The Exchanges

Q Do you think that machine learning and kind of AI will be An IP heavy area in terms of each startup has their own IP on the AI space. Would you think it will essentially be a Oracle solution that's sold as machine learning in a box?

A I don't think that there's anything that looks like AI in a box today for applications that matter. The trend that is interesting is that you see the very big technology players that have access to A lot of data within their walled gardens, like the Googles and Facebooks of the world, they are commoditizing some of the layers you need, right? So you see the open sourcing of TensorFlow, you see even the open sourcing of some of the trained models at this point, and so a lot is coming out of the big technology companies and out of research into the open in the form of open source and APIs. But there's, there's still a ton of domain I think one of the reasons that they're doing this is that the bar is just so high today to build sort of an AI enabled or AI native company that actually builds a dominant product, right? Like you, you need to be a machine learning expert. You need to be a domain expert. Then you still have to design a product that solves a user problem. And so I think that there's an enormous amount of expertise in terms of how you're going to get that data set, what data set matters, the work Workflow, designing systems, even if you have all of those frameworks. So I think it's just the, the systems that you would actually sell as products are so far away from, from AI in a box today that there's a lot of IP that is going into them, despite everything that's coming …

AI assessment note: “there's a lot of IP that is going into them, despite everything”

Q founders who say, you know, bluntly to build what we want to build, we need to raise much larger sums than traditionally were raised at pre-seed or seed rounds. And so we're raising 50 or 75 or even a hundred. Is that true that AI companies are much more capital intensive in the early days? If so, what is the spending on? Can you help me understand that, Sarah, genuinely?

A Yeah. So we're meeting some of the same people that have this point of view. Right. Uh, but I think very rarely is like zero shotting at being like, I'm going to, so the thing that is really expensive, um, I mean, there are many things that can be expensive, but one of the things that is really expensive is I want to train a model from scratch that is very large and it's going to take me, um, you know, low tens of people, probably 20 or 30 people. That know how to do this type of research and, um, you know, 10,000 plus GPUs and x number of months, that is very expensive. Right? Um, like my personal point of view is there's a Less than 10 instances I can think of where that is going to make sense for companies. The vast majority of companies are going to figure out actually how to apply these models that other people have built that are offered by APIs or in the open source or fine tune them or like build some other part of the stack. And so I've honestly seen a lot of smart founders like begin with this premise, especially people who come from a research background and then think through it and adjust course dramatically on like How to sequence into understanding whether or not they even need that, right? Because, like, I think a much bigger question than, like, can you train a large model is, like, does anybody want it, right? Like, is it going to be useful? And, like, you cou…

AI assessment note: “one of the things that is really expensive is I want to train a model”

Q Can I ask, do these, do these co-founders when they come from say accounting, when they come from legal, are they like steeped AI technologists or are they former lawyers? Are they former accountants who are steeped in the domain knowledge? What's more important, like the technical deep knowledge there, All the domain knowledge of knowing accounting back to front, legals back to front. How do you think about that?

A Like, so in the case of Harvey, like it's both, right? One founder worked at Google, um, DeepMind and Facebook, right? In AI research. And one founder is a, you know, was a rising star lawyer at a white shoe law firm who like also hacks, right? And so I'd say, you know, ideally, like you have some combination of like Customer-backed domain knowledge and, um, understanding of, like, product and research. Uh, and so that is something that I think we can try to do, like, help people pair up. I think over time, actually, we spent, you know, we spent a lot of time with the research community, but, um, I think the vast majority of companies, like, software is going to end up being built by, with love and respect, like, run-of-the-mill product-oriented engineers. Like, special founders, but people who come from software engineering, and that's because, like, this is going to become, um, tooling like any other part of software, and the number of people who know how to leverage these models is growing, right? Which is great for you and me. Like, we're going to see more interesting companies from people who are really customer oriented.

AI assessment note: “ideally, like you have some combination of like Customer-backed domain knowledge and, um, understanding”

Q Final one before we do a quick fire, but I'm, I'm too interested. Hunter Walk said that we've seen kind of the death of the generalist seed VC. Do you think he's right in terms of saying that and being that binary, or do you think actually we'll still very much continue to see seed stage specialists that are horizontal and broad?

A Yeah. So just like for your listeners, Hunter's argument goes something like this. Tech is bigger. Networks are too large to own. Technical innovation matters more. Hard to be a generalist. Right. And so like, you know, I think we're aligned with this and that we're absolutely focused on being the best possible partner to AI enabled companies. But, uh, so like we are leaning into this as our advantage, but. As I mean, we've been talking about, it's a very execution, uh, oriented, very personal games. And like, and there are many different ways to be good as an investor at an individual level. Like you have talked to thousands of investors now, um, many of which are great in different ways. Right. And so like when I think about some of my friends, um, or the early stage investors that I like really respect, like some are more specialized. Like Eric Vistria is exceptionally good at enterprise infrastructure and tends not to do things he doesn't understand. That's great discipline. Um, but others, like, you know, Jim Getz has stretched from Palo Alto networks to WhatsApp, right? So, like, empirically, there are different ways to be good at this, including more generalist ways, or even, um, Uh, like, you know, my friend Alan, right, I learned a lot from him, but he seems like quite versant and to have good access across a broad range of technologies, and so I think, you know, uh, I…

AI assessment note: “I tend to be skeptical of conclusive statements about VC strategy.”

Q Can I ask, do these, do these co-founders when they come from say accounting, when they come from legal, are they like steeped AI technologists or are they former lawyers? Are they former accountants who are steeped in the domain knowledge? What's more important, like the technical deep knowledge there, All the domain knowledge of knowing accounting back to front, legals back to front. How do you think about that?

A Like, so in the case of Harvey, like it's both, right? One founder worked at Google, um, DeepMind and Facebook, right? In AI research. And one founder is a, you know, was a rising star lawyer at a white shoe law firm who like also hacks, right? And so I'd say, you know, ideally, like you have some combination of like Customer-backed domain knowledge and, um, understanding of, like, product and research. Uh, and so that is something that I think we can try to do, like, help people pair up. I think over time, actually, we spent, you know, we spent a lot of time with the research community, but, um, I think the vast majority of companies, like, software is going to end up being built by, with love and respect, like, run-of-the-mill product-oriented engineers. Like, special founders, but people who come from software engineering, and that's because, like, this is going to become, um, tooling like any other part of software, and the number of people who know how to leverage these models is growing, right? Which is great for you and me. Like, we're going to see more interesting companies from people who are really customer oriented.

AI assessment note: “ideally, like you have some combination of like Customer-backed domain knowledge and, um, understanding”

Q Final one before we do a quick fire, but I'm, I'm too interested. Hunter Walk said that we've seen kind of the death of the generalist seed VC. Do you think he's right in terms of saying that and being that binary, or do you think actually we'll still very much continue to see seed stage specialists that are horizontal and broad?

A Yeah. So just like for your listeners, Hunter's argument goes something like this. Tech is bigger. Networks are too large to own. Technical innovation matters more. Hard to be a generalist. Right. And so like, you know, I think we're aligned with this and that we're absolutely focused on being the best possible partner to AI enabled companies. But, uh, so like we are leaning into this as our advantage, but. As I mean, we've been talking about, it's a very execution, uh, oriented, very personal games. And like, and there are many different ways to be good as an investor at an individual level. Like you have talked to thousands of investors now, um, many of which are great in different ways. Right. And so like when I think about some of my friends, um, or the early stage investors that I like really respect, like some are more specialized. Like Eric Vistria is exceptionally good at enterprise infrastructure and tends not to do things he doesn't understand. That's great discipline. Um, but others, like, you know, Jim Getz has stretched from Palo Alto networks to WhatsApp, right? So, like, empirically, there are different ways to be good at this, including more generalist ways, or even, um, Uh, like, you know, my friend Alan, right, I learned a lot from him, but he seems like quite versant and to have good access across a broad range of technologies, and so I think, you know, uh, I…

AI assessment note: “I tend to be skeptical of conclusive statements about VC strategy.”

Q Now, I'd love to get started today with a quick bio on you, and how you made your way to one of the world's best funds in Greylock. So what was your kind of origin story?

A So the roots actually go back pretty far for me. My parents are both originally engineers, and they worked at big tech companies like Bell Labs, and eventually... My dad and some of his friends started, uh, a tech startup called Casa Systems, which is now a, a large private, uh, and if you think about physical networking infrastructure in the United States, it was really introduced to deliver, like, cable TV a long time ago, and so, Casa's helping transform that infrastructure from video to internet and to meet, you know, the massive demands of consumers who want more and more internet services all the time. So, if you think about, for example, millions of people getting on house party and, you Spontaneously starting multi-way video, like, we're putting huge stress on the network. So that's what I got to work on when I was in my teens, and it was a very formative experience. Like, I taught myself HTML and CSS to build our first corporate website and sort of discovered the web at that time, and our poor, like, I knew nothing, right? And our poor, totally brilliant head of hardware engineering with his PhD was one of the other founders and infinitely patient with me, and so it was It was sort of learning, learning as you go. And so, uh, I worked with them more in earnest later on, and then I wanted to do my own thing, of course. My own startup didn't work that well. And in busine…

AI assessment note: “So the roots actually go back pretty far for me. My parents are both”

Q Now, I'd love to get started today with a quick bio on you, and how you made your way to one of the world's best funds in Greylock. So what was your kind of origin story?

A So the roots actually go back pretty far for me. My parents are both originally engineers, and they worked at big tech companies like Bell Labs, and eventually... My dad and some of his friends started, uh, a tech startup called Casa Systems, which is now a, a large private, uh, and if you think about physical networking infrastructure in the United States, it was really introduced to deliver, like, cable TV a long time ago, and so, Casa's helping transform that infrastructure from video to internet and to meet, you know, the massive demands of consumers who want more and more internet services all the time. So, if you think about, for example, millions of people getting on house party and, you Spontaneously starting multi-way video, like, we're putting huge stress on the network. So that's what I got to work on when I was in my teens, and it was a very formative experience. Like, I taught myself HTML and CSS to build our first corporate website and sort of discovered the web at that time, and our poor, like, I knew nothing, right? And our poor, totally brilliant head of hardware engineering with his PhD was one of the other founders and infinitely patient with me, and so it was It was sort of learning, learning as you go. And so, uh, I worked with them more in earnest later on, and then I wanted to do my own thing, of course. My own startup didn't work that well. And in busine…

AI assessment note: “So the roots actually go back pretty far for me. My parents are both originally engineers”

Q think about the startup versus incumbent? I love Alex Rampell's quote, which is, you know, the question is, will the incumbent acquire distribution before the, well, sorry, will the incumbent acquire innovation before the startup acquires distribution? I always think of that one, but it's, it's the question of, like, who's best placed and what challenges do each face? How do you think about that when comparing startup versus incumbent?

A Yeah, this is, uh, actually like maybe a very discouraging answer, but I believe in like intellectual honesty, like classically, the only real advantage startups have is speed. Right. And so I don't think this is that different than the traditional battles. I think that speed actually might matter more than ever when the environment seems to be moving at warp speed, right? Like, What's the quote? Some, you know, some decades nothing happens, and some years a decade happens, right? I feel like that is happening right now, and it's hard to make a large organization move at that speed. On the incumbent advantage side, there's a lot of Much ado has been made about this idea of like a data moat. I'm sure you've heard this term, but, but honestly, there's a lot of data out there and entrepreneurs are incredibly creative about collecting it and increasingly about generating it. And so I think it's fun to talk about the structural advantages, but I guess I'm still mostly looking for like, like really special founders and people who are. Like execution oriented with unique ideas. And I don't think it's like, oh, the incumbents are going to win this one or the startups are going to win this one.

AI assessment note: “classically, the only real advantage startups have is speed.”

Q It's slightly a shade early. The importance of market timing has never been more prescient. But the most exciting thing is you've started a new fund recently with conviction, and so I want to start on this. I obviously spoke to many friends and mutual friends before, um, and many of them said that I had to start on this. So why did you decide to leave Greylock first?

A Yeah, Greylock is like this, um, I mean, we have many mutual friends there, some of my dearest. It's a seven-year-old platform with extraordinary history and people, and like, I played for the team for 10 years, right? So, amazing place. Super grateful for the opportunity. Like, lots of mentors there. Anil Bustry, Ashim Chana, Reid Hoffman, David Zee, Jerry Chen. I love the people. I really wanted to focus on early stage investing. Zero to one is just magic, right? And I, I wanted to be an entrepreneur. Again, you can't rationalize that, right? It's a great job being a GP at a big VC firm. It's crazy to leave, but I wanted to operate differently. I had a few ideas for how a small team could do venture, um, how to, how you could change the founder experience, and, and the biggest thing was believing that AI is a breaking change.

AI assessment note: “I really wanted to focus on early stage investing. Zero to one is just magic”

Q actually, as you said, they'd be very upset if you took it away. The thing that worries me, though, is like, regulatory bodies. Again, uh, diving straight in. Like, and I think you've never seen such a big chasm between regulatory body knowledge and, like, the actual technology itself. This worries me that they're not in a position to actually regulate with the main knowledge. Do you share my concern?

A Yeah, I, I think it is a concern. I don't think it is structurally different than other areas of technology, right? So if you have the internet, you have cybersecurity issues. Um, and so I've been a long time cybersecurity investor. I've engaged with like, you know, um, national security bodies on policymaking in this area. Uh, and I'm spending time in DC, um, two weeks from now, um, on, uh, thinking about AI risk as well. And so I think the thing that is different today may be the, um, speed of change, right? Like, I don't think we have decades to adjust to these capabilities in society. And so I think it's incumbent on, um, anybody Producing the technology, enabling the technology to go, like, partner with policymakers and, um, the rest of society and, like, do that education, as you said, and, like, we gotta build a new muscle here. I think it's important.

AI assessment note: “Yeah, I, I think it is a concern. I don't think it is structurally”

Q saying this will go the same, Sarah. You're brilliant. I think the world of you. Uh, but my point is like, I view this as like an enabling technology which everything will be built on top of. I had Navan founder Ariel on, and like, You know, TripAction is what Nirvana is now using and everyone is like sitting on top of it. Why have a vertically centric AI fund?

A You're asking me to like give away the kind of hidden secret of the fund, right? So, so here it is though. If, um, if, uh, like all this is execution anyway, like if we at Conviction are right in the long term, and this is the most important technology change of the decade, and we're good at selection and execution, and we invest in this outsized number of important tech companies, again, it, it just means that they will be the most important companies, period. Right? And so like, yes, Like, you're right. Like, I think it's eventually just a horizontal software fund, but right now, I think it's also useful for us to be specialists, right? Like, the AI community is actually quite limited in size, and so, like, if we are focused on that, we can invest in the community, because applied research matters in a way that has never before, right? I think your average venture capitalist does not spend a lot of time in computer science research, and then you do a lot of community building. Like, we can Be a matchmaker for teams, a sorting hat for people who want to get into AI startups. Um, their strategic relationships that are very specific to AI, right? People need model access, data, GPUs, design partners. Um, and then I think there's like a new set of understanding and tribal knowledge because it's a very, it's a very technical and dynamic field. Like we're rethinking a lot of user e…

AI assessment note: “eventually just a horizontal software fund, but right now, I think it's also useful for us to be specialists”

Q it's like, this, we, we know that restaurant analytics is not a good idea. Like, it's just not. It's, and if it does work, it's gonna be so much harder than anything else you brilliant entrepreneur could do. Um, I want to talk about idea generation. How do you advise startup founders on choosing ideas when the world is moving, as you said, at warp speed faster than ever before?

A I think that looking for ideas, um, I get like a lot of people ask me like, what ideas do you have? And I'm like, I'm happy to go on a tangent of like all the things that we think are really good markets to go after. But, um, uh, the, like if you generically cast about for ideas, you're going to get a generic idea, right? It's not something that you like particularly understand. And so I believe in this idea of, um, Uh, and it applies more to B to B than consumer, right? But this idea of like having high resolution customer conversations. And so if it's solving a problem for yourself or just like really going and looking for problems instead, or even open research questions that you like think are attached to an interesting market, I'll give you an example. So the world is built on three models from everything from entertainment to the physical world around us. Uh, it is an open research question as to whether or not you can generate three D models that are usable in these use cases, but it's like, ah, there's no market risk. It's highly valuable. It's just, can we do it? Right. And so, so I think there's a bunch of different ways you can look for problems that become less generic, where you could come out of it and be like, I understand something as a founder. I have a hunch that like, it's unlikely that every other person that wants to be an entrepreneur is going to have. And…

AI assessment note: “looking for problems instead, or even open research questions”

Q think about the startup versus incumbent? I love Alex Rampell's quote, which is, you know, the question is, will the incumbent acquire distribution before the, well, sorry, will the incumbent acquire innovation before the startup acquires distribution? I always think of that one, but it's, it's the question of, like, who's best placed and what challenges do each face? How do you think about that when comparing startup versus incumbent?

A Yeah, this is, uh, actually like maybe a very discouraging answer, but I believe in like intellectual honesty, like classically, the only real advantage startups have is speed. Right. And so I don't think this is that different than the traditional battles. I think that speed actually might matter more than ever when the environment seems to be moving at warp speed, right? Like, What's the quote? Some, you know, some decades nothing happens, and some years a decade happens, right? I feel like that is happening right now, and it's hard to make a large organization move at that speed. On the incumbent advantage side, there's a lot of Much ado has been made about this idea of like a data moat. I'm sure you've heard this term, but, but honestly, there's a lot of data out there and entrepreneurs are incredibly creative about collecting it and increasingly about generating it. And so I think it's fun to talk about the structural advantages, but I guess I'm still mostly looking for like, like really special founders and people who are. Like execution oriented with unique ideas. And I don't think it's like, oh, the incumbents are going to win this one or the startups are going to win this one.

AI assessment note: “classically, the only real advantage startups have is speed.”

Q actually, as you said, they'd be very upset if you took it away. The thing that worries me, though, is like, regulatory bodies. Again, uh, diving straight in. Like, and I think you've never seen such a big chasm between regulatory body knowledge and, like, the actual technology itself. This worries me that they're not in a position to actually regulate with the main knowledge. Do you share my concern?

A Yeah, I, I think it is a concern. I don't think it is structurally different than other areas of technology, right? So if you have the internet, you have cybersecurity issues. Um, and so I've been a long time cybersecurity investor. I've engaged with like, you know, um, national security bodies on policymaking in this area. Uh, and I'm spending time in DC, um, two weeks from now, um, on, uh, thinking about AI risk as well. And so I think the thing that is different today may be the, um, speed of change, right? Like, I don't think we have decades to adjust to these capabilities in society. And so I think it's incumbent on, um, anybody Producing the technology, enabling the technology to go, like, partner with policymakers and, um, the rest of society and, like, do that education, as you said, and, like, we gotta build a new muscle here. I think it's important.

AI assessment note: “Yeah, I, I think it is a concern. I don't think it is structurally different”

Q saying this will go the same, Sarah. You're brilliant. I think the world of you. Uh, but my point is like, I view this as like an enabling technology which everything will be built on top of. I had Navan founder Ariel on, and like, You know, TripAction is what Nirvana is now using and everyone is like sitting on top of it. Why have a vertically centric AI fund?

A You're asking me to like give away the kind of hidden secret of the fund, right? So, so here it is though. If, um, if, uh, like all this is execution anyway, like if we at Conviction are right in the long term, and this is the most important technology change of the decade, and we're good at selection and execution, and we invest in this outsized number of important tech companies, again, it, it just means that they will be the most important companies, period. Right? And so like, yes, Like, you're right. Like, I think it's eventually just a horizontal software fund, but right now, I think it's also useful for us to be specialists, right? Like, the AI community is actually quite limited in size, and so, like, if we are focused on that, we can invest in the community, because applied research matters in a way that has never before, right? I think your average venture capitalist does not spend a lot of time in computer science research, and then you do a lot of community building. Like, we can Be a matchmaker for teams, a sorting hat for people who want to get into AI startups. Um, their strategic relationships that are very specific to AI, right? People need model access, data, GPUs, design partners. Um, and then I think there's like a new set of understanding and tribal knowledge because it's a very, it's a very technical and dynamic field. Like we're rethinking a lot of user e…

AI assessment note: “eventually just a horizontal software fund, but right now, I think it's also useful for us to be specialists”

Q founders who say, you know, bluntly to build what we want to build, we need to raise much larger sums than traditionally were raised at pre-seed or seed rounds. And so we're raising 50 or 75 or even a hundred. Is that true that AI companies are much more capital intensive in the early days? If so, what is the spending on? Can you help me understand that, Sarah, genuinely?

A Yeah. So we're meeting some of the same people that have this point of view. Right. Uh, but I think very rarely is like zero shotting at being like, I'm going to, so the thing that is really expensive, um, I mean, there are many things that can be expensive, but one of the things that is really expensive is I want to train a model from scratch that is very large and it's going to take me, um, you know, low tens of people, probably 20 or 30 people. That know how to do this type of research and, um, you know, 10,000 plus GPUs and x number of months, that is very expensive. Right? Um, like my personal point of view is there's a Less than 10 instances I can think of where that is going to make sense for companies. The vast majority of companies are going to figure out actually how to apply these models that other people have built that are offered by APIs or in the open source or fine tune them or like build some other part of the stack. And so I've honestly seen a lot of smart founders like begin with this premise, especially people who come from a research background and then think through it and adjust course dramatically on like How to sequence into understanding whether or not they even need that, right? Because, like, I think a much bigger question than, like, can you train a large model is, like, does anybody want it, right? Like, is it going to be useful? And, like, you cou…

AI assessment note: “one of the things that is really expensive is I want to train a model from scratch”

Q of people, we spoke about, kind of, founder versus market, um, and Andy Radcliffe, I think it was, who said that, great founder, bad market. My, my question is, a lot of other investors oscillate on, like, defensibility, and I hear so many give the excuse of, oh, I, I don't think it's very defensible. Um, how do you feel about startup defensibility, Sarah? Let me dangle that one out.

A Yeah, it doesn't exist, right? Like quite literally you're starting with nothing. And so I think that it is a, um, like I think investors are wrong to look for it. What you are investing in is, um, trajectory, right? And the ability for founders to navigate a market and a thesis, right? And so you might believe that a team doesn't have a thesis on defensibility. You might believe that a team is incapable of coming up with a thesis on defensibility if If, you know, somebody is very early, you might as an investor not have one yourself yet, right? You're like, oh, I just don't know how the market really turns out. Um, but I, I think many of these cases like these, um, how a market turns out is actually quite unknowable. Um, and if you are looking for defensibility at the seed, like there's no company yet. This is a mistake.

AI assessment note: “Yeah, it doesn't exist, right? Like quite literally you're starting with nothing.”

Q How do you advise founders then when they, at the early stage, when they have a large, large multi-stage fund and not naming names, genuinely, but like a large, large multi-stage fund and they have a smaller boutique firm, what do you advise them?

A I advise them to like get educated about how these firms work and what the incentives are and then like Make a decision about the type of, um, help they want at this stage in the company. And people are going to make different decisions, but, you know, thinking like, I think people should be like both tactical and long-term oriented, right? The tactical is like, who's going to move the needle for me over the next 18 months? And then long-term oriented, like, who do I trust and want to be around? And, um, you know, how, how should I like Sequence the base of supporters I have over the longterm. And I don't like, there are real advantages to VC scale, right? Like I've experienced it. You, we know all of these people, um, coverage, reach, et cetera, but returns in most firms are dominated by a few good investors, even when the partner group might be 10 or more. And the complexity of interpersonal dynamics and decision making in groups is, like, not well understood by founders, right? And so I think there's, there's real risk to good investment decision making in big groups. Groupthink, seniority overriding, like, positioning in politics. And, and to be clear, again, not every firm, but it's, it's sort of a structural risk that happens. When I don't know how to solve a problem, I tend to make it simpler. Smaller firm, fewer people, only do what matters. It's also, like, much simple…

AI assessment note: “I advise them to like get educated about how these firms work and what the incentives are”

Q Yeah, no, I think that's a great answer. What did you believe in investing that you no longer believe?

A I am more, like, not in a, hopefully not in a sloppy way, but I am increasingly convinced that, like, it's not knowable what the outcomes are from, for companies, like, at the very beginning, and, and specifically, like, how markets play out is unknowable, because, like, there are actors with agency determining how the market is structured, right? So, you or I could tell each other an intellectual Like narrative that holds together about like why structural advantage in some specific market like belongs to an incumbent or a startup or, or whatever, but it's just a convincing story, right? Like what really matters is the actors that are playing. And so I, I'm like much more comfortable without knowing exactly how things are going to play out now or have been taught that.

AI assessment note: “increasingly convinced that, like, it's not knowable what the outcomes are”

Q data sets there. As an investor in early stage startups and a big believer in kind of the enabling technology of AI, do you think then that There is this kind of fundamental inaccessibility for startups to get the data sets required that the incumbents have. Do you think there is this incumbency advantage that's often cited, or do you think there are ways around it that can mitigate this?

A Yeah, I think, um, if your plan as a company is to take internet accessible data sets and do something interesting with them on the machine learning side and productize them, If it's an area that Google and Facebook care deeply about, you're on dangerous ground, right? They, those people have the same expertise and, and much greater resources than, than most startups. But I, I think that there's a very different opportunity on the sort of B to B side. And there's many, there's many data sets that haven't been mined, including ones that are sort of theoretically publicly available. Right. And, and so there have been many examples of this processing weather data for agricultural applications, uh, is, is an often cited one. I also think an interesting opportunity that we will see is building sort of company specific models with internal data. There's, there's a question of how custom software like and services like these companies get, but if, if you are building a A model that works in a specific way with an understanding of how a company works, then that's something that's very unlikely to come out, even if the, the sort of bigger players with access to public data could, in theory, do the same thing.

AI assessment note: “I think that there's a very different opportunity on the sort of B to B side.”

Q You said about the capital gaps there, obviously, uh, suggesting the potential for market expansion as you cited there. What do you mean by the capital gap? I'm intrigued kind of by that notion.

A I think when you are worried about the speed of go to market, Or the market size, you know, how you're really going to get distribution with new technologies. There, there are all of these questions around these AI enabled companies. And when I say capital gap, I'm just talking about sort of VC uncertainty, right? And lack of expertise in these specific verticals. I think you're, you're seeing a lot of people trying to get up the learning curve very quickly in, uh, autonomous vehicles. And I think that in some of these areas, whoever, uh, Gets up that learning curve quickly and makes the right contrarian bets is going to fill that gap of capital because a lot of people are just going to throw up their hands and say, I don't understand it, or the timeline doesn't make sense to me. It's very different from, like, if you, over the last few years, if you saw a company that was executing really well in a known replacement market with some sort of cloud mobile first angle that looks like it was working, like, That's not a contrarian bet, right? If that company is doing really well, they will likely have a number of different capital options. And so, I'm just talking about, like, the more uncertainty there is around that platform shift and the right kinds of bets to make, the fewer VCs are going to do it.

AI assessment note: “when I say capital gap, I'm just talking about sort of VC uncertainty”

Q emerging markets. Um, I, I looked at companies on paper and purely evaluated them on the paper business, and I didn't anticipate politics, weather, and a lot of things that actually can be very harmful to a company, but didn't factor into my model of the world. That was my lesson and my mistake. What was your biggest investing mistake, and how did it impact your mindset, do you think?

A I mean, this is actually probably where one of the investments I regret not making, and there are, you know, the anti-portfolio is pretty significant here, um, but one of the, one of the investments I, like, actually, multiple investments I regret not making, so, um, Benchling, Rippling at the A, right? Like, these are investments you make because of the founder, right? Saji and Parker are, like, really special people. And, um, I think like the recognition of, uh, Collaboration in the life sciences has not traditionally been, like, an amazing SaaS market. It hasn't been much of a market at all. Um, and so, like, you know, can you get confidence on something that's changing in the market, uh, and, like, can a founder change the market? Like, I believe this is possible now, right? With Parker, like, transparently, you know, um, there are risks around somebody who, like, built a company before Which ended controversially in terms of his path there, and, like, I was, um, you know, I, I think the world of Parker Conrad, I think he's an exceptional entrepreneur, and, like, my orientation towards, like, really pushing to take all sorts of risk if the founders are really special is, you know, much stronger than it is, than it was five years ago.

AI assessment note: “multiple investments I regret not making, so, um, Benchling, Rippling at the A”

Q for the variance of thoughts and opinions. If we move on to the next question now of where does value accrue? In the next wave of AI, does it accrue to the startups with innovation at their bones, or does it accrue to the incumbents who have the powers of distribution in their hands? We're going to kick off today with Sarah Guo, founder and general partner at Conviction Capital.

A Yeah, this is maybe a very discouraging answer, but I believe in, like, intellectual honesty. Like, classically, the only real advantage startups have is speed, and speed actually might matter more than ever when the environment seems to be moving at warp Speed, right? What's the quote? Some decades nothing happens and some years a decade happens, right? I feel like that is happening right now. It's hard to make a large organization move at that speed. On the incumbent advantage side, much ado has been made about this idea of a data moat. But honestly, there's a lot of data out there and entrepreneurs are incredibly creative about collecting it and increasingly about generating it. And I don't think it's, oh, the incumbents are going to win this one or the startups are going to win this one.

AI assessment note: “I don't think it's, oh, the incumbents are going to win this one”

Q Final one. What does success look like for you with conviction? This was actually one that Pat suggested. I ask you like, 20 years out. What do you want people to say about conviction? What do you want to have achieved? I think about it a lot and I'm intrigued to hear yours.

A Yeah. Uh, yeah. Brutal. Um, so this is a scary thing to say out loud because like, like with any entrepreneur, like the goals are big goals are always arrogant sounding. Right. But you know, with, with the fund, um, I think the first is like, it's a fund, the measure of performance is returns. Right. And you can define that in different ways. Um, but for me, like I define it on a multiple basis, not an absolute dollar basis. Otherwise like I should have raised a larger fund. Uh, and like, you know, let's put best in class venture multiples on the board, right? I think that's the first thing. I think the second, we started talking a little bit about relevance, right? It's possible to make money without being relevant, and like, we intended to do both, right? We want to be part of very important companies, so we have to pick well. Um, uh, my name's not on the door, right? Like, I want to build a partnership, and so the question is like, can we Can we build a, a very small partnership that, you know, plays better as a team, like makes better decisions, has better access as a team. Um, very simple to say, very hard to do. Um, and I think the last is, like, you know, are we beloved by entrepreneurs? I think if those, like, if those couple things are true and we're in, you know, a set of the, if we're beloved by a set of the most important entrepreneurs of the next generation, like, …

AI assessment note: “let's put best in class venture multiples on the board”

Q I'm really worried about wealth inequality. I think it's never been worse. Yeah. And when we think about, like, teams of 10 and 20 building these billion dollar companies, I agree with you totally. I'm just worried that we're gonna see this centralization of wealth with the evolution of AI and becoming more and more prominent in technology and society. Do you agree, and am I right to be worried?

A I do agree with you. Right. I think that's a, maybe people don't want to say that out loud, but I, I would agree with you, and then also say, um, uh, technology, it drives abundance. Right? Um, if that's anything from agricultural revolution, industrial revolution, computing, like, I think we will produce more, and the question is, like, do we want more if it is going to begin by being, um, distributed very unequally? Uh, my answer is yes. Like, you give people these technologies, and rarely are people, Do they say, take it away? Like I'm going to stop using it. Right. I think the productivity benefit is incredible. That's possible. And that doesn't mean like we as a society and I'm on the policy side and in a very democratic way need to address that distribution. But I think like, it doesn't mean to me, like don't make progress.

AI assessment note: “I do agree with you.”

Q is a fucking hard journey. And there's lots of different aspects of building a company. Beyond the pure technology stack. I can help with them in these ways, and I'm here for you in these ways, and I'm not going to pretend that I'm something else. And that seems to resonate quite well. My point being, do you think most VCs actually get it, or is it kind of BS?

A Um, I think, like, there are different ways to be valuable as an investor, and then, like, different levels of authenticity in the community, right? Um, so I think there's a lot of genuine and justified enthusiasm, as well as a lot of, like, FOMO and pretension, right? But broadly, no, there's not a lot of deep understanding yet. This is a technical and dynamic field, and the research is intersecting with the real world at a pace, like, I've never before encountered in more than a decade of investing, um, so, like, And then you could ask the question, like, is that a good idea, right? Um, and again, different ways to be successful, right? If you're choosing, if you're choosing people and founder quality, like, maybe you could still do really well even against this type of investment. Um, but, you know, buying access to investments without some level of understanding sounds perilous.

AI assessment note: “broadly, no, there's not a lot of deep understanding yet.”

Q of people, we spoke about, kind of, founder versus market, um, and Andy Radcliffe, I think it was, who said that, great founder, bad market. My, my question is, a lot of other investors oscillate on, like, defensibility, and I hear so many give the excuse of, oh, I, I don't think it's very defensible. Um, how do you feel about startup defensibility, Sarah? Let me dangle that one out.

A Yeah, it doesn't exist, right? Like quite literally you're starting with nothing. And so I think that it is a, um, like I think investors are wrong to look for it. What you are investing in is, um, trajectory, right? And the ability for founders to navigate a market and a thesis, right? And so you might believe that a team doesn't have a thesis on defensibility. You might believe that a team is incapable of coming up with a thesis on defensibility if If, you know, somebody is very early, you might as an investor not have one yourself yet, right? You're like, oh, I just don't know how the market really turns out. Um, but I, I think many of these cases like these, um, how a market turns out is actually quite unknowable. Um, and if you are looking for defensibility at the seed, like there's no company yet. This is a mistake.

AI assessment note: “Yeah, it doesn't exist, right? Like quite literally you're starting with nothing.”

Q What trend do you see that others are not seeing, do you think?

A It may be, um, it may not be very well understood that, uh, a significant part of the opportunity for AI is services, not software markets, right? So as a, as a, uh, software investor, traditionally, you're like, okay, here's the stack, right? There's chips and, um, cloud infra and developer tools and observability and security and applications, and then like all the consumer stuff, but, uh, You know, I, I think it's a, I think it's a miss to be like, that's the opportunity for AI because we're doing more work that is today labor, right? And as you said, that opens like real questions in terms of, um, you know, labor displacement, distribution of wealth, but that is the opportunity from a productivity perspective too, like both enablement, um, and, and like replacement.

AI assessment note: “a significant part of the opportunity for AI is services, not software markets”

Q How do you advise founders then when they, at the early stage, when they have a large, large multi-stage fund and not naming names, genuinely, but like a large, large multi-stage fund and they have a smaller boutique firm, what do you advise them?

A I advise them to like get educated about how these firms work and what the incentives are and then like Make a decision about the type of, um, help they want at this stage in the company. And people are going to make different decisions, but, you know, thinking like, I think people should be like both tactical and long-term oriented, right? The tactical is like, who's going to move the needle for me over the next 18 months? And then long-term oriented, like, who do I trust and want to be around? And, um, you know, how, how should I like Sequence the base of supporters I have over the longterm. And I don't like, there are real advantages to VC scale, right? Like I've experienced it. You, we know all of these people, um, coverage, reach, et cetera, but returns in most firms are dominated by a few good investors, even when the partner group might be 10 or more. And the complexity of interpersonal dynamics and decision making in groups is, like, not well understood by founders, right? And so I think there's, there's real risk to good investment decision making in big groups. Groupthink, seniority overriding, like, positioning in politics. And, and to be clear, again, not every firm, but it's, it's sort of a structural risk that happens. When I don't know how to solve a problem, I tend to make it simpler. Smaller firm, fewer people, only do what matters. It's also, like, much simple…

AI assessment note: “I advise them to like get educated about how these firms work”