come up with an organic second successful product in your company is very low. It's like almost, if you do the conditional probability, it's basically the same probability of being successful with the product from the outside. You don't get many advantages once you have a product. There are some distribution advantages, but you don't get much of an advantage for creating a new product. You can acquire things that already work and roll that in, such as how Facebook acquired Instagram or Google acquired YouTube.

42:29But with hardware companies, it's fundamentally different. Basically, every hardware company in history that's had a first successful product will have dozens of subsequent successful products. Like name any hardware company, go on their website, they'll probably have dozens if not hundreds of products. Go look at, you know, Rodcom, Qualcomm, Cisco, Danahair, Tesla, Nvidia, and for a lot of reasons, one is once Apple, like any hardware company, if you're doing it right, I think sometimes you're not taking much market risk, it should be something where if you build it, people want it. But building it is very hard and the hardest part about building it is often it's not designing it.

43:12It's like figuring out the supply chain. It's, you know, it's figuring out the... The cost of scale. The cost of scale, the capital cycle is all this. Yeah. Like take Apple because I think it's a simple example. They have so much leverage over their supply chain now. Right. That after the iPhone, if they want to make the iPad, they have so much leverage and they can go get production capacity from TSMC or whatever. Apple products is the best sensor team in the world, especially for MENs, based sensors, micro -mechanical machines. And they reuse their sensors across all the different polyclines.

43:50They use the infrared camera for face ID in the phone and in the iPad, and now in the VR goggles. And each individual component is in a mode itself. And so what happens is, I think with these hardware companies, once you're successful, that success just compounds. I think at an even greater rate on average, it's harder to get success with the first product, but once you do, it leads to a lot more. It leads to a lot more, whereas the software companies, the first market you go after is much more important. Yeah, I mean, I think that's mostly right. I mean, what was going through my mind is you said that as I was starting to think of examples like a Microsoft or a Workday that do become these, you know, we saw what happened with Teams and Slack And you do that.

44:33So it's not to, it's not to underestimate that distribution advantage. Sure. It's more that the hardware company also has that distribution advantage and now they have this creation. They also have a supply chain advantage and a creation advantage and just much bigger modes. But I think the Microsofts of the world, I think, I think they're few and far between compared to, compared to hardware companies. Like I challenge you to find a hardware company that doesn't have dozens if not hundreds of successful organically grown products. And it's just because once you've already got all that stuff, it's so much easier for you to make the next one.

45:07For sure. For sure. It's actually amazing that Apple restrained itself to as few products as it did for as long as it did given that they could have clearly just proliferated, but like everybody else did. And there's like, we're going to have five. For sure. You have to get to the point where you're really strong before you go start taking on all these other products. But once you're really strong, like with one product, it's going to compound like crazy. As you were talking about how a lot of investors operated decades ago and incubating and GenNNTAC and all these things, there's a part of me that as I reflect on my own sort of journey here where I've been building a company up until a year ago and now I'm investing, which I really love doing.

45:47If there's an insecurity I have, sometimes I'm like, I was doing the work and now I'm supporting the people doing the work. I don't think that that's like a productive of mindset necessarily, but like that, you know, if I'm on a day where I'm like insecure about what I'm doing, that's what the insecurity is. And you also grow out of it. Yeah, hopefully. Yeah, I'll just forget that I did it ever and that'd be great. But you built a company and you were very successful. And now you've been investor for a while, like talk me through, you know, will I grow out of it? Like, did you have that? And how do you think about this?

46:19And are there other ways to do it where you agree with that same investor? No, you'll definitely grow out of it. But you know, that said, you may get the itch at some point to start another company. Like I think they're different phases of life. I'm going to use a few weird analogies. I have a lot of weird analogies. One is with mathematicians. So there's this saying it's not 100 % historically accurate, but that a lot of the best, like almost all of the best mathematical results are from young mathematicians. It's called before the age of 30, roughly, and like the fields metal, it's for work before the age.

46:54You have to be 40 by the time you get it. So, you know, the work has to be a few years before that. You know, there's a saying that mathematics is a young person's game. There are some counter examples, like some incredible mathematical work that people did later in life. But I think for the most part, it's true. Yeah. And as a former kind of mathematical physicist, the reality of life is, like, they're different phases of life. And like, I have two boys, little boys, the best thing in the world, but it would be very hard for me to do math the way I used to, like with all the responsibilities I have now and having a family and being a parent I wanna be, and all this, like, it basically impossible.

47:40When Gregory Pearlman solved the, like the point -create conjecture, basically spent years living in Russian forests, you know, just literally just thinking about this one problem in Max Autist's way, which I respect a lot, he pushed humanity forward in the process, or when Andrew Wiles solved for Max last year, I'm like, he, I think it was seven years of work where he was just fully, it's the only thing waking up, breathing this thing and I think it's hard to, for those types of problems, I think it's hard to do anything else. You have to put all the concepts into your RAM in your head and just keep them there and process.

48:23If you shut down the computer and purge the memory, the IOTime is very long and you'll just never make any progress. I don't interrupt. I'm sure you've read the book on mathematicians' apology. The GH Hardy book. It's about this great mathematician and he reflects back. And hardy's the one that basically found reminutian. Yeah, yeah, exactly. And he's sort of like reflecting later on, I did this work when I was at a certain age to do that work. And then how do you grapple with that over time? And I think different people grapple with that differently. For some people, there's like a, I think the unhealthy, the grappling I don't want to have to bring it to where I think you're going to go with the metaphor of building a company is the negative grappling would be to sort of have those be the glory days.

49:09and you're always like dreaming, you were back in high school on the varsity team, and versus a positive grappling, I imagine, would be to be like, that was a beautiful chapter of life, and now how can I productively make that something I pass on and support people on there, you know, being a 25 -year -old mathematician days? Exactly, right. Like, I think we have to celebrate the different chapters in life. You know, to continue the mathematics example, I have a friend, Yufaiz al, who is a legendary, talented young mathematician at MIT, who he was doing the best work at a young age. He still does incredible work, but he then got really involved in coaching the Putnam team at MIT and basically trained a whole generation of young mathematicians.

49:54He basically broke the Putnam at MIT. And like that work of mentoring the next generation and then taking on a lot of students and teaching them how to kind of write their first paper and do real research grade math math like that's just a different skill, but I think that probably has even more of an impact, like enabling that whole generation of next people. And then, I think you face gonna have another chapter in his life coming up, which another analogy from science, my PhD advisor, John Presco, who's an amazing guy, haven't seen or talked to John in a while, but he's, I'm sure John's gotten shit for my political views recently given the state of academia.

50:38But John, I still love you. You're an amazing guy. I've learned so much from you. But John had a saying, we're basically every 10 years, you should kind of switch subfields of physics. He started his career doing particle physics, high energy physics. I had one of the proposals for a dark matter, a dark matter particle candidate. And then he moved into in the early 90s, kind of the early, like, string theory days, like, callography, how does all that work? And then in the late nine years, he was one of the first kind of real theoretical physicists to go into quantum information theory and early quantum computing.

51:21And then about 10 years he went, and I mean, he built like the top quantum information group in the world. And then over the last 10 years, you kind of went back to thinking about what happens inside black holes. And going back early in his career, he had won a few bets against Stephen Hawking, and they were some of the early people that thought about like the black hole information paradox, but he went back to it 30 years later with much deeper tools. I think this is another philosophy, is like I think that every 10 years to switch what you do a little bit, it's very powerful, because you then cross -pollinate ideas, you basically cross -pollinate relationships, you have wisdom from this area.

52:02Also things just naturally go stale over some period of time. Yeah, and you force yourself back to some amount of beginners mind. Exactly. I think that's what I appreciate it as I got to a place where I was like, I kind of have my ideas about how I should do this as a CEO at this stage and whatever. And you unshackle when you do a new thing and you're like, I have no choice but to go back to thinking like a beginner, which is, it feels healthy. Completely agree. I think good articulation, I think that was in a lot of ways like the key point he was making. So you articulated better than I did. So when you think then about the given sort of this sort of way of doing it in a way that you're you know proud of or excited by or you know resolves nicely in the sort of fuller context of life, are there types then of investing that are more in line with what you think is the word honorable just came to mind that's not the word I mean exactly but like that are more I'm fulfilling and meaningful versus types that are more just like who cares even if I'm to make money on this?

52:57It just doesn't care. What am I doing? I shouldn't answer this, but I'm going to as you started in the beginning, I don't hold back. Look, I generally get way more fulfillment from hardware companies. I think that at the end of the day, hardware companies are the ones that really move the ball forward on humanity in general more than software. And that's not exactly, it's not always true. But as a general statement, I think that hardware companies are something that like if one Hardware Company doesn't happen. The whole category might not happen. Like if Elon didn't push SpaceX, who knows where humanity would be with space today?

53:32If he didn't push Tesla, who knows where EVs would be? If Steve Jobs didn't push Apple, like who knows where personal computing would have been. And like it would have happened, but maybe five, ten years more slowly. You know, if there's just so many examples of this where I think that an individual Hardware company can really change the timeline in which whole industries happen more than software. I think software is more inevitable. Once the macro ingredients come into place, I think the software companies are almost inevitable and going back to science. There's this concept in science that like ideas are in the air.

54:11Calculus was invented simultaneously by Newton and Leibniz and other people like all the wrong ingredients are there. I think with hardware where it requires more of like a stroke of genius or the real... Like great man theory type stuff. Yeah, great man theory. It's like Edison and Tesla were like psychos. And if they didn't exist, you know, like it's hard to know if the Wright Brothers, like it's hard to know what would have happened with aviation. So I do believe a little bit more in the great man theory with this. And so therefore, the places where I've gotten the most fulfillment have been like seeing something with hardware earlier than others and being more instant.

54:50Yeah, I mean, the other big differences, like science and math, you know, you might say eventually must get discovered, like, versus like if it's true, it eventually someone's going to find out that it's true versus with like, nobody had to make Apple. Like Apple didn't have to be like Apple. It could have been anything. Or somebody decided to make it that way. And because Steve did it with such a specific intent, like being like, I just watched an amazing clip yesterday of him talking about Microsoft. And he basically says they had no spirit. They had, and he respects them. They built a great business, but that they had no design sense, no spirit.

55:30And that he viewed Apple as a cultural movement and that it's, for example, if he didn't bring in type setting, like it might not have ever happened. and we might have had ugly text forever. It just not only does it take someone to do it, but the person that does it gets to really set the agenda for how that field happens. So you know, if you're... I saw a clip of him the other day talking about how this is like the long time of decades ago, like the 80s or 90s or something, he's talking about how like wouldn't it be amazing if you could ask Aristotle questions and how like, you know, and you know, maybe that's kind of where AI's going now with stuff.

56:11But to have that kind of vision and narrative, and that's what rallies people to build towards that vision. I think that's like a big part of what's required for these, is somebody has to just hold this North Star for so long to so many people, because it's so hard to make this stuff happen. Maybe this we can end on this question, you know, with that backdrop, you know, and you think about the way that VCs can be operating or should be operating, or it's because, you know, what we're talking about right now, like, I'm like, this has me fired up. Now I'm like, I feel good about being an investor.

56:42This is great. But so much of it is so, it can be so, you know, memetic and there's so much herd mentality and there's so much because you're, you know, because you're abstracted from the building unless you're, you know, incubating and building companies yourself, it, you know, seems very easy for people to get caught up in the wrong stuff. And so I guess like, how do you think about like what VC should be practice like today. Trace Stevens and Markey, I think her last name is Wagner. They wrote this piece a couple of years ago called Choose Good Quest. Yes, I loved that. It was amazing. And I thought that was a great articulation of it.

57:21I'm not going to knock anyone that wants to create a widget. If that's what gives you joy, go create a widget. But in my opinion, I get my joy from either choosing good quest myself or trying to help other people on good quests. There's probably 20%, 30 % of the companies that backed are not there. Like they're more widget companies. And something just to call out, I also love people. And there are some humans where if I deeply love some founder and they are obsessed with some widget, then sometimes I get excited to give them money to go do that. By the way, widgets sometimes surprise everybody.

58:03Exactly. The YC thing that great things often start like a toy and sometimes it looks like a widget now it grows into something unbelievable and so we just start with widgets on. Exactly, exactly. The call is in Brothers before Stripe did actomatic, which I don't even know exactly what Dividu's and I think it was like sub -stack before sub -stack and it became Stripe and - And potentially even on day one of Stripe, you wouldn't have necessarily had this type of sort of like, like star -struck conversation about what it was. They were building and it evolved into something that turned out to be incredibly important.

58:33And I'll just say on that, John and Patrick, they're such curious people. They're just, they're like, maximally curious, maximum voracious readers. And I understand why they, like, I can imagine sitting in an automatic pitch from them at 20 years old or whatever and just seeing their passion for it. And be like, okay, these are brilliant young guys that are, I don't care about this widget, but they're obsessed with it. So I'll give them money to go do it. And I think that there's something very pure in that. And then it kind of, not in that company, not that keptable, but those people and like the kernel of lessons from that company became Stripe, which I think is going to revolutionize financial technologies.

59:19It's already well on the way towards that. And so I, I, to your point, like, you never know where these things are going to go. And that is something investing I do. But I also, I really admire people that choose good questions from the beginning. Sorry, I have to keep asking questions. No, keep going. Do you think that outlier people are the limiting ingredient to us having more outlier companies? I don't think it's the only limiting factor, but I think it's definitely one of them. And if you look kind of in any given year in history, like at the number of unicorns or decaquins that are formed, like the in terms of realized exits, I'm not talking VC fake marks in capital cycles.

1:00:04I'm talking like actual exited companies. It's relatively consistent for a long time. And I think that says something around like at any given moment, there's not that many real big new market opportunities. So I think it says something about that. And I think it also says something either says only purely the number of market opportunities or it says only something about the number of outlier founders or some combination of the two. But I think it's I think it's both. And I do think we're limited by our founders, but I also think we're limited by VCs that are willing to give money to, like, that are able to recognize outlier founders that have a good idea and then give them capital and there's other constraints.

1:00:47As you've sort of, you know, working at a place that's obviously, you know, kind of at the top of the top of the game, have you picked up things there specifically about how to identify what that looks like? Because one of the things I, you know, don't have a good answer to is, I mean, I know, I I know somebody who's outlier now, like I know, you know, when I see the calls and talk or you see these amazing people now, you're like, okay, I know good when I see it now, but that's a very different thing than, you know, they didn't look the same when they were 20 and all of a sudden it like, is that kind of taste in people?

1:01:22Is it teachable? Are there things that you learn by watching or is there things you could learn by reading or thinking? Like what is that? On the first part of the question, I have to say I have learned an unbelievable amount being at Sequoia like really I have learned a lot being at Sequoia And it and that's on all dimensions. It's how to think about markets It's also how to think about founders how to find out our founders We're pretty obsessive around The language we use for how to talk about Founders and I've also I've just learned an incredible amount about company building everything like the place There's 50 years of institutionalized knowledge and an obsessive culture around documenting lessons.

1:02:10That language thing is so hard because you'll hear so frequently people be like, oh, this founder is really spiky. Or you'll hear this language that to me comes off as. Horrible. It's totally inaccurate. And most people are completely uncalibrated. It's unhelpful. It doesn't help me be better at assessing next time. Genuinely, I have learned an unbelievable amount from Sequoia. And, you know, there's people like Mike Ritz, Rulof, Jim Gats, Doug, Alfred, such like, these people are all unbelievable reads of people and I've learned a lot. But I also think I've contributed a few things. And one of the things that I contributed that I'll share here is one way that I think about outlier founders is I think about the chess rating scale.

1:02:55And I kind of wrote something internally on this. And here's a thought experiment for you. Have you played chess? Yeah, I didn't get that far up the elo rating, but I played chess, yeah. So in chess, the highest rated players, you know, 2 ,800 plus like Magnus and others. And like a, still like a pretty good player is even a thousand or whatever. Like a not, not, but like a thousand rated player will be something stupid mistakes. Yeah, they're not making stupid mistakes and they'll be someone that doesn't play any chess. If you, here's thought experiment. If you ask like a thousand rated chess player, you have them watch, they get to see a game, they don't know who's playing, they just see the moves of like 1 ,400 rated players, 1 ,800 rated players, 2 ,200 rated players, 2 ,600 rated players, they get to see just the moves of each of those games.

1:03:46And you ask them to place on the rating scale, like from one game, what is the elo in each of these? games, they can't do it. Like they can't tell the difference of the 2600 versus 22. As was then the farther from you it is the more unable you are to do it. Yeah, 100%. Yeah, within like one standard deviation or something, you usually can, but beyond that you can't. Whereas if you do it the other direction, if you ask the 2600 rated player to judge a 2200 rated game, an 1800 game, a 1400 rated game, a 9000 rated game, they can watch 10 moves and they can basically tell you the elo of those people.

1:04:24And so one of the things that I'm like, I'm obsessed over is calibrating on, you know, like if someone says this person is an outlier in AI, are they? Are you a 1000 saying that 1500 is an outlier? Exactly. Are you 1000 saying 1500 is an outlier? Or like what is the rating of the person making the statement? is this known shazir or really a susquevar or whoever, like saying that this person's really good, or is it like a Stanford undergrad in CS? And a lot of people, they struggle to understand like the level of the person giving them the reference that really fails with tail behavior and tail people.

1:05:10I love this analogy, just to push on it. So I better understand it. And I do watch, I do watch chess on YouTube of 2600s playing and they make a move and I'm like, that was a dumb. I'm like, I know I just don't understand the move and so I just, I know that I'm that. I do, I'm terrible at basketball, but I know what an NBA player looks like. Yeah. And I could see an NBA player. So what parts of being a founder are on a witch? I think the chess scale only applies to purely intellectual things. I think that a lot of other skills like say sales ability. I think that is something that's more like being good at basketball.

1:05:50It's much easier to audit with your own eyes than almost anyone can tell compared to outlier intellect. And I think that outlier intellect, it doesn't always translate. So being really good at chess doesn't mean you're really good at math. I'll give you, I'm going to, I have to kind of go through this because I think this is important. I'm gonna take off my jacket. Yeah, it's a little warm in here, so. No, no, it's great. It's these lights. So I'm gonna give you another crazy example of just how many levels of aloe vera there are in mathematics. In mathematics, I think there are like 20 distinct levels that ordered magnitude beyond just really good at math in a high school class.

1:06:28At the highest end, you have best mathematician in decades or century. these are the like Terry Tao level mathematicians. One level below that, that's kind of a distinct level below, is someone that's basically guaranteed to get a field's metal. It's like best in a decade, it's someone that does three or four things that would be worthy of a field's metal, and they're basically guaranteed to. And they're unmistakably different from each other? They're unmistakably different. The field's metal person would be like, I know that I talked to that person, I know I'm not. That person in the like best in 100 years, the like the gouse or oiler or you know there's a small number of these people in history.

1:07:10They could get a field of metal in almost any sub area of math. Like they can just go and they know more about almost any sub area than the experts in that field. But it's like you have the once in century, you have once in a decade, then you have the like you know the person that easily you got a field's metal. And then you have the person that kind of got a little lucky to get the fields metal. Like there's maybe there was like a 25 % chance or 50 % chance and this political star's line for their brain and for the moment in time and whatever. Yeah. And and like the political, they wrote the thing and like the political tides aligned in the favor their subfield was a little hot at the time or whatever.

1:07:47And then you have another level would be the people that like like don't get a fields medal, but get tenure at a top five math department or really young age. You know, like get Harvard, there was this guy, no milkies who I was one of the youngest, if not the youngest, tenured math professor there. Like early 20s, kind of situation. Yeah, early 20s, mid 20s. You know, and so like this is like another level. Then you have the people that either easily get tenure at a top five department or get tenure, but call it in their early 30s, or get tenure like mid 20s at a five to 20. university. Does that 23 year old Harvard tenured professor do they yet know that they are not one of the higher echelons or is it still an open question at the time they're 23?

1:08:33It's a little bit of an open question but not much. I think that the best mathematicians in the world, like Terry Tao, can talk to almost any mathematician and basically understand where they are in the like almost instantly. Age adjusted and everything. Age adjusted. You know, and not below, not at the age of like 12. Yeah. Because so much of that is just like how passionate have you been at what was your early exposure. But by the time people start doing like research mathematics, I think that people can tell very quickly. It's crazy. You know, another level below that is like, okay, you just, you get tenure at a top five math department at any age.

1:09:09You know, and then it's like you get 10 year to top 20 math department. And then it's just you get a PhD from a top math department easily. And then it's you get a PhD in math from a top 20 department easily. And then it's you just get a PhD in mathematics. And then you studied math in college and you basically were summa cum laude. And then it's like you were, there's still like another five levels. And then it's even the case. And all these levels are still impressive to most of us. Yeah, they're all distinct. And like everything I've mentioned, like obviously this is 800 on the math SAT. Of course, so it's not a useful metric.

1:09:47It's not even a useful metric. There's like 15 distinct levels minimum above 800 on the math SAT, that someone at the top can basically look down and tell you about all of them, almost instantly. So look, you have to like, with founders, you have to think about what is the outlier trait that I'm trying that is important for this company. You know, like if it's a robotics company, being really good at robotics is important, but being good at chess is a relevant. You know, if it's a sales -oriented company, it doesn't matter how great you are, but kind of knowing what dimension matters and then being able to place where on the scale they are so you can actually have like a nuance, you can actually underwrite in your investment thesis.

1:10:25This is very important. Very few people do this. So if you're just the, you're merely the summa cum laude, you know, or you're merely the, I got my PhD easily. But you know that these hard companies are built by mega outliers. Like should you play the game even? Like if you're like, I'm not going to know, Oler, when I see him, like what's the point of even trying that? You know, there's many factors that go into building a company. And so my comma is really just around underwriting for this type of company, I think, you know, So for this AI company, foundation model, just how good are the researchers?

1:11:03I think that is an important part of underwriting an AI research or in the robotics world model companies. Just how good are these researchers? You want to back the absubesca, they're going to track the best, et cetera. But in a basic SaaS company, it's not that important. How does this language show up in a Sequoia analysis of a company? Like, how do you use this metaphor, which I love? How do you apply this? Is it about, is it about which partner we should be listening to? And like, who's got like, you know, like sort of bridge water style? Like, who is the trustworthy voice here? Is it about like, you know, what, what's it about?

1:11:40Like, how do you apply it? Yeah, we just try to get very specific on what traits matter for this company? Is this founder an outlier in those like, in those traits that matter? What level of outlier are they? When we're doing the references on them qualifying, what is the ratings equivalent? Is this an E -Line 25 or 15? Yeah, like who is giving this assessment? Is this a 1000 rated chess player giving the rating or is it a 2400 rated chess player? And so it's, but you can't just say this is a spiky founder. That's a quote. That's not, that will not fly. And we care a lot about the texture of how we describe.

1:12:19It's interesting because I think people who are investors who are sort of more market driven or, you know, often, I think this often comes with later stage investors are, I think, one for precise in the way that they evaluate versus people who are more founder driven or often more vibesy. But I don't think it has to be that way. It feels like you could get merely as intentional and specific about the way that you are founder driven even and that it's just, most people just don't do that work and know even how to talk about it. I am naturally not very good at language. And it was never interested in language.

1:12:57And it's one of the things that I've learned from Sequoia. Like Sequoia is obsessed with language, obsessed with words, things like we don't invest in companies we partner with founders. We don't, you know, do deals we partner with companies. When we write memos, we don't say I, we say we. I think Don Valentine gets a lot of credit for that. he was obsessed with anything Mike Moritz took it to a different level. You do speak in metaphor a lot though, which is something that I think is very necessary. If you're going to try to be accurate about founders because I think so much of it is having those devices to try to like take this very amorphous thing and like put it onto a map that you could do anything with.

1:13:36I think that way, but I didn't connect it to language before sequoia. So this is one of the many things that I've learned there. Well, all right. I'm going to let you go. It's been a long time and it's warm in here. Thank you for doing this. This was really awesome. Thank you for having me. It's been a blast. Thank you, Jack.